diff --git "a/high_quality_eval.jsonl" "b/high_quality_eval.jsonl"
new file mode 100644--- /dev/null
+++ "b/high_quality_eval.jsonl"
@@ -0,0 +1,634 @@
+{"id": "life_daily_dialogue_002985", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Guess, what I'Ve bought for you Oh.\nChunk 2: it ' s a case flowers.\nChunk 3: It ' s very kind of you.\nChunk 4: I hope you like it.\nChunk 5: I love flowers you know.\nChunk 6: Thank you very much.", "streaming_reasoning": "C1 casual_comment=guess, i've. C2 casual_comment=case, flowers. C3 casual_comment=very, kind. C4 preference=true. C5 casual_comment=love, flowers. C6 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Guess, what I'Ve bought for you Oh.\nChunk 2: it ' s a case flowers.\nChunk 3: It ' s very kind of you.\nChunk 4: I hope you like it.\nChunk 5: I love flowers you know.\nChunk 6: Thank you very much."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=guess, i've. C2 casual_comment=case, flowers. C3 casual_comment=very, kind. C4 preference=true. C5 casual_comment=love, flowers. C6 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Guess, what I'Ve bought for you Oh.\nChunk 2: it ' s a case flowers.\nChunk 3: It ' s very kind of you.\nChunk 4: I hope you like it.\nChunk 5: I love flowers you know.\nChunk 6: Thank you very much.", "input_token_count": 44, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on guess. Next, the user comments on case. Next, the user comments on very. Next, preference: true. Finally, the user comments on love.  Some chunks were skipped because they contained thanks_only. In summary, preference: true..", "trace": "C1 casual_comment=guess, i've. C2 casual_comment=case, flowers. C3 casual_comment=very, kind. C4 preference=true. C5 casual_comment=love, flowers. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Guess, what I'Ve bought for you Oh.", "streaming_reasoning": "Initially, the user comments on guess.", "trace": "casual_comment=guess, i've."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "it ' s a case flowers.", "streaming_reasoning": "As more information arrives, the user comments on case.", "trace": "casual_comment=case, flowers."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It ' s very kind of you.", "streaming_reasoning": "As more information arrives, the user comments on very.", "trace": "casual_comment=very, kind."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I hope you like it.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I love flowers you know.", "streaming_reasoning": "As more information arrives, the user comments on love.", "trace": "casual_comment=love, flowers."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002381", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be leaving from Ely.\nChunk 2: I need to depart broxbourne and travel on monday please.\nChunk 3: Yes, please for 8 people.\nChunk 4: I'm also looking for a recommendation on Mexican restaurants in the south.\nChunk 5: Not right now, but could I have the postcode No thank you.", "streaming_reasoning": "C1 intent=context_update. C2 goal=search; day+=monday; destination+=depart broxbourne and travel on monday pl. C3 party_size+=8 people; acceptance=selected_option. C4 area+=south; cuisine+=mexican. C5 goal=request_info; requested_info+=postcode.", "deep_reasoning": "Need goal=search, request_info; area=south; food=mexican; party_size=8 people; destination=depart broxbourne and travel on monday pl; requested_info=postcode; when=monday.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I will be leaving from Ely.\nChunk 2: I need to depart broxbourne and travel on monday please.\nChunk 3: Yes, please for 8 people.\nChunk 4: I'm also looking for a recommendation on Mexican restaurants in the south.\nChunk 5: Not right now, but could I have the postcode No thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=search; day+=monday; destination+=depart broxbourne and travel on monday pl. C3 party_size+=8 people; acceptance=selected_option. C4 area+=south; cuisine+=mexican. C5 goal=request_info; requested_info+=postcode.\n\nDeep reasoning: Need goal=search, request_info; area=south; food=mexican; party_size=8 people; destination=depart broxbourne and travel on monday pl; requested_info=postcode; when=monday.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be leaving from Ely.\nChunk 2: I need to depart broxbourne and travel on monday please.\nChunk 3: Yes, please for 8 people.\nChunk 4: I'm also looking for a recommendation on Mexican restaurants in the south.\nChunk 5: Not right now, but could I have the postcode No thank you.", "input_token_count": 55, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is search; day: monday; destination: depart broxbourne and travel on monday pl. Next, party size: 8 people; acceptance: selected_option. Next, area: south; cuisine: mexican. Finally, the goal is request info; requested information: postcode. In summary, the goal is request info. intent: context_update.; day: monday; destination: depart broxbourne and travel on monday pl.; party size: 8 people; acceptance: selected_option.; area: south; cuisine: mexican.; requested information: postcode..", "trace": "C1 intent=context_update. C2 goal=search; day+=monday; destination+=depart broxbourne and travel on monday pl. C3 party_size+=8 people; acceptance=selected_option. C4 area+=south; cuisine+=mexican. C5 goal=request_info; requested_info+=postcode.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I will be leaving from Ely.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to depart broxbourne and travel on monday please.", "streaming_reasoning": "As more information arrives, the goal is search; day: monday; destination: depart broxbourne and travel on monday pl..", "trace": "goal=search; day+=monday; destination+=depart broxbourne and travel on monday pl."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, please for 8 people.", "streaming_reasoning": "As more information arrives, party size: 8 people; acceptance: selected_option..", "trace": "party_size+=8 people; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm also looking for a recommendation on Mexican restaurants in the south.", "streaming_reasoning": "As more information arrives, area: south; cuisine: mexican..", "trace": "area+=south; cuisine+=mexican."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Not right now, but could I have the postcode No thank you.", "streaming_reasoning": "Finally, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}]}, "output": {"deep_reasoning": "Need goal=search, request_info; area=south; food=mexican; party_size=8 people; destination=depart broxbourne and travel on monday pl; requested_info=postcode; when=monday.", "answer": "I can help with that and include the postcode once I find the matching option."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_002991", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks Here you are.\nChunk 2: You must return them within a month.\nChunk 3: What happens if I'm not finished with them in a month?\nChunk 4: You can come in and renew them unless someone else has reserved them.\nChunk 5: OK.\nChunk 6: Thank you very much for your trouble.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 casual_comment=must, return. C3 question=true. C4 casual_comment=come, renew. C5 [SKIP: backchannel_only]. C6 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thanks Here you are.\nChunk 2: You must return them within a month.\nChunk 3: What happens if I'm not finished with them in a month?\nChunk 4: You can come in and renew them unless someone else has reserved them.\nChunk 5: OK.\nChunk 6: Thank you very much for your trouble."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 casual_comment=must, return. C3 question=true. C4 casual_comment=come, renew. C5 [SKIP: backchannel_only]. C6 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks Here you are.\nChunk 2: You must return them within a month.\nChunk 3: What happens if I'm not finished with them in a month?\nChunk 4: You can come in and renew them unless someone else has reserved them.\nChunk 5: OK.\nChunk 6: Thank you very much for your trouble.", "input_token_count": 55, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on must. Next, the input provides additional context about question=true. Finally, the user comments on come.  Some chunks were skipped because they contained backchannel_only or thanks_only.", "trace": "C1 [SKIP: thanks_only]. C2 casual_comment=must, return. C3 question=true. C4 casual_comment=come, renew. C5 [SKIP: backchannel_only]. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thanks Here you are.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "You must return them within a month.", "streaming_reasoning": "As more information arrives, the user comments on must.", "trace": "casual_comment=must, return."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What happens if I'm not finished with them in a month?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "You can come in and renew them unless someone else has reserved them.", "streaming_reasoning": "As more information arrives, the user comments on come.", "trace": "casual_comment=come, renew."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "OK.", "streaming_reasoning": "The content at C5 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you very much for your trouble.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002382", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a moderately priced resturant in the centre of town.\nChunk 2: I would like lebanese food.\nChunk 3: Yes, I want to book a table for 3 people at 20:00 on thursday.\nChunk 4: No, I think that's all I need Thank you!", "streaming_reasoning": "C1 goal=search; area+=centre; price+=moderate. C2 domain=restaurant. C3 goal=confirm_booking; time+=3, 20:00; day+=thursday; party_size+=3 people; goal=confirm_booking. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; price=moderate; party_size=3 people; when=thursday, 3, 20:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a moderately priced resturant in the centre of town.\nChunk 2: I would like lebanese food.\nChunk 3: Yes, I want to book a table for 3 people at 20:00 on thursday.\nChunk 4: No, I think that's all I need Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre; price+=moderate. C2 domain=restaurant. C3 goal=confirm_booking; time+=3, 20:00; day+=thursday; party_size+=3 people; goal=confirm_booking. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; price=moderate; party_size=3 people; when=thursday, 3, 20:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a moderately priced resturant in the centre of town.\nChunk 2: I would like lebanese food.\nChunk 3: Yes, I want to book a table for 3 people at 20:00 on thursday.\nChunk 4: No, I think that's all I need Thank you!", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre; price: moderate. Next, the topic is restaurant. Finally, the goal is confirm booking.; time: 3; day: thursday; party size: 3 people.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant.. the goal is confirm booking.. area: centre; price: moderate.; time: 3; day: thursday; party size: 3 people.", "trace": "C1 goal=search; area+=centre; price+=moderate. C2 domain=restaurant. C3 goal=confirm_booking; time+=3, 20:00; day+=thursday; party_size+=3 people; goal=confirm_booking. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a moderately priced resturant in the centre of town.", "streaming_reasoning": "Initially, the goal is search; area: centre; price: moderate..", "trace": "goal=search; area+=centre; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like lebanese food.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I want to book a table for 3 people at 20:00 on thursday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 3; day: thursday; party size: 3 people.", "trace": "goal=confirm_booking; time+=3, 20:00; day+=thursday; party_size+=3 people; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, I think that's all I need Thank you!", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is moderate; party size is 3 people; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; price=moderate; party_size=3 people; when=thursday, 3, 20:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_002995", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I have to stay in bed today, but I'll be able to come tomorrow That's all right.\nChunk 3: Have a good rest until you feel well enough.\nChunk 4: Thank you, Mr. Smith Goodbye Goodbye, Lucy.\nChunk 5: I would like to take this opportunity to welcome Monica to our company and introduce her to her department and colleagues.\nChunk 6: For all of you, we hired Monica because she is a very professional accountant and we are very happy to have her in the finance department She has lots.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 [SKIP: closing_only]. C3 casual_comment=rest, until. C4 [SKIP: thanks_only]. C5 preference=true. C6 casual_comment=all, hired.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I have to stay in bed today, but I'll be able to come tomorrow That's all right.\nChunk 3: Have a good rest until you feel well enough.\nChunk 4: Thank you, Mr. Smith Goodbye Goodbye, Lucy.\nChunk 5: I would like to take this opportunity to welcome Monica to our company and introduce her to her department and colleagues.\nChunk 6: For all of you, we hired Monica because she is a very professional accountant and we are very happy to have her in the finance department She has lots."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 [SKIP: closing_only]. C3 casual_comment=rest, until. C4 [SKIP: thanks_only]. C5 preference=true. C6 casual_comment=all, hired.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I have to stay in bed today, but I'll be able to come tomorrow That's all right.\nChunk 3: Have a good rest until you feel well enough.\nChunk 4: Thank you, Mr. Smith Goodbye Goodbye, Lucy.\nChunk 5: I would like to take this opportunity to welcome Monica to our company and introduce her to her department and colleagues.\nChunk 6: For all of you, we hired Monica because she is a very professional accountant and we are very happy to have her in the finance department She has lots.", "input_token_count": 96, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on rest. Next, preference: true. Finally, the user comments on all.  Some chunks were skipped because they contained acknowledgement_only or closing_only or thanks_only. In summary, preference: true..", "trace": "C1 [SKIP: acknowledgement_only]. C2 [SKIP: closing_only]. C3 casual_comment=rest, until. C4 [SKIP: thanks_only]. C5 preference=true. C6 casual_comment=all, hired.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I have to stay in bed today, but I'll be able to come tomorrow That's all right.", "streaming_reasoning": "The content at C2 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Have a good rest until you feel well enough.", "streaming_reasoning": "As more information arrives, the user comments on rest.", "trace": "casual_comment=rest, until."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you, Mr. Smith Goodbye Goodbye, Lucy.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like to take this opportunity to welcome Monica to our company and introduce her to her department and colleagues.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "For all of you, we hired Monica because she is a very professional accountant and we are very happy to have her in the finance department She has lots.", "streaming_reasoning": "Finally, the user comments on all.", "trace": "casual_comment=all, hired."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002383", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No any part of town will work.\nChunk 2: Can I just get the area, phone number, and postcode of it?\nChunk 3: Thanks.\nChunk 4: Also I am looking for a guesthouse hotel with 2 stars in the north.\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the north part of town Yes, please.\nChunk 7: I need a room for 1 person, 3 nights.\nChunk 8: I'll be arriving on Saturday.\nChunk 9: The Ashley is fine.\nChunk 10: Thank you, that should be all.", "streaming_reasoning": "C1 goal=modify_constraint. C2 goal=request_info; requested_info+=phone, postcode. C3 [SKIP: thanks_only]. C4 domain=hotel; goal=search; area+=north; hotel_type+=guesthouse, hotel; stars+=2 stars. C5 destination+=find a hotel. C6 [SKIP: repeated_information]. C7 stay_length+=3 nights. C8 day+=saturday. C9 intent=context_update. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=request_info, search; area=north; stay_length=3 nights; stars=2 stars; destination=find a hotel; requested_info=phone, postcode; when=saturday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No any part of town will work.\nChunk 2: Can I just get the area, phone number, and postcode of it?\nChunk 3: Thanks.\nChunk 4: Also I am looking for a guesthouse hotel with 2 stars in the north.\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the north part of town Yes, please.\nChunk 7: I need a room for 1 person, 3 nights.\nChunk 8: I'll be arriving on Saturday.\nChunk 9: The Ashley is fine.\nChunk 10: Thank you, that should be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=modify_constraint. C2 goal=request_info; requested_info+=phone, postcode. C3 [SKIP: thanks_only]. C4 domain=hotel; goal=search; area+=north; hotel_type+=guesthouse, hotel; stars+=2 stars. C5 destination+=find a hotel. C6 [SKIP: repeated_information]. C7 stay_length+=3 nights. C8 day+=saturday. C9 intent=context_update. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info, search; area=north; stay_length=3 nights; stars=2 stars; destination=find a hotel; requested_info=phone, postcode; when=saturday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No any part of town will work.\nChunk 2: Can I just get the area, phone number, and postcode of it?\nChunk 3: Thanks.\nChunk 4: Also I am looking for a guesthouse hotel with 2 stars in the north.\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the north part of town Yes, please.\nChunk 7: I need a room for 1 person, 3 nights.\nChunk 8: I'll be arriving on Saturday.\nChunk 9: The Ashley is fine.\nChunk 10: Thank you, that should be all.", "input_token_count": 95, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is modify constraint. Next, the goal is request info; requested information: phone. Next, the topic is hotel; the goal is search; area: north; hotel type: guesthouse; star rating: 2 stars. Next, destination: find a hotel. Next, stay length: 3 nights. Next, day: saturday. Finally, intent: context_update.  Some chunks were skipped because they contained repeated_information or thanks_only. In summary, The overall topic is hotel. the goal is search. requested information: phone; area: north; hotel type: guesthouse; star rating: 2 stars.; destination: find a hotel.; stay length: 3 nights.; day: saturday.; intent: context_update..", "trace": "C1 goal=modify_constraint. C2 goal=request_info; requested_info+=phone, postcode. C3 [SKIP: thanks_only]. C4 domain=hotel; goal=search; area+=north; hotel_type+=guesthouse, hotel; stars+=2 stars. C5 destination+=find a hotel. C6 [SKIP: repeated_information]. C7 stay_length+=3 nights. C8 day+=saturday. C9 intent=context_update. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No any part of town will work.", "streaming_reasoning": "Initially, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I just get the area, phone number, and postcode of it?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Also I am looking for a guesthouse hotel with 2 stars in the north.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; area: north; hotel type: guesthouse; star rating: 2 stars..", "trace": "domain=hotel; goal=search; area+=north; hotel_type+=guesthouse, hotel; stars+=2 stars."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, destination: find a hotel..", "trace": "destination+=find a hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It should be in the north part of town Yes, please.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need a room for 1 person, 3 nights.", "streaming_reasoning": "As more information arrives, stay length: 3 nights..", "trace": "stay_length+=3 nights."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'll be arriving on Saturday.", "streaming_reasoning": "As more information arrives, day: saturday..", "trace": "day+=saturday."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "The Ashley is fine.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you, that should be all.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: area is north; stay length is 3 nights; star rating is 2 stars; destination is find a hotel; requested information is phone; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search; area=north; stay_length=3 nights; stars=2 stars; destination=find a hotel; requested_info=phone, postcode; when=saturday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002384", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant.\nChunk 2: The restaurant should be in the centre and should serve persian food.\nChunk 3: Yes, I am looking for a moderate price range.\nChunk 4: What about modern european foods?\nChunk 5: Yes, I want a reservation for 8 people at 16:00 on Sunday.\nChunk 6: ok ill check latter.", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 area+=centre; cuisine+=persian. C3 price+=moderate; acceptance=selected_option. C4 goal=recommendation; cuisine+=european. C5 goal=confirm_booking; time+=8, 16:00; day+=sunday; party_size+=8 people; goal=confirm_booking. C6 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, booking, confirm_booking; area=centre; food=persian, european; price=moderate; party_size=8 people; when=sunday, 8, 16:00.", "answer": "Got it. I will use restaurant, centre, persian, european, moderate, 8 people, sunday, 8, 16:00 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant.\nChunk 2: The restaurant should be in the centre and should serve persian food.\nChunk 3: Yes, I am looking for a moderate price range.\nChunk 4: What about modern european foods?\nChunk 5: Yes, I want a reservation for 8 people at 16:00 on Sunday.\nChunk 6: ok ill check latter."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 area+=centre; cuisine+=persian. C3 price+=moderate; acceptance=selected_option. C4 goal=recommendation; cuisine+=european. C5 goal=confirm_booking; time+=8, 16:00; day+=sunday; party_size+=8 people; goal=confirm_booking. C6 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, booking, confirm_booking; area=centre; food=persian, european; price=moderate; party_size=8 people; when=sunday, 8, 16:00.\n\nAnswer: Got it. I will use restaurant, centre, persian, european, moderate, 8 people, sunday, 8, 16:00 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant.\nChunk 2: The restaurant should be in the centre and should serve persian food.\nChunk 3: Yes, I am looking for a moderate price range.\nChunk 4: What about modern european foods?\nChunk 5: Yes, I want a reservation for 8 people at 16:00 on Sunday.\nChunk 6: ok ill check latter.", "input_token_count": 61, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, area: centre; cuisine: persian. Next, price: moderate; acceptance: selected_option. Next, the goal is recommendation; cuisine: european. Next, the goal is confirm booking.; time: 8; day: sunday; party size: 8 people. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is confirm booking.. area: centre; cuisine: persian., european.; price: moderate; acceptance: selected_option.; time: 8; day: sunday; party size: 8 people; intent: context_update..", "trace": "C1 domain=restaurant; goal=search. C2 area+=centre; cuisine+=persian. C3 price+=moderate; acceptance=selected_option. C4 goal=recommendation; cuisine+=european. C5 goal=confirm_booking; time+=8, 16:00; day+=sunday; party_size+=8 people; goal=confirm_booking. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The restaurant should be in the centre and should serve persian food.", "streaming_reasoning": "As more information arrives, area: centre; cuisine: persian..", "trace": "area+=centre; cuisine+=persian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I am looking for a moderate price range.", "streaming_reasoning": "As more information arrives, price: moderate; acceptance: selected_option..", "trace": "price+=moderate; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What about modern european foods?", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: european..", "trace": "goal=recommendation; cuisine+=european."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, I want a reservation for 8 people at 16:00 on Sunday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 8; day: sunday; party size: 8 people.", "trace": "goal=confirm_booking; time+=8, 16:00; day+=sunday; party_size+=8 people; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "ok ill check latter.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is persian; price is moderate; party size is 8 people; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use restaurant, centre, persian, european, moderate, 8 people, sunday, 8, 16:00 and move the task forward.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, booking, confirm_booking; area=centre; food=persian, european; price=moderate; party_size=8 people; when=sunday, 8, 16:00."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002385", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, price does not matter.\nChunk 2: Right now I'd just like a recommendation.\nChunk 3: Let's go with that What's the address?\nChunk 4: I want to find a hotel.\nChunk 5: The time is 09:15.\nChunk 6: Please make a booking Great!\nChunk 7: Thank you for your help.\nChunk 8: No That is all Again thank you.\nChunk 9: thank you for your help goodbye.", "streaming_reasoning": "C1 goal=modify_constraint. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C5 time+=09:15. C6 goal=booking. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=request_info, search, booking; destination=find a hotel; requested_info=address; when=09:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, price does not matter.\nChunk 2: Right now I'd just like a recommendation.\nChunk 3: Let's go with that What's the address?\nChunk 4: I want to find a hotel.\nChunk 5: The time is 09:15.\nChunk 6: Please make a booking Great!\nChunk 7: Thank you for your help.\nChunk 8: No That is all Again thank you.\nChunk 9: thank you for your help goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=modify_constraint. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C5 time+=09:15. C6 goal=booking. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info, search, booking; destination=find a hotel; requested_info=address; when=09:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, price does not matter.\nChunk 2: Right now I'd just like a recommendation.\nChunk 3: Let's go with that What's the address?\nChunk 4: I want to find a hotel.\nChunk 5: The time is 09:15.\nChunk 6: Please make a booking Great!\nChunk 7: Thank you for your help.\nChunk 8: No That is all Again thank you.\nChunk 9: thank you for your help goodbye.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is modify constraint. Next, intent: context_update. Next, the goal is request info; requested information: address. Next, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, time: 09:15. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is booking.. intent: context_update.; requested information: address.; hotel type: hotel; destination: find a hotel.; time: 09:15..", "trace": "C1 goal=modify_constraint. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C5 time+=09:15. C6 goal=booking. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, price does not matter.", "streaming_reasoning": "Initially, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Right now I'd just like a recommendation.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Let's go with that What's the address?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is 09:15.", "streaming_reasoning": "As more information arrives, time: 09:15..", "trace": "time+=09:15."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking Great!", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No That is all Again thank you.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "thank you for your help goodbye.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: destination is find a hotel; requested information is address; timing is 09:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search, booking; destination=find a hotel; requested_info=address; when=09:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002386", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: Actually, I would like to book 8 tickets for that train, please.\nChunk 3: I want to find a cheap korean restaurant.\nChunk 4: It should be in the west part of town.\nChunk 5: Why don't you try vietnamese food.\nChunk 6: Yes, please book it.\nChunk 7: I would also like the address.\nChunk 8: I just needed that info Thank you.\nChunk 9: No thats all i wanted thank you.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=booking. C3 domain=restaurant; goal=search; cuisine+=korean; price+=cheap; destination+=find a cheap korean restaurant. C4 area+=west. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 goal=request_info; requested_info+=address. C8 intent=context_update. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, restaurant; goal=booking, search, request_info; area=west; food=korean; price=cheap; destination=find a cheap korean restaurant; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: Actually, I would like to book 8 tickets for that train, please.\nChunk 3: I want to find a cheap korean restaurant.\nChunk 4: It should be in the west part of town.\nChunk 5: Why don't you try vietnamese food.\nChunk 6: Yes, please book it.\nChunk 7: I would also like the address.\nChunk 8: I just needed that info Thank you.\nChunk 9: No thats all i wanted thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=booking. C3 domain=restaurant; goal=search; cuisine+=korean; price+=cheap; destination+=find a cheap korean restaurant. C4 area+=west. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 goal=request_info; requested_info+=address. C8 intent=context_update. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=booking, search, request_info; area=west; food=korean; price=cheap; destination=find a cheap korean restaurant; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: Actually, I would like to book 8 tickets for that train, please.\nChunk 3: I want to find a cheap korean restaurant.\nChunk 4: It should be in the west part of town.\nChunk 5: Why don't you try vietnamese food.\nChunk 6: Yes, please book it.\nChunk 7: I would also like the address.\nChunk 8: I just needed that info Thank you.\nChunk 9: No thats all i wanted thank you.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is booking. Next, the topic is restaurant; the goal is search; cuisine: korean; price: cheap; destination: find a cheap korean restaurant. Next, area: west. Next, intent: context_update. Next, the goal is request info; requested information: address. Finally, intent: context_update.  Some chunks were skipped because they contained acknowledgement_only or closing_only or repeated_information. In summary, The overall topic is restaurant. the goal is request info. cuisine: korean; price: cheap; destination: find a cheap korean restaurant.; area: west.; intent: context_update.; requested information: address..", "trace": "C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=booking. C3 domain=restaurant; goal=search; cuisine+=korean; price+=cheap; destination+=find a cheap korean restaurant. C4 area+=west. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 goal=request_info; requested_info+=address. C8 intent=context_update. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Actually, I would like to book 8 tickets for that train, please.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is booking..", "trace": "domain=train; goal=booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a cheap korean restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; cuisine: korean; price: cheap; destination: find a cheap korean restaurant..", "trace": "domain=restaurant; goal=search; cuisine+=korean; price+=cheap; destination+=find a cheap korean restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It should be in the west part of town.", "streaming_reasoning": "As more information arrives, area: west..", "trace": "area+=west."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Why don't you try vietnamese food.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, please book it.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I would also like the address.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I just needed that info Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No thats all i wanted thank you.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: area is west; cuisine is korean; price is cheap; destination is find a cheap korean restaurant; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=booking, search, request_info; area=west; food=korean; price=cheap; destination=find a cheap korean restaurant; requested_info=address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002387", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Which ever one is your favorite will do.\nChunk 2: Can I have their contact information and what is the entrance fee?\nChunk 3: I need the post code also for the museum please.\nChunk 4: I want to find a guesthouse.\nChunk 5: It should be in the north part of town.\nChunk 6: Not right now, but could you tell me their postcode?\nChunk 7: Yeah, can you have a taxi pick me up at the Acorn and take me to the Artworks, say around 24:45?\nChunk 8: No that's all I needed thank you!", "streaming_reasoning": "C1 goal=recommendation. C2 goal=request_info; requested_info+=entrance_fee. C3 domain=attraction; goal=search; requested_info+=postcode. C4 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C5 area+=north. C6 goal=request_info. C7 domain=taxi; time+=24:45; destination+=the artworks. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, hotel, taxi; goal=recommendation, request_info, search; area=north; destination=find a guesthouse, the artworks; requested_info=entrance_fee, postcode; when=24:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Which ever one is your favorite will do.\nChunk 2: Can I have their contact information and what is the entrance fee?\nChunk 3: I need the post code also for the museum please.\nChunk 4: I want to find a guesthouse.\nChunk 5: It should be in the north part of town.\nChunk 6: Not right now, but could you tell me their postcode?\nChunk 7: Yeah, can you have a taxi pick me up at the Acorn and take me to the Artworks, say around 24:45?\nChunk 8: No that's all I needed thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=recommendation. C2 goal=request_info; requested_info+=entrance_fee. C3 domain=attraction; goal=search; requested_info+=postcode. C4 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C5 area+=north. C6 goal=request_info. C7 domain=taxi; time+=24:45; destination+=the artworks. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, hotel, taxi; goal=recommendation, request_info, search; area=north; destination=find a guesthouse, the artworks; requested_info=entrance_fee, postcode; when=24:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Which ever one is your favorite will do.\nChunk 2: Can I have their contact information and what is the entrance fee?\nChunk 3: I need the post code also for the museum please.\nChunk 4: I want to find a guesthouse.\nChunk 5: It should be in the north part of town.\nChunk 6: Not right now, but could you tell me their postcode?\nChunk 7: Yeah, can you have a taxi pick me up at the Acorn and take me to the Artworks, say around 24:45?\nChunk 8: No that's all I needed thank you!", "input_token_count": 100, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is recommendation. Next, the goal is request info; requested information: entrance_fee. Next, the topic is attraction; the goal is search; requested information: postcode. Next, the topic is hotel; hotel type: guesthouse; destination: find a guesthouse. Next, area: north. Next, the goal is request info. Finally, the topic is taxi; time: 24:45; destination: the artworks.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is request info.. requested information: entrance_fee., postcode.; hotel type: guesthouse; destination: find a guesthouse., the artworks.; area: north.; time: 24:45.", "trace": "C1 goal=recommendation. C2 goal=request_info; requested_info+=entrance_fee. C3 domain=attraction; goal=search; requested_info+=postcode. C4 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C5 area+=north. C6 goal=request_info. C7 domain=taxi; time+=24:45; destination+=the artworks. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Which ever one is your favorite will do.", "streaming_reasoning": "Initially, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I have their contact information and what is the entrance fee?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need the post code also for the museum please.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is search; requested information: postcode..", "trace": "domain=attraction; goal=search; requested_info+=postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want to find a guesthouse.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse; destination: find a guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Not right now, but could you tell me their postcode?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yeah, can you have a taxi pick me up at the Acorn and take me to the Artworks, say around 24:45?", "streaming_reasoning": "As more information arrives, the topic is taxi; time: 24:45; destination: the artworks..", "trace": "domain=taxi; time+=24:45; destination+=the artworks."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No that's all I needed thank you!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of recommendation. Key information: area is north; destination is find a guesthouse; requested information is entrance_fee; timing is 24:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, hotel, taxi; goal=recommendation, request_info, search; area=north; destination=find a guesthouse, the artworks; requested_info=entrance_fee, postcode; when=24:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002388", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you please find me cinemas?\nChunk 2: What is the postcode and phone number for one of them Thank you!\nChunk 3: Yes, I also need a train to Cambridge that arrives by 09:00, please.\nChunk 4: I will be departing from Leicester on Friday.\nChunk 5: I need help with train.\nChunk 6: The time is today.\nChunk 7: Please make a booking.\nChunk 8: I also need the travel time.\nChunk 9: I also need the price No that's all.\nChunk 10: Thanks for your help.", "streaming_reasoning": "C1 goal=search. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=train; time+=09:00; destination+=cambridge that arrives by 09:00; acceptance=selected_option. C4 day+=friday; departure+=leicester on friday. C5 intent=context_update. C6 day+=today. C7 goal=booking. C8 requested_info+=travel_time. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search, request_info, booking; destination=cambridge that arrives by 09:00; departure=leicester on friday; requested_info=phone, postcode, travel_time; when=friday, today, 09:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you please find me cinemas?\nChunk 2: What is the postcode and phone number for one of them Thank you!\nChunk 3: Yes, I also need a train to Cambridge that arrives by 09:00, please.\nChunk 4: I will be departing from Leicester on Friday.\nChunk 5: I need help with train.\nChunk 6: The time is today.\nChunk 7: Please make a booking.\nChunk 8: I also need the travel time.\nChunk 9: I also need the price No that's all.\nChunk 10: Thanks for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=train; time+=09:00; destination+=cambridge that arrives by 09:00; acceptance=selected_option. C4 day+=friday; departure+=leicester on friday. C5 intent=context_update. C6 day+=today. C7 goal=booking. C8 requested_info+=travel_time. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking; destination=cambridge that arrives by 09:00; departure=leicester on friday; requested_info=phone, postcode, travel_time; when=friday, today, 09:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you please find me cinemas?\nChunk 2: What is the postcode and phone number for one of them Thank you!\nChunk 3: Yes, I also need a train to Cambridge that arrives by 09:00, please.\nChunk 4: I will be departing from Leicester on Friday.\nChunk 5: I need help with train.\nChunk 6: The time is today.\nChunk 7: Please make a booking.\nChunk 8: I also need the travel time.\nChunk 9: I also need the price No that's all.\nChunk 10: Thanks for your help.", "input_token_count": 92, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, the goal is request info; requested information: phone. Next, the topic is train; time: 09:00; destination: cambridge that arrives by 09:00; acceptance: selected_option. Next, day: friday; departure point: leicester on friday. Next, intent: context_update. Next, day: today. Next, the goal is booking. Finally, requested information: travel_time.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is booking.. requested information: phone, travel_time.; time: 09:00; destination: cambridge that arrives by 09:00; acceptance: selected_option.; day: friday, today.; departure point: leicester on friday.; intent: context_update..", "trace": "C1 goal=search. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=train; time+=09:00; destination+=cambridge that arrives by 09:00; acceptance=selected_option. C4 day+=friday; departure+=leicester on friday. C5 intent=context_update. C6 day+=today. C7 goal=booking. C8 requested_info+=travel_time. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you please find me cinemas?", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the postcode and phone number for one of them Thank you!", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I also need a train to Cambridge that arrives by 09:00, please.", "streaming_reasoning": "As more information arrives, the topic is train; time: 09:00; destination: cambridge that arrives by 09:00; acceptance: selected_option..", "trace": "domain=train; time+=09:00; destination+=cambridge that arrives by 09:00; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I will be departing from Leicester on Friday.", "streaming_reasoning": "As more information arrives, day: friday; departure point: leicester on friday..", "trace": "day+=friday; departure+=leicester on friday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is today.", "streaming_reasoning": "As more information arrives, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need the travel time.", "streaming_reasoning": "As more information arrives, requested information: travel_time..", "trace": "requested_info+=travel_time."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need the price No that's all.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thanks for your help.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge that arrives by 09:00; departure point is leicester on friday; requested information is phone; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking; destination=cambridge that arrives by 09:00; departure=leicester on friday; requested_info=phone, postcode, travel_time; when=friday, today, 09:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002389", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to leave after 16:45, depart from Birmingham New Street.\nChunk 2: This time works fine for me.\nChunk 3: thanks, i'm also looking for some museums.\nChunk 4: Yes, do you have any in the centre?\nChunk 5: Anyone of those would work.\nChunk 6: Could you recommend something for me?\nChunk 7: I'll need the phone number, and address as well.\nChunk 8: What area is it in?", "streaming_reasoning": "C1 goal=search; time+=16:45; departure+=birmingham new street. C2 intent=context_update. C3 [SKIP: thanks_only]. C4 area+=centre; acceptance=selected_option. C5 intent=context_update. C6 goal=recommendation. C7 goal=request_info; requested_info+=address, phone. C8 goal=request_info.", "deep_reasoning": "Need goal=search, recommendation, request_info; area=centre; departure=birmingham new street; requested_info=address, phone; when=16:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to leave after 16:45, depart from Birmingham New Street.\nChunk 2: This time works fine for me.\nChunk 3: thanks, i'm also looking for some museums.\nChunk 4: Yes, do you have any in the centre?\nChunk 5: Anyone of those would work.\nChunk 6: Could you recommend something for me?\nChunk 7: I'll need the phone number, and address as well.\nChunk 8: What area is it in?"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; time+=16:45; departure+=birmingham new street. C2 intent=context_update. C3 [SKIP: thanks_only]. C4 area+=centre; acceptance=selected_option. C5 intent=context_update. C6 goal=recommendation. C7 goal=request_info; requested_info+=address, phone. C8 goal=request_info.\n\nDeep reasoning: Need goal=search, recommendation, request_info; area=centre; departure=birmingham new street; requested_info=address, phone; when=16:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to leave after 16:45, depart from Birmingham New Street.\nChunk 2: This time works fine for me.\nChunk 3: thanks, i'm also looking for some museums.\nChunk 4: Yes, do you have any in the centre?\nChunk 5: Anyone of those would work.\nChunk 6: Could you recommend something for me?\nChunk 7: I'll need the phone number, and address as well.\nChunk 8: What area is it in?", "input_token_count": 74, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; time: 16:45; departure point: birmingham new street. Next, intent: context_update. Next, area: centre; acceptance: selected_option. Next, intent: context_update. Next, the goal is recommendation. Next, the goal is request info; requested information: address. Finally, the goal is request info.  Some chunks were skipped because they contained thanks_only. In summary, the goal is request info.. time: 16:45; departure point: birmingham new street.; intent: context_update.; area: centre; acceptance: selected_option.; requested information: address.", "trace": "C1 goal=search; time+=16:45; departure+=birmingham new street. C2 intent=context_update. C3 [SKIP: thanks_only]. C4 area+=centre; acceptance=selected_option. C5 intent=context_update. C6 goal=recommendation. C7 goal=request_info; requested_info+=address, phone. C8 goal=request_info.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to leave after 16:45, depart from Birmingham New Street.", "streaming_reasoning": "Initially, the goal is search; time: 16:45; departure point: birmingham new street..", "trace": "goal=search; time+=16:45; departure+=birmingham new street."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "This time works fine for me.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "thanks, i'm also looking for some museums.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, do you have any in the centre?", "streaming_reasoning": "As more information arrives, area: centre; acceptance: selected_option..", "trace": "area+=centre; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Anyone of those would work.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could you recommend something for me?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'll need the phone number, and address as well.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "What area is it in?", "streaming_reasoning": "Finally, the goal is request info..", "trace": "goal=request_info."}]}, "output": {"deep_reasoning": "Need goal=search, recommendation, request_info; area=centre; departure=birmingham new street; requested_info=address, phone; when=16:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002390", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a restaurant in the centre of Cambridge which is pretty cheap in terms of prices.\nChunk 2: cheap food is preferred, but i'm not picky.\nChunk 3: I want to find a restaurant.\nChunk 4: It is for 5 people.\nChunk 5: The time is thursday, 5, 12:30.\nChunk 6: Please make a booking.\nChunk 7: I am also looking for the Cambridge Belfry.\nChunk 8: Yes.\nChunk 9: For the same group of people for 3 nights starting on the same day Yes that's all.\nChunk 10: Thank you very much.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; price+=cheap. C2 preference=flexible. C3 destination+=find a restaurant. C4 party_size+=5 people. C5 time+=5, 12:30; day+=thursday. C6 goal=booking. C7 intent=context_update. C8 goal=confirm_booking. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking; area=centre; price=cheap; party_size=5 people; destination=find a restaurant; when=thursday, 5, 12:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a restaurant in the centre of Cambridge which is pretty cheap in terms of prices.\nChunk 2: cheap food is preferred, but i'm not picky.\nChunk 3: I want to find a restaurant.\nChunk 4: It is for 5 people.\nChunk 5: The time is thursday, 5, 12:30.\nChunk 6: Please make a booking.\nChunk 7: I am also looking for the Cambridge Belfry.\nChunk 8: Yes.\nChunk 9: For the same group of people for 3 nights starting on the same day Yes that's all.\nChunk 10: Thank you very much."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; price+=cheap. C2 preference=flexible. C3 destination+=find a restaurant. C4 party_size+=5 people. C5 time+=5, 12:30; day+=thursday. C6 goal=booking. C7 intent=context_update. C8 goal=confirm_booking. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking; area=centre; price=cheap; party_size=5 people; destination=find a restaurant; when=thursday, 5, 12:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a restaurant in the centre of Cambridge which is pretty cheap in terms of prices.\nChunk 2: cheap food is preferred, but i'm not picky.\nChunk 3: I want to find a restaurant.\nChunk 4: It is for 5 people.\nChunk 5: The time is thursday, 5, 12:30.\nChunk 6: Please make a booking.\nChunk 7: I am also looking for the Cambridge Belfry.\nChunk 8: Yes.\nChunk 9: For the same group of people for 3 nights starting on the same day Yes that's all.\nChunk 10: Thank you very much.", "input_token_count": 98, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: cheap. Next, preference: flexible. Next, destination: find a restaurant. Next, party size: 5 people. Next, time: 5; day: thursday. Next, the goal is booking. Next, intent: context_update. Finally, the goal is confirm booking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is confirm booking.. area: centre; price: cheap.; preference: flexible.; destination: find a restaurant.; party size: 5 people.; time: 5; day: thursday.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; area+=centre; price+=cheap. C2 preference=flexible. C3 destination+=find a restaurant. C4 party_size+=5 people. C5 time+=5, 12:30; day+=thursday. C6 goal=booking. C7 intent=context_update. C8 goal=confirm_booking. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a restaurant in the centre of Cambridge which is pretty cheap in terms of prices.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: cheap..", "trace": "domain=restaurant; goal=search; area+=centre; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "cheap food is preferred, but i'm not picky.", "streaming_reasoning": "As more information arrives, preference: flexible..", "trace": "preference=flexible."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, destination: find a restaurant..", "trace": "destination+=find a restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It is for 5 people.", "streaming_reasoning": "As more information arrives, party size: 5 people..", "trace": "party_size+=5 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is thursday, 5, 12:30.", "streaming_reasoning": "As more information arrives, time: 5; day: thursday..", "trace": "time+=5, 12:30; day+=thursday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am also looking for the Cambridge Belfry.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Yes.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "For the same group of people for 3 nights starting on the same day Yes that's all.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is cheap; party size is 5 people; destination is find a restaurant; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking; area=centre; price=cheap; party_size=5 people; destination=find a restaurant; when=thursday, 5, 12:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003004", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I've got it Thank you.\nChunk 2: Now I see that you are my true friend.\nChunk 3: Most of my so-called friends left me at the moment my company went bankrupt.\nChunk 4: You are the only one who has stood by me the whole time.\nChunk 5: I am just doing what I think I should do.\nChunk 6: Thank you for being a friend of mine.\nChunk 7: This isn't like you...\nChunk 8: Well, I hope you will have a nice flight and a successful start in business.", "streaming_reasoning": "C1 casual_comment=i've, thank. C2 casual_comment=now, see. C3 casual_comment=most, so-called. C4 casual_comment=one, who. C5 casual_comment=think. C6 [SKIP: thanks_only]. C7 preference=true. C8 casual_comment=hope, will.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I've got it Thank you.\nChunk 2: Now I see that you are my true friend.\nChunk 3: Most of my so-called friends left me at the moment my company went bankrupt.\nChunk 4: You are the only one who has stood by me the whole time.\nChunk 5: I am just doing what I think I should do.\nChunk 6: Thank you for being a friend of mine.\nChunk 7: This isn't like you...\nChunk 8: Well, I hope you will have a nice flight and a successful start in business."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=i've, thank. C2 casual_comment=now, see. C3 casual_comment=most, so-called. C4 casual_comment=one, who. C5 casual_comment=think. C6 [SKIP: thanks_only]. C7 preference=true. C8 casual_comment=hope, will.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I've got it Thank you.\nChunk 2: Now I see that you are my true friend.\nChunk 3: Most of my so-called friends left me at the moment my company went bankrupt.\nChunk 4: You are the only one who has stood by me the whole time.\nChunk 5: I am just doing what I think I should do.\nChunk 6: Thank you for being a friend of mine.\nChunk 7: This isn't like you...\nChunk 8: Well, I hope you will have a nice flight and a successful start in business.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on i've. Next, the user comments on now. Next, the user comments on most. Next, the user comments on one. Next, the user comments on think. Next, preference: true. Finally, the user comments on hope.  Some chunks were skipped because they contained thanks_only. In summary, preference: true..", "trace": "C1 casual_comment=i've, thank. C2 casual_comment=now, see. C3 casual_comment=most, so-called. C4 casual_comment=one, who. C5 casual_comment=think. C6 [SKIP: thanks_only]. C7 preference=true. C8 casual_comment=hope, will.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I've got it Thank you.", "streaming_reasoning": "Initially, the user comments on i've.", "trace": "casual_comment=i've, thank."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Now I see that you are my true friend.", "streaming_reasoning": "As more information arrives, the user comments on now.", "trace": "casual_comment=now, see."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Most of my so-called friends left me at the moment my company went bankrupt.", "streaming_reasoning": "As more information arrives, the user comments on most.", "trace": "casual_comment=most, so-called."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "You are the only one who has stood by me the whole time.", "streaming_reasoning": "As more information arrives, the user comments on one.", "trace": "casual_comment=one, who."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I am just doing what I think I should do.", "streaming_reasoning": "As more information arrives, the user comments on think..", "trace": "casual_comment=think."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for being a friend of mine.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "This isn't like you...", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Well, I hope you will have a nice flight and a successful start in business.", "streaming_reasoning": "Finally, the user comments on hope.", "trace": "casual_comment=hope, will."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002391", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to find a moderately priced restaurant in the west part of town.\nChunk 2: west part of town.\nChunk 3: Can you please let me know the address?\nChunk 4: It should be in the west part of town.\nChunk 5: I also need the address.\nChunk 6: I also need the price Thank you goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=west; price+=moderate; destination+=find a moderately priced restaurant in th. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: repeated_information]. C5 [SKIP: repeated_information]. C6 requested_info+=price.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=west; price=moderate; destination=find a moderately priced restaurant in th; requested_info=address, price.", "answer": "I can help with that and include the address, price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to find a moderately priced restaurant in the west part of town.\nChunk 2: west part of town.\nChunk 3: Can you please let me know the address?\nChunk 4: It should be in the west part of town.\nChunk 5: I also need the address.\nChunk 6: I also need the price Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=west; price+=moderate; destination+=find a moderately priced restaurant in th. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: repeated_information]. C5 [SKIP: repeated_information]. C6 requested_info+=price.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=west; price=moderate; destination=find a moderately priced restaurant in th; requested_info=address, price.\n\nAnswer: I can help with that and include the address, price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to find a moderately priced restaurant in the west part of town.\nChunk 2: west part of town.\nChunk 3: Can you please let me know the address?\nChunk 4: It should be in the west part of town.\nChunk 5: I also need the address.\nChunk 6: I also need the price Thank you goodbye.", "input_token_count": 61, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: west; price: moderate; destination: find a moderately priced restaurant in th. Next, intent: context_update. Next, the goal is request info; requested information: address. Finally, requested information: price.  Some chunks were skipped because they contained repeated_information. In summary, The overall topic is restaurant. the goal is request info. area: west; price: moderate; destination: find a moderately priced restaurant in th.; intent: context_update.; requested information: address., price..", "trace": "C1 domain=restaurant; goal=search; area+=west; price+=moderate; destination+=find a moderately priced restaurant in th. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: repeated_information]. C5 [SKIP: repeated_information]. C6 requested_info+=price.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to find a moderately priced restaurant in the west part of town.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: west; price: moderate; destination: find a moderately priced restaurant in th..", "trace": "domain=restaurant; goal=search; area+=west; price+=moderate; destination+=find a moderately priced restaurant in th."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "west part of town.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you please let me know the address?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It should be in the west part of town.", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the address.", "streaming_reasoning": "The content at C5 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need the price Thank you goodbye.", "streaming_reasoning": "Finally, requested information: price..", "trace": "requested_info+=price."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is west; price is moderate; destination is find a moderately priced restaurant in th; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, price once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=west; price=moderate; destination=find a moderately priced restaurant in th; requested_info=address, price."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002392", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you tell me the address, including post code?\nChunk 2: I am looking for gastropub food around the same area as the hotel.\nChunk 3: No particular price range.\nChunk 4: Which one do you recommend?\nChunk 5: Yes, If you could that would be great Thank you.\nChunk 6: I need a table for 8 at 15:45 on Friday.\nChunk 7: No that was all I needed thank you so much.", "streaming_reasoning": "C1 goal=request_info; requested_info+=address, postcode. C2 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C3 goal=modify_constraint. C4 goal=recommendation. C5 acceptance=selected_option. C6 time+=8, 15:45; day+=friday. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel; goal=request_info, search, modify_constraint, recommendation; requested_info=address, postcode; when=friday, 8, 15:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you tell me the address, including post code?\nChunk 2: I am looking for gastropub food around the same area as the hotel.\nChunk 3: No particular price range.\nChunk 4: Which one do you recommend?\nChunk 5: Yes, If you could that would be great Thank you.\nChunk 6: I need a table for 8 at 15:45 on Friday.\nChunk 7: No that was all I needed thank you so much."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address, postcode. C2 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C3 goal=modify_constraint. C4 goal=recommendation. C5 acceptance=selected_option. C6 time+=8, 15:45; day+=friday. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel; goal=request_info, search, modify_constraint, recommendation; requested_info=address, postcode; when=friday, 8, 15:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you tell me the address, including post code?\nChunk 2: I am looking for gastropub food around the same area as the hotel.\nChunk 3: No particular price range.\nChunk 4: Which one do you recommend?\nChunk 5: Yes, If you could that would be great Thank you.\nChunk 6: I need a table for 8 at 15:45 on Friday.\nChunk 7: No that was all I needed thank you so much.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the topic is hotel; the goal is modify constraint; hotel type: hotel. Next, the goal is modify constraint. Next, the goal is recommendation. Next, acceptance: selected_option. Finally, time: 8; day: friday.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is recommendation.. requested information: address; hotel type: hotel.; acceptance: selected_option.; time: 8; day: friday..", "trace": "C1 goal=request_info; requested_info+=address, postcode. C2 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C3 goal=modify_constraint. C4 goal=recommendation. C5 acceptance=selected_option. C6 time+=8, 15:45; day+=friday. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you tell me the address, including post code?", "streaming_reasoning": "Initially, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am looking for gastropub food around the same area as the hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is modify constraint; hotel type: hotel..", "trace": "domain=hotel; goal=modify_constraint; hotel_type+=hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No particular price range.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Which one do you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, If you could that would be great Thank you.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need a table for 8 at 15:45 on Friday.", "streaming_reasoning": "As more information arrives, time: 8; day: friday..", "trace": "time+=8, 15:45; day+=friday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No that was all I needed thank you so much.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=request_info, search, modify_constraint, recommendation; requested_info=address, postcode; when=friday, 8, 15:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002393", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a moderately priced polish food restaurant.\nChunk 2: yes, can you please check for a turkish restaurant?\nChunk 3: May I have the address for Anatolia Thank You.", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=moderate. C2 cuisine+=turkish; acceptance=selected_option. C3 goal=request_info; requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; food=turkish; price=moderate; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a moderately priced polish food restaurant.\nChunk 2: yes, can you please check for a turkish restaurant?\nChunk 3: May I have the address for Anatolia Thank You."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=moderate. C2 cuisine+=turkish; acceptance=selected_option. C3 goal=request_info; requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; food=turkish; price=moderate; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a moderately priced polish food restaurant.\nChunk 2: yes, can you please check for a turkish restaurant?\nChunk 3: May I have the address for Anatolia Thank You.", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate. Next, cuisine: turkish; acceptance: selected_option. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. price: moderate.; cuisine: turkish; acceptance: selected_option.; requested information: address..", "trace": "C1 domain=restaurant; goal=search; price+=moderate. C2 cuisine+=turkish; acceptance=selected_option. C3 goal=request_info; requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a moderately priced polish food restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate..", "trace": "domain=restaurant; goal=search; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "yes, can you please check for a turkish restaurant?", "streaming_reasoning": "As more information arrives, cuisine: turkish; acceptance: selected_option..", "trace": "cuisine+=turkish; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "May I have the address for Anatolia Thank You.", "streaming_reasoning": "Finally, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is turkish; price is moderate; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; food=turkish; price=moderate; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002394", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That doesn't matter as long as I'm in the east part of town.\nChunk 2: Can you please check again?\nChunk 3: Hopefully, there was just an error in inputting the information into the search system.\nChunk 4: Thanks.\nChunk 5: Can you check for a guesthouse with those requirements mentioned above?\nChunk 6: I really don't have a price range in mind.\nChunk 7: I'm still not sure I want to stay in a guesthouse, hotels are so much better for me.\nChunk 8: Ok, I guess we can book that one then.\nChunk 9: There will be 3 of us staying 4 nights, starting sunday.\nChunk 10: No, that'll be it.\nChunk 11: Thanks for the help.", "streaming_reasoning": "C1 area+=east. C2 goal=request_info. C3 goal=search. C4 [SKIP: thanks_only]. C5 domain=hotel; hotel_type+=guesthouse. C6 intent=context_update. C7 hotel_type+=hotel; destination+=stay in a guesthouse. C8 goal=booking. C9 time+=4; day+=sunday; stay_length+=4 nights. C10 goal=modify_constraint. C11 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking; area=east; stay_length=4 nights; destination=stay in a guesthouse; when=sunday, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: That doesn't matter as long as I'm in the east part of town.\nChunk 2: Can you please check again?\nChunk 3: Hopefully, there was just an error in inputting the information into the search system.\nChunk 4: Thanks.\nChunk 5: Can you check for a guesthouse with those requirements mentioned above?\nChunk 6: I really don't have a price range in mind.\nChunk 7: I'm still not sure I want to stay in a guesthouse, hotels are so much better for me.\nChunk 8: Ok, I guess we can book that one then.\nChunk 9: There will be 3 of us staying 4 nights, starting sunday.\nChunk 10: No, that'll be it.\nChunk 11: Thanks for the help."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=east. C2 goal=request_info. C3 goal=search. C4 [SKIP: thanks_only]. C5 domain=hotel; hotel_type+=guesthouse. C6 intent=context_update. C7 hotel_type+=hotel; destination+=stay in a guesthouse. C8 goal=booking. C9 time+=4; day+=sunday; stay_length+=4 nights. C10 goal=modify_constraint. C11 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking; area=east; stay_length=4 nights; destination=stay in a guesthouse; when=sunday, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That doesn't matter as long as I'm in the east part of town.\nChunk 2: Can you please check again?\nChunk 3: Hopefully, there was just an error in inputting the information into the search system.\nChunk 4: Thanks.\nChunk 5: Can you check for a guesthouse with those requirements mentioned above?\nChunk 6: I really don't have a price range in mind.\nChunk 7: I'm still not sure I want to stay in a guesthouse, hotels are so much better for me.\nChunk 8: Ok, I guess we can book that one then.\nChunk 9: There will be 3 of us staying 4 nights, starting sunday.\nChunk 10: No, that'll be it.\nChunk 11: Thanks for the help.", "input_token_count": 121, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, area: east. Next, the goal is request info. Next, the goal is search. Next, the topic is hotel; hotel type: guesthouse. Next, intent: context_update. Next, hotel type: hotel; destination: stay in a guesthouse. Next, the goal is booking. Next, time: 4; day: sunday; stay length: 4 nights. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is modify constraint.. area: east.; hotel type: guesthouse., hotel; intent: context_update.; destination: stay in a guesthouse.; time: 4; day: sunday; stay length: 4 nights..", "trace": "C1 area+=east. C2 goal=request_info. C3 goal=search. C4 [SKIP: thanks_only]. C5 domain=hotel; hotel_type+=guesthouse. C6 intent=context_update. C7 hotel_type+=hotel; destination+=stay in a guesthouse. C8 goal=booking. C9 time+=4; day+=sunday; stay_length+=4 nights. C10 goal=modify_constraint. C11 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "That doesn't matter as long as I'm in the east part of town.", "streaming_reasoning": "Initially, area: east..", "trace": "area+=east."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you please check again?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Hopefully, there was just an error in inputting the information into the search system.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you check for a guesthouse with those requirements mentioned above?", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I really don't have a price range in mind.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'm still not sure I want to stay in a guesthouse, hotels are so much better for me.", "streaming_reasoning": "As more information arrives, hotel type: hotel; destination: stay in a guesthouse..", "trace": "hotel_type+=hotel; destination+=stay in a guesthouse."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Ok, I guess we can book that one then.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "There will be 3 of us staying 4 nights, starting sunday.", "streaming_reasoning": "As more information arrives, time: 4; day: sunday; stay length: 4 nights..", "trace": "time+=4; day+=sunday; stay_length+=4 nights."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "No, that'll be it.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Thanks for the help.", "streaming_reasoning": "The content at C11 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is east; stay length is 4 nights; destination is stay in a guesthouse; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking; area=east; stay_length=4 nights; destination=stay in a guesthouse; when=sunday, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002395", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be needing a taxi from broxbourne train station.\nChunk 2: I must arrive there by 23:30.\nChunk 3: I'm going to india house Nope.\nChunk 4: That should be it.\nChunk 5: Thank you so much for your help.", "streaming_reasoning": "C1 domain=train. C2 time+=23:30. C3 destination+=india house nope. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi, train; destination=india house nope; when=23:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I will be needing a taxi from broxbourne train station.\nChunk 2: I must arrive there by 23:30.\nChunk 3: I'm going to india house Nope.\nChunk 4: That should be it.\nChunk 5: Thank you so much for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train. C2 time+=23:30. C3 destination+=india house nope. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi, train; destination=india house nope; when=23:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be needing a taxi from broxbourne train station.\nChunk 2: I must arrive there by 23:30.\nChunk 3: I'm going to india house Nope.\nChunk 4: That should be it.\nChunk 5: Thank you so much for your help.", "input_token_count": 44, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train. Next, time: 23:30. Finally, destination: india house nope.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train.. time: 23:30.; destination: india house nope..", "trace": "C1 domain=train. C2 time+=23:30. C3 destination+=india house nope. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I will be needing a taxi from broxbourne train station.", "streaming_reasoning": "Initially, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I must arrive there by 23:30.", "streaming_reasoning": "As more information arrives, time: 23:30..", "trace": "time+=23:30."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm going to india house Nope.", "streaming_reasoning": "As more information arrives, destination: india house nope..", "trace": "destination+=india house nope."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That should be it.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you so much for your help.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user's request falls within the taxi domain. Key information: destination is india house nope; timing is 23:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, train; destination=india house nope; when=23:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003010", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks.\nChunk 2: Do you think we have enough for the kids to eat and drink?\nChunk 3: I'm sure of that.\nChunk 4: There ' s enough food here to feed an army!\nChunk 5: That birthday cake looks wonderful, but you haven ' t put any candles on it yet.\nChunk 6: Thanks for reminding me.\nChunk 7: I'Ve prepared some party games for the children too.\nChunk 8: I'Ve brought a tape with lots of children ' s songs on it.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=i'm. C4 casual_comment=enough, food. C5 casual_comment=birthday, cake. C6 [SKIP: thanks_only]. C7 casual_comment=i've, prepared. C8 casual_comment=i've, brought.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thanks.\nChunk 2: Do you think we have enough for the kids to eat and drink?\nChunk 3: I'm sure of that.\nChunk 4: There ' s enough food here to feed an army!\nChunk 5: That birthday cake looks wonderful, but you haven ' t put any candles on it yet.\nChunk 6: Thanks for reminding me.\nChunk 7: I'Ve prepared some party games for the children too.\nChunk 8: I'Ve brought a tape with lots of children ' s songs on it."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=i'm. C4 casual_comment=enough, food. C5 casual_comment=birthday, cake. C6 [SKIP: thanks_only]. C7 casual_comment=i've, prepared. C8 casual_comment=i've, brought.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks.\nChunk 2: Do you think we have enough for the kids to eat and drink?\nChunk 3: I'm sure of that.\nChunk 4: There ' s enough food here to feed an army!\nChunk 5: That birthday cake looks wonderful, but you haven ' t put any candles on it yet.\nChunk 6: Thanks for reminding me.\nChunk 7: I'Ve prepared some party games for the children too.\nChunk 8: I'Ve brought a tape with lots of children ' s songs on it.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on i'm. Next, the user comments on enough. Next, the user comments on birthday. Next, the user comments on i've. Finally, the user comments on i've.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=i'm. C4 casual_comment=enough, food. C5 casual_comment=birthday, cake. C6 [SKIP: thanks_only]. C7 casual_comment=i've, prepared. C8 casual_comment=i've, brought.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thanks.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do you think we have enough for the kids to eat and drink?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm sure of that.", "streaming_reasoning": "As more information arrives, the user comments on i'm..", "trace": "casual_comment=i'm."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "There ' s enough food here to feed an army!", "streaming_reasoning": "As more information arrives, the user comments on enough.", "trace": "casual_comment=enough, food."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That birthday cake looks wonderful, but you haven ' t put any candles on it yet.", "streaming_reasoning": "As more information arrives, the user comments on birthday.", "trace": "casual_comment=birthday, cake."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks for reminding me.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'Ve prepared some party games for the children too.", "streaming_reasoning": "As more information arrives, the user comments on i've.", "trace": "casual_comment=i've, prepared."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'Ve brought a tape with lots of children ' s songs on it.", "streaming_reasoning": "Finally, the user comments on i've.", "trace": "casual_comment=i've, brought."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002396", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is it located near Alimentum?\nChunk 2: I'm looking for something in the same area as the restaurant That will do.\nChunk 3: Please get me their address.\nChunk 4: Yes, I would like to book a taxi from the restaurant to the entertainment.\nChunk 5: It doesn't matter, I just need to get there.\nChunk 6: Great, thank you so much for your help!\nChunk 7: That's everything I'll need today Splendid!\nChunk 8: Thank you for all your help.\nChunk 9: That's all I need Goodbye.", "streaming_reasoning": "C1 goal=request_info. C2 domain=restaurant; goal=modify_constraint. C3 goal=request_info; requested_info+=address. C4 domain=taxi; goal=confirm_booking; destination+=the entertainment; departure+=the restaurant; goal=confirm_booking. C5 intent=context_update. C6 intent=context_update. C7 day+=today. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi; goal=search, modify_constraint, request_info, booking, confirm_booking; destination=the entertainment; departure=the restaurant; requested_info=address; when=today; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Is it located near Alimentum?\nChunk 2: I'm looking for something in the same area as the restaurant That will do.\nChunk 3: Please get me their address.\nChunk 4: Yes, I would like to book a taxi from the restaurant to the entertainment.\nChunk 5: It doesn't matter, I just need to get there.\nChunk 6: Great, thank you so much for your help!\nChunk 7: That's everything I'll need today Splendid!\nChunk 8: Thank you for all your help.\nChunk 9: That's all I need Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 domain=restaurant; goal=modify_constraint. C3 goal=request_info; requested_info+=address. C4 domain=taxi; goal=confirm_booking; destination+=the entertainment; departure+=the restaurant; goal=confirm_booking. C5 intent=context_update. C6 intent=context_update. C7 day+=today. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi; goal=search, modify_constraint, request_info, booking, confirm_booking; destination=the entertainment; departure=the restaurant; requested_info=address; when=today; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is it located near Alimentum?\nChunk 2: I'm looking for something in the same area as the restaurant That will do.\nChunk 3: Please get me their address.\nChunk 4: Yes, I would like to book a taxi from the restaurant to the entertainment.\nChunk 5: It doesn't matter, I just need to get there.\nChunk 6: Great, thank you so much for your help!\nChunk 7: That's everything I'll need today Splendid!\nChunk 8: Thank you for all your help.\nChunk 9: That's all I need Goodbye.", "input_token_count": 90, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, the topic is restaurant; the goal is modify constraint. Next, the goal is request info; requested information: address. Next, the topic is taxi; the goal is confirm booking.; destination: the entertainment; departure point: the restaurant. Next, intent: context_update. Next, intent: context_update. Finally, day: today.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is confirm booking.. requested information: address.; destination: the entertainment; departure point: the restaurant; intent: context_update.; day: today..", "trace": "C1 goal=request_info. C2 domain=restaurant; goal=modify_constraint. C3 goal=request_info; requested_info+=address. C4 domain=taxi; goal=confirm_booking; destination+=the entertainment; departure+=the restaurant; goal=confirm_booking. C5 intent=context_update. C6 intent=context_update. C7 day+=today. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Is it located near Alimentum?", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm looking for something in the same area as the restaurant That will do.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint..", "trace": "domain=restaurant; goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Please get me their address.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I would like to book a taxi from the restaurant to the entertainment.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is confirm booking.; destination: the entertainment; departure point: the restaurant.", "trace": "domain=taxi; goal=confirm_booking; destination+=the entertainment; departure+=the restaurant; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It doesn't matter, I just need to get there.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Great, thank you so much for your help!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's everything I'll need today Splendid!", "streaming_reasoning": "As more information arrives, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That's all I need Goodbye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: destination is the entertainment; departure point is the restaurant; requested information is address; timing is today. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi; goal=search, modify_constraint, request_info, booking, confirm_booking; destination=the entertainment; departure=the restaurant; requested_info=address; when=today; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002397", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for an expensive hotel to stay at in Cambridge, please.\nChunk 2: I don't care what part of town, just so that it has a 4 star rating.\nChunk 3: The University Arms Hotel.\nChunk 4: Can you book that for 5 nights please?\nChunk 5: Myself and my wife will be staying 5 nights starting on wednesday.\nChunk 6: I want to find a restaurant.\nChunk 7: I also need the phone.\nChunk 8: I also need the postcode.\nChunk 9: I also need the price.\nChunk 10: That's all I needed, thanks so much for your help.", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=expensive; hotel_type+=hotel; destination+=stay at in cambridge. C2 stars+=4 stars. C3 intent=context_update. C4 goal=booking; stay_length+=5 nights. C5 time+=5; day+=wednesday. C6 domain=restaurant; destination+=find a restaurant. C7 goal=request_info; requested_info+=phone. C8 requested_info+=postcode. C9 requested_info+=price. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, booking, request_info; price=expensive; stay_length=5 nights; stars=4 stars; destination=stay at in cambridge, find a restaurant; requested_info=phone, postcode, price; when=wednesday, 5; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for an expensive hotel to stay at in Cambridge, please.\nChunk 2: I don't care what part of town, just so that it has a 4 star rating.\nChunk 3: The University Arms Hotel.\nChunk 4: Can you book that for 5 nights please?\nChunk 5: Myself and my wife will be staying 5 nights starting on wednesday.\nChunk 6: I want to find a restaurant.\nChunk 7: I also need the phone.\nChunk 8: I also need the postcode.\nChunk 9: I also need the price.\nChunk 10: That's all I needed, thanks so much for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=expensive; hotel_type+=hotel; destination+=stay at in cambridge. C2 stars+=4 stars. C3 intent=context_update. C4 goal=booking; stay_length+=5 nights. C5 time+=5; day+=wednesday. C6 domain=restaurant; destination+=find a restaurant. C7 goal=request_info; requested_info+=phone. C8 requested_info+=postcode. C9 requested_info+=price. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, booking, request_info; price=expensive; stay_length=5 nights; stars=4 stars; destination=stay at in cambridge, find a restaurant; requested_info=phone, postcode, price; when=wednesday, 5; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for an expensive hotel to stay at in Cambridge, please.\nChunk 2: I don't care what part of town, just so that it has a 4 star rating.\nChunk 3: The University Arms Hotel.\nChunk 4: Can you book that for 5 nights please?\nChunk 5: Myself and my wife will be staying 5 nights starting on wednesday.\nChunk 6: I want to find a restaurant.\nChunk 7: I also need the phone.\nChunk 8: I also need the postcode.\nChunk 9: I also need the price.\nChunk 10: That's all I needed, thanks so much for your help.", "input_token_count": 104, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: expensive; hotel type: hotel; destination: stay at in cambridge. Next, star rating: 4 stars. Next, intent: context_update. Next, the goal is booking; stay length: 5 nights. Next, time: 5; day: wednesday. Next, the topic is restaurant; destination: find a restaurant. Next, the goal is request info; requested information: phone. Next, requested information: postcode. Finally, requested information: price.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. price: expensive; hotel type: hotel; destination: stay at in cambridge., find a restaurant.; star rating: 4 stars.; intent: context_update.; stay length: 5 nights.; time: 5; day: wednesday.; requested information: phone., postcode., price..", "trace": "C1 domain=hotel; goal=search; price+=expensive; hotel_type+=hotel; destination+=stay at in cambridge. C2 stars+=4 stars. C3 intent=context_update. C4 goal=booking; stay_length+=5 nights. C5 time+=5; day+=wednesday. C6 domain=restaurant; destination+=find a restaurant. C7 goal=request_info; requested_info+=phone. C8 requested_info+=postcode. C9 requested_info+=price. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for an expensive hotel to stay at in Cambridge, please.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: expensive; hotel type: hotel; destination: stay at in cambridge..", "trace": "domain=hotel; goal=search; price+=expensive; hotel_type+=hotel; destination+=stay at in cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I don't care what part of town, just so that it has a 4 star rating.", "streaming_reasoning": "As more information arrives, star rating: 4 stars..", "trace": "stars+=4 stars."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The University Arms Hotel.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you book that for 5 nights please?", "streaming_reasoning": "As more information arrives, the goal is booking; stay length: 5 nights..", "trace": "goal=booking; stay_length+=5 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Myself and my wife will be staying 5 nights starting on wednesday.", "streaming_reasoning": "As more information arrives, time: 5; day: wednesday..", "trace": "time+=5; day+=wednesday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: find a restaurant..", "trace": "domain=restaurant; destination+=find a restaurant."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need the postcode.", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need the price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That's all I needed, thanks so much for your help.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is expensive; stay length is 5 nights; star rating is 4 stars; destination is stay at in cambridge; requested information is phone; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, booking, request_info; price=expensive; stay_length=5 nights; stars=4 stars; destination=stay at in cambridge, find a restaurant; requested_info=phone, postcode, price; when=wednesday, 5; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002399", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a train that leaves on Saturday and arrives by 08:45.\nChunk 2: I'll be leaving Cambridge to get to Ely.\nChunk 3: Yes, can you book that for 7?\nChunk 4: Are there anything fun to do in city centre?\nChunk 5: what is their postcode?\nChunk 6: That's it Thank you.", "streaming_reasoning": "C1 domain=train; goal=search; time+=08:45; day+=saturday; destination+=find a train that leaves on saturday and. C2 goal=request_info. C3 goal=confirm_booking; goal=confirm_booking. C4 area+=centre; destination+=do in city centre. C5 requested_info+=postcode. C6 intent=context_update.", "deep_reasoning": "Need domain=train; goal=search, request_info, booking, confirm_booking; area=centre; destination=find a train that leaves on saturday and, do in city centre; requested_info=postcode; when=saturday, 08:45.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to find a train that leaves on Saturday and arrives by 08:45.\nChunk 2: I'll be leaving Cambridge to get to Ely.\nChunk 3: Yes, can you book that for 7?\nChunk 4: Are there anything fun to do in city centre?\nChunk 5: what is their postcode?\nChunk 6: That's it Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; time+=08:45; day+=saturday; destination+=find a train that leaves on saturday and. C2 goal=request_info. C3 goal=confirm_booking; goal=confirm_booking. C4 area+=centre; destination+=do in city centre. C5 requested_info+=postcode. C6 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking, confirm_booking; area=centre; destination=find a train that leaves on saturday and, do in city centre; requested_info=postcode; when=saturday, 08:45.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a train that leaves on Saturday and arrives by 08:45.\nChunk 2: I'll be leaving Cambridge to get to Ely.\nChunk 3: Yes, can you book that for 7?\nChunk 4: Are there anything fun to do in city centre?\nChunk 5: what is their postcode?\nChunk 6: That's it Thank you.", "input_token_count": 59, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 08:45; day: saturday; destination: find a train that leaves on saturday and. Next, the goal is request info. Next, the goal is confirm booking. Next, area: centre; destination: do in city centre. Next, requested information: postcode. Finally, intent: context_update. In summary, The overall topic is train. the goal is confirm booking.. time: 08:45; day: saturday; destination: find a train that leaves on saturday and., do in city centre.; area: centre; requested information: postcode.; intent: context_update..", "trace": "C1 domain=train; goal=search; time+=08:45; day+=saturday; destination+=find a train that leaves on saturday and. C2 goal=request_info. C3 goal=confirm_booking; goal=confirm_booking. C4 area+=centre; destination+=do in city centre. C5 requested_info+=postcode. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to find a train that leaves on Saturday and arrives by 08:45.", "streaming_reasoning": "Initially, the topic is train; the goal is search; time: 08:45; day: saturday; destination: find a train that leaves on saturday and..", "trace": "domain=train; goal=search; time+=08:45; day+=saturday; destination+=find a train that leaves on saturday and."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'll be leaving Cambridge to get to Ely.", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, can you book that for 7?", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Are there anything fun to do in city centre?", "streaming_reasoning": "As more information arrives, area: centre; destination: do in city centre..", "trace": "area+=centre; destination+=do in city centre."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "what is their postcode?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's it Thank you.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is centre; destination is find a train that leaves on saturday and; requested information is postcode; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking, confirm_booking; area=centre; destination=find a train that leaves on saturday and, do in city centre; requested_info=postcode; when=saturday, 08:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002400", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a steakhouse restaurant in the east part of town.\nChunk 2: Any price range will be fine.\nChunk 3: I really need something in the east part of town.\nChunk 4: How about Indian food?\nChunk 5: Sounds great, what is their address and phone number Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=east. C2 intent=context_update. C3 intent=context_update. C4 goal=recommendation; cuisine+=indian. C5 goal=request_info; requested_info+=address, phone.", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, request_info; area=east; food=indian; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a steakhouse restaurant in the east part of town.\nChunk 2: Any price range will be fine.\nChunk 3: I really need something in the east part of town.\nChunk 4: How about Indian food?\nChunk 5: Sounds great, what is their address and phone number Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=east. C2 intent=context_update. C3 intent=context_update. C4 goal=recommendation; cuisine+=indian. C5 goal=request_info; requested_info+=address, phone.\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, request_info; area=east; food=indian; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a steakhouse restaurant in the east part of town.\nChunk 2: Any price range will be fine.\nChunk 3: I really need something in the east part of town.\nChunk 4: How about Indian food?\nChunk 5: Sounds great, what is their address and phone number Thank you, goodbye.", "input_token_count": 54, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: east. Next, intent: context_update. Next, intent: context_update. Next, the goal is recommendation; cuisine: indian. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. area: east.; intent: context_update.; cuisine: indian.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; area+=east. C2 intent=context_update. C3 intent=context_update. C4 goal=recommendation; cuisine+=indian. C5 goal=request_info; requested_info+=address, phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a steakhouse restaurant in the east part of town.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: east..", "trace": "domain=restaurant; goal=search; area+=east."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Any price range will be fine.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I really need something in the east part of town.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "How about Indian food?", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: indian..", "trace": "goal=recommendation; cuisine+=indian."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Sounds great, what is their address and phone number Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is east; cuisine is indian; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, request_info; area=east; food=indian; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002401", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello I need a train to Bishops Stortford please.\nChunk 2: I will be traveling on Thursday and would like to leave after 16:30 No thanks.\nChunk 3: No need to book.\nChunk 4: But, can you tell me the price for the ticket Thank you.\nChunk 5: I also need the phone number for an attraction called great saint mary's church.\nChunk 6: Can I get the address also please?\nChunk 7: That will help a lot Thanks so much!\nChunk 8: that isenough for today.\nChunk 9: thank you for helping.", "streaming_reasoning": "C1 domain=train; goal=search; destination+=bishops stortford please. C2 time+=16:30; day+=thursday; destination+=leave after 16:30 no thanks. C3 goal=booking. C4 goal=request_info; requested_info+=price. C5 domain=attraction; requested_info+=phone. C6 requested_info+=address. C7 intent=context_update. C8 day+=today. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, attraction; goal=search, booking, request_info; destination=bishops stortford please, leave after 16:30 no thanks; requested_info=price, phone, address; when=thursday, today, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello I need a train to Bishops Stortford please.\nChunk 2: I will be traveling on Thursday and would like to leave after 16:30 No thanks.\nChunk 3: No need to book.\nChunk 4: But, can you tell me the price for the ticket Thank you.\nChunk 5: I also need the phone number for an attraction called great saint mary's church.\nChunk 6: Can I get the address also please?\nChunk 7: That will help a lot Thanks so much!\nChunk 8: that isenough for today.\nChunk 9: thank you for helping."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=bishops stortford please. C2 time+=16:30; day+=thursday; destination+=leave after 16:30 no thanks. C3 goal=booking. C4 goal=request_info; requested_info+=price. C5 domain=attraction; requested_info+=phone. C6 requested_info+=address. C7 intent=context_update. C8 day+=today. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, attraction; goal=search, booking, request_info; destination=bishops stortford please, leave after 16:30 no thanks; requested_info=price, phone, address; when=thursday, today, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello I need a train to Bishops Stortford please.\nChunk 2: I will be traveling on Thursday and would like to leave after 16:30 No thanks.\nChunk 3: No need to book.\nChunk 4: But, can you tell me the price for the ticket Thank you.\nChunk 5: I also need the phone number for an attraction called great saint mary's church.\nChunk 6: Can I get the address also please?\nChunk 7: That will help a lot Thanks so much!\nChunk 8: that isenough for today.\nChunk 9: thank you for helping.", "input_token_count": 96, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: bishops stortford please. Next, time: 16:30; day: thursday; destination: leave after 16:30 no thanks. Next, the goal is booking. Next, the goal is request info; requested information: price. Next, the topic is attraction; requested information: phone. Next, requested information: address. Next, intent: context_update. Finally, day: today.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction. the goal is request info. destination: bishops stortford please., leave after 16:30 no thanks.; time: 16:30; day: thursday, today.; requested information: price., phone., address.; intent: context_update..", "trace": "C1 domain=train; goal=search; destination+=bishops stortford please. C2 time+=16:30; day+=thursday; destination+=leave after 16:30 no thanks. C3 goal=booking. C4 goal=request_info; requested_info+=price. C5 domain=attraction; requested_info+=phone. C6 requested_info+=address. C7 intent=context_update. C8 day+=today. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello I need a train to Bishops Stortford please.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: bishops stortford please..", "trace": "domain=train; goal=search; destination+=bishops stortford please."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be traveling on Thursday and would like to leave after 16:30 No thanks.", "streaming_reasoning": "As more information arrives, time: 16:30; day: thursday; destination: leave after 16:30 no thanks..", "trace": "time+=16:30; day+=thursday; destination+=leave after 16:30 no thanks."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No need to book.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "But, can you tell me the price for the ticket Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the phone number for an attraction called great saint mary's church.", "streaming_reasoning": "As more information arrives, the topic is attraction; requested information: phone..", "trace": "domain=attraction; requested_info+=phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I get the address also please?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That will help a lot Thanks so much!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "that isenough for today.", "streaming_reasoning": "As more information arrives, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "thank you for helping.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is bishops stortford please; requested information is price; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=search, booking, request_info; destination=bishops stortford please, leave after 16:30 no thanks; requested_info=price, phone, address; when=thursday, today, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003014", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Right.\nChunk 2: Well, given that your colleagues are working so hard on this project, I suppose we could change that deadline to Monday morning, I won't have time to look over it on the weekend anyway.\nChunk 3: That'd be very helpful.\nChunk 4: An extra weekend is all they really need.\nChunk 5: Thanks That's alright.\nChunk 6: Make sure everyone knows that we must stick to the new deadline I will.\nChunk 7: I know you have a tight schedule, so I won't take up more of your time.\nChunk 8: Have a good evening.", "streaming_reasoning": "C1 [SKIP: low_information]. C2 casual_comment=given, colleagues. C3 casual_comment=that'd, very. C4 casual_comment=extra, weekend. C5 [SKIP: thanks_only]. C6 casual_comment=make, everyone. C7 casual_comment=tight, schedule. C8 casual_comment=evening.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Right.\nChunk 2: Well, given that your colleagues are working so hard on this project, I suppose we could change that deadline to Monday morning, I won't have time to look over it on the weekend anyway.\nChunk 3: That'd be very helpful.\nChunk 4: An extra weekend is all they really need.\nChunk 5: Thanks That's alright.\nChunk 6: Make sure everyone knows that we must stick to the new deadline I will.\nChunk 7: I know you have a tight schedule, so I won't take up more of your time.\nChunk 8: Have a good evening."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: low_information]. C2 casual_comment=given, colleagues. C3 casual_comment=that'd, very. C4 casual_comment=extra, weekend. C5 [SKIP: thanks_only]. C6 casual_comment=make, everyone. C7 casual_comment=tight, schedule. C8 casual_comment=evening.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Right.\nChunk 2: Well, given that your colleagues are working so hard on this project, I suppose we could change that deadline to Monday morning, I won't have time to look over it on the weekend anyway.\nChunk 3: That'd be very helpful.\nChunk 4: An extra weekend is all they really need.\nChunk 5: Thanks That's alright.\nChunk 6: Make sure everyone knows that we must stick to the new deadline I will.\nChunk 7: I know you have a tight schedule, so I won't take up more of your time.\nChunk 8: Have a good evening.", "input_token_count": 100, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the user comments on given. Next, the user comments on that'd. Next, the user comments on extra. Next, the user comments on make. Next, the user comments on tight. Finally, the user comments on evening.  Some chunks were skipped because they contained low_information or thanks_only.", "trace": "C1 [SKIP: low_information]. C2 casual_comment=given, colleagues. C3 casual_comment=that'd, very. C4 casual_comment=extra, weekend. C5 [SKIP: thanks_only]. C6 casual_comment=make, everyone. C7 casual_comment=tight, schedule. C8 casual_comment=evening.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Right.", "streaming_reasoning": "The content at C1 was skipped (low_information).", "trace": "[SKIP: low_information]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Well, given that your colleagues are working so hard on this project, I suppose we could change that deadline to Monday morning, I won't have time to look over it on the weekend anyway.", "streaming_reasoning": "As more information arrives, the user comments on given.", "trace": "casual_comment=given, colleagues."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That'd be very helpful.", "streaming_reasoning": "As more information arrives, the user comments on that'd.", "trace": "casual_comment=that'd, very."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "An extra weekend is all they really need.", "streaming_reasoning": "As more information arrives, the user comments on extra.", "trace": "casual_comment=extra, weekend."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks That's alright.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Make sure everyone knows that we must stick to the new deadline I will.", "streaming_reasoning": "As more information arrives, the user comments on make.", "trace": "casual_comment=make, everyone."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I know you have a tight schedule, so I won't take up more of your time.", "streaming_reasoning": "As more information arrives, the user comments on tight.", "trace": "casual_comment=tight, schedule."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Have a good evening.", "streaming_reasoning": "Finally, the user comments on evening..", "trace": "casual_comment=evening."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002402", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No specific area.\nChunk 2: Just the first thing that pops up.\nChunk 3: Okay how much does it cost?\nChunk 4: And where the postal code?\nChunk 5: I am also looking for a train for Thursday departing from Stevenage.\nChunk 6: I would like to arrive in cambridge by 11:30 That sounds good.\nChunk 7: I need tickets for 4 people.\nChunk 8: Can I get a reference number?\nChunk 9: Great, that's all I need.\nChunk 10: You can end this conversation now.\nChunk 11: Thanks!", "streaming_reasoning": "C1 goal=modify_constraint. C2 intent=context_update. C3 goal=request_info; requested_info+=price. C4 requested_info+=postcode. C5 domain=train; goal=search; day+=thursday; departure+=stevenage. C6 time+=11:30; destination+=arrive in cambridge by 11:30 that sounds; acceptance=selected_option. C7 party_size+=4 people. C8 requested_info+=reference_number. C9 [SKIP: closing_only]. C10 intent=context_update. C11 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=request_info, search; party_size=4 people; destination=arrive in cambridge by 11:30 that sounds; departure=stevenage; requested_info=price, postcode, reference_number; when=thursday, 11:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No specific area.\nChunk 2: Just the first thing that pops up.\nChunk 3: Okay how much does it cost?\nChunk 4: And where the postal code?\nChunk 5: I am also looking for a train for Thursday departing from Stevenage.\nChunk 6: I would like to arrive in cambridge by 11:30 That sounds good.\nChunk 7: I need tickets for 4 people.\nChunk 8: Can I get a reference number?\nChunk 9: Great, that's all I need.\nChunk 10: You can end this conversation now.\nChunk 11: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=modify_constraint. C2 intent=context_update. C3 goal=request_info; requested_info+=price. C4 requested_info+=postcode. C5 domain=train; goal=search; day+=thursday; departure+=stevenage. C6 time+=11:30; destination+=arrive in cambridge by 11:30 that sounds; acceptance=selected_option. C7 party_size+=4 people. C8 requested_info+=reference_number. C9 [SKIP: closing_only]. C10 intent=context_update. C11 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search; party_size=4 people; destination=arrive in cambridge by 11:30 that sounds; departure=stevenage; requested_info=price, postcode, reference_number; when=thursday, 11:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No specific area.\nChunk 2: Just the first thing that pops up.\nChunk 3: Okay how much does it cost?\nChunk 4: And where the postal code?\nChunk 5: I am also looking for a train for Thursday departing from Stevenage.\nChunk 6: I would like to arrive in cambridge by 11:30 That sounds good.\nChunk 7: I need tickets for 4 people.\nChunk 8: Can I get a reference number?\nChunk 9: Great, that's all I need.\nChunk 10: You can end this conversation now.\nChunk 11: Thanks!", "input_token_count": 92, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is modify constraint. Next, intent: context_update. Next, the goal is request info; requested information: price. Next, requested information: postcode. Next, the topic is train; the goal is search; day: thursday; departure point: stevenage. Next, time: 11:30; destination: arrive in cambridge by 11:30 that sounds; acceptance: selected_option. Next, party size: 4 people. Next, requested information: reference_number. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is search. intent: context_update.; requested information: price., postcode., reference_number.; day: thursday; departure point: stevenage.; time: 11:30; destination: arrive in cambridge by 11:30 that sounds; acceptance: selected_option.; party size: 4 people..", "trace": "C1 goal=modify_constraint. C2 intent=context_update. C3 goal=request_info; requested_info+=price. C4 requested_info+=postcode. C5 domain=train; goal=search; day+=thursday; departure+=stevenage. C6 time+=11:30; destination+=arrive in cambridge by 11:30 that sounds; acceptance=selected_option. C7 party_size+=4 people. C8 requested_info+=reference_number. C9 [SKIP: closing_only]. C10 intent=context_update. C11 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No specific area.", "streaming_reasoning": "Initially, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Just the first thing that pops up.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Okay how much does it cost?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "And where the postal code?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I am also looking for a train for Thursday departing from Stevenage.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: thursday; departure point: stevenage..", "trace": "domain=train; goal=search; day+=thursday; departure+=stevenage."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I would like to arrive in cambridge by 11:30 That sounds good.", "streaming_reasoning": "As more information arrives, time: 11:30; destination: arrive in cambridge by 11:30 that sounds; acceptance: selected_option..", "trace": "time+=11:30; destination+=arrive in cambridge by 11:30 that sounds; acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need tickets for 4 people.", "streaming_reasoning": "As more information arrives, party size: 4 people..", "trace": "party_size+=4 people."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Can I get a reference number?", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Great, that's all I need.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "You can end this conversation now.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Thanks!", "streaming_reasoning": "The content at C11 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: party size is 4 people; destination is arrive in cambridge by 11:30 that sounds; departure point is stevenage; requested information is price; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search; party_size=4 people; destination=arrive in cambridge by 11:30 that sounds; departure=stevenage; requested_info=price, postcode, reference_number; when=thursday, 11:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002404", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for an Italian restaurant in the east Yes, please.\nChunk 2: 1 person at 16:45 on saturday That was all.\nChunk 3: Thanks!", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=east; cuisine+=italian; acceptance=selected_option. C2 time+=1, 16:45; day+=saturday. C3 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search; area=east; food=italian; when=saturday, 1, 16:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for an Italian restaurant in the east Yes, please.\nChunk 2: 1 person at 16:45 on saturday That was all.\nChunk 3: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=east; cuisine+=italian; acceptance=selected_option. C2 time+=1, 16:45; day+=saturday. C3 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search; area=east; food=italian; when=saturday, 1, 16:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for an Italian restaurant in the east Yes, please.\nChunk 2: 1 person at 16:45 on saturday That was all.\nChunk 3: Thanks!", "input_token_count": 28, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: east; cuisine: italian; acceptance: selected_option. Finally, time: 1; day: saturday.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is search. area: east; cuisine: italian; acceptance: selected_option.; time: 1; day: saturday..", "trace": "C1 domain=restaurant; goal=search; area+=east; cuisine+=italian; acceptance=selected_option. C2 time+=1, 16:45; day+=saturday. C3 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for an Italian restaurant in the east Yes, please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: east; cuisine: italian; acceptance: selected_option..", "trace": "domain=restaurant; goal=search; area+=east; cuisine+=italian; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "1 person at 16:45 on saturday That was all.", "streaming_reasoning": "As more information arrives, time: 1; day: saturday..", "trace": "time+=1, 16:45; day+=saturday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks!", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is east; cuisine is italian; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search; area=east; food=italian; when=saturday, 1, 16:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002405", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant that serves Malaysian food and is in the cheap price range.\nChunk 2: How about vietnamese food, please That sounds great!\nChunk 3: May I have their phone number please?\nChunk 4: Okay, thank you for your help!", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=cheap. C2 goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, request_info; price=cheap; requested_info=phone.", "answer": "I can help with that and include the phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant that serves Malaysian food and is in the cheap price range.\nChunk 2: How about vietnamese food, please That sounds great!\nChunk 3: May I have their phone number please?\nChunk 4: Okay, thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=cheap. C2 goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, request_info; price=cheap; requested_info=phone.\n\nAnswer: I can help with that and include the phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant that serves Malaysian food and is in the cheap price range.\nChunk 2: How about vietnamese food, please That sounds great!\nChunk 3: May I have their phone number please?\nChunk 4: Okay, thank you for your help!", "input_token_count": 46, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: cheap. Next, the goal is recommendation. Next, the goal is request info; requested information: phone. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is request info. price: cheap.; requested information: phone.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; price+=cheap. C2 goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant that serves Malaysian food and is in the cheap price range.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: cheap..", "trace": "domain=restaurant; goal=search; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How about vietnamese food, please That sounds great!", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "May I have their phone number please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Okay, thank you for your help!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: price is cheap; requested information is phone.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, request_info; price=cheap; requested_info=phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002406", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for a guesthouse in the south part of town.\nChunk 2: Do you have anything in that category?\nChunk 3: Moderate, please, and make sure they have free parking.\nChunk 4: Do they have free parking?\nChunk 5: And do you know if they have a star rating Not right now.\nChunk 6: I'd just like their phone number, please Great.\nChunk 7: Thanks for all your help.\nChunk 8: Bye!", "streaming_reasoning": "C1 domain=hotel; goal=search; area+=south; hotel_type+=guesthouse. C2 goal=request_info. C3 price+=moderate; amenities+=parking, free parking. C4 [SKIP: repeated_information]. C5 goal=modify_constraint. C6 goal=request_info; requested_info+=phone. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info; area=south; price=moderate; amenities=parking, free parking; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I'm looking for a guesthouse in the south part of town.\nChunk 2: Do you have anything in that category?\nChunk 3: Moderate, please, and make sure they have free parking.\nChunk 4: Do they have free parking?\nChunk 5: And do you know if they have a star rating Not right now.\nChunk 6: I'd just like their phone number, please Great.\nChunk 7: Thanks for all your help.\nChunk 8: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; area+=south; hotel_type+=guesthouse. C2 goal=request_info. C3 price+=moderate; amenities+=parking, free parking. C4 [SKIP: repeated_information]. C5 goal=modify_constraint. C6 goal=request_info; requested_info+=phone. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info; area=south; price=moderate; amenities=parking, free parking; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for a guesthouse in the south part of town.\nChunk 2: Do you have anything in that category?\nChunk 3: Moderate, please, and make sure they have free parking.\nChunk 4: Do they have free parking?\nChunk 5: And do you know if they have a star rating Not right now.\nChunk 6: I'd just like their phone number, please Great.\nChunk 7: Thanks for all your help.\nChunk 8: Bye!", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: south; hotel type: guesthouse. Next, the goal is request info. Next, price: moderate; amenities: parking. Next, the goal is modify constraint. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only or repeated_information or thanks_only. In summary, The overall topic is hotel. the goal is request info. area: south; hotel type: guesthouse.; price: moderate; amenities: parking; requested information: phone..", "trace": "C1 domain=hotel; goal=search; area+=south; hotel_type+=guesthouse. C2 goal=request_info. C3 price+=moderate; amenities+=parking, free parking. C4 [SKIP: repeated_information]. C5 goal=modify_constraint. C6 goal=request_info; requested_info+=phone. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I'm looking for a guesthouse in the south part of town.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: south; hotel type: guesthouse..", "trace": "domain=hotel; goal=search; area+=south; hotel_type+=guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do you have anything in that category?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Moderate, please, and make sure they have free parking.", "streaming_reasoning": "As more information arrives, price: moderate; amenities: parking.", "trace": "price+=moderate; amenities+=parking, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Do they have free parking?", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "And do you know if they have a star rating Not right now.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'd just like their phone number, please Great.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks for all your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Bye!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is south; price is moderate; amenities is parking; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info; area=south; price=moderate; amenities=parking, free parking; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002407", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I have been hurt and I need a hospital!\nChunk 2: Where is there one close by?\nChunk 3: I need the phone number, postcode.\nChunk 4: Okay.\nChunk 5: Thanks for your help.\nChunk 6: No thank you that is all I needed today.", "streaming_reasoning": "C1 domain=hospital; goal=search. C2 goal=request_info. C3 goal=request_info; requested_info+=phone, postcode. C4 [SKIP: backchannel_only]. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search, request_info; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I have been hurt and I need a hospital!\nChunk 2: Where is there one close by?\nChunk 3: I need the phone number, postcode.\nChunk 4: Okay.\nChunk 5: Thanks for your help.\nChunk 6: No thank you that is all I needed today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search. C2 goal=request_info. C3 goal=request_info; requested_info+=phone, postcode. C4 [SKIP: backchannel_only]. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I have been hurt and I need a hospital!\nChunk 2: Where is there one close by?\nChunk 3: I need the phone number, postcode.\nChunk 4: Okay.\nChunk 5: Thanks for your help.\nChunk 6: No thank you that is all I needed today.", "input_token_count": 47, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search. Next, the goal is request info. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained backchannel_only or closing_only or thanks_only. In summary, The overall topic is hospital. the goal is request info. requested information: phone.", "trace": "C1 domain=hospital; goal=search. C2 goal=request_info. C3 goal=request_info; requested_info+=phone, postcode. C4 [SKIP: backchannel_only]. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I have been hurt and I need a hospital!", "streaming_reasoning": "Initially, the topic is hospital; the goal is search..", "trace": "domain=hospital; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Where is there one close by?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need the phone number, postcode.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Okay.", "streaming_reasoning": "The content at C4 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks for your help.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No thank you that is all I needed today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002408", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you find me a welsh restaurant in the cheap price range?\nChunk 2: How about italian type of food?\nChunk 3: Any area will be fine.\nChunk 4: What is their address and phone number?\nChunk 5: OK thank you for your help!", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=cheap; requested_info+=price. C2 goal=recommendation; cuisine+=italian. C3 area+=any. C4 goal=request_info; requested_info+=address, phone. C5 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, request_info; area=any; food=italian; price=cheap; requested_info=price, address, phone.", "answer": "I can help with that and include the price, address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Could you find me a welsh restaurant in the cheap price range?\nChunk 2: How about italian type of food?\nChunk 3: Any area will be fine.\nChunk 4: What is their address and phone number?\nChunk 5: OK thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=cheap; requested_info+=price. C2 goal=recommendation; cuisine+=italian. C3 area+=any. C4 goal=request_info; requested_info+=address, phone. C5 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, request_info; area=any; food=italian; price=cheap; requested_info=price, address, phone.\n\nAnswer: I can help with that and include the price, address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you find me a welsh restaurant in the cheap price range?\nChunk 2: How about italian type of food?\nChunk 3: Any area will be fine.\nChunk 4: What is their address and phone number?\nChunk 5: OK thank you for your help!", "input_token_count": 46, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: cheap; requested information: price. Next, the goal is recommendation; cuisine: italian. Next, area: any. Next, the goal is request info; requested information: address. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is request info. price: cheap; requested information: price., address; cuisine: italian.; area: any.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; price+=cheap; requested_info+=price. C2 goal=recommendation; cuisine+=italian. C3 area+=any. C4 goal=request_info; requested_info+=address, phone. C5 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Could you find me a welsh restaurant in the cheap price range?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: cheap; requested information: price..", "trace": "domain=restaurant; goal=search; price+=cheap; requested_info+=price."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How about italian type of food?", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: italian..", "trace": "goal=recommendation; cuisine+=italian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Any area will be fine.", "streaming_reasoning": "As more information arrives, area: any..", "trace": "area+=any."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is their address and phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "OK thank you for your help!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is any; cuisine is italian; price is cheap; requested information is price. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the price, address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, request_info; area=any; food=italian; price=cheap; requested_info=price, address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002409", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place to stay.\nChunk 2: The hotel should have a star of 3 and should be in the moderate price range.\nChunk 3: I'm not too particular about which particular area I say in, but I do need free parking.\nChunk 4: No, I just need the address, please.\nChunk 5: That's all I need, thank you!!\nChunk 6: Thanks, that's all Good bye.", "streaming_reasoning": "C1 domain=hotel; goal=search; destination+=stay. C2 price+=moderate; hotel_type+=hotel. C3 amenities+=parking, free parking. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only]. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info; price=moderate; amenities=parking, free parking; destination=stay; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a place to stay.\nChunk 2: The hotel should have a star of 3 and should be in the moderate price range.\nChunk 3: I'm not too particular about which particular area I say in, but I do need free parking.\nChunk 4: No, I just need the address, please.\nChunk 5: That's all I need, thank you!!\nChunk 6: Thanks, that's all Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; destination+=stay. C2 price+=moderate; hotel_type+=hotel. C3 amenities+=parking, free parking. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only]. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info; price=moderate; amenities=parking, free parking; destination=stay; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place to stay.\nChunk 2: The hotel should have a star of 3 and should be in the moderate price range.\nChunk 3: I'm not too particular about which particular area I say in, but I do need free parking.\nChunk 4: No, I just need the address, please.\nChunk 5: That's all I need, thank you!!\nChunk 6: Thanks, that's all Good bye.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay. Next, price: moderate; hotel type: hotel. Next, amenities: parking. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. destination: stay.; price: moderate; hotel type: hotel.; amenities: parking; requested information: address..", "trace": "C1 domain=hotel; goal=search; destination+=stay. C2 price+=moderate; hotel_type+=hotel. C3 amenities+=parking, free parking. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only]. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a place to stay.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The hotel should have a star of 3 and should be in the moderate price range.", "streaming_reasoning": "As more information arrives, price: moderate; hotel type: hotel..", "trace": "price+=moderate; hotel_type+=hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm not too particular about which particular area I say in, but I do need free parking.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, I just need the address, please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That's all I need, thank you!!", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks, that's all Good bye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is moderate; amenities is parking; destination is stay; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info; price=moderate; amenities=parking, free parking; destination=stay; requested_info=address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002410", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: I also need the phone.\nChunk 3: Does the hotel have a restaurant attached to it No thank you.\nChunk 4: is there any restaurant close to the Gonville Hotel?\nChunk 5: what kind of hotel is it?\nChunk 6: Can I have their number?\nChunk 7: That's all I need for now.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 goal=request_info; requested_info+=phone. C3 domain=restaurant; destination+=it no thank you. C4 destination+=the gonville hotel. C5 goal=request_info. C6 goal=request_info. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, request_info; destination=find a hotel, it no thank you, the gonville hotel; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a hotel.\nChunk 2: I also need the phone.\nChunk 3: Does the hotel have a restaurant attached to it No thank you.\nChunk 4: is there any restaurant close to the Gonville Hotel?\nChunk 5: what kind of hotel is it?\nChunk 6: Can I have their number?\nChunk 7: That's all I need for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 goal=request_info; requested_info+=phone. C3 domain=restaurant; destination+=it no thank you. C4 destination+=the gonville hotel. C5 goal=request_info. C6 goal=request_info. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, request_info; destination=find a hotel, it no thank you, the gonville hotel; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: I also need the phone.\nChunk 3: Does the hotel have a restaurant attached to it No thank you.\nChunk 4: is there any restaurant close to the Gonville Hotel?\nChunk 5: what kind of hotel is it?\nChunk 6: Can I have their number?\nChunk 7: That's all I need for now.", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, the goal is request info; requested information: phone. Next, the topic is restaurant; destination: it no thank you. Next, destination: the gonville hotel. Next, the goal is request info. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info.. hotel type: hotel; destination: find a hotel., it no thank you., the gonville hotel.; requested information: phone..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 goal=request_info; requested_info+=phone. C3 domain=restaurant; destination+=it no thank you. C4 destination+=the gonville hotel. C5 goal=request_info. C6 goal=request_info. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Does the hotel have a restaurant attached to it No thank you.", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: it no thank you..", "trace": "domain=restaurant; destination+=it no thank you."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "is there any restaurant close to the Gonville Hotel?", "streaming_reasoning": "As more information arrives, destination: the gonville hotel..", "trace": "destination+=the gonville hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "what kind of hotel is it?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I have their number?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's all I need for now.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: destination is find a hotel; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, request_info; destination=find a hotel, it no thank you, the gonville hotel; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002411", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a european restaurant.\nChunk 2: I also need the phone.\nChunk 3: I also need the price.\nChunk 4: I don't care about the area Anywhere Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=european; destination+=find a european restaurant. C2 goal=request_info; requested_info+=phone. C3 requested_info+=price. C4 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; food=european; destination=find a european restaurant; requested_info=phone, price.", "answer": "I can help with that and include the phone, price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a european restaurant.\nChunk 2: I also need the phone.\nChunk 3: I also need the price.\nChunk 4: I don't care about the area Anywhere Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=european; destination+=find a european restaurant. C2 goal=request_info; requested_info+=phone. C3 requested_info+=price. C4 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; food=european; destination=find a european restaurant; requested_info=phone, price.\n\nAnswer: I can help with that and include the phone, price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a european restaurant.\nChunk 2: I also need the phone.\nChunk 3: I also need the price.\nChunk 4: I don't care about the area Anywhere Thank you, goodbye.", "input_token_count": 35, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: european; destination: find a european restaurant. Next, the goal is request info; requested information: phone. Next, requested information: price. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is request info. cuisine: european; destination: find a european restaurant.; requested information: phone., price.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; cuisine+=european; destination+=find a european restaurant. C2 goal=request_info; requested_info+=phone. C3 requested_info+=price. C4 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a european restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: european; destination: find a european restaurant..", "trace": "domain=restaurant; goal=search; cuisine+=european; destination+=find a european restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't care about the area Anywhere Thank you, goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is european; destination is find a european restaurant; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, price once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; food=european; destination=find a european restaurant; requested_info=phone, price."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002412", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It is for 5 people.\nChunk 2: The time is wednesday, 5, 12:00.\nChunk 3: Please make a booking.\nChunk 4: I also need the reference number.\nChunk 5: Thank you very much, yes, I also need to book a train ticket.\nChunk 6: I'd like to take the train on the same day and arrive by 09:45 if possible.\nChunk 7: I'll be leaving from kings lynn.\nChunk 8: Any train that gets me there close to the arrival time will be fine That works perfectly.\nChunk 9: Please make the booking for five people, and include my reference number, thank you.\nChunk 10: Thank you very much for your help.\nChunk 11: Have a great day!\nChunk 12: Nope that should do it.", "streaming_reasoning": "C1 party_size+=5 people. C2 time+=5, 12:00; day+=wednesday. C3 goal=booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=train; goal=confirm_booking; goal=confirm_booking. C6 time+=09:45; destination+=take the train on the same day and arrive. C7 intent=context_update. C8 destination+=the arrival time will be fine that works; goal=confirm_booking. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 [SKIP: closing_only]. C12 intent=context_update.", "deep_reasoning": "Need domain=train; goal=booking, search, request_info, confirm_booking; party_size=5 people; destination=take the train on the same day and arrive, the arrival time will be fine that works; requested_info=reference_number; when=wednesday, 5, 12:00, 09:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: It is for 5 people.\nChunk 2: The time is wednesday, 5, 12:00.\nChunk 3: Please make a booking.\nChunk 4: I also need the reference number.\nChunk 5: Thank you very much, yes, I also need to book a train ticket.\nChunk 6: I'd like to take the train on the same day and arrive by 09:45 if possible.\nChunk 7: I'll be leaving from kings lynn.\nChunk 8: Any train that gets me there close to the arrival time will be fine That works perfectly.\nChunk 9: Please make the booking for five people, and include my reference number, thank you.\nChunk 10: Thank you very much for your help.\nChunk 11: Have a great day!\nChunk 12: Nope that should do it."}, {"role": "assistant", "content": "Streaming reasoning: C1 party_size+=5 people. C2 time+=5, 12:00; day+=wednesday. C3 goal=booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=train; goal=confirm_booking; goal=confirm_booking. C6 time+=09:45; destination+=take the train on the same day and arrive. C7 intent=context_update. C8 destination+=the arrival time will be fine that works; goal=confirm_booking. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 [SKIP: closing_only]. C12 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=booking, search, request_info, confirm_booking; party_size=5 people; destination=take the train on the same day and arrive, the arrival time will be fine that works; requested_info=reference_number; when=wednesday, 5, 12:00, 09:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It is for 5 people.\nChunk 2: The time is wednesday, 5, 12:00.\nChunk 3: Please make a booking.\nChunk 4: I also need the reference number.\nChunk 5: Thank you very much, yes, I also need to book a train ticket.\nChunk 6: I'd like to take the train on the same day and arrive by 09:45 if possible.\nChunk 7: I'll be leaving from kings lynn.\nChunk 8: Any train that gets me there close to the arrival time will be fine That works perfectly.\nChunk 9: Please make the booking for five people, and include my reference number, thank you.\nChunk 10: Thank you very much for your help.\nChunk 11: Have a great day!\nChunk 12: Nope that should do it.", "input_token_count": 129, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, party size: 5 people. Next, time: 5; day: wednesday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the topic is train; the goal is confirm booking. Next, time: 09:45; destination: take the train on the same day and arrive. Next, intent: context_update. Next, the goal is confirm booking.; destination: the arrival time will be fine that works. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is confirm booking.. party size: 5 people.; time: 5, 09:45; day: wednesday.; requested information: reference_number.; destination: take the train on the same day and arrive., the arrival time will be fine that works; intent: context_update..", "trace": "C1 party_size+=5 people. C2 time+=5, 12:00; day+=wednesday. C3 goal=booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=train; goal=confirm_booking; goal=confirm_booking. C6 time+=09:45; destination+=take the train on the same day and arrive. C7 intent=context_update. C8 destination+=the arrival time will be fine that works; goal=confirm_booking. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 [SKIP: closing_only]. C12 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "It is for 5 people.", "streaming_reasoning": "Initially, party size: 5 people..", "trace": "party_size+=5 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is wednesday, 5, 12:00.", "streaming_reasoning": "As more information arrives, time: 5; day: wednesday..", "trace": "time+=5, 12:00; day+=wednesday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you very much, yes, I also need to book a train ticket.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is confirm booking..", "trace": "domain=train; goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'd like to take the train on the same day and arrive by 09:45 if possible.", "streaming_reasoning": "As more information arrives, time: 09:45; destination: take the train on the same day and arrive..", "trace": "time+=09:45; destination+=take the train on the same day and arrive."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'll be leaving from kings lynn.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Any train that gets me there close to the arrival time will be fine That works perfectly.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; destination: the arrival time will be fine that works.", "trace": "destination+=the arrival time will be fine that works; goal=confirm_booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Please make the booking for five people, and include my reference number, thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you very much for your help.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Have a great day!", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C12", "chunk_index": 11, "observed_text": "Nope that should do it.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: party size is 5 people; destination is take the train on the same day and arrive; requested information is reference_number; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, search, request_info, confirm_booking; party_size=5 people; destination=take the train on the same day and arrive, the arrival time will be fine that works; requested_info=reference_number; when=wednesday, 5, 12:00, 09:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001621", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I don't watch scary shows, but I have been watching the new stephen king show on hulu.\nChunk 2: Yes, I watch the show.\nChunk 3: That is a bit scary though but not that much.\nChunk 4: The first episode was fine but I don't thik I will go past episode three Im terrified.\nChunk 5: Ohh come on its not that scary, you should watch whole season.\nChunk 6: You don't know me lol.", "streaming_reasoning": "C1 emotion=anxious; cause=I don't watch shows, but I have been watching the new stephen; need=reassurance. C2 support_signal=received. C3 emotion=anxious. C4 support_signal=received. C5 emotion=anxious. C6 emotion=confused.", "deep_reasoning": "User feels confused after I don't watch shows, but I have been watching the new stephen and needs reassurance.", "answer": "It makes sense to feel confused after I don't watch shows, but I have been watching the new stephen. Slow down, check what is actually known, and take one small step before deciding what comes next.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I don't watch scary shows, but I have been watching the new stephen king show on hulu.\nChunk 2: Yes, I watch the show.\nChunk 3: That is a bit scary though but not that much.\nChunk 4: The first episode was fine but I don't thik I will go past episode three Im terrified.\nChunk 5: Ohh come on its not that scary, you should watch whole season.\nChunk 6: You don't know me lol."}, {"role": "assistant", "content": "Streaming reasoning: C1 emotion=anxious; cause=I don't watch shows, but I have been watching the new stephen; need=reassurance. C2 support_signal=received. C3 emotion=anxious. C4 support_signal=received. C5 emotion=anxious. C6 emotion=confused.\n\nDeep reasoning: User feels confused after I don't watch shows, but I have been watching the new stephen and needs reassurance.\n\nAnswer: It makes sense to feel confused after I don't watch shows, but I have been watching the new stephen. Slow down, check what is actually known, and take one small step before deciding what comes next."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I don't watch scary shows, but I have been watching the new stephen king show on hulu.\nChunk 2: Yes, I watch the show.\nChunk 3: That is a bit scary though but not that much.\nChunk 4: The first episode was fine but I don't thik I will go past episode three Im terrified.\nChunk 5: Ohh come on its not that scary, you should watch whole season.\nChunk 6: You don't know me lol.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user expresses anxious about I don't watch shows; the user needs reassurance. Next, the user signals support or acknowledgment. Next, the user expresses anxious. Next, the user signals support or acknowledgment. Next, the user expresses anxious. Finally, the user expresses confused.", "trace": "C1 emotion=anxious; cause=I don't watch shows, but I have been watching the new stephen; need=reassurance. C2 support_signal=received. C3 emotion=anxious. C4 support_signal=received. C5 emotion=anxious. C6 emotion=confused.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I don't watch scary shows, but I have been watching the new stephen king show on hulu.", "streaming_reasoning": "Initially, the user expresses anxious about I don't watch shows; the user needs reassurance..", "trace": "emotion=anxious; cause=I don't watch shows, but I have been watching the new stephen; need=reassurance."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I watch the show.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That is a bit scary though but not that much.", "streaming_reasoning": "As more information arrives, the user expresses anxious..", "trace": "emotion=anxious."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The first episode was fine but I don't thik I will go past episode three Im terrified.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Ohh come on its not that scary, you should watch whole season.", "streaming_reasoning": "As more information arrives, the user expresses anxious..", "trace": "emotion=anxious."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "You don't know me lol.", "streaming_reasoning": "Finally, the user expresses confused..", "trace": "emotion=confused."}]}, "output": {"deep_reasoning": "User feels confused after I don't watch shows, but I have been watching the new stephen and needs reassurance.", "answer": "It makes sense to feel confused after I don't watch shows, but I have been watching the new stephen. Slow down, check what is actually known, and take one small step before deciding what comes next."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003025", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello.\nChunk 2: I need to find out if a Receipt of Proceeds has arrived.\nChunk 3: I'm from Felix Wasserman Associates.\nChunk 4: Thanks.\nChunk 5: Have you got the L / C number It's NX567822100007.\nChunk 6: Hang on a tick and I'll check for you I'm sorry.\nChunk 7: we have no record of that arriving.\nChunk 8: OK, thanks for checking.\nChunk 9: Could you give me a ring when it arrives, please?", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 casual_comment=find, out. C3 casual_comment=i'm, felix. C4 [SKIP: thanks_only]. C5 casual_comment=number. C6 casual_comment=hang, tick. C7 casual_comment=record, arriving. C8 casual_comment=thanks, checking. C9 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello.\nChunk 2: I need to find out if a Receipt of Proceeds has arrived.\nChunk 3: I'm from Felix Wasserman Associates.\nChunk 4: Thanks.\nChunk 5: Have you got the L / C number It's NX567822100007.\nChunk 6: Hang on a tick and I'll check for you I'm sorry.\nChunk 7: we have no record of that arriving.\nChunk 8: OK, thanks for checking.\nChunk 9: Could you give me a ring when it arrives, please?"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 casual_comment=find, out. C3 casual_comment=i'm, felix. C4 [SKIP: thanks_only]. C5 casual_comment=number. C6 casual_comment=hang, tick. C7 casual_comment=record, arriving. C8 casual_comment=thanks, checking. C9 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello.\nChunk 2: I need to find out if a Receipt of Proceeds has arrived.\nChunk 3: I'm from Felix Wasserman Associates.\nChunk 4: Thanks.\nChunk 5: Have you got the L / C number It's NX567822100007.\nChunk 6: Hang on a tick and I'll check for you I'm sorry.\nChunk 7: we have no record of that arriving.\nChunk 8: OK, thanks for checking.\nChunk 9: Could you give me a ring when it arrives, please?", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on find. Next, the user comments on i'm. Next, the user comments on number. Next, the user comments on hang. Next, the user comments on record. Next, the user comments on thanks. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained greeting_only or thanks_only.", "trace": "C1 [SKIP: greeting_only]. C2 casual_comment=find, out. C3 casual_comment=i'm, felix. C4 [SKIP: thanks_only]. C5 casual_comment=number. C6 casual_comment=hang, tick. C7 casual_comment=record, arriving. C8 casual_comment=thanks, checking. C9 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello.", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to find out if a Receipt of Proceeds has arrived.", "streaming_reasoning": "As more information arrives, the user comments on find.", "trace": "casual_comment=find, out."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm from Felix Wasserman Associates.", "streaming_reasoning": "As more information arrives, the user comments on i'm.", "trace": "casual_comment=i'm, felix."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Have you got the L / C number It's NX567822100007.", "streaming_reasoning": "As more information arrives, the user comments on number..", "trace": "casual_comment=number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Hang on a tick and I'll check for you I'm sorry.", "streaming_reasoning": "As more information arrives, the user comments on hang.", "trace": "casual_comment=hang, tick."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "we have no record of that arriving.", "streaming_reasoning": "As more information arrives, the user comments on record.", "trace": "casual_comment=record, arriving."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "OK, thanks for checking.", "streaming_reasoning": "As more information arrives, the user comments on thanks.", "trace": "casual_comment=thanks, checking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Could you give me a ring when it arrives, please?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002413", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, can you look up Darrys Cookhouse and Wine Shop for me That's it.\nChunk 2: Can you make a reservation for me?\nChunk 3: There are 5 of us and we would like to reserve Sunday at 11:45 if possible.\nChunk 4: Thank you for the helpful information!\nChunk 5: That is all, thanks.\nChunk 6: Have a nice day.\nChunk 7: Bye!", "streaming_reasoning": "C1 intent=context_update. C2 goal=booking. C3 time+=11:45; day+=sunday; destination+=reserve sunday at 11:45 if possible. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only]. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need goal=booking; destination=reserve sunday at 11:45 if possible; when=sunday, 11:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, can you look up Darrys Cookhouse and Wine Shop for me That's it.\nChunk 2: Can you make a reservation for me?\nChunk 3: There are 5 of us and we would like to reserve Sunday at 11:45 if possible.\nChunk 4: Thank you for the helpful information!\nChunk 5: That is all, thanks.\nChunk 6: Have a nice day.\nChunk 7: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=booking. C3 time+=11:45; day+=sunday; destination+=reserve sunday at 11:45 if possible. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only]. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need goal=booking; destination=reserve sunday at 11:45 if possible; when=sunday, 11:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, can you look up Darrys Cookhouse and Wine Shop for me That's it.\nChunk 2: Can you make a reservation for me?\nChunk 3: There are 5 of us and we would like to reserve Sunday at 11:45 if possible.\nChunk 4: Thank you for the helpful information!\nChunk 5: That is all, thanks.\nChunk 6: Have a nice day.\nChunk 7: Bye!", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is booking. Finally, time: 11:45; day: sunday; destination: reserve sunday at 11:45 if possible.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is booking.. intent: context_update.; time: 11:45; day: sunday; destination: reserve sunday at 11:45 if possible..", "trace": "C1 intent=context_update. C2 goal=booking. C3 time+=11:45; day+=sunday; destination+=reserve sunday at 11:45 if possible. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only]. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, can you look up Darrys Cookhouse and Wine Shop for me That's it.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you make a reservation for me?", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "There are 5 of us and we would like to reserve Sunday at 11:45 if possible.", "streaming_reasoning": "As more information arrives, time: 11:45; day: sunday; destination: reserve sunday at 11:45 if possible..", "trace": "time+=11:45; day+=sunday; destination+=reserve sunday at 11:45 if possible."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you for the helpful information!", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That is all, thanks.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Have a nice day.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Bye!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=booking; destination=reserve sunday at 11:45 if possible; when=sunday, 11:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003028", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Do you have the five dollars I lent you yesterday Oh I forgot!\nChunk 2: I'll run home real quickly and bring you the money.\nChunk 3: You don't have to go right away.", "streaming_reasoning": "C1 casual_comment=five, dollars. C2 casual_comment=i'll, run. C3 leaving_reason=needs_to_go.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Do you have the five dollars I lent you yesterday Oh I forgot!\nChunk 2: I'll run home real quickly and bring you the money.\nChunk 3: You don't have to go right away."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=five, dollars. C2 casual_comment=i'll, run. C3 leaving_reason=needs_to_go.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Do you have the five dollars I lent you yesterday Oh I forgot!\nChunk 2: I'll run home real quickly and bring you the money.\nChunk 3: You don't have to go right away.", "input_token_count": 36, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on five. Next, the user comments on i'll. Finally, leaving reason: needs_to_go. In summary, leaving reason: needs_to_go..", "trace": "C1 casual_comment=five, dollars. C2 casual_comment=i'll, run. C3 leaving_reason=needs_to_go.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Do you have the five dollars I lent you yesterday Oh I forgot!", "streaming_reasoning": "Initially, the user comments on five.", "trace": "casual_comment=five, dollars."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'll run home real quickly and bring you the money.", "streaming_reasoning": "As more information arrives, the user comments on i'll.", "trace": "casual_comment=i'll, run."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "You don't have to go right away.", "streaming_reasoning": "Finally, leaving reason: needs_to_go..", "trace": "leaving_reason=needs_to_go."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002414", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant in the cheap price range that serves Italian food.\nChunk 2: I don't care which area.\nChunk 3: Yes please, I would like their address Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=italian; price+=cheap. C2 intent=context_update. C3 goal=request_info; requested_info+=address; acceptance=selected_option.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; food=italian; price=cheap; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant in the cheap price range that serves Italian food.\nChunk 2: I don't care which area.\nChunk 3: Yes please, I would like their address Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=italian; price+=cheap. C2 intent=context_update. C3 goal=request_info; requested_info+=address; acceptance=selected_option.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; food=italian; price=cheap; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant in the cheap price range that serves Italian food.\nChunk 2: I don't care which area.\nChunk 3: Yes please, I would like their address Thank you, goodbye.", "input_token_count": 36, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: italian; price: cheap. Next, intent: context_update. Finally, the goal is request info; requested information: address; acceptance: selected_option. In summary, The overall topic is restaurant. the goal is request info. cuisine: italian; price: cheap.; intent: context_update.; requested information: address; acceptance: selected_option..", "trace": "C1 domain=restaurant; goal=search; cuisine+=italian; price+=cheap. C2 intent=context_update. C3 goal=request_info; requested_info+=address; acceptance=selected_option.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant in the cheap price range that serves Italian food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: italian; price: cheap..", "trace": "domain=restaurant; goal=search; cuisine+=italian; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I don't care which area.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes please, I would like their address Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=address; acceptance=selected_option."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is italian; price is cheap; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; food=italian; price=cheap; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002415", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i need a place to stay.\nChunk 2: Price range doesn't really matter, but I do want a 4-star place with free parking and internet.\nChunk 3: The area doesn't matter.\nChunk 4: Please book for 6 people on Saturday with 4 nights stay.\nChunk 5: Can you give me a suggestion for a hotel and make that reservation please?\nChunk 6: Thanks.", "streaming_reasoning": "C1 domain=hotel; goal=search; destination+=stay. C2 amenities+=parking, internet, free parking. C3 intent=context_update. C4 goal=booking; day+=saturday; party_size+=6 people; stay_length+=4 nights. C5 goal=request_info; hotel_type+=hotel. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking, request_info; party_size=6 people; stay_length=4 nights; amenities=parking, internet, free parking; destination=stay; when=saturday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i need a place to stay.\nChunk 2: Price range doesn't really matter, but I do want a 4-star place with free parking and internet.\nChunk 3: The area doesn't matter.\nChunk 4: Please book for 6 people on Saturday with 4 nights stay.\nChunk 5: Can you give me a suggestion for a hotel and make that reservation please?\nChunk 6: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; destination+=stay. C2 amenities+=parking, internet, free parking. C3 intent=context_update. C4 goal=booking; day+=saturday; party_size+=6 people; stay_length+=4 nights. C5 goal=request_info; hotel_type+=hotel. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking, request_info; party_size=6 people; stay_length=4 nights; amenities=parking, internet, free parking; destination=stay; when=saturday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i need a place to stay.\nChunk 2: Price range doesn't really matter, but I do want a 4-star place with free parking and internet.\nChunk 3: The area doesn't matter.\nChunk 4: Please book for 6 people on Saturday with 4 nights stay.\nChunk 5: Can you give me a suggestion for a hotel and make that reservation please?\nChunk 6: Thanks.", "input_token_count": 65, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay. Next, amenities: parking. Next, intent: context_update. Next, the goal is booking; day: saturday; party size: 6 people; stay length: 4 nights. Finally, the goal is request info; hotel type: hotel.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is request info. destination: stay.; amenities: parking; intent: context_update.; day: saturday; party size: 6 people; stay length: 4 nights.; hotel type: hotel..", "trace": "C1 domain=hotel; goal=search; destination+=stay. C2 amenities+=parking, internet, free parking. C3 intent=context_update. C4 goal=booking; day+=saturday; party_size+=6 people; stay_length+=4 nights. C5 goal=request_info; hotel_type+=hotel. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i need a place to stay.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Price range doesn't really matter, but I do want a 4-star place with free parking and internet.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, internet, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The area doesn't matter.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please book for 6 people on Saturday with 4 nights stay.", "streaming_reasoning": "As more information arrives, the goal is booking; day: saturday; party size: 6 people; stay length: 4 nights..", "trace": "goal=booking; day+=saturday; party_size+=6 people; stay_length+=4 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you give me a suggestion for a hotel and make that reservation please?", "streaming_reasoning": "As more information arrives, the goal is request info; hotel type: hotel..", "trace": "goal=request_info; hotel_type+=hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 6 people; stay length is 4 nights; amenities is parking; destination is stay; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, request_info; party_size=6 people; stay_length=4 nights; amenities=parking, internet, free parking; destination=stay; when=saturday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002416", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: book it for 6 people and 4 nights starting from monday.\nChunk 2: Thank you very much!\nChunk 3: I need a train on wednesday which will go to liverpool street in london.\nChunk 4: I need to arrive by 18:30 and need to depart from Cambridge Just for myself.\nChunk 5: Give me the travel tiem and the train ID please.\nChunk 6: That will be all thank you for your help.", "streaming_reasoning": "C1 goal=booking; time+=6, 4; day+=monday; party_size+=6 people; stay_length+=4 nights. C2 [SKIP: thanks_only]. C3 domain=train; goal=search; day+=wednesday; amenities+=pool; destination+=liverpool street in london. C4 time+=18:30; departure+=cambridge just for myself. C5 goal=request_info. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=booking, search, request_info; party_size=6 people; stay_length=4 nights; amenities=pool; destination=liverpool street in london; departure=cambridge just for myself; when=monday, wednesday, 6, 4, 18:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: book it for 6 people and 4 nights starting from monday.\nChunk 2: Thank you very much!\nChunk 3: I need a train on wednesday which will go to liverpool street in london.\nChunk 4: I need to arrive by 18:30 and need to depart from Cambridge Just for myself.\nChunk 5: Give me the travel tiem and the train ID please.\nChunk 6: That will be all thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=6, 4; day+=monday; party_size+=6 people; stay_length+=4 nights. C2 [SKIP: thanks_only]. C3 domain=train; goal=search; day+=wednesday; amenities+=pool; destination+=liverpool street in london. C4 time+=18:30; departure+=cambridge just for myself. C5 goal=request_info. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=booking, search, request_info; party_size=6 people; stay_length=4 nights; amenities=pool; destination=liverpool street in london; departure=cambridge just for myself; when=monday, wednesday, 6, 4, 18:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: book it for 6 people and 4 nights starting from monday.\nChunk 2: Thank you very much!\nChunk 3: I need a train on wednesday which will go to liverpool street in london.\nChunk 4: I need to arrive by 18:30 and need to depart from Cambridge Just for myself.\nChunk 5: Give me the travel tiem and the train ID please.\nChunk 6: That will be all thank you for your help.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 6; day: monday; party size: 6 people; stay length: 4 nights. Next, the topic is train; the goal is search; day: wednesday; amenities: pool; destination: liverpool street in london. Next, time: 18:30; departure point: cambridge just for myself. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is request info.. time: 6, 18:30; day: monday, wednesday; party size: 6 people; stay length: 4 nights.; amenities: pool; destination: liverpool street in london.; departure point: cambridge just for myself..", "trace": "C1 goal=booking; time+=6, 4; day+=monday; party_size+=6 people; stay_length+=4 nights. C2 [SKIP: thanks_only]. C3 domain=train; goal=search; day+=wednesday; amenities+=pool; destination+=liverpool street in london. C4 time+=18:30; departure+=cambridge just for myself. C5 goal=request_info. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "book it for 6 people and 4 nights starting from monday.", "streaming_reasoning": "Initially, the goal is booking; time: 6; day: monday; party size: 6 people; stay length: 4 nights..", "trace": "goal=booking; time+=6, 4; day+=monday; party_size+=6 people; stay_length+=4 nights."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thank you very much!", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need a train on wednesday which will go to liverpool street in london.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: wednesday; amenities: pool; destination: liverpool street in london..", "trace": "domain=train; goal=search; day+=wednesday; amenities+=pool; destination+=liverpool street in london."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to arrive by 18:30 and need to depart from Cambridge Just for myself.", "streaming_reasoning": "As more information arrives, time: 18:30; departure point: cambridge just for myself..", "trace": "time+=18:30; departure+=cambridge just for myself."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Give me the travel tiem and the train ID please.", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That will be all thank you for your help.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: party size is 6 people; stay length is 4 nights; amenities is pool; destination is liverpool street in london; departure point is cambridge just for myself; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, search, request_info; party_size=6 people; stay_length=4 nights; amenities=pool; destination=liverpool street in london; departure=cambridge just for myself; when=monday, wednesday, 6, 4, 18:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002417", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please for 7 people for 4 nights starting thursday and I need the reference number Thank you.\nChunk 2: I am also looking for a Chinese restaurant in the same area as the Huntingdon Marriott Hotel.\nChunk 3: Are there any Chinese restaurants within a short distance outside the area which are in the same price range as the hotel?\nChunk 4: Excellent, can I get the address of the Ugly Duckling?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:30.\nChunk 7: Please make a booking.\nChunk 8: No, I do not think so.\nChunk 9: Thank you for your help!", "streaming_reasoning": "C1 goal=request_info; time+=7, 4; day+=thursday; party_size+=7 people; stay_length+=4 nights; requested_info+=reference_number; acceptance=selected_option. C2 domain=hotel; goal=modify_constraint; cuisine+=chinese; hotel_type+=hotel. C3 price+=same price. C4 requested_info+=address. C5 destination+=find a restaurant. C6 time+=17:30. C7 goal=booking. C8 goal=modify_constraint. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, hotel; goal=search, request_info, modify_constraint, booking; food=chinese; price=same price; party_size=7 people; stay_length=4 nights; destination=find a restaurant; requested_info=reference_number, address; when=thursday, 7, 4, 17:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please for 7 people for 4 nights starting thursday and I need the reference number Thank you.\nChunk 2: I am also looking for a Chinese restaurant in the same area as the Huntingdon Marriott Hotel.\nChunk 3: Are there any Chinese restaurants within a short distance outside the area which are in the same price range as the hotel?\nChunk 4: Excellent, can I get the address of the Ugly Duckling?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:30.\nChunk 7: Please make a booking.\nChunk 8: No, I do not think so.\nChunk 9: Thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; time+=7, 4; day+=thursday; party_size+=7 people; stay_length+=4 nights; requested_info+=reference_number; acceptance=selected_option. C2 domain=hotel; goal=modify_constraint; cuisine+=chinese; hotel_type+=hotel. C3 price+=same price. C4 requested_info+=address. C5 destination+=find a restaurant. C6 time+=17:30. C7 goal=booking. C8 goal=modify_constraint. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, hotel; goal=search, request_info, modify_constraint, booking; food=chinese; price=same price; party_size=7 people; stay_length=4 nights; destination=find a restaurant; requested_info=reference_number, address; when=thursday, 7, 4, 17:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please for 7 people for 4 nights starting thursday and I need the reference number Thank you.\nChunk 2: I am also looking for a Chinese restaurant in the same area as the Huntingdon Marriott Hotel.\nChunk 3: Are there any Chinese restaurants within a short distance outside the area which are in the same price range as the hotel?\nChunk 4: Excellent, can I get the address of the Ugly Duckling?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:30.\nChunk 7: Please make a booking.\nChunk 8: No, I do not think so.\nChunk 9: Thank you for your help!", "input_token_count": 111, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; time: 7; day: thursday; party size: 7 people; stay length: 4 nights; requested information: reference_number; acceptance: selected_option. Next, the topic is hotel; the goal is modify constraint; cuisine: chinese; hotel type: hotel. Next, price: same price. Next, requested information: address. Next, destination: find a restaurant. Next, time: 17:30. Next, the goal is booking. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is modify constraint.. time: 7, 17:30.; day: thursday; party size: 7 people; stay length: 4 nights; requested information: reference_number, address.; acceptance: selected_option.; cuisine: chinese; hotel type: hotel.; price: same price.; destination: find a restaurant..", "trace": "C1 goal=request_info; time+=7, 4; day+=thursday; party_size+=7 people; stay_length+=4 nights; requested_info+=reference_number; acceptance=selected_option. C2 domain=hotel; goal=modify_constraint; cuisine+=chinese; hotel_type+=hotel. C3 price+=same price. C4 requested_info+=address. C5 destination+=find a restaurant. C6 time+=17:30. C7 goal=booking. C8 goal=modify_constraint. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please for 7 people for 4 nights starting thursday and I need the reference number Thank you.", "streaming_reasoning": "Initially, the goal is request info; time: 7; day: thursday; party size: 7 people; stay length: 4 nights; requested information: reference_number; acceptance: selected_option..", "trace": "goal=request_info; time+=7, 4; day+=thursday; party_size+=7 people; stay_length+=4 nights; requested_info+=reference_number; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also looking for a Chinese restaurant in the same area as the Huntingdon Marriott Hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is modify constraint; cuisine: chinese; hotel type: hotel..", "trace": "domain=hotel; goal=modify_constraint; cuisine+=chinese; hotel_type+=hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Are there any Chinese restaurants within a short distance outside the area which are in the same price range as the hotel?", "streaming_reasoning": "As more information arrives, price: same price..", "trace": "price+=same price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Excellent, can I get the address of the Ugly Duckling?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, destination: find a restaurant..", "trace": "destination+=find a restaurant."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 17:30.", "streaming_reasoning": "As more information arrives, time: 17:30..", "trace": "time+=17:30."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, I do not think so.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you for your help!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is chinese; price is same price; party size is 7 people; stay length is 4 nights; destination is find a restaurant; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=search, request_info, modify_constraint, booking; food=chinese; price=same price; party_size=7 people; stay_length=4 nights; destination=find a restaurant; requested_info=reference_number, address; when=thursday, 7, 4, 17:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002418", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you.\nChunk 2: I'm also looking for a place to stay in the east with free parking.\nChunk 3: The hotel should be in the moderate price range Great.\nChunk 4: I need to make a reservation for Saturday.\nChunk 5: It will be 2 nights and for 1 person Yes please.\nChunk 6: I would like it for one person for 2 nights.\nChunk 7: that will be it for now.\nChunk 8: thanks.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; area+=east; amenities+=parking, free parking; destination+=stay in the east with free parking. C3 price+=moderate; hotel_type+=hotel. C4 goal=booking; day+=saturday; destination+=make a reservation for saturday. C5 stay_length+=2 nights; goal=confirm_booking. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking; area=east; price=moderate; stay_length=2 nights; amenities=parking, free parking; destination=stay in the east with free parking, make a reservation for saturday; when=saturday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you.\nChunk 2: I'm also looking for a place to stay in the east with free parking.\nChunk 3: The hotel should be in the moderate price range Great.\nChunk 4: I need to make a reservation for Saturday.\nChunk 5: It will be 2 nights and for 1 person Yes please.\nChunk 6: I would like it for one person for 2 nights.\nChunk 7: that will be it for now.\nChunk 8: thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; area+=east; amenities+=parking, free parking; destination+=stay in the east with free parking. C3 price+=moderate; hotel_type+=hotel. C4 goal=booking; day+=saturday; destination+=make a reservation for saturday. C5 stay_length+=2 nights; goal=confirm_booking. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking; area=east; price=moderate; stay_length=2 nights; amenities=parking, free parking; destination=stay in the east with free parking, make a reservation for saturday; when=saturday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you.\nChunk 2: I'm also looking for a place to stay in the east with free parking.\nChunk 3: The hotel should be in the moderate price range Great.\nChunk 4: I need to make a reservation for Saturday.\nChunk 5: It will be 2 nights and for 1 person Yes please.\nChunk 6: I would like it for one person for 2 nights.\nChunk 7: that will be it for now.\nChunk 8: thanks.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: east; amenities: parking; destination: stay in the east with free parking. Next, price: moderate; hotel type: hotel. Next, the goal is booking; day: saturday; destination: make a reservation for saturday. Next, the goal is confirm booking.; stay length: 2 nights. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is confirm booking.. area: east; amenities: parking; destination: stay in the east with free parking., make a reservation for saturday.; price: moderate; hotel type: hotel.; day: saturday; stay length: 2 nights; intent: context_update..", "trace": "C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; area+=east; amenities+=parking, free parking; destination+=stay in the east with free parking. C3 price+=moderate; hotel_type+=hotel. C4 goal=booking; day+=saturday; destination+=make a reservation for saturday. C5 stay_length+=2 nights; goal=confirm_booking. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm also looking for a place to stay in the east with free parking.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; area: east; amenities: parking; destination: stay in the east with free parking..", "trace": "domain=hotel; goal=search; area+=east; amenities+=parking, free parking; destination+=stay in the east with free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The hotel should be in the moderate price range Great.", "streaming_reasoning": "As more information arrives, price: moderate; hotel type: hotel..", "trace": "price+=moderate; hotel_type+=hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to make a reservation for Saturday.", "streaming_reasoning": "As more information arrives, the goal is booking; day: saturday; destination: make a reservation for saturday..", "trace": "goal=booking; day+=saturday; destination+=make a reservation for saturday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It will be 2 nights and for 1 person Yes please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; stay length: 2 nights.", "trace": "stay_length+=2 nights; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I would like it for one person for 2 nights.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "that will be it for now.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "thanks.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is east; price is moderate; stay length is 2 nights; amenities is parking; destination is stay in the east with free parking; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking; area=east; price=moderate; stay_length=2 nights; amenities=parking, free parking; destination=stay in the east with free parking, make a reservation for saturday; when=saturday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002419", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Help me find a restaurant called hakka please.\nChunk 2: I'd like to book a table for 3 people for saturday at 1815 please.\nChunk 3: Thank you for your help, good day.\nChunk 4: Of course Thanks, good bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 goal=booking; time+=3; day+=saturday; party_size+=3 people. C3 [SKIP: thanks_only]. C4 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, booking; party_size=3 people; when=saturday, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Help me find a restaurant called hakka please.\nChunk 2: I'd like to book a table for 3 people for saturday at 1815 please.\nChunk 3: Thank you for your help, good day.\nChunk 4: Of course Thanks, good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 goal=booking; time+=3; day+=saturday; party_size+=3 people. C3 [SKIP: thanks_only]. C4 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, booking; party_size=3 people; when=saturday, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Help me find a restaurant called hakka please.\nChunk 2: I'd like to book a table for 3 people for saturday at 1815 please.\nChunk 3: Thank you for your help, good day.\nChunk 4: Of course Thanks, good bye.", "input_token_count": 42, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, the goal is booking; time: 3; day: saturday; party size: 3 people. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is booking. time: 3; day: saturday; party size: 3 people.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search. C2 goal=booking; time+=3; day+=saturday; party_size+=3 people. C3 [SKIP: thanks_only]. C4 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Help me find a restaurant called hakka please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to book a table for 3 people for saturday at 1815 please.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 3; day: saturday; party size: 3 people..", "trace": "goal=booking; time+=3; day+=saturday; party_size+=3 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you for your help, good day.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Of course Thanks, good bye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 3 people; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking; party_size=3 people; when=saturday, 3; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003036", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm not feeling too well.\nChunk 2: Mr.: Would you like to go to the nurse's Yes, I would.\nChunk 3: Mr.: Here's a hall pass for it.\nChunk 4: Do you need someone to walk you there?\nChunk 5: I can manage on my own.\nChunk 6: Thanks.", "streaming_reasoning": "C1 casual_comment=i'm, not. C2 invitation=true. C3 casual_comment=here's, hall. C4 question=true. C5 casual_comment=manage, own. C6 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm not feeling too well.\nChunk 2: Mr.: Would you like to go to the nurse's Yes, I would.\nChunk 3: Mr.: Here's a hall pass for it.\nChunk 4: Do you need someone to walk you there?\nChunk 5: I can manage on my own.\nChunk 6: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=i'm, not. C2 invitation=true. C3 casual_comment=here's, hall. C4 question=true. C5 casual_comment=manage, own. C6 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm not feeling too well.\nChunk 2: Mr.: Would you like to go to the nurse's Yes, I would.\nChunk 3: Mr.: Here's a hall pass for it.\nChunk 4: Do you need someone to walk you there?\nChunk 5: I can manage on my own.\nChunk 6: Thanks.", "input_token_count": 51, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on i'm. Next, invitation: true. Next, the user comments on here's. Next, the input provides additional context about question=true. Finally, the user comments on manage.  Some chunks were skipped because they contained thanks_only. In summary, invitation: true..", "trace": "C1 casual_comment=i'm, not. C2 invitation=true. C3 casual_comment=here's, hall. C4 question=true. C5 casual_comment=manage, own. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm not feeling too well.", "streaming_reasoning": "Initially, the user comments on i'm.", "trace": "casual_comment=i'm, not."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Mr.: Would you like to go to the nurse's Yes, I would.", "streaming_reasoning": "As more information arrives, invitation: true..", "trace": "invitation=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Mr.: Here's a hall pass for it.", "streaming_reasoning": "As more information arrives, the user comments on here's.", "trace": "casual_comment=here's, hall."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Do you need someone to walk you there?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I can manage on my own.", "streaming_reasoning": "As more information arrives, the user comments on manage.", "trace": "casual_comment=manage, own."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002420", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm shopping for colleges.\nChunk 2: Can you help me find one to visit in the city centre, please?\nChunk 3: Can you name them off for me?\nChunk 4: Can I get the post code for Christ's College?\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the centre part of town.\nChunk 7: Yes, I would like to stay within the moderate price range, if possible.", "streaming_reasoning": "C1 intent=context_update. C2 goal=search; area+=centre; destination+=visit in the city centre. C3 goal=request_info. C4 domain=attraction; goal=request_info; requested_info+=postcode. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 intent=context_update. C7 price+=moderate; destination+=stay within the moderate price range; acceptance=selected_option.", "deep_reasoning": "Need domain=attraction, hotel; goal=search, request_info; area=centre; price=moderate; destination=visit in the city centre, find a hotel, stay within the moderate price range; requested_info=postcode.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I'm shopping for colleges.\nChunk 2: Can you help me find one to visit in the city centre, please?\nChunk 3: Can you name them off for me?\nChunk 4: Can I get the post code for Christ's College?\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the centre part of town.\nChunk 7: Yes, I would like to stay within the moderate price range, if possible."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=search; area+=centre; destination+=visit in the city centre. C3 goal=request_info. C4 domain=attraction; goal=request_info; requested_info+=postcode. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 intent=context_update. C7 price+=moderate; destination+=stay within the moderate price range; acceptance=selected_option.\n\nDeep reasoning: Need domain=attraction, hotel; goal=search, request_info; area=centre; price=moderate; destination=visit in the city centre, find a hotel, stay within the moderate price range; requested_info=postcode.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm shopping for colleges.\nChunk 2: Can you help me find one to visit in the city centre, please?\nChunk 3: Can you name them off for me?\nChunk 4: Can I get the post code for Christ's College?\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the centre part of town.\nChunk 7: Yes, I would like to stay within the moderate price range, if possible.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is search; area: centre; destination: visit in the city centre. Next, the goal is request info. Next, the topic is attraction; the goal is request info; requested information: postcode. Next, the topic is hotel; hotel type: hotel; destination: find a hotel. Next, intent: context_update. Finally, price: moderate; destination: stay within the moderate price range; acceptance: selected_option. In summary, The overall topic is hotel. the goal is request info. intent: context_update.; area: centre; destination: visit in the city centre., find a hotel., stay within the moderate price range; requested information: postcode.; hotel type: hotel; price: moderate; acceptance: selected_option..", "trace": "C1 intent=context_update. C2 goal=search; area+=centre; destination+=visit in the city centre. C3 goal=request_info. C4 domain=attraction; goal=request_info; requested_info+=postcode. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 intent=context_update. C7 price+=moderate; destination+=stay within the moderate price range; acceptance=selected_option.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I'm shopping for colleges.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you help me find one to visit in the city centre, please?", "streaming_reasoning": "As more information arrives, the goal is search; area: centre; destination: visit in the city centre..", "trace": "goal=search; area+=centre; destination+=visit in the city centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you name them off for me?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I get the post code for Christ's College?", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is request info; requested information: postcode..", "trace": "domain=attraction; goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, I would like to stay within the moderate price range, if possible.", "streaming_reasoning": "Finally, price: moderate; destination: stay within the moderate price range; acceptance: selected_option..", "trace": "price+=moderate; destination+=stay within the moderate price range; acceptance=selected_option."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; price is moderate; destination is visit in the city centre; requested information is postcode.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=attraction, hotel; goal=search, request_info; area=centre; price=moderate; destination=visit in the city centre, find a hotel, stay within the moderate price range; requested_info=postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002422", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find a train for Friday?\nChunk 2: i'm headed to cambridge.\nChunk 3: I'll be leaving from the stansted airport, and any time after 8:00 is fine.\nChunk 4: Can you tell me how much that will cost?\nChunk 5: Yes, that would be great.\nChunk 6: I am also looking for any parks in the north side of the city, do you know any?\nChunk 7: Can you provide me with the phone number, address and postcode please?\nChunk 8: Great that is all the information I need, thank you.", "streaming_reasoning": "C1 domain=train; goal=search; day+=friday. C2 destination+=cambridge. C3 time+=8:00. C4 goal=request_info; requested_info+=price. C5 acceptance=selected_option. C6 area+=north. C7 requested_info+=address, phone, postcode. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; area=north; destination=cambridge; requested_info=price, address, phone, postcode; when=friday, 8:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you help me find a train for Friday?\nChunk 2: i'm headed to cambridge.\nChunk 3: I'll be leaving from the stansted airport, and any time after 8:00 is fine.\nChunk 4: Can you tell me how much that will cost?\nChunk 5: Yes, that would be great.\nChunk 6: I am also looking for any parks in the north side of the city, do you know any?\nChunk 7: Can you provide me with the phone number, address and postcode please?\nChunk 8: Great that is all the information I need, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=friday. C2 destination+=cambridge. C3 time+=8:00. C4 goal=request_info; requested_info+=price. C5 acceptance=selected_option. C6 area+=north. C7 requested_info+=address, phone, postcode. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; area=north; destination=cambridge; requested_info=price, address, phone, postcode; when=friday, 8:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find a train for Friday?\nChunk 2: i'm headed to cambridge.\nChunk 3: I'll be leaving from the stansted airport, and any time after 8:00 is fine.\nChunk 4: Can you tell me how much that will cost?\nChunk 5: Yes, that would be great.\nChunk 6: I am also looking for any parks in the north side of the city, do you know any?\nChunk 7: Can you provide me with the phone number, address and postcode please?\nChunk 8: Great that is all the information I need, thank you.", "input_token_count": 98, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: friday. Next, destination: cambridge. Next, time: 8:00. Next, the goal is request info; requested information: price. Next, acceptance: selected_option. Next, area: north. Finally, requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. day: friday.; destination: cambridge.; time: 8:00.; requested information: price., address; acceptance: selected_option.; area: north..", "trace": "C1 domain=train; goal=search; day+=friday. C2 destination+=cambridge. C3 time+=8:00. C4 goal=request_info; requested_info+=price. C5 acceptance=selected_option. C6 area+=north. C7 requested_info+=address, phone, postcode. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you help me find a train for Friday?", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: friday..", "trace": "domain=train; goal=search; day+=friday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "i'm headed to cambridge.", "streaming_reasoning": "As more information arrives, destination: cambridge..", "trace": "destination+=cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'll be leaving from the stansted airport, and any time after 8:00 is fine.", "streaming_reasoning": "As more information arrives, time: 8:00..", "trace": "time+=8:00."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you tell me how much that will cost?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, that would be great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I am also looking for any parks in the north side of the city, do you know any?", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can you provide me with the phone number, address and postcode please?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, phone, postcode."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Great that is all the information I need, thank you.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is north; destination is cambridge; requested information is price; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; area=north; destination=cambridge; requested_info=price, address, phone, postcode; when=friday, 8:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002423", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I am also looking for a Train leaving some time after 9:15 from Bishops Stortford.\nChunk 2: I will be leaving on thursday.\nChunk 3: My destination is Cambridge.\nChunk 4: I need help with train.\nChunk 5: The time is thursday, 9:15 Brilliant.\nChunk 6: Thanks for your help today.\nChunk 7: Yes that is all You were great Thanks again.", "streaming_reasoning": "C1 domain=train; goal=search; time+=9:15; acceptance=selected_option. C2 day+=thursday. C3 intent=context_update. C4 intent=context_update. C5 intent=context_update. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search; when=thursday, 9:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I am also looking for a Train leaving some time after 9:15 from Bishops Stortford.\nChunk 2: I will be leaving on thursday.\nChunk 3: My destination is Cambridge.\nChunk 4: I need help with train.\nChunk 5: The time is thursday, 9:15 Brilliant.\nChunk 6: Thanks for your help today.\nChunk 7: Yes that is all You were great Thanks again."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; time+=9:15; acceptance=selected_option. C2 day+=thursday. C3 intent=context_update. C4 intent=context_update. C5 intent=context_update. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search; when=thursday, 9:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I am also looking for a Train leaving some time after 9:15 from Bishops Stortford.\nChunk 2: I will be leaving on thursday.\nChunk 3: My destination is Cambridge.\nChunk 4: I need help with train.\nChunk 5: The time is thursday, 9:15 Brilliant.\nChunk 6: Thanks for your help today.\nChunk 7: Yes that is all You were great Thanks again.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 9:15; acceptance: selected_option. Next, day: thursday. Next, intent: context_update. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is search. time: 9:15; acceptance: selected_option.; day: thursday.; intent: context_update..", "trace": "C1 domain=train; goal=search; time+=9:15; acceptance=selected_option. C2 day+=thursday. C3 intent=context_update. C4 intent=context_update. C5 intent=context_update. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I am also looking for a Train leaving some time after 9:15 from Bishops Stortford.", "streaming_reasoning": "Initially, the topic is train; the goal is search; time: 9:15; acceptance: selected_option..", "trace": "domain=train; goal=search; time+=9:15; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be leaving on thursday.", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "My destination is Cambridge.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is thursday, 9:15 Brilliant.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks for your help today.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes that is all You were great Thanks again.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search; when=thursday, 9:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002424", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am also looking for a moderately priced restaurant in the same area as Corpus Christi.\nChunk 2: I am looking for Asian Oriental.\nChunk 3: The time is wednesday, 4, 18:45.\nChunk 4: Please make a booking.\nChunk 5: thanks so much for all of your help!\nChunk 6: That is all thank you.\nChunk 7: Thank you, that is all I need.", "streaming_reasoning": "C1 domain=restaurant; goal=modify_constraint; price+=moderate. C2 intent=context_update. C3 time+=4, 18:45; day+=wednesday. C4 goal=booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, modify_constraint, booking; price=moderate; when=wednesday, 4, 18:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am also looking for a moderately priced restaurant in the same area as Corpus Christi.\nChunk 2: I am looking for Asian Oriental.\nChunk 3: The time is wednesday, 4, 18:45.\nChunk 4: Please make a booking.\nChunk 5: thanks so much for all of your help!\nChunk 6: That is all thank you.\nChunk 7: Thank you, that is all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=modify_constraint; price+=moderate. C2 intent=context_update. C3 time+=4, 18:45; day+=wednesday. C4 goal=booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, modify_constraint, booking; price=moderate; when=wednesday, 4, 18:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am also looking for a moderately priced restaurant in the same area as Corpus Christi.\nChunk 2: I am looking for Asian Oriental.\nChunk 3: The time is wednesday, 4, 18:45.\nChunk 4: Please make a booking.\nChunk 5: thanks so much for all of your help!\nChunk 6: That is all thank you.\nChunk 7: Thank you, that is all I need.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is modify constraint; price: moderate. Next, intent: context_update. Next, time: 4; day: wednesday. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is booking.. price: moderate.; intent: context_update.; time: 4; day: wednesday..", "trace": "C1 domain=restaurant; goal=modify_constraint; price+=moderate. C2 intent=context_update. C3 time+=4, 18:45; day+=wednesday. C4 goal=booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am also looking for a moderately priced restaurant in the same area as Corpus Christi.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is modify constraint; price: moderate..", "trace": "domain=restaurant; goal=modify_constraint; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am looking for Asian Oriental.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is wednesday, 4, 18:45.", "streaming_reasoning": "As more information arrives, time: 4; day: wednesday..", "trace": "time+=4, 18:45; day+=wednesday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "thanks so much for all of your help!", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you, that is all I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: price is moderate; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, modify_constraint, booking; price=moderate; when=wednesday, 4, 18:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003040", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: What time do you open and close on Saturday?\nChunk 3: The hours are from 9 am - 6.\nChunk 4: Okay.\nChunk 5: Thank you very much.\nChunk 6: Do you need anything else?", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 question=true. C3 casual_comment=hours. C4 [SKIP: backchannel_only]. C5 [SKIP: thanks_only]. C6 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: What time do you open and close on Saturday?\nChunk 3: The hours are from 9 am - 6.\nChunk 4: Okay.\nChunk 5: Thank you very much.\nChunk 6: Do you need anything else?"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 question=true. C3 casual_comment=hours. C4 [SKIP: backchannel_only]. C5 [SKIP: thanks_only]. C6 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: What time do you open and close on Saturday?\nChunk 3: The hours are from 9 am - 6.\nChunk 4: Okay.\nChunk 5: Thank you very much.\nChunk 6: Do you need anything else?", "input_token_count": 39, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on hours. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained acknowledgement_only or backchannel_only or thanks_only.", "trace": "C1 [SKIP: acknowledgement_only]. C2 question=true. C3 casual_comment=hours. C4 [SKIP: backchannel_only]. C5 [SKIP: thanks_only]. C6 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What time do you open and close on Saturday?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The hours are from 9 am - 6.", "streaming_reasoning": "As more information arrives, the user comments on hours..", "trace": "casual_comment=hours."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Okay.", "streaming_reasoning": "The content at C4 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Do you need anything else?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003042", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you, Mr. Davis.\nChunk 2: Oh, any chance of a table by the window?\nChunk 3: My wife loves the bird's eye view.\nChunk 4: As it's her birthday, I want it to be a celebration I see.\nChunk 5: We have already received many bookings and though I can't guarantee anything, please be assured that we'll try our best, Mr. Davis.\nChunk 6: I hope you'll understand.\nChunk 7: I do, but I would appreciate you, if it could be arranged.\nChunk 8: We'll try our best.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=wife, loves. C4 casual_comment=her, birthday. C5 schedule_conflict=true. C6 casual_comment=hope, you'll. C7 casual_comment=appreciate, arranged. C8 casual_comment=we'll, try.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you, Mr. Davis.\nChunk 2: Oh, any chance of a table by the window?\nChunk 3: My wife loves the bird's eye view.\nChunk 4: As it's her birthday, I want it to be a celebration I see.\nChunk 5: We have already received many bookings and though I can't guarantee anything, please be assured that we'll try our best, Mr. Davis.\nChunk 6: I hope you'll understand.\nChunk 7: I do, but I would appreciate you, if it could be arranged.\nChunk 8: We'll try our best."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=wife, loves. C4 casual_comment=her, birthday. C5 schedule_conflict=true. C6 casual_comment=hope, you'll. C7 casual_comment=appreciate, arranged. C8 casual_comment=we'll, try.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you, Mr. Davis.\nChunk 2: Oh, any chance of a table by the window?\nChunk 3: My wife loves the bird's eye view.\nChunk 4: As it's her birthday, I want it to be a celebration I see.\nChunk 5: We have already received many bookings and though I can't guarantee anything, please be assured that we'll try our best, Mr. Davis.\nChunk 6: I hope you'll understand.\nChunk 7: I do, but I would appreciate you, if it could be arranged.\nChunk 8: We'll try our best.", "input_token_count": 91, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on wife. Next, the user comments on her. Next, schedule conflict: true. Next, the user comments on hope. Next, the user comments on appreciate. Finally, the user comments on we'll.  Some chunks were skipped because they contained thanks_only. In summary, schedule conflict: true..", "trace": "C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=wife, loves. C4 casual_comment=her, birthday. C5 schedule_conflict=true. C6 casual_comment=hope, you'll. C7 casual_comment=appreciate, arranged. C8 casual_comment=we'll, try.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you, Mr. Davis.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Oh, any chance of a table by the window?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "My wife loves the bird's eye view.", "streaming_reasoning": "As more information arrives, the user comments on wife.", "trace": "casual_comment=wife, loves."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "As it's her birthday, I want it to be a celebration I see.", "streaming_reasoning": "As more information arrives, the user comments on her.", "trace": "casual_comment=her, birthday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "We have already received many bookings and though I can't guarantee anything, please be assured that we'll try our best, Mr. Davis.", "streaming_reasoning": "As more information arrives, schedule conflict: true..", "trace": "schedule_conflict=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I hope you'll understand.", "streaming_reasoning": "As more information arrives, the user comments on hope.", "trace": "casual_comment=hope, you'll."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I do, but I would appreciate you, if it could be arranged.", "streaming_reasoning": "As more information arrives, the user comments on appreciate.", "trace": "casual_comment=appreciate, arranged."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "We'll try our best.", "streaming_reasoning": "Finally, the user comments on we'll.", "trace": "casual_comment=we'll, try."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002425", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to find an expensive restaurant in the east part of town I don't care.\nChunk 2: Just the phone number is fine, please.\nChunk 3: That is all, thank you very much Good bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=east; price+=expensive; destination+=find an expensive restaurant in the east. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=east; price=expensive; destination=find an expensive restaurant in the east; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to find an expensive restaurant in the east part of town I don't care.\nChunk 2: Just the phone number is fine, please.\nChunk 3: That is all, thank you very much Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=east; price+=expensive; destination+=find an expensive restaurant in the east. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=east; price=expensive; destination=find an expensive restaurant in the east; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to find an expensive restaurant in the east part of town I don't care.\nChunk 2: Just the phone number is fine, please.\nChunk 3: That is all, thank you very much Good bye.", "input_token_count": 39, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: east; price: expensive; destination: find an expensive restaurant in the east. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. area: east; price: expensive; destination: find an expensive restaurant in the east.; requested information: phone..", "trace": "C1 domain=restaurant; goal=search; area+=east; price+=expensive; destination+=find an expensive restaurant in the east. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to find an expensive restaurant in the east part of town I don't care.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: east; price: expensive; destination: find an expensive restaurant in the east..", "trace": "domain=restaurant; goal=search; area+=east; price+=expensive; destination+=find an expensive restaurant in the east."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Just the phone number is fine, please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That is all, thank you very much Good bye.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is east; price is expensive; destination is find an expensive restaurant in the east; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=east; price=expensive; destination=find an expensive restaurant in the east; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002426", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I want to find some water and go boating somewhere around town.\nChunk 2: What do you have listed?\nChunk 3: I think maybe the north for this trip.\nChunk 4: That is all I need, thank you.", "streaming_reasoning": "C1 goal=search; destination+=find some water and go boating somewhere. C2 goal=request_info. C3 area+=north. C4 [SKIP: closing_only].", "deep_reasoning": "Need goal=search; area=north; destination=find some water and go boating somewhere; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I want to find some water and go boating somewhere around town.\nChunk 2: What do you have listed?\nChunk 3: I think maybe the north for this trip.\nChunk 4: That is all I need, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; destination+=find some water and go boating somewhere. C2 goal=request_info. C3 area+=north. C4 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search; area=north; destination=find some water and go boating somewhere; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I want to find some water and go boating somewhere around town.\nChunk 2: What do you have listed?\nChunk 3: I think maybe the north for this trip.\nChunk 4: That is all I need, thank you.", "input_token_count": 41, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; destination: find some water and go boating somewhere. Next, the goal is request info. Finally, area: north.  Some chunks were skipped because they contained closing_only. In summary, the goal is request info.. destination: find some water and go boating somewhere.; area: north..", "trace": "C1 goal=search; destination+=find some water and go boating somewhere. C2 goal=request_info. C3 area+=north. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I want to find some water and go boating somewhere around town.", "streaming_reasoning": "Initially, the goal is search; destination: find some water and go boating somewhere..", "trace": "goal=search; destination+=find some water and go boating somewhere."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What do you have listed?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I think maybe the north for this trip.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That is all I need, thank you.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search; area=north; destination=find some water and go boating somewhere; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002427", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a taxi to take me today to camboats.\nChunk 2: kings hedges learner pool.\nChunk 3: I want to arrive by 02:45 Fabulous.\nChunk 4: Thanks so much for your help.\nChunk 5: Bye!", "streaming_reasoning": "C1 domain=taxi; goal=search; day+=today; destination+=take me today to camboats. C2 amenities+=pool. C3 time+=02:45; destination+=arrive by 02:45 fabulous. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi; goal=search; amenities=pool; destination=take me today to camboats, arrive by 02:45 fabulous; when=today, 02:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a taxi to take me today to camboats.\nChunk 2: kings hedges learner pool.\nChunk 3: I want to arrive by 02:45 Fabulous.\nChunk 4: Thanks so much for your help.\nChunk 5: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search; day+=today; destination+=take me today to camboats. C2 amenities+=pool. C3 time+=02:45; destination+=arrive by 02:45 fabulous. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi; goal=search; amenities=pool; destination=take me today to camboats, arrive by 02:45 fabulous; when=today, 02:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a taxi to take me today to camboats.\nChunk 2: kings hedges learner pool.\nChunk 3: I want to arrive by 02:45 Fabulous.\nChunk 4: Thanks so much for your help.\nChunk 5: Bye!", "input_token_count": 39, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search; day: today; destination: take me today to camboats. Next, amenities: pool. Finally, time: 02:45; destination: arrive by 02:45 fabulous.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is search. day: today; destination: take me today to camboats., arrive by 02:45 fabulous.; amenities: pool.; time: 02:45.", "trace": "C1 domain=taxi; goal=search; day+=today; destination+=take me today to camboats. C2 amenities+=pool. C3 time+=02:45; destination+=arrive by 02:45 fabulous. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a taxi to take me today to camboats.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search; day: today; destination: take me today to camboats..", "trace": "domain=taxi; goal=search; day+=today; destination+=take me today to camboats."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "kings hedges learner pool.", "streaming_reasoning": "As more information arrives, amenities: pool..", "trace": "amenities+=pool."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to arrive by 02:45 Fabulous.", "streaming_reasoning": "As more information arrives, time: 02:45; destination: arrive by 02:45 fabulous..", "trace": "time+=02:45; destination+=arrive by 02:45 fabulous."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks so much for your help.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Bye!", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: amenities is pool; destination is take me today to camboats; timing is today. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search; amenities=pool; destination=take me today to camboats, arrive by 02:45 fabulous; when=today, 02:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002428", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: If there is no hotel availability, I will accept a guesthouse Is one available?\nChunk 2: Do any of the guesthouses have access to internet for their guests?\nChunk 3: How about free parking?\nChunk 4: Could I get the phone number and address of one of them?\nChunk 5: Also can you find me a nightclub nearby and give me their postcode?\nChunk 6: Okay.\nChunk 7: Thank you very much for your help.\nChunk 8: I think that takes care of everything.", "streaming_reasoning": "C1 domain=hotel; hotel_type+=guesthouse, hotel. C2 amenities+=internet; destination+=internet for their guests. C3 goal=recommendation; amenities+=parking, free parking. C4 goal=request_info; requested_info+=address, phone. C5 goal=search; requested_info+=postcode. C6 [SKIP: backchannel_only]. C7 [SKIP: thanks_only]. C8 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=recommendation, request_info, search; amenities=internet, parking, free parking; destination=internet for their guests; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: If there is no hotel availability, I will accept a guesthouse Is one available?\nChunk 2: Do any of the guesthouses have access to internet for their guests?\nChunk 3: How about free parking?\nChunk 4: Could I get the phone number and address of one of them?\nChunk 5: Also can you find me a nightclub nearby and give me their postcode?\nChunk 6: Okay.\nChunk 7: Thank you very much for your help.\nChunk 8: I think that takes care of everything."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=guesthouse, hotel. C2 amenities+=internet; destination+=internet for their guests. C3 goal=recommendation; amenities+=parking, free parking. C4 goal=request_info; requested_info+=address, phone. C5 goal=search; requested_info+=postcode. C6 [SKIP: backchannel_only]. C7 [SKIP: thanks_only]. C8 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=recommendation, request_info, search; amenities=internet, parking, free parking; destination=internet for their guests; requested_info=address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: If there is no hotel availability, I will accept a guesthouse Is one available?\nChunk 2: Do any of the guesthouses have access to internet for their guests?\nChunk 3: How about free parking?\nChunk 4: Could I get the phone number and address of one of them?\nChunk 5: Also can you find me a nightclub nearby and give me their postcode?\nChunk 6: Okay.\nChunk 7: Thank you very much for your help.\nChunk 8: I think that takes care of everything.", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse. Next, amenities: internet; destination: internet for their guests. Next, the goal is recommendation; amenities: parking. Next, the goal is request info; requested information: address. Next, the goal is search; requested information: postcode. Finally, intent: context_update.  Some chunks were skipped because they contained backchannel_only or thanks_only. In summary, The overall topic is hotel. the goal is search. hotel type: guesthouse; amenities: internet, parking; destination: internet for their guests.; requested information: address, postcode.; intent: context_update..", "trace": "C1 domain=hotel; hotel_type+=guesthouse, hotel. C2 amenities+=internet; destination+=internet for their guests. C3 goal=recommendation; amenities+=parking, free parking. C4 goal=request_info; requested_info+=address, phone. C5 goal=search; requested_info+=postcode. C6 [SKIP: backchannel_only]. C7 [SKIP: thanks_only]. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "If there is no hotel availability, I will accept a guesthouse Is one available?", "streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse.", "trace": "domain=hotel; hotel_type+=guesthouse, hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do any of the guesthouses have access to internet for their guests?", "streaming_reasoning": "As more information arrives, amenities: internet; destination: internet for their guests..", "trace": "amenities+=internet; destination+=internet for their guests."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about free parking?", "streaming_reasoning": "As more information arrives, the goal is recommendation; amenities: parking.", "trace": "goal=recommendation; amenities+=parking, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could I get the phone number and address of one of them?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Also can you find me a nightclub nearby and give me their postcode?", "streaming_reasoning": "As more information arrives, the goal is search; requested information: postcode..", "trace": "goal=search; requested_info+=postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Okay.", "streaming_reasoning": "The content at C6 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you very much for your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I think that takes care of everything.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of recommendation. Key information: amenities is internet; destination is internet for their guests; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=recommendation, request_info, search; amenities=internet, parking, free parking; destination=internet for their guests; requested_info=address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002430", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a place near the center of town that serves european food.\nChunk 2: Yes, that would work.\nChunk 3: Could you make it for Sunday at 16:30 for 1.\nChunk 4: How about 15:30 Thank you.\nChunk 5: Is there a museum in the same area as the restaurant that I could go to?\nChunk 6: Alright, that sounds good to me.\nChunk 7: Could you give me their address and phone number please Thank you.\nChunk 8: that is all the information I'l be needing today!", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=european. C2 acceptance=selected_option. C3 goal=modify_constraint; time+=16:30, 1; day+=sunday. C4 goal=recommendation; time+=15:30. C5 domain=attraction. C6 acceptance=selected_option. C7 goal=request_info; requested_info+=address, phone. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, attraction; goal=search, modify_constraint, recommendation, request_info; area=centre; food=european; requested_info=address, phone; when=sunday, 16:30, 1, 15:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a place near the center of town that serves european food.\nChunk 2: Yes, that would work.\nChunk 3: Could you make it for Sunday at 16:30 for 1.\nChunk 4: How about 15:30 Thank you.\nChunk 5: Is there a museum in the same area as the restaurant that I could go to?\nChunk 6: Alright, that sounds good to me.\nChunk 7: Could you give me their address and phone number please Thank you.\nChunk 8: that is all the information I'l be needing today!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; cuisine+=european. C2 acceptance=selected_option. C3 goal=modify_constraint; time+=16:30, 1; day+=sunday. C4 goal=recommendation; time+=15:30. C5 domain=attraction. C6 acceptance=selected_option. C7 goal=request_info; requested_info+=address, phone. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, attraction; goal=search, modify_constraint, recommendation, request_info; area=centre; food=european; requested_info=address, phone; when=sunday, 16:30, 1, 15:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a place near the center of town that serves european food.\nChunk 2: Yes, that would work.\nChunk 3: Could you make it for Sunday at 16:30 for 1.\nChunk 4: How about 15:30 Thank you.\nChunk 5: Is there a museum in the same area as the restaurant that I could go to?\nChunk 6: Alright, that sounds good to me.\nChunk 7: Could you give me their address and phone number please Thank you.\nChunk 8: that is all the information I'l be needing today!", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: european. Next, acceptance: selected_option. Next, the goal is modify constraint; time: 16:30; day: sunday. Next, the goal is recommendation; time: 15:30. Next, the topic is attraction. Next, acceptance: selected_option. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction.. the goal is request info. area: centre; cuisine: european.; acceptance: selected_option.; time: 16:30, 15:30.; day: sunday.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=european. C2 acceptance=selected_option. C3 goal=modify_constraint; time+=16:30, 1; day+=sunday. C4 goal=recommendation; time+=15:30. C5 domain=attraction. C6 acceptance=selected_option. C7 goal=request_info; requested_info+=address, phone. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a place near the center of town that serves european food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: european..", "trace": "domain=restaurant; goal=search; area+=centre; cuisine+=european."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, that would work.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Could you make it for Sunday at 16:30 for 1.", "streaming_reasoning": "As more information arrives, the goal is modify constraint; time: 16:30; day: sunday..", "trace": "goal=modify_constraint; time+=16:30, 1; day+=sunday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "How about 15:30 Thank you.", "streaming_reasoning": "As more information arrives, the goal is recommendation; time: 15:30..", "trace": "goal=recommendation; time+=15:30."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Is there a museum in the same area as the restaurant that I could go to?", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Alright, that sounds good to me.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Could you give me their address and phone number please Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "that is all the information I'l be needing today!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is european; requested information is address; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction; goal=search, modify_constraint, recommendation, request_info; area=centre; food=european; requested_info=address, phone; when=sunday, 16:30, 1, 15:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002431", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place to stay.\nChunk 2: The hotel should be in the expensive price range and should be in the type of guesthouse.\nChunk 3: I want to find a expensive guesthouse.\nChunk 4: It should be in the north part of town.\nChunk 5: how about something in the moderate price range?\nChunk 6: Sure, please make a reservation for 2 people 2 nights starting on thursday.\nChunk 7: Can we make it 1 night then?\nChunk 8: Thank you for assisting me with that.\nChunk 9: I won't need anything else today.", "streaming_reasoning": "C1 domain=hotel; goal=search; destination+=stay. C2 price+=expensive; hotel_type+=guesthouse, hotel. C3 destination+=find a expensive guesthouse. C4 area+=north. C5 goal=recommendation; price+=moderate. C6 goal=booking; time+=2; day+=thursday; party_size+=2 people; stay_length+=2 nights. C7 goal=modify_constraint; stay_length+=1 nights. C8 [SKIP: thanks_only]. C9 goal=compare_alternative; day+=today.", "deep_reasoning": "Need domain=hotel; goal=search, recommendation, booking, modify_constraint, compare_alternative; area=north; price=expensive, moderate; party_size=2 people; stay_length=2 nights, 1 nights; destination=stay, find a expensive guesthouse; when=thursday, today, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a place to stay.\nChunk 2: The hotel should be in the expensive price range and should be in the type of guesthouse.\nChunk 3: I want to find a expensive guesthouse.\nChunk 4: It should be in the north part of town.\nChunk 5: how about something in the moderate price range?\nChunk 6: Sure, please make a reservation for 2 people 2 nights starting on thursday.\nChunk 7: Can we make it 1 night then?\nChunk 8: Thank you for assisting me with that.\nChunk 9: I won't need anything else today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; destination+=stay. C2 price+=expensive; hotel_type+=guesthouse, hotel. C3 destination+=find a expensive guesthouse. C4 area+=north. C5 goal=recommendation; price+=moderate. C6 goal=booking; time+=2; day+=thursday; party_size+=2 people; stay_length+=2 nights. C7 goal=modify_constraint; stay_length+=1 nights. C8 [SKIP: thanks_only]. C9 goal=compare_alternative; day+=today.\n\nDeep reasoning: Need domain=hotel; goal=search, recommendation, booking, modify_constraint, compare_alternative; area=north; price=expensive, moderate; party_size=2 people; stay_length=2 nights, 1 nights; destination=stay, find a expensive guesthouse; when=thursday, today, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place to stay.\nChunk 2: The hotel should be in the expensive price range and should be in the type of guesthouse.\nChunk 3: I want to find a expensive guesthouse.\nChunk 4: It should be in the north part of town.\nChunk 5: how about something in the moderate price range?\nChunk 6: Sure, please make a reservation for 2 people 2 nights starting on thursday.\nChunk 7: Can we make it 1 night then?\nChunk 8: Thank you for assisting me with that.\nChunk 9: I won't need anything else today.", "input_token_count": 100, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay. Next, price: expensive; hotel type: guesthouse. Next, destination: find a expensive guesthouse. Next, area: north. Next, the goal is recommendation; price: moderate. Next, the goal is booking; time: 2; day: thursday; party size: 2 people; stay length: 2 nights. Next, the goal is modify constraint; stay length: 1 nights. Finally, the goal is compare alternative; day: today.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is compare alternative. destination: stay., find a expensive guesthouse.; price: expensive, moderate.; hotel type: guesthouse; area: north.; time: 2; day: thursday, today.; party size: 2 people; stay length: 2 nights., 1 nights..", "trace": "C1 domain=hotel; goal=search; destination+=stay. C2 price+=expensive; hotel_type+=guesthouse, hotel. C3 destination+=find a expensive guesthouse. C4 area+=north. C5 goal=recommendation; price+=moderate. C6 goal=booking; time+=2; day+=thursday; party_size+=2 people; stay_length+=2 nights. C7 goal=modify_constraint; stay_length+=1 nights. C8 [SKIP: thanks_only]. C9 goal=compare_alternative; day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a place to stay.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The hotel should be in the expensive price range and should be in the type of guesthouse.", "streaming_reasoning": "As more information arrives, price: expensive; hotel type: guesthouse.", "trace": "price+=expensive; hotel_type+=guesthouse, hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a expensive guesthouse.", "streaming_reasoning": "As more information arrives, destination: find a expensive guesthouse..", "trace": "destination+=find a expensive guesthouse."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "how about something in the moderate price range?", "streaming_reasoning": "As more information arrives, the goal is recommendation; price: moderate..", "trace": "goal=recommendation; price+=moderate."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Sure, please make a reservation for 2 people 2 nights starting on thursday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 2; day: thursday; party size: 2 people; stay length: 2 nights..", "trace": "goal=booking; time+=2; day+=thursday; party_size+=2 people; stay_length+=2 nights."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can we make it 1 night then?", "streaming_reasoning": "As more information arrives, the goal is modify constraint; stay length: 1 nights..", "trace": "goal=modify_constraint; stay_length+=1 nights."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for assisting me with that.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I won't need anything else today.", "streaming_reasoning": "Finally, the goal is compare alternative; day: today..", "trace": "goal=compare_alternative; day+=today."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; price is expensive; party size is 2 people; stay length is 2 nights; destination is stay; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, recommendation, booking, modify_constraint, compare_alternative; area=north; price=expensive, moderate; party_size=2 people; stay_length=2 nights, 1 nights; destination=stay, find a expensive guesthouse; when=thursday, today, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002432", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, but I'm interested in train information.\nChunk 2: Is there anything running from Peterborough on Wednesday?\nChunk 3: I will be going to Cambridge.\nChunk 4: I would like to arrive by 12:30.\nChunk 5: Departure time doesn't matter to me.\nChunk 6: Yes, please book a ticket for me.\nChunk 7: What's the travel time for this train trip?\nChunk 8: What is the departure time of my train?\nChunk 9: Thank you have a nice day.", "streaming_reasoning": "C1 domain=train. C2 day+=wednesday. C3 destination+=cambridge. C4 time+=12:30; destination+=arrive by 12:30. C5 intent=context_update. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; requested_info+=travel_time. C8 [SKIP: repeated_information]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=booking, confirm_booking, request_info; destination=cambridge, arrive by 12:30; requested_info=travel_time; when=wednesday, 12:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, but I'm interested in train information.\nChunk 2: Is there anything running from Peterborough on Wednesday?\nChunk 3: I will be going to Cambridge.\nChunk 4: I would like to arrive by 12:30.\nChunk 5: Departure time doesn't matter to me.\nChunk 6: Yes, please book a ticket for me.\nChunk 7: What's the travel time for this train trip?\nChunk 8: What is the departure time of my train?\nChunk 9: Thank you have a nice day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train. C2 day+=wednesday. C3 destination+=cambridge. C4 time+=12:30; destination+=arrive by 12:30. C5 intent=context_update. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; requested_info+=travel_time. C8 [SKIP: repeated_information]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=booking, confirm_booking, request_info; destination=cambridge, arrive by 12:30; requested_info=travel_time; when=wednesday, 12:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, but I'm interested in train information.\nChunk 2: Is there anything running from Peterborough on Wednesday?\nChunk 3: I will be going to Cambridge.\nChunk 4: I would like to arrive by 12:30.\nChunk 5: Departure time doesn't matter to me.\nChunk 6: Yes, please book a ticket for me.\nChunk 7: What's the travel time for this train trip?\nChunk 8: What is the departure time of my train?\nChunk 9: Thank you have a nice day.", "input_token_count": 82, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train. Next, day: wednesday. Next, destination: cambridge. Next, time: 12:30; destination: arrive by 12:30. Next, intent: context_update. Next, the goal is confirm booking. Finally, the goal is request info; requested information: travel_time.  Some chunks were skipped because they contained repeated_information or thanks_only. In summary, The overall topic is train.. the goal is request info. day: wednesday.; destination: cambridge., arrive by 12:30.; time: 12:30; intent: context_update.; requested information: travel_time..", "trace": "C1 domain=train. C2 day+=wednesday. C3 destination+=cambridge. C4 time+=12:30; destination+=arrive by 12:30. C5 intent=context_update. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; requested_info+=travel_time. C8 [SKIP: repeated_information]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, but I'm interested in train information.", "streaming_reasoning": "Initially, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there anything running from Peterborough on Wednesday?", "streaming_reasoning": "As more information arrives, day: wednesday..", "trace": "day+=wednesday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I will be going to Cambridge.", "streaming_reasoning": "As more information arrives, destination: cambridge..", "trace": "destination+=cambridge."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like to arrive by 12:30.", "streaming_reasoning": "As more information arrives, time: 12:30; destination: arrive by 12:30..", "trace": "time+=12:30; destination+=arrive by 12:30."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Departure time doesn't matter to me.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, please book a ticket for me.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "What's the travel time for this train trip?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "What is the departure time of my train?", "streaming_reasoning": "The content at C8 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you have a nice day.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: destination is cambridge; requested information is travel_time; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, confirm_booking, request_info; destination=cambridge, arrive by 12:30; requested_info=travel_time; when=wednesday, 12:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001632", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I had one time where I was at a party and a girl started to act really flirty with me and we were both kinda drunk.\nChunk 2: I had a girlfriend at the time so I made sure to let her know so that she didn't get the wrong idea.\nChunk 3: One time I was at this party and a girl started to get really touchy feely and flirting with me.\nChunk 4: I had a girlfriend at the time.\nChunk 5: what did you do?\nChunk 6: I was way too close to my girlfriend to do anything, so I just let her know that I was in a relationship so that she wouldn't get the wrong idea.", "streaming_reasoning": "C1 need=validation. C2 emotion=frustrated; cause=I had a girlfriend at the time so I made sure to. C3 support_signal=received. C4 [SKIP: repeated_information]. C5 support_signal=received. C6 need=encouragement.", "deep_reasoning": "User feels frustrated after I had a girlfriend at the time so I made sure to and needs encouragement.", "answer": "It makes sense to feel frustrated after I had a girlfriend at the time so I made sure to. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I had one time where I was at a party and a girl started to act really flirty with me and we were both kinda drunk.\nChunk 2: I had a girlfriend at the time so I made sure to let her know so that she didn't get the wrong idea.\nChunk 3: One time I was at this party and a girl started to get really touchy feely and flirting with me.\nChunk 4: I had a girlfriend at the time.\nChunk 5: what did you do?\nChunk 6: I was way too close to my girlfriend to do anything, so I just let her know that I was in a relationship so that she wouldn't get the wrong idea."}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 emotion=frustrated; cause=I had a girlfriend at the time so I made sure to. C3 support_signal=received. C4 [SKIP: repeated_information]. C5 support_signal=received. C6 need=encouragement.\n\nDeep reasoning: User feels frustrated after I had a girlfriend at the time so I made sure to and needs encouragement.\n\nAnswer: It makes sense to feel frustrated after I had a girlfriend at the time so I made sure to. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I had one time where I was at a party and a girl started to act really flirty with me and we were both kinda drunk.\nChunk 2: I had a girlfriend at the time so I made sure to let her know so that she didn't get the wrong idea.\nChunk 3: One time I was at this party and a girl started to get really touchy feely and flirting with me.\nChunk 4: I had a girlfriend at the time.\nChunk 5: what did you do?\nChunk 6: I was way too close to my girlfriend to do anything, so I just let her know that I was in a relationship so that she wouldn't get the wrong idea.", "input_token_count": 123, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user expresses frustrated about I had a girlfriend at the time so I made sure to. Next, the user signals support or acknowledgment. Next, the user signals support or acknowledgment. Finally, the user needs encouragement.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 need=validation. C2 emotion=frustrated; cause=I had a girlfriend at the time so I made sure to. C3 support_signal=received. C4 [SKIP: repeated_information]. C5 support_signal=received. C6 need=encouragement.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I had one time where I was at a party and a girl started to act really flirty with me and we were both kinda drunk.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I had a girlfriend at the time so I made sure to let her know so that she didn't get the wrong idea.", "streaming_reasoning": "As more information arrives, the user expresses frustrated about I had a girlfriend at the time so I made sure to..", "trace": "emotion=frustrated; cause=I had a girlfriend at the time so I made sure to."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "One time I was at this party and a girl started to get really touchy feely and flirting with me.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I had a girlfriend at the time.", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "what did you do?", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I was way too close to my girlfriend to do anything, so I just let her know that I was in a relationship so that she wouldn't get the wrong idea.", "streaming_reasoning": "Finally, the user needs encouragement..", "trace": "need=encouragement."}]}, "output": {"deep_reasoning": "User feels frustrated after I had a girlfriend at the time so I made sure to and needs encouragement.", "answer": "It makes sense to feel frustrated after I had a girlfriend at the time so I made sure to. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002433", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be staying 5 nights starting from Saturday.\nChunk 2: Yes, can you book it for 6 people Thank you.\nChunk 3: I also need a train to Kings Lynn that leaves on Sunday.\nChunk 4: I want the train to leave after 16:30.\nChunk 5: I need 6 tickets, please.\nChunk 6: No, that will be all Thank you!", "streaming_reasoning": "C1 time+=5; day+=saturday; stay_length+=5 nights. C2 goal=confirm_booking; party_size+=6 people; goal=confirm_booking. C3 domain=train; goal=search; day+=sunday; destination+=kings lynn that leaves on sunday. C4 time+=16:30; destination+=leave after 16:30. C5 intent=context_update. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=booking, confirm_booking, search; party_size=6 people; stay_length=5 nights; destination=kings lynn that leaves on sunday, leave after 16:30; when=saturday, sunday, 5, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I will be staying 5 nights starting from Saturday.\nChunk 2: Yes, can you book it for 6 people Thank you.\nChunk 3: I also need a train to Kings Lynn that leaves on Sunday.\nChunk 4: I want the train to leave after 16:30.\nChunk 5: I need 6 tickets, please.\nChunk 6: No, that will be all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=5; day+=saturday; stay_length+=5 nights. C2 goal=confirm_booking; party_size+=6 people; goal=confirm_booking. C3 domain=train; goal=search; day+=sunday; destination+=kings lynn that leaves on sunday. C4 time+=16:30; destination+=leave after 16:30. C5 intent=context_update. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=booking, confirm_booking, search; party_size=6 people; stay_length=5 nights; destination=kings lynn that leaves on sunday, leave after 16:30; when=saturday, sunday, 5, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be staying 5 nights starting from Saturday.\nChunk 2: Yes, can you book it for 6 people Thank you.\nChunk 3: I also need a train to Kings Lynn that leaves on Sunday.\nChunk 4: I want the train to leave after 16:30.\nChunk 5: I need 6 tickets, please.\nChunk 6: No, that will be all Thank you!", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 5; day: saturday; stay length: 5 nights. Next, the goal is confirm booking.; party size: 6 people. Next, the topic is train; the goal is search; day: sunday; destination: kings lynn that leaves on sunday. Next, time: 16:30; destination: leave after 16:30. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is search. time: 5, 16:30; day: saturday, sunday; stay length: 5 nights.; party size: 6 people; destination: kings lynn that leaves on sunday., leave after 16:30.; intent: context_update..", "trace": "C1 time+=5; day+=saturday; stay_length+=5 nights. C2 goal=confirm_booking; party_size+=6 people; goal=confirm_booking. C3 domain=train; goal=search; day+=sunday; destination+=kings lynn that leaves on sunday. C4 time+=16:30; destination+=leave after 16:30. C5 intent=context_update. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I will be staying 5 nights starting from Saturday.", "streaming_reasoning": "Initially, time: 5; day: saturday; stay length: 5 nights..", "trace": "time+=5; day+=saturday; stay_length+=5 nights."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, can you book it for 6 people Thank you.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; party size: 6 people.", "trace": "goal=confirm_booking; party_size+=6 people; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need a train to Kings Lynn that leaves on Sunday.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: sunday; destination: kings lynn that leaves on sunday..", "trace": "domain=train; goal=search; day+=sunday; destination+=kings lynn that leaves on sunday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want the train to leave after 16:30.", "streaming_reasoning": "As more information arrives, time: 16:30; destination: leave after 16:30..", "trace": "time+=16:30; destination+=leave after 16:30."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need 6 tickets, please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, that will be all Thank you!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: party size is 6 people; stay length is 5 nights; destination is kings lynn that leaves on sunday; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, confirm_booking, search; party_size=6 people; stay_length=5 nights; destination=kings lynn that leaves on sunday, leave after 16:30; when=saturday, sunday, 5, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002434", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please show me where the nearest hospital is Thank you.\nChunk 2: Can you book a taxi to take me there?\nChunk 3: Nevermind, I don't need a taxi.\nChunk 4: Thanks for your help That's all.\nChunk 5: Thank you, good bye.", "streaming_reasoning": "C1 domain=hospital. C2 domain=taxi; goal=booking; destination+=take me there. C3 goal=search. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hospital, taxi; goal=booking, search; destination=take me there; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Please show me where the nearest hospital is Thank you.\nChunk 2: Can you book a taxi to take me there?\nChunk 3: Nevermind, I don't need a taxi.\nChunk 4: Thanks for your help That's all.\nChunk 5: Thank you, good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital. C2 domain=taxi; goal=booking; destination+=take me there. C3 goal=search. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hospital, taxi; goal=booking, search; destination=take me there; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please show me where the nearest hospital is Thank you.\nChunk 2: Can you book a taxi to take me there?\nChunk 3: Nevermind, I don't need a taxi.\nChunk 4: Thanks for your help That's all.\nChunk 5: Thank you, good bye.", "input_token_count": 45, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital. Next, the topic is taxi; the goal is booking; destination: take me there. Finally, the goal is search.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is search.. destination: take me there..", "trace": "C1 domain=hospital. C2 domain=taxi; goal=booking; destination+=take me there. C3 goal=search. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Please show me where the nearest hospital is Thank you.", "streaming_reasoning": "Initially, the topic is hospital..", "trace": "domain=hospital."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you book a taxi to take me there?", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is booking; destination: take me there..", "trace": "domain=taxi; goal=booking; destination+=take me there."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Nevermind, I don't need a taxi.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks for your help That's all.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you, good bye.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of booking. Key information: destination is take me there. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital, taxi; goal=booking, search; destination=take me there; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002435", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That is perfect can I have the postcode please?\nChunk 2: Thanks.\nChunk 3: Last time I stayed in Cambridge several years ago I stayed at the carolina bed and breakfast.\nChunk 4: Is it still around?\nChunk 5: I just need to verify some information before I book anything.\nChunk 6: Do they still have wifi, and have the prices stayed moderate?\nChunk 7: Oh, and they are in the East, correct Awesome!\nChunk 8: I will also need to book a tai to go from the hotel to the nightclub.\nChunk 9: Yes, I would like to book a taxi to leave the hotel by 11:00.\nChunk 10: That is all I need today.\nChunk 11: Thank you for your help!", "streaming_reasoning": "C1 goal=request_info; requested_info+=postcode; acceptance=selected_option. C2 [SKIP: thanks_only]. C3 domain=restaurant; amenities+=breakfast. C4 goal=request_info. C5 goal=booking. C6 price+=moderate; amenities+=wifi. C7 area+=east. C8 domain=hotel; hotel_type+=hotel; destination+=the nightclub; departure+=the hotel. C9 domain=taxi; goal=confirm_booking; time+=11:00; goal=confirm_booking. C10 [SKIP: closing_only]. C11 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, hotel, taxi; goal=request_info, search, booking, confirm_booking; area=east; price=moderate; amenities=breakfast, wifi; destination=the nightclub; departure=the hotel; requested_info=postcode; when=11:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: That is perfect can I have the postcode please?\nChunk 2: Thanks.\nChunk 3: Last time I stayed in Cambridge several years ago I stayed at the carolina bed and breakfast.\nChunk 4: Is it still around?\nChunk 5: I just need to verify some information before I book anything.\nChunk 6: Do they still have wifi, and have the prices stayed moderate?\nChunk 7: Oh, and they are in the East, correct Awesome!\nChunk 8: I will also need to book a tai to go from the hotel to the nightclub.\nChunk 9: Yes, I would like to book a taxi to leave the hotel by 11:00.\nChunk 10: That is all I need today.\nChunk 11: Thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=postcode; acceptance=selected_option. C2 [SKIP: thanks_only]. C3 domain=restaurant; amenities+=breakfast. C4 goal=request_info. C5 goal=booking. C6 price+=moderate; amenities+=wifi. C7 area+=east. C8 domain=hotel; hotel_type+=hotel; destination+=the nightclub; departure+=the hotel. C9 domain=taxi; goal=confirm_booking; time+=11:00; goal=confirm_booking. C10 [SKIP: closing_only]. C11 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, hotel, taxi; goal=request_info, search, booking, confirm_booking; area=east; price=moderate; amenities=breakfast, wifi; destination=the nightclub; departure=the hotel; requested_info=postcode; when=11:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That is perfect can I have the postcode please?\nChunk 2: Thanks.\nChunk 3: Last time I stayed in Cambridge several years ago I stayed at the carolina bed and breakfast.\nChunk 4: Is it still around?\nChunk 5: I just need to verify some information before I book anything.\nChunk 6: Do they still have wifi, and have the prices stayed moderate?\nChunk 7: Oh, and they are in the East, correct Awesome!\nChunk 8: I will also need to book a tai to go from the hotel to the nightclub.\nChunk 9: Yes, I would like to book a taxi to leave the hotel by 11:00.\nChunk 10: That is all I need today.\nChunk 11: Thank you for your help!", "input_token_count": 126, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: postcode; acceptance: selected_option. Next, the topic is restaurant; amenities: breakfast. Next, the goal is request info. Next, the goal is booking. Next, price: moderate; amenities: wifi. Next, area: east. Next, the topic is hotel; hotel type: hotel; destination: the nightclub; departure point: the hotel. Finally, the topic is taxi; the goal is confirm booking.; time: 11:00.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is confirm booking.. requested information: postcode; acceptance: selected_option.; amenities: breakfast., wifi.; price: moderate; area: east.; hotel type: hotel; destination: the nightclub; departure point: the hotel.; time: 11:00.", "trace": "C1 goal=request_info; requested_info+=postcode; acceptance=selected_option. C2 [SKIP: thanks_only]. C3 domain=restaurant; amenities+=breakfast. C4 goal=request_info. C5 goal=booking. C6 price+=moderate; amenities+=wifi. C7 area+=east. C8 domain=hotel; hotel_type+=hotel; destination+=the nightclub; departure+=the hotel. C9 domain=taxi; goal=confirm_booking; time+=11:00; goal=confirm_booking. C10 [SKIP: closing_only]. C11 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "That is perfect can I have the postcode please?", "streaming_reasoning": "Initially, the goal is request info; requested information: postcode; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=postcode; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Last time I stayed in Cambridge several years ago I stayed at the carolina bed and breakfast.", "streaming_reasoning": "As more information arrives, the topic is restaurant; amenities: breakfast..", "trace": "domain=restaurant; amenities+=breakfast."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is it still around?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I just need to verify some information before I book anything.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Do they still have wifi, and have the prices stayed moderate?", "streaming_reasoning": "As more information arrives, price: moderate; amenities: wifi..", "trace": "price+=moderate; amenities+=wifi."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Oh, and they are in the East, correct Awesome!", "streaming_reasoning": "As more information arrives, area: east..", "trace": "area+=east."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I will also need to book a tai to go from the hotel to the nightclub.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: the nightclub; departure point: the hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=the nightclub; departure+=the hotel."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Yes, I would like to book a taxi to leave the hotel by 11:00.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is confirm booking.; time: 11:00.", "trace": "domain=taxi; goal=confirm_booking; time+=11:00; goal=confirm_booking."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That is all I need today.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Thank you for your help!", "streaming_reasoning": "The content at C11 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is east; price is moderate; amenities is breakfast; destination is the nightclub; departure point is the hotel; requested information is postcode; timing is 11:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel, taxi; goal=request_info, search, booking, confirm_booking; area=east; price=moderate; amenities=breakfast, wifi; destination=the nightclub; departure=the hotel; requested_info=postcode; when=11:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002436", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a moderately priced restaurant in the south part of town.\nChunk 2: Can you give me their address and phone number Thank you goodbye.", "streaming_reasoning": "C1 domain=restaurant; area+=south; price+=moderate. C2 goal=request_info; requested_info+=address, phone.", "deep_reasoning": "Need domain=restaurant; goal=request_info; area=south; price=moderate; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a moderately priced restaurant in the south part of town.\nChunk 2: Can you give me their address and phone number Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=south; price+=moderate. C2 goal=request_info; requested_info+=address, phone.\n\nDeep reasoning: Need domain=restaurant; goal=request_info; area=south; price=moderate; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a moderately priced restaurant in the south part of town.\nChunk 2: Can you give me their address and phone number Thank you goodbye.", "input_token_count": 29, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: south; price: moderate. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. area: south; price: moderate.; requested information: address.", "trace": "C1 domain=restaurant; area+=south; price+=moderate. C2 goal=request_info; requested_info+=address, phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a moderately priced restaurant in the south part of town.", "streaming_reasoning": "Initially, the topic is restaurant; area: south; price: moderate..", "trace": "domain=restaurant; area+=south; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you give me their address and phone number Thank you goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is south; price is moderate; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info; area=south; price=moderate; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002437", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for the Addenbrookes Hospital with a haematology day unit.\nChunk 2: Thanks, can I also get the postcode?\nChunk 3: I think you have given me all that I need.", "streaming_reasoning": "C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=postcode. C3 intent=context_update.", "deep_reasoning": "Need domain=hospital; goal=search, request_info; requested_info=postcode.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for the Addenbrookes Hospital with a haematology day unit.\nChunk 2: Thanks, can I also get the postcode?\nChunk 3: I think you have given me all that I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=postcode. C3 intent=context_update.\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; requested_info=postcode.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for the Addenbrookes Hospital with a haematology day unit.\nChunk 2: Thanks, can I also get the postcode?\nChunk 3: I think you have given me all that I need.", "input_token_count": 34, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search. Next, the goal is request info; requested information: postcode. Finally, intent: context_update. In summary, The overall topic is hospital. the goal is request info. requested information: postcode.; intent: context_update..", "trace": "C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=postcode. C3 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for the Addenbrookes Hospital with a haematology day unit.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search..", "trace": "domain=hospital; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks, can I also get the postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I think you have given me all that I need.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is postcode.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; requested_info=postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002438", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am planning a trip to Cambridge on a train.\nChunk 2: I want to leave form bishops stortford...can you help me with that?\nChunk 3: I would like to travel on Saturday, arriving at 8:00.\nChunk 4: No need to book it for me.\nChunk 5: I can do that.\nChunk 6: But can you tell me the travel time in minutes?\nChunk 7: I am also looking for a attraction called queens' college, can you get me information on that Great.\nChunk 8: And what is the postcode And attraction type?\nChunk 9: That is all I need today, thank you.", "streaming_reasoning": "C1 domain=train; destination+=cambridge on a train. C2 goal=search; destination+=leave form bishops stortford. C3 time+=8:00; day+=saturday; destination+=travel on saturday. C4 goal=booking. C5 intent=context_update. C6 goal=request_info; requested_info+=travel_time. C7 domain=attraction. C8 requested_info+=postcode. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, attraction; goal=search, booking, request_info; destination=cambridge on a train, leave form bishops stortford, travel on saturday; requested_info=travel_time, postcode; when=saturday, 8:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am planning a trip to Cambridge on a train.\nChunk 2: I want to leave form bishops stortford...can you help me with that?\nChunk 3: I would like to travel on Saturday, arriving at 8:00.\nChunk 4: No need to book it for me.\nChunk 5: I can do that.\nChunk 6: But can you tell me the travel time in minutes?\nChunk 7: I am also looking for a attraction called queens' college, can you get me information on that Great.\nChunk 8: And what is the postcode And attraction type?\nChunk 9: That is all I need today, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; destination+=cambridge on a train. C2 goal=search; destination+=leave form bishops stortford. C3 time+=8:00; day+=saturday; destination+=travel on saturday. C4 goal=booking. C5 intent=context_update. C6 goal=request_info; requested_info+=travel_time. C7 domain=attraction. C8 requested_info+=postcode. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, attraction; goal=search, booking, request_info; destination=cambridge on a train, leave form bishops stortford, travel on saturday; requested_info=travel_time, postcode; when=saturday, 8:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am planning a trip to Cambridge on a train.\nChunk 2: I want to leave form bishops stortford...can you help me with that?\nChunk 3: I would like to travel on Saturday, arriving at 8:00.\nChunk 4: No need to book it for me.\nChunk 5: I can do that.\nChunk 6: But can you tell me the travel time in minutes?\nChunk 7: I am also looking for a attraction called queens' college, can you get me information on that Great.\nChunk 8: And what is the postcode And attraction type?\nChunk 9: That is all I need today, thank you.", "input_token_count": 107, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; destination: cambridge on a train. Next, the goal is search; destination: leave form bishops stortford. Next, time: 8:00; day: saturday; destination: travel on saturday. Next, the goal is booking. Next, intent: context_update. Next, the goal is request info; requested information: travel_time. Next, the topic is attraction. Finally, requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction.. the goal is request info. destination: cambridge on a train., leave form bishops stortford., travel on saturday.; time: 8:00; day: saturday; intent: context_update.; requested information: travel_time., postcode..", "trace": "C1 domain=train; destination+=cambridge on a train. C2 goal=search; destination+=leave form bishops stortford. C3 time+=8:00; day+=saturday; destination+=travel on saturday. C4 goal=booking. C5 intent=context_update. C6 goal=request_info; requested_info+=travel_time. C7 domain=attraction. C8 requested_info+=postcode. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am planning a trip to Cambridge on a train.", "streaming_reasoning": "Initially, the topic is train; destination: cambridge on a train..", "trace": "domain=train; destination+=cambridge on a train."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to leave form bishops stortford...can you help me with that?", "streaming_reasoning": "As more information arrives, the goal is search; destination: leave form bishops stortford..", "trace": "goal=search; destination+=leave form bishops stortford."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to travel on Saturday, arriving at 8:00.", "streaming_reasoning": "As more information arrives, time: 8:00; day: saturday; destination: travel on saturday..", "trace": "time+=8:00; day+=saturday; destination+=travel on saturday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No need to book it for me.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I can do that.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "But can you tell me the travel time in minutes?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am also looking for a attraction called queens' college, can you get me information on that Great.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "And what is the postcode And attraction type?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That is all I need today, thank you.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge on a train; requested information is travel_time; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=search, booking, request_info; destination=cambridge on a train, leave form bishops stortford, travel on saturday; requested_info=travel_time, postcode; when=saturday, 8:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002439", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for attractions in the town centre.\nChunk 2: What is their phone number?\nChunk 3: No, that is all I need for today Thank you.", "streaming_reasoning": "C1 goal=search; area+=centre. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only].", "deep_reasoning": "Need goal=search, request_info; area=centre; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for attractions in the town centre.\nChunk 2: What is their phone number?\nChunk 3: No, that is all I need for today Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search, request_info; area=centre; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for attractions in the town centre.\nChunk 2: What is their phone number?\nChunk 3: No, that is all I need for today Thank you.", "input_token_count": 30, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, the goal is request info. area: centre.; requested information: phone..", "trace": "C1 goal=search; area+=centre. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for attractions in the town centre.", "streaming_reasoning": "Initially, the goal is search; area: centre..", "trace": "goal=search; area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is their phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, that is all I need for today Thank you.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search, request_info; area=centre; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002440", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you give me the contact info for the nearest police station?\nChunk 2: Thank you very much.\nChunk 3: I will contact them now.", "streaming_reasoning": "C1 domain=train; goal=request_info. C2 [SKIP: thanks_only]. C3 intent=context_update.", "deep_reasoning": "Need domain=train; goal=request_info; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you give me the contact info for the nearest police station?\nChunk 2: Thank you very much.\nChunk 3: I will contact them now."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=request_info. C2 [SKIP: thanks_only]. C3 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=request_info; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you give me the contact info for the nearest police station?\nChunk 2: Thank you very much.\nChunk 3: I will contact them now.", "input_token_count": 27, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is request info. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is request info.. intent: context_update..", "trace": "C1 domain=train; goal=request_info. C2 [SKIP: thanks_only]. C3 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you give me the contact info for the nearest police station?", "streaming_reasoning": "Initially, the topic is train; the goal is request info..", "trace": "domain=train; goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I will contact them now.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "Need domain=train; goal=request_info; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002441", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Area doesn't matter but I need to know if they have free parking.\nChunk 2: Sounds great, Thank you.\nChunk 3: Yes please make a reservation in my name Thank you.\nChunk 4: I'm sorry I don't need a reservation right now.\nChunk 5: Can you just tell me if they offer free parking Great, thanks.\nChunk 6: That is all I needed.\nChunk 7: No, I can book myself later Thanks Good bye.", "streaming_reasoning": "C1 goal=search; amenities+=parking, free parking; destination+=know if they have free parking. C2 intent=context_update. C3 goal=confirm_booking; goal=confirm_booking. C4 intent=context_update. C5 goal=request_info. C6 [SKIP: closing_only]. C7 goal=modify_constraint.", "deep_reasoning": "Need goal=search, booking, confirm_booking, request_info; amenities=parking, free parking; destination=know if they have free parking; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Area doesn't matter but I need to know if they have free parking.\nChunk 2: Sounds great, Thank you.\nChunk 3: Yes please make a reservation in my name Thank you.\nChunk 4: I'm sorry I don't need a reservation right now.\nChunk 5: Can you just tell me if they offer free parking Great, thanks.\nChunk 6: That is all I needed.\nChunk 7: No, I can book myself later Thanks Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; amenities+=parking, free parking; destination+=know if they have free parking. C2 intent=context_update. C3 goal=confirm_booking; goal=confirm_booking. C4 intent=context_update. C5 goal=request_info. C6 [SKIP: closing_only]. C7 goal=modify_constraint.\n\nDeep reasoning: Need goal=search, booking, confirm_booking, request_info; amenities=parking, free parking; destination=know if they have free parking; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Area doesn't matter but I need to know if they have free parking.\nChunk 2: Sounds great, Thank you.\nChunk 3: Yes please make a reservation in my name Thank you.\nChunk 4: I'm sorry I don't need a reservation right now.\nChunk 5: Can you just tell me if they offer free parking Great, thanks.\nChunk 6: That is all I needed.\nChunk 7: No, I can book myself later Thanks Good bye.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; amenities: parking; destination: know if they have free parking. Next, intent: context_update. Next, the goal is confirm booking. Next, intent: context_update. Next, the goal is request info. Finally, the goal is modify constraint.  Some chunks were skipped because they contained closing_only. In summary, the goal is modify constraint.. amenities: parking; destination: know if they have free parking.; intent: context_update..", "trace": "C1 goal=search; amenities+=parking, free parking; destination+=know if they have free parking. C2 intent=context_update. C3 goal=confirm_booking; goal=confirm_booking. C4 intent=context_update. C5 goal=request_info. C6 [SKIP: closing_only]. C7 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Area doesn't matter but I need to know if they have free parking.", "streaming_reasoning": "Initially, the goal is search; amenities: parking; destination: know if they have free parking..", "trace": "goal=search; amenities+=parking, free parking; destination+=know if they have free parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Sounds great, Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes please make a reservation in my name Thank you.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm sorry I don't need a reservation right now.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you just tell me if they offer free parking Great, thanks.", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all I needed.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, I can book myself later Thanks Good bye.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "Need goal=search, booking, confirm_booking, request_info; amenities=parking, free parking; destination=know if they have free parking; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003060", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I know what you ' re saying, but I have to go over the books with you before I go see our tax guy Right.\nChunk 2: Okay, let me see what I can do.\nChunk 3: How about 1:30 right after my lunch meeting?\nChunk 4: It won ' t take more than a half hour, will it John?\nChunk 5: It ' s Susan Miller.\nChunk 6: Hi, Susan What ' s up?\nChunk 7: Do you know where that memo about office procedures is?\nChunk 8: I want to give my secretary a copy.", "streaming_reasoning": "C1 leaving_reason=needs_to_go. C2 casual_comment=okay, let. C3 question=true. C4 question=true. C5 casual_comment=susan, miller. C6 [SKIP: repeated_information]. C7 question=true. C8 casual_comment=give, secretary.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I know what you ' re saying, but I have to go over the books with you before I go see our tax guy Right.\nChunk 2: Okay, let me see what I can do.\nChunk 3: How about 1:30 right after my lunch meeting?\nChunk 4: It won ' t take more than a half hour, will it John?\nChunk 5: It ' s Susan Miller.\nChunk 6: Hi, Susan What ' s up?\nChunk 7: Do you know where that memo about office procedures is?\nChunk 8: I want to give my secretary a copy."}, {"role": "assistant", "content": "Streaming reasoning: C1 leaving_reason=needs_to_go. C2 casual_comment=okay, let. C3 question=true. C4 question=true. C5 casual_comment=susan, miller. C6 [SKIP: repeated_information]. C7 question=true. C8 casual_comment=give, secretary.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I know what you ' re saying, but I have to go over the books with you before I go see our tax guy Right.\nChunk 2: Okay, let me see what I can do.\nChunk 3: How about 1:30 right after my lunch meeting?\nChunk 4: It won ' t take more than a half hour, will it John?\nChunk 5: It ' s Susan Miller.\nChunk 6: Hi, Susan What ' s up?\nChunk 7: Do you know where that memo about office procedures is?\nChunk 8: I want to give my secretary a copy.", "input_token_count": 96, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, leaving reason: needs_to_go. Next, the user comments on okay. Next, the input provides additional context about question=true. Next, the input provides additional context about question=true. Next, the user comments on susan. Next, the input provides additional context about question=true. Finally, the user comments on give.  Some chunks were skipped because they contained repeated_information. In summary, leaving reason: needs_to_go..", "trace": "C1 leaving_reason=needs_to_go. C2 casual_comment=okay, let. C3 question=true. C4 question=true. C5 casual_comment=susan, miller. C6 [SKIP: repeated_information]. C7 question=true. C8 casual_comment=give, secretary.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I know what you ' re saying, but I have to go over the books with you before I go see our tax guy Right.", "streaming_reasoning": "Initially, leaving reason: needs_to_go..", "trace": "leaving_reason=needs_to_go."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Okay, let me see what I can do.", "streaming_reasoning": "As more information arrives, the user comments on okay.", "trace": "casual_comment=okay, let."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about 1:30 right after my lunch meeting?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It won ' t take more than a half hour, will it John?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It ' s Susan Miller.", "streaming_reasoning": "As more information arrives, the user comments on susan.", "trace": "casual_comment=susan, miller."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Hi, Susan What ' s up?", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Do you know where that memo about office procedures is?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I want to give my secretary a copy.", "streaming_reasoning": "Finally, the user comments on give.", "trace": "casual_comment=give, secretary."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002444", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Does it leave on Sunday?\nChunk 2: Yes please book a seat and send me a reference number Thanks so much.\nChunk 3: Can you also find me a place to stay?\nChunk 4: I would like a 4 star moderately priced guesthouse in the north No that's ok.\nChunk 5: Can I just get the phone number and postcode?\nChunk 6: That will be all for today thanks!", "streaming_reasoning": "C1 day+=sunday. C2 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C3 domain=hotel; goal=search; destination+=stay. C4 area+=north; price+=moderate; hotel_type+=guesthouse; stars+=4 stars. C5 requested_info+=phone, postcode. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=booking, request_info, confirm_booking, search; area=north; price=moderate; stars=4 stars; destination=stay; requested_info=reference_number, phone, postcode; when=sunday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Does it leave on Sunday?\nChunk 2: Yes please book a seat and send me a reference number Thanks so much.\nChunk 3: Can you also find me a place to stay?\nChunk 4: I would like a 4 star moderately priced guesthouse in the north No that's ok.\nChunk 5: Can I just get the phone number and postcode?\nChunk 6: That will be all for today thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=sunday. C2 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C3 domain=hotel; goal=search; destination+=stay. C4 area+=north; price+=moderate; hotel_type+=guesthouse; stars+=4 stars. C5 requested_info+=phone, postcode. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=booking, request_info, confirm_booking, search; area=north; price=moderate; stars=4 stars; destination=stay; requested_info=reference_number, phone, postcode; when=sunday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Does it leave on Sunday?\nChunk 2: Yes please book a seat and send me a reference number Thanks so much.\nChunk 3: Can you also find me a place to stay?\nChunk 4: I would like a 4 star moderately priced guesthouse in the north No that's ok.\nChunk 5: Can I just get the phone number and postcode?\nChunk 6: That will be all for today thanks!", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, day: sunday. Next, the goal is confirm booking.; requested information: reference_number. Next, the topic is hotel; the goal is search; destination: stay. Next, area: north; price: moderate; hotel type: guesthouse; star rating: 4 stars. Finally, requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is search. day: sunday.; requested information: reference_number, phone; destination: stay.; area: north; price: moderate; hotel type: guesthouse; star rating: 4 stars..", "trace": "C1 day+=sunday. C2 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C3 domain=hotel; goal=search; destination+=stay. C4 area+=north; price+=moderate; hotel_type+=guesthouse; stars+=4 stars. C5 requested_info+=phone, postcode. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Does it leave on Sunday?", "streaming_reasoning": "Initially, day: sunday..", "trace": "day+=sunday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes please book a seat and send me a reference number Thanks so much.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you also find me a place to stay?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like a 4 star moderately priced guesthouse in the north No that's ok.", "streaming_reasoning": "As more information arrives, area: north; price: moderate; hotel type: guesthouse; star rating: 4 stars..", "trace": "area+=north; price+=moderate; hotel_type+=guesthouse; stars+=4 stars."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I just get the phone number and postcode?", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That will be all for today thanks!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: area is north; price is moderate; star rating is 4 stars; destination is stay; requested information is reference_number; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, request_info, confirm_booking, search; area=north; price=moderate; stars=4 stars; destination=stay; requested_info=reference_number, phone, postcode; when=sunday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001641", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My cat recently died.\nChunk 2: I had her since I was 5 years old She was 23.\nChunk 3: I feel so lost and lonely without her.\nChunk 4: My cat died last week.\nChunk 5: I feel so lost without her.\nChunk 6: :( I am so sorry to hear that...\nChunk 7: how old was she?\nChunk 8: She was 23 years old.\nChunk 9: I got her when I was 5.", "streaming_reasoning": "C1 cause=someone important passed away; need=encouragement. C2 support_signal=received. C3 emotion=lonely; cause=so lost and without her; need=validation. C4 need=encouragement. C5 [SKIP: repeated_information]. C6 support_signal=received. C7 [SKIP: repeated_information]. C8 [SKIP: repeated_information]. C9 [SKIP: repeated_information].", "deep_reasoning": "User feels lonely after so lost and without her and needs encouragement.", "answer": "It makes sense to feel lonely after so lost and without her. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: My cat recently died.\nChunk 2: I had her since I was 5 years old She was 23.\nChunk 3: I feel so lost and lonely without her.\nChunk 4: My cat died last week.\nChunk 5: I feel so lost without her.\nChunk 6: :( I am so sorry to hear that...\nChunk 7: how old was she?\nChunk 8: She was 23 years old.\nChunk 9: I got her when I was 5."}, {"role": "assistant", "content": "Streaming reasoning: C1 cause=someone important passed away; need=encouragement. C2 support_signal=received. C3 emotion=lonely; cause=so lost and without her; need=validation. C4 need=encouragement. C5 [SKIP: repeated_information]. C6 support_signal=received. C7 [SKIP: repeated_information]. C8 [SKIP: repeated_information]. C9 [SKIP: repeated_information].\n\nDeep reasoning: User feels lonely after so lost and without her and needs encouragement.\n\nAnswer: It makes sense to feel lonely after so lost and without her. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My cat recently died.\nChunk 2: I had her since I was 5 years old She was 23.\nChunk 3: I feel so lost and lonely without her.\nChunk 4: My cat died last week.\nChunk 5: I feel so lost without her.\nChunk 6: :( I am so sorry to hear that...\nChunk 7: how old was she?\nChunk 8: She was 23 years old.\nChunk 9: I got her when I was 5.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user mentions someone important passed away; the user needs encouragement. Next, the user signals support or acknowledgment. Next, the user expresses lonely about so lost and without her; the user needs validation. Next, the user needs encouragement. Finally, the user signals support or acknowledgment.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 cause=someone important passed away; need=encouragement. C2 support_signal=received. C3 emotion=lonely; cause=so lost and without her; need=validation. C4 need=encouragement. C5 [SKIP: repeated_information]. C6 support_signal=received. C7 [SKIP: repeated_information]. C8 [SKIP: repeated_information]. C9 [SKIP: repeated_information].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "My cat recently died.", "streaming_reasoning": "Initially, the user mentions someone important passed away; the user needs encouragement..", "trace": "cause=someone important passed away; need=encouragement."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I had her since I was 5 years old She was 23.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I feel so lost and lonely without her.", "streaming_reasoning": "As more information arrives, the user expresses lonely about so lost and without her; the user needs validation..", "trace": "emotion=lonely; cause=so lost and without her; need=validation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "My cat died last week.", "streaming_reasoning": "As more information arrives, the user needs encouragement..", "trace": "need=encouragement."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I feel so lost without her.", "streaming_reasoning": "The content at C5 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": ":( I am so sorry to hear that...", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "how old was she?", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "She was 23 years old.", "streaming_reasoning": "The content at C8 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I got her when I was 5.", "streaming_reasoning": "The content at C9 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}]}, "output": {"deep_reasoning": "User feels lonely after so lost and without her and needs encouragement.", "answer": "It makes sense to feel lonely after so lost and without her. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002446", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for an expensive restaurant in the centre please.\nChunk 2: I think Chinese sounds good, are there any of those in the centre?\nChunk 3: yes please, book a table for 8 people at 19:30 on thursday.\nChunk 4: I am also trying to find places to go for entertainment.\nChunk 5: Can you please help me?\nChunk 6: Could you give me the area, address, and entrance fee fo the Funky Fun House?\nChunk 7: I'm actually all set now, thanks so much Take care now!", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; price+=expensive. C2 cuisine+=chinese; acceptance=selected_option. C3 goal=confirm_booking; time+=8, 19:30; day+=thursday; party_size+=8 people; goal=confirm_booking. C4 destination+=find places to go for entertainment. C5 goal=request_info. C6 goal=request_info; requested_info+=address, entrance_fee. C7 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, booking, confirm_booking, request_info; area=centre; food=chinese; price=expensive; party_size=8 people; destination=find places to go for entertainment; requested_info=address, entrance_fee; when=thursday, 8, 19:30.", "answer": "I can help with that and include the address, entrance fee once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for an expensive restaurant in the centre please.\nChunk 2: I think Chinese sounds good, are there any of those in the centre?\nChunk 3: yes please, book a table for 8 people at 19:30 on thursday.\nChunk 4: I am also trying to find places to go for entertainment.\nChunk 5: Can you please help me?\nChunk 6: Could you give me the area, address, and entrance fee fo the Funky Fun House?\nChunk 7: I'm actually all set now, thanks so much Take care now!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; price+=expensive. C2 cuisine+=chinese; acceptance=selected_option. C3 goal=confirm_booking; time+=8, 19:30; day+=thursday; party_size+=8 people; goal=confirm_booking. C4 destination+=find places to go for entertainment. C5 goal=request_info. C6 goal=request_info; requested_info+=address, entrance_fee. C7 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, confirm_booking, request_info; area=centre; food=chinese; price=expensive; party_size=8 people; destination=find places to go for entertainment; requested_info=address, entrance_fee; when=thursday, 8, 19:30.\n\nAnswer: I can help with that and include the address, entrance fee once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for an expensive restaurant in the centre please.\nChunk 2: I think Chinese sounds good, are there any of those in the centre?\nChunk 3: yes please, book a table for 8 people at 19:30 on thursday.\nChunk 4: I am also trying to find places to go for entertainment.\nChunk 5: Can you please help me?\nChunk 6: Could you give me the area, address, and entrance fee fo the Funky Fun House?\nChunk 7: I'm actually all set now, thanks so much Take care now!", "input_token_count": 92, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: expensive. Next, cuisine: chinese; acceptance: selected_option. Next, the goal is confirm booking.; time: 8; day: thursday; party size: 8 people. Next, destination: find places to go for entertainment. Next, the goal is request info. Next, the goal is request info; requested information: address. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is request info. area: centre; price: expensive.; cuisine: chinese; acceptance: selected_option.; time: 8; day: thursday; party size: 8 people; destination: find places to go for entertainment.; requested information: address; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; area+=centre; price+=expensive. C2 cuisine+=chinese; acceptance=selected_option. C3 goal=confirm_booking; time+=8, 19:30; day+=thursday; party_size+=8 people; goal=confirm_booking. C4 destination+=find places to go for entertainment. C5 goal=request_info. C6 goal=request_info; requested_info+=address, entrance_fee. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for an expensive restaurant in the centre please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: expensive..", "trace": "domain=restaurant; goal=search; area+=centre; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I think Chinese sounds good, are there any of those in the centre?", "streaming_reasoning": "As more information arrives, cuisine: chinese; acceptance: selected_option..", "trace": "cuisine+=chinese; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "yes please, book a table for 8 people at 19:30 on thursday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 8; day: thursday; party size: 8 people.", "trace": "goal=confirm_booking; time+=8, 19:30; day+=thursday; party_size+=8 people; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am also trying to find places to go for entertainment.", "streaming_reasoning": "As more information arrives, destination: find places to go for entertainment..", "trace": "destination+=find places to go for entertainment."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you please help me?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could you give me the area, address, and entrance fee fo the Funky Fun House?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, entrance_fee."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'm actually all set now, thanks so much Take care now!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; price is expensive; party size is 8 people; destination is find places to go for entertainment; requested information is address; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, entrance fee once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, confirm_booking, request_info; area=centre; food=chinese; price=expensive; party_size=8 people; destination=find places to go for entertainment; requested_info=address, entrance_fee; when=thursday, 8, 19:30."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002448", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need the train to get to Stevenage on Monday, please.\nChunk 2: I think that is all for the moment.\nChunk 3: Let me think, thanks.\nChunk 4: I am looking for emmanuel college.\nChunk 5: Can you tell me what area Emmanuel College is in?\nChunk 6: postcode, phone number, and area.\nChunk 7: Nope that is all I can think of.\nChunk 8: Thank you so much for the help!", "streaming_reasoning": "C1 domain=train; goal=request_info; day+=monday. C2 [SKIP: closing_only]. C3 intent=context_update. C4 domain=attraction. C5 goal=request_info. C6 requested_info+=phone, postcode. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, attraction; goal=search, request_info; requested_info=phone, postcode; when=monday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need the train to get to Stevenage on Monday, please.\nChunk 2: I think that is all for the moment.\nChunk 3: Let me think, thanks.\nChunk 4: I am looking for emmanuel college.\nChunk 5: Can you tell me what area Emmanuel College is in?\nChunk 6: postcode, phone number, and area.\nChunk 7: Nope that is all I can think of.\nChunk 8: Thank you so much for the help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=request_info; day+=monday. C2 [SKIP: closing_only]. C3 intent=context_update. C4 domain=attraction. C5 goal=request_info. C6 requested_info+=phone, postcode. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, attraction; goal=search, request_info; requested_info=phone, postcode; when=monday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need the train to get to Stevenage on Monday, please.\nChunk 2: I think that is all for the moment.\nChunk 3: Let me think, thanks.\nChunk 4: I am looking for emmanuel college.\nChunk 5: Can you tell me what area Emmanuel College is in?\nChunk 6: postcode, phone number, and area.\nChunk 7: Nope that is all I can think of.\nChunk 8: Thank you so much for the help!", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is request info; day: monday. Next, intent: context_update. Next, the topic is attraction. Next, the goal is request info. Finally, requested information: phone.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction.. the goal is request info.. day: monday.; intent: context_update.; requested information: phone.", "trace": "C1 domain=train; goal=request_info; day+=monday. C2 [SKIP: closing_only]. C3 intent=context_update. C4 domain=attraction. C5 goal=request_info. C6 requested_info+=phone, postcode. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need the train to get to Stevenage on Monday, please.", "streaming_reasoning": "Initially, the topic is train; the goal is request info; day: monday..", "trace": "domain=train; goal=request_info; day+=monday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I think that is all for the moment.", "streaming_reasoning": "The content at C2 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Let me think, thanks.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am looking for emmanuel college.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you tell me what area Emmanuel College is in?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "postcode, phone number, and area.", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Nope that is all I can think of.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you so much for the help!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=search, request_info; requested_info=phone, postcode; when=monday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002449", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a danish restaurant in the south part of town.\nChunk 2: Yes, please look for Portuguese food.\nChunk 3: Can I get the phone number and address Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=south; cuisine+=danish. C2 acceptance=selected_option. C3 goal=request_info; requested_info+=address, phone.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=south; food=danish; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a danish restaurant in the south part of town.\nChunk 2: Yes, please look for Portuguese food.\nChunk 3: Can I get the phone number and address Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=south; cuisine+=danish. C2 acceptance=selected_option. C3 goal=request_info; requested_info+=address, phone.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=south; food=danish; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a danish restaurant in the south part of town.\nChunk 2: Yes, please look for Portuguese food.\nChunk 3: Can I get the phone number and address Thank you, goodbye.", "input_token_count": 36, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: south; cuisine: danish. Next, acceptance: selected_option. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. area: south; cuisine: danish.; acceptance: selected_option.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; area+=south; cuisine+=danish. C2 acceptance=selected_option. C3 goal=request_info; requested_info+=address, phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a danish restaurant in the south part of town.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: south; cuisine: danish..", "trace": "domain=restaurant; goal=search; area+=south; cuisine+=danish."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, please look for Portuguese food.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I get the phone number and address Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; cuisine is danish; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=south; food=danish; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002451", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm trying to find Addenbrookes Hospital and they're supposed to have a medical decisions unit department, right?\nChunk 2: Can you confirm Addenbrookes has a medical decisions unit?\nChunk 3: Can I also get the postcode and address please?\nChunk 4: Thanks for all the info.\nChunk 5: I will contact the hospital now Goodbye.", "streaming_reasoning": "C1 domain=hospital; goal=search; destination+=find addenbrookes hospital and they're su. C2 goal=request_info. C3 goal=request_info; requested_info+=address, postcode. C4 [SKIP: thanks_only]. C5 intent=context_update.", "deep_reasoning": "Need domain=hospital; goal=search, request_info; destination=find addenbrookes hospital and they're su; requested_info=address, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I'm trying to find Addenbrookes Hospital and they're supposed to have a medical decisions unit department, right?\nChunk 2: Can you confirm Addenbrookes has a medical decisions unit?\nChunk 3: Can I also get the postcode and address please?\nChunk 4: Thanks for all the info.\nChunk 5: I will contact the hospital now Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search; destination+=find addenbrookes hospital and they're su. C2 goal=request_info. C3 goal=request_info; requested_info+=address, postcode. C4 [SKIP: thanks_only]. C5 intent=context_update.\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; destination=find addenbrookes hospital and they're su; requested_info=address, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm trying to find Addenbrookes Hospital and they're supposed to have a medical decisions unit department, right?\nChunk 2: Can you confirm Addenbrookes has a medical decisions unit?\nChunk 3: Can I also get the postcode and address please?\nChunk 4: Thanks for all the info.\nChunk 5: I will contact the hospital now Goodbye.", "input_token_count": 58, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find addenbrookes hospital and they're su. Next, the goal is request info. Next, the goal is request info; requested information: address. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hospital. the goal is request info. destination: find addenbrookes hospital and they're su.; requested information: address; intent: context_update..", "trace": "C1 domain=hospital; goal=search; destination+=find addenbrookes hospital and they're su. C2 goal=request_info. C3 goal=request_info; requested_info+=address, postcode. C4 [SKIP: thanks_only]. C5 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I'm trying to find Addenbrookes Hospital and they're supposed to have a medical decisions unit department, right?", "streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find addenbrookes hospital and they're su..", "trace": "domain=hospital; goal=search; destination+=find addenbrookes hospital and they're su."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you confirm Addenbrookes has a medical decisions unit?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I also get the postcode and address please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks for all the info.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will contact the hospital now Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: destination is find addenbrookes hospital and they're su; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; destination=find addenbrookes hospital and they're su; requested_info=address, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002452", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to get to Ely by 19:00.\nChunk 2: No I need to know the departure time for that ride.\nChunk 3: Yes, I'd like to find an Indian restaurant in the west area also please.\nChunk 4: Is it in the moderate price range?\nChunk 5: It is for 5 people.\nChunk 6: The time is 5, 10:45.\nChunk 7: Please make a booking.\nChunk 8: I also need the reference number Thank you.\nChunk 9: My visit is set with your help.\nChunk 10: Have a nice day Goodbye.", "streaming_reasoning": "C1 goal=request_info; time+=19:00. C2 destination+=know the departure time for that ride. C3 domain=restaurant; area+=west; cuisine+=indian; destination+=find an indian restaurant in the west are; acceptance=selected_option. C4 price+=moderate. C5 party_size+=5 people. C6 time+=5, 10:45. C7 goal=booking. C8 requested_info+=reference_number. C9 intent=context_update. C10 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, booking; area=west; food=indian; price=moderate; party_size=5 people; destination=know the departure time for that ride, find an indian restaurant in the west are; requested_info=reference_number; when=19:00, 5, 10:45.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to get to Ely by 19:00.\nChunk 2: No I need to know the departure time for that ride.\nChunk 3: Yes, I'd like to find an Indian restaurant in the west area also please.\nChunk 4: Is it in the moderate price range?\nChunk 5: It is for 5 people.\nChunk 6: The time is 5, 10:45.\nChunk 7: Please make a booking.\nChunk 8: I also need the reference number Thank you.\nChunk 9: My visit is set with your help.\nChunk 10: Have a nice day Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; time+=19:00. C2 destination+=know the departure time for that ride. C3 domain=restaurant; area+=west; cuisine+=indian; destination+=find an indian restaurant in the west are; acceptance=selected_option. C4 price+=moderate. C5 party_size+=5 people. C6 time+=5, 10:45. C7 goal=booking. C8 requested_info+=reference_number. C9 intent=context_update. C10 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, booking; area=west; food=indian; price=moderate; party_size=5 people; destination=know the departure time for that ride, find an indian restaurant in the west are; requested_info=reference_number; when=19:00, 5, 10:45.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to get to Ely by 19:00.\nChunk 2: No I need to know the departure time for that ride.\nChunk 3: Yes, I'd like to find an Indian restaurant in the west area also please.\nChunk 4: Is it in the moderate price range?\nChunk 5: It is for 5 people.\nChunk 6: The time is 5, 10:45.\nChunk 7: Please make a booking.\nChunk 8: I also need the reference number Thank you.\nChunk 9: My visit is set with your help.\nChunk 10: Have a nice day Goodbye.", "input_token_count": 96, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; time: 19:00. Next, destination: know the departure time for that ride. Next, the topic is restaurant; area: west; cuisine: indian; destination: find an indian restaurant in the west are; acceptance: selected_option. Next, price: moderate. Next, party size: 5 people. Next, time: 5. Next, the goal is booking. Next, requested information: reference_number. Next, intent: context_update. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is booking.. time: 19:00., 5; destination: know the departure time for that ride., find an indian restaurant in the west are; area: west; cuisine: indian; acceptance: selected_option.; price: moderate.; party size: 5 people.; requested information: reference_number.; intent: context_update..", "trace": "C1 goal=request_info; time+=19:00. C2 destination+=know the departure time for that ride. C3 domain=restaurant; area+=west; cuisine+=indian; destination+=find an indian restaurant in the west are; acceptance=selected_option. C4 price+=moderate. C5 party_size+=5 people. C6 time+=5, 10:45. C7 goal=booking. C8 requested_info+=reference_number. C9 intent=context_update. C10 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to get to Ely by 19:00.", "streaming_reasoning": "Initially, the goal is request info; time: 19:00..", "trace": "goal=request_info; time+=19:00."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No I need to know the departure time for that ride.", "streaming_reasoning": "As more information arrives, destination: know the departure time for that ride..", "trace": "destination+=know the departure time for that ride."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I'd like to find an Indian restaurant in the west area also please.", "streaming_reasoning": "As more information arrives, the topic is restaurant; area: west; cuisine: indian; destination: find an indian restaurant in the west are; acceptance: selected_option..", "trace": "domain=restaurant; area+=west; cuisine+=indian; destination+=find an indian restaurant in the west are; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is it in the moderate price range?", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It is for 5 people.", "streaming_reasoning": "As more information arrives, party size: 5 people..", "trace": "party_size+=5 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 5, 10:45.", "streaming_reasoning": "As more information arrives, time: 5.", "trace": "time+=5, 10:45."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need the reference number Thank you.", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "My visit is set with your help.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Have a nice day Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is west; cuisine is indian; price is moderate; party size is 5 people; destination is know the departure time for that ride; requested information is reference_number; timing is 19:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, booking; area=west; food=indian; price=moderate; party_size=5 people; destination=know the departure time for that ride, find an indian restaurant in the west are; requested_info=reference_number; when=19:00, 5, 10:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002453", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Actually, I am also looking for places to go in the same area as Chiquito Restaurant is.\nChunk 2: A museum would be great.\nChunk 3: Could I have the address of one you suggest That sounds great.\nChunk 4: May I have the address, please?\nChunk 5: Yes can you book me a taxi to take me to the restaurant from the museum?\nChunk 6: Yes, will there be any theater performances on the next night, Tuesday?\nChunk 7: Actually that is all I need.\nChunk 8: thank you for you're help.", "streaming_reasoning": "C1 domain=restaurant; goal=modify_constraint; destination+=go in the same area as chiquito restauran. C2 domain=attraction. C3 goal=request_info; requested_info+=address. C4 goal=request_info. C5 domain=taxi; goal=confirm_booking; goal=confirm_booking. C6 day+=tuesday; goal=confirm_booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, attraction, taxi; goal=search, modify_constraint, recommendation, request_info, booking, confirm_booking; destination=go in the same area as chiquito restauran; requested_info=address; when=tuesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Actually, I am also looking for places to go in the same area as Chiquito Restaurant is.\nChunk 2: A museum would be great.\nChunk 3: Could I have the address of one you suggest That sounds great.\nChunk 4: May I have the address, please?\nChunk 5: Yes can you book me a taxi to take me to the restaurant from the museum?\nChunk 6: Yes, will there be any theater performances on the next night, Tuesday?\nChunk 7: Actually that is all I need.\nChunk 8: thank you for you're help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=modify_constraint; destination+=go in the same area as chiquito restauran. C2 domain=attraction. C3 goal=request_info; requested_info+=address. C4 goal=request_info. C5 domain=taxi; goal=confirm_booking; goal=confirm_booking. C6 day+=tuesday; goal=confirm_booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, attraction, taxi; goal=search, modify_constraint, recommendation, request_info, booking, confirm_booking; destination=go in the same area as chiquito restauran; requested_info=address; when=tuesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Actually, I am also looking for places to go in the same area as Chiquito Restaurant is.\nChunk 2: A museum would be great.\nChunk 3: Could I have the address of one you suggest That sounds great.\nChunk 4: May I have the address, please?\nChunk 5: Yes can you book me a taxi to take me to the restaurant from the museum?\nChunk 6: Yes, will there be any theater performances on the next night, Tuesday?\nChunk 7: Actually that is all I need.\nChunk 8: thank you for you're help.", "input_token_count": 95, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is modify constraint; destination: go in the same area as chiquito restauran. Next, the topic is attraction. Next, the goal is request info; requested information: address. Next, the goal is request info. Next, the topic is taxi; the goal is confirm booking. Finally, the goal is confirm booking.; day: tuesday.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is confirm booking.. destination: go in the same area as chiquito restauran.; requested information: address.; day: tuesday.", "trace": "C1 domain=restaurant; goal=modify_constraint; destination+=go in the same area as chiquito restauran. C2 domain=attraction. C3 goal=request_info; requested_info+=address. C4 goal=request_info. C5 domain=taxi; goal=confirm_booking; goal=confirm_booking. C6 day+=tuesday; goal=confirm_booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Actually, I am also looking for places to go in the same area as Chiquito Restaurant is.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is modify constraint; destination: go in the same area as chiquito restauran..", "trace": "domain=restaurant; goal=modify_constraint; destination+=go in the same area as chiquito restauran."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "A museum would be great.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Could I have the address of one you suggest That sounds great.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "May I have the address, please?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes can you book me a taxi to take me to the restaurant from the museum?", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is confirm booking..", "trace": "domain=taxi; goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, will there be any theater performances on the next night, Tuesday?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; day: tuesday.", "trace": "day+=tuesday; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Actually that is all I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "thank you for you're help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: destination is go in the same area as chiquito restauran; requested information is address; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction, taxi; goal=search, modify_constraint, recommendation, request_info, booking, confirm_booking; destination=go in the same area as chiquito restauran; requested_info=address; when=tuesday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002454", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a moderate guesthouse.\nChunk 2: I also need the address That works!\nChunk 3: Please book it!\nChunk 4: How many stars is Acorn Guesthouse, and what is its address?\nChunk 5: No, don't book it.\nChunk 6: Can you look for a train that leaves Cambridge on Wednesday That sounds good.\nChunk 7: What is the train ID number?\nChunk 8: I also need the price and travel time.\nChunk 9: Thanks, that's all I need today Goodbye!", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=moderate; hotel_type+=guesthouse; destination+=find a moderate guesthouse. C2 goal=request_info; requested_info+=address; acceptance=selected_option. C3 goal=booking. C4 goal=request_info. C5 goal=modify_constraint. C6 domain=train; day+=wednesday; goal=confirm_booking. C7 goal=request_info. C8 requested_info+=travel_time, price. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, train; goal=search, request_info, booking; price=moderate; destination=find a moderate guesthouse; requested_info=address, travel_time, price; when=wednesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a moderate guesthouse.\nChunk 2: I also need the address That works!\nChunk 3: Please book it!\nChunk 4: How many stars is Acorn Guesthouse, and what is its address?\nChunk 5: No, don't book it.\nChunk 6: Can you look for a train that leaves Cambridge on Wednesday That sounds good.\nChunk 7: What is the train ID number?\nChunk 8: I also need the price and travel time.\nChunk 9: Thanks, that's all I need today Goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=moderate; hotel_type+=guesthouse; destination+=find a moderate guesthouse. C2 goal=request_info; requested_info+=address; acceptance=selected_option. C3 goal=booking. C4 goal=request_info. C5 goal=modify_constraint. C6 domain=train; day+=wednesday; goal=confirm_booking. C7 goal=request_info. C8 requested_info+=travel_time, price. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, train; goal=search, request_info, booking; price=moderate; destination=find a moderate guesthouse; requested_info=address, travel_time, price; when=wednesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a moderate guesthouse.\nChunk 2: I also need the address That works!\nChunk 3: Please book it!\nChunk 4: How many stars is Acorn Guesthouse, and what is its address?\nChunk 5: No, don't book it.\nChunk 6: Can you look for a train that leaves Cambridge on Wednesday That sounds good.\nChunk 7: What is the train ID number?\nChunk 8: I also need the price and travel time.\nChunk 9: Thanks, that's all I need today Goodbye!", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: moderate; hotel type: guesthouse; destination: find a moderate guesthouse. Next, the goal is request info; requested information: address; acceptance: selected_option. Next, the goal is booking. Next, the goal is request info. Next, the goal is modify constraint. Next, the topic is train; the goal is confirm booking.; day: wednesday. Next, the goal is request info. Finally, requested information: travel_time.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info.. price: moderate; hotel type: guesthouse; destination: find a moderate guesthouse.; requested information: address, travel_time; acceptance: selected_option.; day: wednesday.", "trace": "C1 domain=hotel; goal=search; price+=moderate; hotel_type+=guesthouse; destination+=find a moderate guesthouse. C2 goal=request_info; requested_info+=address; acceptance=selected_option. C3 goal=booking. C4 goal=request_info. C5 goal=modify_constraint. C6 domain=train; day+=wednesday; goal=confirm_booking. C7 goal=request_info. C8 requested_info+=travel_time, price. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a moderate guesthouse.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: moderate; hotel type: guesthouse; destination: find a moderate guesthouse..", "trace": "domain=hotel; goal=search; price+=moderate; hotel_type+=guesthouse; destination+=find a moderate guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need the address That works!", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=address; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Please book it!", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "How many stars is Acorn Guesthouse, and what is its address?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, don't book it.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you look for a train that leaves Cambridge on Wednesday That sounds good.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is confirm booking.; day: wednesday.", "trace": "domain=train; day+=wednesday; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "What is the train ID number?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need the price and travel time.", "streaming_reasoning": "As more information arrives, requested information: travel_time.", "trace": "requested_info+=travel_time, price."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks, that's all I need today Goodbye!", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is moderate; destination is find a moderate guesthouse; requested information is address; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, train; goal=search, request_info, booking; price=moderate; destination=find a moderate guesthouse; requested_info=address, travel_time, price; when=wednesday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002455", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, please make a booking for 3 people.\nChunk 2: Thank you for your time and help, sorry for the confusion.\nChunk 3: Have a great day!\nChunk 4: Have a nice day.\nChunk 5: I need help with attraction.\nChunk 6: It should be in the centre part of town.\nChunk 7: I also need the phone.\nChunk 8: I also need the entrance fee.\nChunk 9: Please get me their phone number That is all.", "streaming_reasoning": "C1 goal=booking; party_size+=3 people; goal=confirm_booking. C2 [SKIP: thanks_only]. C3 [SKIP: closing_only]. C4 [SKIP: closing_only]. C5 domain=attraction; goal=search. C6 area+=centre. C7 goal=request_info; requested_info+=phone. C8 requested_info+=entrance_fee. C9 intent=context_update.", "deep_reasoning": "Need domain=attraction; goal=booking, search, request_info; area=centre; party_size=3 people; requested_info=phone, entrance_fee; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, please make a booking for 3 people.\nChunk 2: Thank you for your time and help, sorry for the confusion.\nChunk 3: Have a great day!\nChunk 4: Have a nice day.\nChunk 5: I need help with attraction.\nChunk 6: It should be in the centre part of town.\nChunk 7: I also need the phone.\nChunk 8: I also need the entrance fee.\nChunk 9: Please get me their phone number That is all."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; party_size+=3 people; goal=confirm_booking. C2 [SKIP: thanks_only]. C3 [SKIP: closing_only]. C4 [SKIP: closing_only]. C5 domain=attraction; goal=search. C6 area+=centre. C7 goal=request_info; requested_info+=phone. C8 requested_info+=entrance_fee. C9 intent=context_update.\n\nDeep reasoning: Need domain=attraction; goal=booking, search, request_info; area=centre; party_size=3 people; requested_info=phone, entrance_fee; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, please make a booking for 3 people.\nChunk 2: Thank you for your time and help, sorry for the confusion.\nChunk 3: Have a great day!\nChunk 4: Have a nice day.\nChunk 5: I need help with attraction.\nChunk 6: It should be in the centre part of town.\nChunk 7: I also need the phone.\nChunk 8: I also need the entrance fee.\nChunk 9: Please get me their phone number That is all.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is confirm booking.; party size: 3 people. Next, the topic is attraction; the goal is search. Next, area: centre. Next, the goal is request info; requested information: phone. Next, requested information: entrance_fee. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction. the goal is request info. party size: 3 people; area: centre.; requested information: phone., entrance_fee.; intent: context_update..", "trace": "C1 goal=booking; party_size+=3 people; goal=confirm_booking. C2 [SKIP: thanks_only]. C3 [SKIP: closing_only]. C4 [SKIP: closing_only]. C5 domain=attraction; goal=search. C6 area+=centre. C7 goal=request_info; requested_info+=phone. C8 requested_info+=entrance_fee. C9 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, please make a booking for 3 people.", "streaming_reasoning": "Initially, the goal is confirm booking.; party size: 3 people.", "trace": "goal=booking; party_size+=3 people; goal=confirm_booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thank you for your time and help, sorry for the confusion.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Have a great day!", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Have a nice day.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need help with attraction.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is search..", "trace": "domain=attraction; goal=search."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need the entrance fee.", "streaming_reasoning": "As more information arrives, requested information: entrance_fee..", "trace": "requested_info+=entrance_fee."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Please get me their phone number That is all.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of booking. Key information: area is centre; party size is 3 people; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=booking, search, request_info; area=centre; party_size=3 people; requested_info=phone, entrance_fee; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002457", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like for it to have a 4 star rating and be located in the east section of town.\nChunk 2: If you could tell me hotel types of both and phone number please Thank you!\nChunk 3: Can you help me book a taxi from the college to my hotel?\nChunk 4: I'll be staying at The Carolina Bed and Breakfast.\nChunk 5: I'd like to leave by 6AM Okay thank you.\nChunk 6: That is all I need for now.", "streaming_reasoning": "C1 area+=east; stars+=4 stars; destination+=have a 4 star rating and be located in th. C2 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone. C3 domain=attraction; goal=booking; destination+=my hotel; departure+=the college. C4 domain=restaurant; amenities+=breakfast. C5 time+=6am; destination+=leave by 6am okay thank you. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, taxi, attraction, restaurant; goal=request_info, search, booking; area=east; stars=4 stars; amenities=breakfast; destination=have a 4 star rating and be located in th, my hotel, leave by 6am okay thank you; departure=the college; requested_info=phone; when=6am; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like for it to have a 4 star rating and be located in the east section of town.\nChunk 2: If you could tell me hotel types of both and phone number please Thank you!\nChunk 3: Can you help me book a taxi from the college to my hotel?\nChunk 4: I'll be staying at The Carolina Bed and Breakfast.\nChunk 5: I'd like to leave by 6AM Okay thank you.\nChunk 6: That is all I need for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=east; stars+=4 stars; destination+=have a 4 star rating and be located in th. C2 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone. C3 domain=attraction; goal=booking; destination+=my hotel; departure+=the college. C4 domain=restaurant; amenities+=breakfast. C5 time+=6am; destination+=leave by 6am okay thank you. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, taxi, attraction, restaurant; goal=request_info, search, booking; area=east; stars=4 stars; amenities=breakfast; destination=have a 4 star rating and be located in th, my hotel, leave by 6am okay thank you; departure=the college; requested_info=phone; when=6am; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like for it to have a 4 star rating and be located in the east section of town.\nChunk 2: If you could tell me hotel types of both and phone number please Thank you!\nChunk 3: Can you help me book a taxi from the college to my hotel?\nChunk 4: I'll be staying at The Carolina Bed and Breakfast.\nChunk 5: I'd like to leave by 6AM Okay thank you.\nChunk 6: That is all I need for now.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: east; star rating: 4 stars; destination: have a 4 star rating and be located in th. Next, the topic is hotel; the goal is request info; hotel type: hotel; requested information: phone. Next, the topic is attraction; the goal is booking; destination: my hotel; departure point: the college. Next, the topic is restaurant; amenities: breakfast. Finally, time: 6am; destination: leave by 6am okay thank you.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. area: east; star rating: 4 stars; destination: have a 4 star rating and be located in th., my hotel, leave by 6am okay thank you.; hotel type: hotel; requested information: phone.; departure point: the college.; amenities: breakfast.; time: 6am.", "trace": "C1 area+=east; stars+=4 stars; destination+=have a 4 star rating and be located in th. C2 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone. C3 domain=attraction; goal=booking; destination+=my hotel; departure+=the college. C4 domain=restaurant; amenities+=breakfast. C5 time+=6am; destination+=leave by 6am okay thank you. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like for it to have a 4 star rating and be located in the east section of town.", "streaming_reasoning": "Initially, area: east; star rating: 4 stars; destination: have a 4 star rating and be located in th..", "trace": "area+=east; stars+=4 stars; destination+=have a 4 star rating and be located in th."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "If you could tell me hotel types of both and phone number please Thank you!", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is request info; hotel type: hotel; requested information: phone..", "trace": "domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you help me book a taxi from the college to my hotel?", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is booking; destination: my hotel; departure point: the college..", "trace": "domain=attraction; goal=booking; destination+=my hotel; departure+=the college."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll be staying at The Carolina Bed and Breakfast.", "streaming_reasoning": "As more information arrives, the topic is restaurant; amenities: breakfast..", "trace": "domain=restaurant; amenities+=breakfast."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'd like to leave by 6AM Okay thank you.", "streaming_reasoning": "As more information arrives, time: 6am; destination: leave by 6am okay thank you..", "trace": "time+=6am; destination+=leave by 6am okay thank you."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all I need for now.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: area is east; star rating is 4 stars; amenities is breakfast; destination is have a 4 star rating and be located in th; departure point is the college; requested information is phone; timing is 6am. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, taxi, attraction, restaurant; goal=request_info, search, booking; area=east; stars=4 stars; amenities=breakfast; destination=have a 4 star rating and be located in th, my hotel, leave by 6am okay thank you; departure=the college; requested_info=phone; when=6am; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002458", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure.\nChunk 2: I would like to book a table for 5 people at 11:00 on Saturday.\nChunk 3: Book it for XXXX, can I please get a reference number?\nChunk 4: Are there any other cheap restaurants in the area?\nChunk 5: Are there any in the same area and price range but not Chinese?\nChunk 6: Yes, please try J Restaurant.\nChunk 7: Asian Oriental food sounds good.\nChunk 8: Thank you for your help!\nChunk 9: That will be all Good Bye.", "streaming_reasoning": "C1 [SKIP: backchannel_only]. C2 goal=booking; time+=5, 11:00; day+=saturday; party_size+=5 people. C3 goal=request_info; requested_info+=reference_number. C4 price+=cheap. C5 goal=modify_constraint; cuisine+=chinese. C6 domain=restaurant; goal=confirm_booking. C7 goal=confirm_booking. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=booking, request_info, modify_constraint; food=chinese; price=cheap; party_size=5 people; requested_info=reference_number; when=saturday, 5, 11:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sure.\nChunk 2: I would like to book a table for 5 people at 11:00 on Saturday.\nChunk 3: Book it for XXXX, can I please get a reference number?\nChunk 4: Are there any other cheap restaurants in the area?\nChunk 5: Are there any in the same area and price range but not Chinese?\nChunk 6: Yes, please try J Restaurant.\nChunk 7: Asian Oriental food sounds good.\nChunk 8: Thank you for your help!\nChunk 9: That will be all Good Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: backchannel_only]. C2 goal=booking; time+=5, 11:00; day+=saturday; party_size+=5 people. C3 goal=request_info; requested_info+=reference_number. C4 price+=cheap. C5 goal=modify_constraint; cuisine+=chinese. C6 domain=restaurant; goal=confirm_booking. C7 goal=confirm_booking. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=booking, request_info, modify_constraint; food=chinese; price=cheap; party_size=5 people; requested_info=reference_number; when=saturday, 5, 11:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure.\nChunk 2: I would like to book a table for 5 people at 11:00 on Saturday.\nChunk 3: Book it for XXXX, can I please get a reference number?\nChunk 4: Are there any other cheap restaurants in the area?\nChunk 5: Are there any in the same area and price range but not Chinese?\nChunk 6: Yes, please try J Restaurant.\nChunk 7: Asian Oriental food sounds good.\nChunk 8: Thank you for your help!\nChunk 9: That will be all Good Bye.", "input_token_count": 88, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 5; day: saturday; party size: 5 people. Next, the goal is request info; requested information: reference_number. Next, price: cheap. Next, the goal is modify constraint; cuisine: chinese. Next, the topic is restaurant; the goal is confirm booking. Finally, the goal is confirm booking.  Some chunks were skipped because they contained backchannel_only or closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is confirm booking.. time: 5; day: saturday; party size: 5 people.; requested information: reference_number.; price: cheap.; cuisine: chinese..", "trace": "C1 [SKIP: backchannel_only]. C2 goal=booking; time+=5, 11:00; day+=saturday; party_size+=5 people. C3 goal=request_info; requested_info+=reference_number. C4 price+=cheap. C5 goal=modify_constraint; cuisine+=chinese. C6 domain=restaurant; goal=confirm_booking. C7 goal=confirm_booking. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sure.", "streaming_reasoning": "The content at C1 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to book a table for 5 people at 11:00 on Saturday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 5; day: saturday; party size: 5 people..", "trace": "goal=booking; time+=5, 11:00; day+=saturday; party_size+=5 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Book it for XXXX, can I please get a reference number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Are there any other cheap restaurants in the area?", "streaming_reasoning": "As more information arrives, price: cheap..", "trace": "price+=cheap."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Are there any in the same area and price range but not Chinese?", "streaming_reasoning": "As more information arrives, the goal is modify constraint; cuisine: chinese..", "trace": "goal=modify_constraint; cuisine+=chinese."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, please try J Restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is confirm booking..", "trace": "domain=restaurant; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Asian Oriental food sounds good.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for your help!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That will be all Good Bye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: cuisine is chinese; price is cheap; party size is 5 people; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=booking, request_info, modify_constraint; food=chinese; price=cheap; party_size=5 people; requested_info=reference_number; when=saturday, 5, 11:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002459", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Where can I find malaysian food?\nChunk 2: I prefer an expensive restaurant please.\nChunk 3: How about an expensive Malaysian restraint in the south?\nChunk 4: Is there anything available Yes, please.\nChunk 5: How about Indian food Perfect, yes.\nChunk 6: I want a table for 5 at 16:00 on monday Thank you.\nChunk 7: That was all I needed today Goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=request_info. C2 price+=expensive. C3 goal=recommendation; area+=south. C4 acceptance=selected_option. C5 cuisine+=indian; acceptance=selected_option. C6 time+=5, 16:00; day+=monday. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, recommendation; area=south; food=indian; price=expensive; when=monday, 5, 16:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Where can I find malaysian food?\nChunk 2: I prefer an expensive restaurant please.\nChunk 3: How about an expensive Malaysian restraint in the south?\nChunk 4: Is there anything available Yes, please.\nChunk 5: How about Indian food Perfect, yes.\nChunk 6: I want a table for 5 at 16:00 on monday Thank you.\nChunk 7: That was all I needed today Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=request_info. C2 price+=expensive. C3 goal=recommendation; area+=south. C4 acceptance=selected_option. C5 cuisine+=indian; acceptance=selected_option. C6 time+=5, 16:00; day+=monday. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, recommendation; area=south; food=indian; price=expensive; when=monday, 5, 16:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Where can I find malaysian food?\nChunk 2: I prefer an expensive restaurant please.\nChunk 3: How about an expensive Malaysian restraint in the south?\nChunk 4: Is there anything available Yes, please.\nChunk 5: How about Indian food Perfect, yes.\nChunk 6: I want a table for 5 at 16:00 on monday Thank you.\nChunk 7: That was all I needed today Goodbye.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is request info. Next, price: expensive. Next, the goal is recommendation; area: south. Next, acceptance: selected_option. Next, cuisine: indian; acceptance: selected_option. Finally, time: 5; day: monday.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is recommendation. price: expensive.; area: south.; acceptance: selected_option.; cuisine: indian; time: 5; day: monday..", "trace": "C1 domain=restaurant; goal=request_info. C2 price+=expensive. C3 goal=recommendation; area+=south. C4 acceptance=selected_option. C5 cuisine+=indian; acceptance=selected_option. C6 time+=5, 16:00; day+=monday. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Where can I find malaysian food?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is request info..", "trace": "domain=restaurant; goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I prefer an expensive restaurant please.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about an expensive Malaysian restraint in the south?", "streaming_reasoning": "As more information arrives, the goal is recommendation; area: south..", "trace": "goal=recommendation; area+=south."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is there anything available Yes, please.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "How about Indian food Perfect, yes.", "streaming_reasoning": "As more information arrives, cuisine: indian; acceptance: selected_option..", "trace": "cuisine+=indian; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want a table for 5 at 16:00 on monday Thank you.", "streaming_reasoning": "As more information arrives, time: 5; day: monday..", "trace": "time+=5, 16:00; day+=monday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That was all I needed today Goodbye.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; cuisine is indian; price is expensive; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, recommendation; area=south; food=indian; price=expensive; when=monday, 5, 16:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002460", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Not really, and I'm not really concerned with wifi either.\nChunk 2: Which one do you recommend?\nChunk 3: What is the hotel's rating?\nChunk 4: Actually, could you double check whether the Acorn has free wifi?\nChunk 5: I want to find a hotel.\nChunk 6: The time is thursday.\nChunk 7: OK, can you please pay attention to my questions?\nChunk 8: I need a room, please.\nChunk 9: No that will be all.\nChunk 10: Thanks!", "streaming_reasoning": "C1 amenities+=wifi. C2 goal=recommendation. C3 domain=hotel; goal=request_info; hotel_type+=hotel. C4 goal=request_info. C5 goal=search; destination+=find a hotel. C6 day+=thursday. C7 destination+=my questions. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=recommendation, request_info, search; amenities=wifi; destination=find a hotel, my questions; when=thursday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Not really, and I'm not really concerned with wifi either.\nChunk 2: Which one do you recommend?\nChunk 3: What is the hotel's rating?\nChunk 4: Actually, could you double check whether the Acorn has free wifi?\nChunk 5: I want to find a hotel.\nChunk 6: The time is thursday.\nChunk 7: OK, can you please pay attention to my questions?\nChunk 8: I need a room, please.\nChunk 9: No that will be all.\nChunk 10: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 amenities+=wifi. C2 goal=recommendation. C3 domain=hotel; goal=request_info; hotel_type+=hotel. C4 goal=request_info. C5 goal=search; destination+=find a hotel. C6 day+=thursday. C7 destination+=my questions. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=recommendation, request_info, search; amenities=wifi; destination=find a hotel, my questions; when=thursday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Not really, and I'm not really concerned with wifi either.\nChunk 2: Which one do you recommend?\nChunk 3: What is the hotel's rating?\nChunk 4: Actually, could you double check whether the Acorn has free wifi?\nChunk 5: I want to find a hotel.\nChunk 6: The time is thursday.\nChunk 7: OK, can you please pay attention to my questions?\nChunk 8: I need a room, please.\nChunk 9: No that will be all.\nChunk 10: Thanks!", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, amenities: wifi. Next, the goal is recommendation. Next, the topic is hotel; the goal is request info; hotel type: hotel. Next, the goal is request info. Next, the goal is search; destination: find a hotel. Next, day: thursday. Next, destination: my questions. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is search. amenities: wifi.; hotel type: hotel.; destination: find a hotel., my questions.; day: thursday.; intent: context_update..", "trace": "C1 amenities+=wifi. C2 goal=recommendation. C3 domain=hotel; goal=request_info; hotel_type+=hotel. C4 goal=request_info. C5 goal=search; destination+=find a hotel. C6 day+=thursday. C7 destination+=my questions. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Not really, and I'm not really concerned with wifi either.", "streaming_reasoning": "Initially, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Which one do you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the hotel's rating?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is request info; hotel type: hotel..", "trace": "domain=hotel; goal=request_info; hotel_type+=hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Actually, could you double check whether the Acorn has free wifi?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the goal is search; destination: find a hotel..", "trace": "goal=search; destination+=find a hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is thursday.", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "OK, can you please pay attention to my questions?", "streaming_reasoning": "As more information arrives, destination: my questions..", "trace": "destination+=my questions."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I need a room, please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No that will be all.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thanks!", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of recommendation. Key information: amenities is wifi; destination is find a hotel; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=recommendation, request_info, search; amenities=wifi; destination=find a hotel, my questions; when=thursday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003085", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Then I'll take them How much?\nChunk 2: $ 120.The small gift box is complementary.\nChunk 3: Here is $ 150.Keep the change Thank you!\nChunk 4: Have a nice day!", "streaming_reasoning": "C1 question=true. C2 casual_comment=small, gift. C3 casual_comment=here, keep. C4 [SKIP: closing_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Then I'll take them How much?\nChunk 2: $ 120.The small gift box is complementary.\nChunk 3: Here is $ 150.Keep the change Thank you!\nChunk 4: Have a nice day!"}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 casual_comment=small, gift. C3 casual_comment=here, keep. C4 [SKIP: closing_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Then I'll take them How much?\nChunk 2: $ 120.The small gift box is complementary.\nChunk 3: Here is $ 150.Keep the change Thank you!\nChunk 4: Have a nice day!", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on small. Finally, the user comments on here.  Some chunks were skipped because they contained closing_only.", "trace": "C1 question=true. C2 casual_comment=small, gift. C3 casual_comment=here, keep. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Then I'll take them How much?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "$ 120.The small gift box is complementary.", "streaming_reasoning": "As more information arrives, the user comments on small.", "trace": "casual_comment=small, gift."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Here is $ 150.Keep the change Thank you!", "streaming_reasoning": "As more information arrives, the user comments on here.", "trace": "casual_comment=here, keep."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Have a nice day!", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002461", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Oh I almost forgot, I also need the hotel to provide free wifi.\nChunk 2: That may narrow my options down a bit Can you check That is great.\nChunk 3: I need it for Tuesday.\nChunk 4: 7 people lasting 5 nights.\nChunk 5: Yes, I would also like to find a Spanish place to eat at Surprise me!\nChunk 6: I really don't care.\nChunk 7: Great, lets set up a reservation for 7 people at 20:00 on Tuesday Thank you.\nChunk 8: That is all that I need.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=wifi; destination+=provide free wifi. C2 intent=context_update. C3 day+=tuesday. C4 party_size+=7 people; stay_length+=5 nights. C5 domain=restaurant; destination+=find a spanish place to eat at surprise m; acceptance=selected_option. C6 intent=context_update. C7 goal=booking; time+=7, 20:00. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, booking; party_size=7 people; stay_length=5 nights; amenities=wifi; destination=provide free wifi, find a spanish place to eat at surprise m; when=tuesday, 7, 20:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Oh I almost forgot, I also need the hotel to provide free wifi.\nChunk 2: That may narrow my options down a bit Can you check That is great.\nChunk 3: I need it for Tuesday.\nChunk 4: 7 people lasting 5 nights.\nChunk 5: Yes, I would also like to find a Spanish place to eat at Surprise me!\nChunk 6: I really don't care.\nChunk 7: Great, lets set up a reservation for 7 people at 20:00 on Tuesday Thank you.\nChunk 8: That is all that I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=wifi; destination+=provide free wifi. C2 intent=context_update. C3 day+=tuesday. C4 party_size+=7 people; stay_length+=5 nights. C5 domain=restaurant; destination+=find a spanish place to eat at surprise m; acceptance=selected_option. C6 intent=context_update. C7 goal=booking; time+=7, 20:00. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, booking; party_size=7 people; stay_length=5 nights; amenities=wifi; destination=provide free wifi, find a spanish place to eat at surprise m; when=tuesday, 7, 20:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Oh I almost forgot, I also need the hotel to provide free wifi.\nChunk 2: That may narrow my options down a bit Can you check That is great.\nChunk 3: I need it for Tuesday.\nChunk 4: 7 people lasting 5 nights.\nChunk 5: Yes, I would also like to find a Spanish place to eat at Surprise me!\nChunk 6: I really don't care.\nChunk 7: Great, lets set up a reservation for 7 people at 20:00 on Tuesday Thank you.\nChunk 8: That is all that I need.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; amenities: wifi; destination: provide free wifi. Next, intent: context_update. Next, day: tuesday. Next, party size: 7 people; stay length: 5 nights. Next, the topic is restaurant; destination: find a spanish place to eat at surprise m; acceptance: selected_option. Next, intent: context_update. Finally, the goal is booking; time: 7.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. hotel type: hotel; amenities: wifi; destination: provide free wifi., find a spanish place to eat at surprise m; intent: context_update.; day: tuesday.; party size: 7 people; stay length: 5 nights.; acceptance: selected_option.; time: 7.", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=wifi; destination+=provide free wifi. C2 intent=context_update. C3 day+=tuesday. C4 party_size+=7 people; stay_length+=5 nights. C5 domain=restaurant; destination+=find a spanish place to eat at surprise m; acceptance=selected_option. C6 intent=context_update. C7 goal=booking; time+=7, 20:00. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Oh I almost forgot, I also need the hotel to provide free wifi.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; amenities: wifi; destination: provide free wifi..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; amenities+=wifi; destination+=provide free wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "That may narrow my options down a bit Can you check That is great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need it for Tuesday.", "streaming_reasoning": "As more information arrives, day: tuesday..", "trace": "day+=tuesday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "7 people lasting 5 nights.", "streaming_reasoning": "As more information arrives, party size: 7 people; stay length: 5 nights..", "trace": "party_size+=7 people; stay_length+=5 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, I would also like to find a Spanish place to eat at Surprise me!", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: find a spanish place to eat at surprise m; acceptance: selected_option..", "trace": "domain=restaurant; destination+=find a spanish place to eat at surprise m; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I really don't care.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Great, lets set up a reservation for 7 people at 20:00 on Tuesday Thank you.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 7.", "trace": "goal=booking; time+=7, 20:00."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all that I need.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 7 people; stay length is 5 nights; amenities is wifi; destination is provide free wifi; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, booking; party_size=7 people; stay_length=5 nights; amenities=wifi; destination=provide free wifi, find a spanish place to eat at surprise m; when=tuesday, 7, 20:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002462", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Excellent, thank you so much.\nChunk 2: I also need a train to cambridge on sunday.\nChunk 3: actually, i'm so stupid.\nChunk 4: i need a train FROM cambridge.\nChunk 5: i'm going to broxbourne.\nChunk 6: I am leaving anytime after 11:30 from cambridge to broxbourne, what is the arrival time?\nChunk 7: No thanks, I just wanted to know the arrival time.\nChunk 8: No, You have helped with everything I needed.\nChunk 9: Thanks so much for your time.\nChunk 10: Bye.", "streaming_reasoning": "C1 intent=context_update. C2 domain=train; goal=search; day+=sunday; destination+=cambridge on sunday. C3 intent=context_update. C4 [SKIP: repeated_information]. C5 destination+=broxbourne. C6 goal=request_info; time+=11:30; departure+=cambridge. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=cambridge on sunday, broxbourne; departure=cambridge; when=sunday, 11:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Excellent, thank you so much.\nChunk 2: I also need a train to cambridge on sunday.\nChunk 3: actually, i'm so stupid.\nChunk 4: i need a train FROM cambridge.\nChunk 5: i'm going to broxbourne.\nChunk 6: I am leaving anytime after 11:30 from cambridge to broxbourne, what is the arrival time?\nChunk 7: No thanks, I just wanted to know the arrival time.\nChunk 8: No, You have helped with everything I needed.\nChunk 9: Thanks so much for your time.\nChunk 10: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 domain=train; goal=search; day+=sunday; destination+=cambridge on sunday. C3 intent=context_update. C4 [SKIP: repeated_information]. C5 destination+=broxbourne. C6 goal=request_info; time+=11:30; departure+=cambridge. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=cambridge on sunday, broxbourne; departure=cambridge; when=sunday, 11:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Excellent, thank you so much.\nChunk 2: I also need a train to cambridge on sunday.\nChunk 3: actually, i'm so stupid.\nChunk 4: i need a train FROM cambridge.\nChunk 5: i'm going to broxbourne.\nChunk 6: I am leaving anytime after 11:30 from cambridge to broxbourne, what is the arrival time?\nChunk 7: No thanks, I just wanted to know the arrival time.\nChunk 8: No, You have helped with everything I needed.\nChunk 9: Thanks so much for your time.\nChunk 10: Bye.", "input_token_count": 89, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the topic is train; the goal is search; day: sunday; destination: cambridge on sunday. Next, intent: context_update. Next, destination: broxbourne. Finally, the goal is request info; time: 11:30; departure point: cambridge.  Some chunks were skipped because they contained closing_only or repeated_information or thanks_only. In summary, The overall topic is train. the goal is request info. intent: context_update.; day: sunday; destination: cambridge on sunday., broxbourne.; time: 11:30; departure point: cambridge..", "trace": "C1 intent=context_update. C2 domain=train; goal=search; day+=sunday; destination+=cambridge on sunday. C3 intent=context_update. C4 [SKIP: repeated_information]. C5 destination+=broxbourne. C6 goal=request_info; time+=11:30; departure+=cambridge. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Excellent, thank you so much.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need a train to cambridge on sunday.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: sunday; destination: cambridge on sunday..", "trace": "domain=train; goal=search; day+=sunday; destination+=cambridge on sunday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "actually, i'm so stupid.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "i need a train FROM cambridge.", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "i'm going to broxbourne.", "streaming_reasoning": "As more information arrives, destination: broxbourne..", "trace": "destination+=broxbourne."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I am leaving anytime after 11:30 from cambridge to broxbourne, what is the arrival time?", "streaming_reasoning": "As more information arrives, the goal is request info; time: 11:30; departure point: cambridge..", "trace": "goal=request_info; time+=11:30; departure+=cambridge."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No thanks, I just wanted to know the arrival time.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, You have helped with everything I needed.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks so much for your time.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Bye.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge on sunday; departure point is cambridge; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=cambridge on sunday, broxbourne; departure=cambridge; when=sunday, 11:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002463", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'll be traveling on Monday and I would like to leave after 15:00.\nChunk 2: It doesn't matter, just so it leaves after 15:00.\nChunk 3: I'll just need the train id and arrival time please No thank you.\nChunk 4: I would like to know the arrival time, though.\nChunk 5: Thanks.\nChunk 6: Can you also find a museum?\nChunk 7: No, whatever your recommendation is.\nChunk 8: I will just need the area it's in and the entrance fee please No thanks.\nChunk 9: That gives me all I need Take care Goodbye.", "streaming_reasoning": "C1 time+=15:00; day+=monday; destination+=leave after 15:00. C2 intent=context_update. C3 domain=train; goal=search. C4 destination+=know the arrival time. C5 [SKIP: thanks_only]. C6 domain=attraction. C7 goal=modify_constraint. C8 goal=request_info; requested_info+=entrance_fee. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, attraction; goal=search, request_info; destination=leave after 15:00, know the arrival time; requested_info=entrance_fee; when=monday, 15:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'll be traveling on Monday and I would like to leave after 15:00.\nChunk 2: It doesn't matter, just so it leaves after 15:00.\nChunk 3: I'll just need the train id and arrival time please No thank you.\nChunk 4: I would like to know the arrival time, though.\nChunk 5: Thanks.\nChunk 6: Can you also find a museum?\nChunk 7: No, whatever your recommendation is.\nChunk 8: I will just need the area it's in and the entrance fee please No thanks.\nChunk 9: That gives me all I need Take care Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=15:00; day+=monday; destination+=leave after 15:00. C2 intent=context_update. C3 domain=train; goal=search. C4 destination+=know the arrival time. C5 [SKIP: thanks_only]. C6 domain=attraction. C7 goal=modify_constraint. C8 goal=request_info; requested_info+=entrance_fee. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, attraction; goal=search, request_info; destination=leave after 15:00, know the arrival time; requested_info=entrance_fee; when=monday, 15:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'll be traveling on Monday and I would like to leave after 15:00.\nChunk 2: It doesn't matter, just so it leaves after 15:00.\nChunk 3: I'll just need the train id and arrival time please No thank you.\nChunk 4: I would like to know the arrival time, though.\nChunk 5: Thanks.\nChunk 6: Can you also find a museum?\nChunk 7: No, whatever your recommendation is.\nChunk 8: I will just need the area it's in and the entrance fee please No thanks.\nChunk 9: That gives me all I need Take care Goodbye.", "input_token_count": 100, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, time: 15:00; day: monday; destination: leave after 15:00. Next, intent: context_update. Next, the topic is train; the goal is search. Next, destination: know the arrival time. Next, the topic is attraction. Next, the goal is modify constraint. Finally, the goal is request info; requested information: entrance_fee.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction.. the goal is request info. time: 15:00; day: monday; destination: leave after 15:00., know the arrival time.; intent: context_update.; requested information: entrance_fee..", "trace": "C1 time+=15:00; day+=monday; destination+=leave after 15:00. C2 intent=context_update. C3 domain=train; goal=search. C4 destination+=know the arrival time. C5 [SKIP: thanks_only]. C6 domain=attraction. C7 goal=modify_constraint. C8 goal=request_info; requested_info+=entrance_fee. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'll be traveling on Monday and I would like to leave after 15:00.", "streaming_reasoning": "Initially, time: 15:00; day: monday; destination: leave after 15:00..", "trace": "time+=15:00; day+=monday; destination+=leave after 15:00."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It doesn't matter, just so it leaves after 15:00.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'll just need the train id and arrival time please No thank you.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like to know the arrival time, though.", "streaming_reasoning": "As more information arrives, destination: know the arrival time..", "trace": "destination+=know the arrival time."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you also find a museum?", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, whatever your recommendation is.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I will just need the area it's in and the entrance fee please No thanks.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That gives me all I need Take care Goodbye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is leave after 15:00; requested information is entrance_fee; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=search, request_info; destination=leave after 15:00, know the arrival time; requested_info=entrance_fee; when=monday, 15:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002464", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like something in the north and has free wifi and free parking if possible.\nChunk 2: Can you book the Acorn Guesthouse for Thursday?\nChunk 3: Great, I need it for 5 people for 3 nights, and let me know the reference number Excellent Thank you!\nChunk 4: Actually that is all.\nChunk 5: Have a lovely day Thanks Bye now.", "streaming_reasoning": "C1 area+=north; amenities+=parking, wifi, free parking. C2 domain=hotel; goal=booking; day+=thursday; hotel_type+=guesthouse. C3 goal=request_info; party_size+=5 people; stay_length+=3 nights; requested_info+=reference_number. C4 [SKIP: closing_only]. C5 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=booking, search, request_info; area=north; party_size=5 people; stay_length=3 nights; amenities=parking, wifi, free parking; requested_info=reference_number; when=thursday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like something in the north and has free wifi and free parking if possible.\nChunk 2: Can you book the Acorn Guesthouse for Thursday?\nChunk 3: Great, I need it for 5 people for 3 nights, and let me know the reference number Excellent Thank you!\nChunk 4: Actually that is all.\nChunk 5: Have a lovely day Thanks Bye now."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=north; amenities+=parking, wifi, free parking. C2 domain=hotel; goal=booking; day+=thursday; hotel_type+=guesthouse. C3 goal=request_info; party_size+=5 people; stay_length+=3 nights; requested_info+=reference_number. C4 [SKIP: closing_only]. C5 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=booking, search, request_info; area=north; party_size=5 people; stay_length=3 nights; amenities=parking, wifi, free parking; requested_info=reference_number; when=thursday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like something in the north and has free wifi and free parking if possible.\nChunk 2: Can you book the Acorn Guesthouse for Thursday?\nChunk 3: Great, I need it for 5 people for 3 nights, and let me know the reference number Excellent Thank you!\nChunk 4: Actually that is all.\nChunk 5: Have a lovely day Thanks Bye now.", "input_token_count": 65, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: north; amenities: parking. Next, the topic is hotel; the goal is booking; day: thursday; hotel type: guesthouse. Next, the goal is request info; party size: 5 people; stay length: 3 nights; requested information: reference_number. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. area: north; amenities: parking; day: thursday; hotel type: guesthouse.; party size: 5 people; stay length: 3 nights; requested information: reference_number.; intent: context_update..", "trace": "C1 area+=north; amenities+=parking, wifi, free parking. C2 domain=hotel; goal=booking; day+=thursday; hotel_type+=guesthouse. C3 goal=request_info; party_size+=5 people; stay_length+=3 nights; requested_info+=reference_number. C4 [SKIP: closing_only]. C5 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like something in the north and has free wifi and free parking if possible.", "streaming_reasoning": "Initially, area: north; amenities: parking.", "trace": "area+=north; amenities+=parking, wifi, free parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you book the Acorn Guesthouse for Thursday?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is booking; day: thursday; hotel type: guesthouse..", "trace": "domain=hotel; goal=booking; day+=thursday; hotel_type+=guesthouse."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Great, I need it for 5 people for 3 nights, and let me know the reference number Excellent Thank you!", "streaming_reasoning": "As more information arrives, the goal is request info; party size: 5 people; stay length: 3 nights; requested information: reference_number..", "trace": "goal=request_info; party_size+=5 people; stay_length+=3 nights; requested_info+=reference_number."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Actually that is all.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Have a lovely day Thanks Bye now.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: area is north; party size is 5 people; stay length is 3 nights; amenities is parking; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, search, request_info; area=north; party_size=5 people; stay_length=3 nights; amenities=parking, wifi, free parking; requested_info=reference_number; when=thursday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002465", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any trains arriving by 15:15 on Thursday?\nChunk 2: I need to go to Broxbourne, I'll be leaving Cambridge I said Thursday.\nChunk 3: Yes please book for 8 people.\nChunk 4: I need the reference number.\nChunk 5: Also, I want information on a restaurant called Bangkok City.\nChunk 6: yes how did you know lol.\nChunk 7: Can I have their phone number please.\nChunk 8: That is all thank you goodbye.", "streaming_reasoning": "C1 time+=15:15; day+=thursday. C2 goal=search; destination+=go to broxbourne. C3 goal=confirm_booking; party_size+=8 people; goal=confirm_booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=restaurant. C6 goal=confirm_booking. C7 requested_info+=phone. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, confirm_booking, request_info; party_size=8 people; destination=go to broxbourne; requested_info=reference_number, phone; when=thursday, 15:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Are there any trains arriving by 15:15 on Thursday?\nChunk 2: I need to go to Broxbourne, I'll be leaving Cambridge I said Thursday.\nChunk 3: Yes please book for 8 people.\nChunk 4: I need the reference number.\nChunk 5: Also, I want information on a restaurant called Bangkok City.\nChunk 6: yes how did you know lol.\nChunk 7: Can I have their phone number please.\nChunk 8: That is all thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=15:15; day+=thursday. C2 goal=search; destination+=go to broxbourne. C3 goal=confirm_booking; party_size+=8 people; goal=confirm_booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=restaurant. C6 goal=confirm_booking. C7 requested_info+=phone. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, confirm_booking, request_info; party_size=8 people; destination=go to broxbourne; requested_info=reference_number, phone; when=thursday, 15:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any trains arriving by 15:15 on Thursday?\nChunk 2: I need to go to Broxbourne, I'll be leaving Cambridge I said Thursday.\nChunk 3: Yes please book for 8 people.\nChunk 4: I need the reference number.\nChunk 5: Also, I want information on a restaurant called Bangkok City.\nChunk 6: yes how did you know lol.\nChunk 7: Can I have their phone number please.\nChunk 8: That is all thank you goodbye.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 15:15; day: thursday. Next, the goal is search; destination: go to broxbourne. Next, the goal is confirm booking.; party size: 8 people. Next, the goal is request info; requested information: reference_number. Next, the topic is restaurant. Next, the goal is confirm booking. Finally, requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant.. the goal is confirm booking.. time: 15:15; day: thursday.; destination: go to broxbourne.; party size: 8 people; requested information: reference_number., phone..", "trace": "C1 time+=15:15; day+=thursday. C2 goal=search; destination+=go to broxbourne. C3 goal=confirm_booking; party_size+=8 people; goal=confirm_booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=restaurant. C6 goal=confirm_booking. C7 requested_info+=phone. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Are there any trains arriving by 15:15 on Thursday?", "streaming_reasoning": "Initially, time: 15:15; day: thursday..", "trace": "time+=15:15; day+=thursday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to go to Broxbourne, I'll be leaving Cambridge I said Thursday.", "streaming_reasoning": "As more information arrives, the goal is search; destination: go to broxbourne..", "trace": "goal=search; destination+=go to broxbourne."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes please book for 8 people.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; party size: 8 people.", "trace": "goal=confirm_booking; party_size+=8 people; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Also, I want information on a restaurant called Bangkok City.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "yes how did you know lol.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can I have their phone number please.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all thank you goodbye.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 8 people; destination is go to broxbourne; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, confirm_booking, request_info; party_size=8 people; destination=go to broxbourne; requested_info=reference_number, phone; when=thursday, 15:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002466", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i am also looking for a moderately priced restaurant that serves european food.\nChunk 2: I need one that is in the centre.\nChunk 3: Is either of those?\nChunk 4: just make sure you get phone number, postcode, and address Just for myself.\nChunk 5: Yes, that would be great.\nChunk 6: Actually, that will be all for today.\nChunk 7: You've been a great help Goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=european; price+=moderate. C2 area+=centre. C3 goal=request_info. C4 goal=request_info; requested_info+=address, phone, postcode. C5 acceptance=selected_option. C6 [SKIP: closing_only]. C7 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=centre; food=european; price=moderate; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i am also looking for a moderately priced restaurant that serves european food.\nChunk 2: I need one that is in the centre.\nChunk 3: Is either of those?\nChunk 4: just make sure you get phone number, postcode, and address Just for myself.\nChunk 5: Yes, that would be great.\nChunk 6: Actually, that will be all for today.\nChunk 7: You've been a great help Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=european; price+=moderate. C2 area+=centre. C3 goal=request_info. C4 goal=request_info; requested_info+=address, phone, postcode. C5 acceptance=selected_option. C6 [SKIP: closing_only]. C7 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=centre; food=european; price=moderate; requested_info=address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i am also looking for a moderately priced restaurant that serves european food.\nChunk 2: I need one that is in the centre.\nChunk 3: Is either of those?\nChunk 4: just make sure you get phone number, postcode, and address Just for myself.\nChunk 5: Yes, that would be great.\nChunk 6: Actually, that will be all for today.\nChunk 7: You've been a great help Goodbye.", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: european; price: moderate. Next, area: centre. Next, the goal is request info. Next, the goal is request info; requested information: address. Next, acceptance: selected_option. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. cuisine: european; price: moderate.; area: centre.; requested information: address; acceptance: selected_option.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; cuisine+=european; price+=moderate. C2 area+=centre. C3 goal=request_info. C4 goal=request_info; requested_info+=address, phone, postcode. C5 acceptance=selected_option. C6 [SKIP: closing_only]. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i am also looking for a moderately priced restaurant that serves european food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: european; price: moderate..", "trace": "domain=restaurant; goal=search; cuisine+=european; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need one that is in the centre.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Is either of those?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "just make sure you get phone number, postcode, and address Just for myself.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, that would be great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Actually, that will be all for today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "You've been a great help Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is european; price is moderate; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=centre; food=european; price=moderate; requested_info=address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002468", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to find something fun to do in the center of town.\nChunk 2: Are there any movie theaters?\nChunk 3: Can I get the address for the Cinema please?\nChunk 4: I am also looking for a train.", "streaming_reasoning": "C1 goal=search; area+=centre; destination+=find something fun to do in the center of. C2 goal=request_info. C3 goal=request_info; requested_info+=address. C4 domain=train.", "deep_reasoning": "Need domain=train; goal=search, request_info; area=centre; destination=find something fun to do in the center of; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like to find something fun to do in the center of town.\nChunk 2: Are there any movie theaters?\nChunk 3: Can I get the address for the Cinema please?\nChunk 4: I am also looking for a train."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre; destination+=find something fun to do in the center of. C2 goal=request_info. C3 goal=request_info; requested_info+=address. C4 domain=train.\n\nDeep reasoning: Need domain=train; goal=search, request_info; area=centre; destination=find something fun to do in the center of; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to find something fun to do in the center of town.\nChunk 2: Are there any movie theaters?\nChunk 3: Can I get the address for the Cinema please?\nChunk 4: I am also looking for a train.", "input_token_count": 42, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre; destination: find something fun to do in the center of. Next, the goal is request info. Next, the goal is request info; requested information: address. Finally, the topic is train. In summary, The overall topic is train.. the goal is request info. area: centre; destination: find something fun to do in the center of.; requested information: address..", "trace": "C1 goal=search; area+=centre; destination+=find something fun to do in the center of. C2 goal=request_info. C3 goal=request_info; requested_info+=address. C4 domain=train.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like to find something fun to do in the center of town.", "streaming_reasoning": "Initially, the goal is search; area: centre; destination: find something fun to do in the center of..", "trace": "goal=search; area+=centre; destination+=find something fun to do in the center of."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Are there any movie theaters?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I get the address for the Cinema please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am also looking for a train.", "streaming_reasoning": "Finally, the topic is train..", "trace": "domain=train."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is centre; destination is find something fun to do in the center of; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; area=centre; destination=find something fun to do in the center of; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002469", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: University Arms Hotel Yes thank you.\nChunk 2: 2 nights for two people starting on monday.\nChunk 3: I also need a train going to Stevenage on Tuesday.\nChunk 4: I'd like to leave after 11:45, please.\nChunk 5: I am departing from cambridge.\nChunk 6: Can you please provide me with the train id and travel time thank you.\nChunk 7: Excellent, thanks for all of your help!", "streaming_reasoning": "C1 domain=hotel; hotel_type+=hotel; acceptance=selected_option. C2 day+=monday; party_size+=2 people; stay_length+=2 nights. C3 domain=train; goal=search; day+=tuesday; destination+=stevenage on tuesday. C4 time+=11:45; destination+=leave after 11:45. C5 departure+=cambridge. C6 goal=request_info; requested_info+=travel_time. C7 intent=context_update.", "deep_reasoning": "Need domain=hotel, train; goal=search, request_info; party_size=2 people; stay_length=2 nights; destination=stevenage on tuesday, leave after 11:45; departure=cambridge; requested_info=travel_time; when=monday, tuesday, 11:45.", "answer": "I can help with that and include the travel time once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: University Arms Hotel Yes thank you.\nChunk 2: 2 nights for two people starting on monday.\nChunk 3: I also need a train going to Stevenage on Tuesday.\nChunk 4: I'd like to leave after 11:45, please.\nChunk 5: I am departing from cambridge.\nChunk 6: Can you please provide me with the train id and travel time thank you.\nChunk 7: Excellent, thanks for all of your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=hotel; acceptance=selected_option. C2 day+=monday; party_size+=2 people; stay_length+=2 nights. C3 domain=train; goal=search; day+=tuesday; destination+=stevenage on tuesday. C4 time+=11:45; destination+=leave after 11:45. C5 departure+=cambridge. C6 goal=request_info; requested_info+=travel_time. C7 intent=context_update.\n\nDeep reasoning: Need domain=hotel, train; goal=search, request_info; party_size=2 people; stay_length=2 nights; destination=stevenage on tuesday, leave after 11:45; departure=cambridge; requested_info=travel_time; when=monday, tuesday, 11:45.\n\nAnswer: I can help with that and include the travel time once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: University Arms Hotel Yes thank you.\nChunk 2: 2 nights for two people starting on monday.\nChunk 3: I also need a train going to Stevenage on Tuesday.\nChunk 4: I'd like to leave after 11:45, please.\nChunk 5: I am departing from cambridge.\nChunk 6: Can you please provide me with the train id and travel time thank you.\nChunk 7: Excellent, thanks for all of your help!", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: hotel; acceptance: selected_option. Next, day: monday; party size: 2 people; stay length: 2 nights. Next, the topic is train; the goal is search; day: tuesday; destination: stevenage on tuesday. Next, time: 11:45; destination: leave after 11:45. Next, departure point: cambridge. Next, the goal is request info; requested information: travel_time. Finally, intent: context_update. In summary, The overall topic is train. the goal is request info. hotel type: hotel; acceptance: selected_option.; day: monday, tuesday; party size: 2 people; stay length: 2 nights.; destination: stevenage on tuesday., leave after 11:45.; time: 11:45; departure point: cambridge.; requested information: travel_time.; intent: context_update..", "trace": "C1 domain=hotel; hotel_type+=hotel; acceptance=selected_option. C2 day+=monday; party_size+=2 people; stay_length+=2 nights. C3 domain=train; goal=search; day+=tuesday; destination+=stevenage on tuesday. C4 time+=11:45; destination+=leave after 11:45. C5 departure+=cambridge. C6 goal=request_info; requested_info+=travel_time. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "University Arms Hotel Yes thank you.", "streaming_reasoning": "Initially, the topic is hotel; hotel type: hotel; acceptance: selected_option..", "trace": "domain=hotel; hotel_type+=hotel; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "2 nights for two people starting on monday.", "streaming_reasoning": "As more information arrives, day: monday; party size: 2 people; stay length: 2 nights..", "trace": "day+=monday; party_size+=2 people; stay_length+=2 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need a train going to Stevenage on Tuesday.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: tuesday; destination: stevenage on tuesday..", "trace": "domain=train; goal=search; day+=tuesday; destination+=stevenage on tuesday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd like to leave after 11:45, please.", "streaming_reasoning": "As more information arrives, time: 11:45; destination: leave after 11:45..", "trace": "time+=11:45; destination+=leave after 11:45."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I am departing from cambridge.", "streaming_reasoning": "As more information arrives, departure point: cambridge..", "trace": "departure+=cambridge."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you please provide me with the train id and travel time thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Excellent, thanks for all of your help!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 2 people; stay length is 2 nights; destination is stevenage on tuesday; departure point is cambridge; requested information is travel_time; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the travel time once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel, train; goal=search, request_info; party_size=2 people; stay_length=2 nights; destination=stevenage on tuesday, leave after 11:45; departure=cambridge; requested_info=travel_time; when=monday, tuesday, 11:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002470", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should go to saigon city and should arrive by 24:45.\nChunk 3: I will be departing from parkside pools.\nChunk 4: No thank you that's all.", "streaming_reasoning": "C1 domain=taxi; goal=booking. C2 time+=24:45; destination+=saigon city and should arrive by 24:45. C3 amenities+=pool; departure+=parkside pools. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi; goal=search, booking; amenities=pool; destination=saigon city and should arrive by 24:45; departure=parkside pools; when=24:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i want to book a taxi.\nChunk 2: The taxi should go to saigon city and should arrive by 24:45.\nChunk 3: I will be departing from parkside pools.\nChunk 4: No thank you that's all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=booking. C2 time+=24:45; destination+=saigon city and should arrive by 24:45. C3 amenities+=pool; departure+=parkside pools. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi; goal=search, booking; amenities=pool; destination=saigon city and should arrive by 24:45; departure=parkside pools; when=24:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should go to saigon city and should arrive by 24:45.\nChunk 3: I will be departing from parkside pools.\nChunk 4: No thank you that's all.", "input_token_count": 39, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is booking. Next, time: 24:45; destination: saigon city and should arrive by 24:45. Finally, amenities: pool; departure point: parkside pools.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is booking.. time: 24:45; destination: saigon city and should arrive by 24:45.; amenities: pool; departure point: parkside pools..", "trace": "C1 domain=taxi; goal=booking. C2 time+=24:45; destination+=saigon city and should arrive by 24:45. C3 amenities+=pool; departure+=parkside pools. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i want to book a taxi.", "streaming_reasoning": "Initially, the topic is taxi; the goal is booking..", "trace": "domain=taxi; goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The taxi should go to saigon city and should arrive by 24:45.", "streaming_reasoning": "As more information arrives, time: 24:45; destination: saigon city and should arrive by 24:45..", "trace": "time+=24:45; destination+=saigon city and should arrive by 24:45."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I will be departing from parkside pools.", "streaming_reasoning": "As more information arrives, amenities: pool; departure point: parkside pools..", "trace": "amenities+=pool; departure+=parkside pools."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No thank you that's all.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: amenities is pool; destination is saigon city and should arrive by 24:45; departure point is parkside pools; timing is 24:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search, booking; amenities=pool; destination=saigon city and should arrive by 24:45; departure=parkside pools; when=24:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002471", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant in the centre that serves modern European food.\nChunk 2: I would like one in the expensive price range please.\nChunk 3: Do they have booking available for 7 people at 16:30 on tuesday?\nChunk 4: Is there another restaurant in the area in that price range that is available at that time No thanks.\nChunk 5: Thank you and goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=european. C2 price+=expensive. C3 goal=booking; time+=7, 16:30; day+=tuesday; party_size+=7 people. C4 goal=compare_alternative. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, compare_alternative; area=centre; food=european; price=expensive; party_size=7 people; when=tuesday, 7, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant in the centre that serves modern European food.\nChunk 2: I would like one in the expensive price range please.\nChunk 3: Do they have booking available for 7 people at 16:30 on tuesday?\nChunk 4: Is there another restaurant in the area in that price range that is available at that time No thanks.\nChunk 5: Thank you and goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; cuisine+=european. C2 price+=expensive. C3 goal=booking; time+=7, 16:30; day+=tuesday; party_size+=7 people. C4 goal=compare_alternative. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, compare_alternative; area=centre; food=european; price=expensive; party_size=7 people; when=tuesday, 7, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant in the centre that serves modern European food.\nChunk 2: I would like one in the expensive price range please.\nChunk 3: Do they have booking available for 7 people at 16:30 on tuesday?\nChunk 4: Is there another restaurant in the area in that price range that is available at that time No thanks.\nChunk 5: Thank you and goodbye.", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: european. Next, price: expensive. Next, the goal is booking; time: 7; day: tuesday; party size: 7 people. Finally, the goal is compare alternative.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is compare alternative.. area: centre; cuisine: european.; price: expensive.; time: 7; day: tuesday; party size: 7 people..", "trace": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=european. C2 price+=expensive. C3 goal=booking; time+=7, 16:30; day+=tuesday; party_size+=7 people. C4 goal=compare_alternative. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant in the centre that serves modern European food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: european..", "trace": "domain=restaurant; goal=search; area+=centre; cuisine+=european."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like one in the expensive price range please.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Do they have booking available for 7 people at 16:30 on tuesday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 7; day: tuesday; party size: 7 people..", "trace": "goal=booking; time+=7, 16:30; day+=tuesday; party_size+=7 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is there another restaurant in the area in that price range that is available at that time No thanks.", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you and goodbye.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is european; price is expensive; party size is 7 people; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, compare_alternative; area=centre; food=european; price=expensive; party_size=7 people; when=tuesday, 7, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003108", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would you allow me to drive your car?\nChunk 2: No problem, but you've got to be careful Surely I will.", "streaming_reasoning": "C1 question=true. C2 safety_reminder=true.", "deep_reasoning": "Conversation is closing with a safety reminder; answer politely and acknowledge caution.", "answer": "Thanks, I'll be careful. See you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Would you allow me to drive your car?\nChunk 2: No problem, but you've got to be careful Surely I will."}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 safety_reminder=true.\n\nDeep reasoning: Conversation is closing with a safety reminder; answer politely and acknowledge caution.\n\nAnswer: Thanks, I'll be careful. See you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would you allow me to drive your car?\nChunk 2: No problem, but you've got to be careful Surely I will.", "input_token_count": 23, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Finally, safety reminder: true. In summary, safety reminder: true..", "trace": "C1 question=true. C2 safety_reminder=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Would you allow me to drive your car?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No problem, but you've got to be careful Surely I will.", "streaming_reasoning": "Finally, safety reminder: true..", "trace": "safety_reminder=true."}]}, "output": {"deep_reasoning": "Conversation is closing with a safety reminder; answer politely and acknowledge caution.", "answer": "Thanks, I'll be careful. See you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002473", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you find me a restaurant in the centre with moderate prices Surprise me.\nChunk 2: Yes please book a table for 7 people at 15:45 on monday.\nChunk 3: I need help with taxi.\nChunk 4: The time is 12:00.\nChunk 5: Please make a booking.\nChunk 6: I will need 7 tickets.\nChunk 7: And can you please provide me with the reference number please Thank you.\nChunk 8: That is all for now.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 goal=confirm_booking; time+=7, 15:45; day+=monday; party_size+=7 people; goal=confirm_booking. C3 domain=taxi. C4 time+=12:00. C5 intent=context_update. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi; goal=search, booking, confirm_booking, request_info; area=centre; price=moderate; party_size=7 people; requested_info=reference_number; when=monday, 7, 15:45, 12:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you find me a restaurant in the centre with moderate prices Surprise me.\nChunk 2: Yes please book a table for 7 people at 15:45 on monday.\nChunk 3: I need help with taxi.\nChunk 4: The time is 12:00.\nChunk 5: Please make a booking.\nChunk 6: I will need 7 tickets.\nChunk 7: And can you please provide me with the reference number please Thank you.\nChunk 8: That is all for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 goal=confirm_booking; time+=7, 15:45; day+=monday; party_size+=7 people; goal=confirm_booking. C3 domain=taxi. C4 time+=12:00. C5 intent=context_update. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi; goal=search, booking, confirm_booking, request_info; area=centre; price=moderate; party_size=7 people; requested_info=reference_number; when=monday, 7, 15:45, 12:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you find me a restaurant in the centre with moderate prices Surprise me.\nChunk 2: Yes please book a table for 7 people at 15:45 on monday.\nChunk 3: I need help with taxi.\nChunk 4: The time is 12:00.\nChunk 5: Please make a booking.\nChunk 6: I will need 7 tickets.\nChunk 7: And can you please provide me with the reference number please Thank you.\nChunk 8: That is all for now.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: moderate. Next, the goal is confirm booking.; time: 7; day: monday; party size: 7 people. Next, the topic is taxi. Next, time: 12:00. Next, intent: context_update. Next, intent: context_update. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi.. the goal is request info. area: centre; price: moderate.; time: 7, 12:00.; day: monday; party size: 7 people; intent: context_update.; requested information: reference_number..", "trace": "C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 goal=confirm_booking; time+=7, 15:45; day+=monday; party_size+=7 people; goal=confirm_booking. C3 domain=taxi. C4 time+=12:00. C5 intent=context_update. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you find me a restaurant in the centre with moderate prices Surprise me.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: moderate..", "trace": "domain=restaurant; goal=search; area+=centre; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes please book a table for 7 people at 15:45 on monday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 7; day: monday; party size: 7 people.", "trace": "goal=confirm_booking; time+=7, 15:45; day+=monday; party_size+=7 people; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need help with taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is 12:00.", "streaming_reasoning": "As more information arrives, time: 12:00..", "trace": "time+=12:00."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I will need 7 tickets.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "And can you please provide me with the reference number please Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all for now.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is moderate; party size is 7 people; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi; goal=search, booking, confirm_booking, request_info; area=centre; price=moderate; party_size=7 people; requested_info=reference_number; when=monday, 7, 15:45, 12:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002474", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a train from broxbourne.\nChunk 2: Yes, I'd like to leave for cambridge after 13:30 on sunday That sounds great.\nChunk 3: I'll need 7 tickets.\nChunk 4: Yeah, can to tell me about colleges in the centre of town it doesn't matter.\nChunk 5: could you provide the postcode, phone number, and address for one that you suggest?\nChunk 6: That should be it for today thanks!", "streaming_reasoning": "C1 domain=train; goal=search. C2 time+=13:30; day+=sunday; destination+=leave for cambridge after 13:30 on sunday; acceptance=selected_option. C3 intent=context_update. C4 goal=request_info; area+=centre; destination+=tell me about colleges in the centre of t. C5 goal=recommendation; requested_info+=address, phone, postcode. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info, recommendation; area=centre; destination=leave for cambridge after 13:30 on sunday, tell me about colleges in the centre of t; requested_info=address, phone, postcode; when=sunday, 13:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a train from broxbourne.\nChunk 2: Yes, I'd like to leave for cambridge after 13:30 on sunday That sounds great.\nChunk 3: I'll need 7 tickets.\nChunk 4: Yeah, can to tell me about colleges in the centre of town it doesn't matter.\nChunk 5: could you provide the postcode, phone number, and address for one that you suggest?\nChunk 6: That should be it for today thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 time+=13:30; day+=sunday; destination+=leave for cambridge after 13:30 on sunday; acceptance=selected_option. C3 intent=context_update. C4 goal=request_info; area+=centre; destination+=tell me about colleges in the centre of t. C5 goal=recommendation; requested_info+=address, phone, postcode. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info, recommendation; area=centre; destination=leave for cambridge after 13:30 on sunday, tell me about colleges in the centre of t; requested_info=address, phone, postcode; when=sunday, 13:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a train from broxbourne.\nChunk 2: Yes, I'd like to leave for cambridge after 13:30 on sunday That sounds great.\nChunk 3: I'll need 7 tickets.\nChunk 4: Yeah, can to tell me about colleges in the centre of town it doesn't matter.\nChunk 5: could you provide the postcode, phone number, and address for one that you suggest?\nChunk 6: That should be it for today thanks!", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, time: 13:30; day: sunday; destination: leave for cambridge after 13:30 on sunday; acceptance: selected_option. Next, intent: context_update. Next, the goal is request info; area: centre; destination: tell me about colleges in the centre of t. Finally, the goal is recommendation; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is recommendation. time: 13:30; day: sunday; destination: leave for cambridge after 13:30 on sunday, tell me about colleges in the centre of t.; acceptance: selected_option.; intent: context_update.; area: centre; requested information: address.", "trace": "C1 domain=train; goal=search. C2 time+=13:30; day+=sunday; destination+=leave for cambridge after 13:30 on sunday; acceptance=selected_option. C3 intent=context_update. C4 goal=request_info; area+=centre; destination+=tell me about colleges in the centre of t. C5 goal=recommendation; requested_info+=address, phone, postcode. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a train from broxbourne.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I'd like to leave for cambridge after 13:30 on sunday That sounds great.", "streaming_reasoning": "As more information arrives, time: 13:30; day: sunday; destination: leave for cambridge after 13:30 on sunday; acceptance: selected_option..", "trace": "time+=13:30; day+=sunday; destination+=leave for cambridge after 13:30 on sunday; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'll need 7 tickets.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yeah, can to tell me about colleges in the centre of town it doesn't matter.", "streaming_reasoning": "As more information arrives, the goal is request info; area: centre; destination: tell me about colleges in the centre of t..", "trace": "goal=request_info; area+=centre; destination+=tell me about colleges in the centre of t."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "could you provide the postcode, phone number, and address for one that you suggest?", "streaming_reasoning": "As more information arrives, the goal is recommendation; requested information: address.", "trace": "goal=recommendation; requested_info+=address, phone, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That should be it for today thanks!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is centre; destination is leave for cambridge after 13:30 on sunday; requested information is address; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, recommendation; area=centre; destination=leave for cambridge after 13:30 on sunday, tell me about colleges in the centre of t; requested_info=address, phone, postcode; when=sunday, 13:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003113", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Did you check before you left the shop Yes, I did.\nChunk 2: But when I got home, my son put it on and we found the hole Really?\nChunk 3: Let me have a look at it Mm.\nChunk 4: OK.\nChunk 5: Let me change it for another one.\nChunk 6: Thank you very much.\nChunk 7: Thanks for your hospitality.", "streaming_reasoning": "C1 casual_comment=did, check. C2 question=true. C3 casual_comment=let, look. C4 [SKIP: backchannel_only]. C5 casual_comment=let, change. C6 [SKIP: thanks_only]. C7 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Did you check before you left the shop Yes, I did.\nChunk 2: But when I got home, my son put it on and we found the hole Really?\nChunk 3: Let me have a look at it Mm.\nChunk 4: OK.\nChunk 5: Let me change it for another one.\nChunk 6: Thank you very much.\nChunk 7: Thanks for your hospitality."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=did, check. C2 question=true. C3 casual_comment=let, look. C4 [SKIP: backchannel_only]. C5 casual_comment=let, change. C6 [SKIP: thanks_only]. C7 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Did you check before you left the shop Yes, I did.\nChunk 2: But when I got home, my son put it on and we found the hole Really?\nChunk 3: Let me have a look at it Mm.\nChunk 4: OK.\nChunk 5: Let me change it for another one.\nChunk 6: Thank you very much.\nChunk 7: Thanks for your hospitality.", "input_token_count": 65, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on did. Next, the input provides additional context about question=true. Next, the user comments on let. Finally, the user comments on let.  Some chunks were skipped because they contained backchannel_only or thanks_only.", "trace": "C1 casual_comment=did, check. C2 question=true. C3 casual_comment=let, look. C4 [SKIP: backchannel_only]. C5 casual_comment=let, change. C6 [SKIP: thanks_only]. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Did you check before you left the shop Yes, I did.", "streaming_reasoning": "Initially, the user comments on did.", "trace": "casual_comment=did, check."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "But when I got home, my son put it on and we found the hole Really?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Let me have a look at it Mm.", "streaming_reasoning": "As more information arrives, the user comments on let.", "trace": "casual_comment=let, look."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "OK.", "streaming_reasoning": "The content at C4 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Let me change it for another one.", "streaming_reasoning": "As more information arrives, the user comments on let.", "trace": "casual_comment=let, change."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks for your hospitality.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002475", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a train into Cambridge that will arrive by 09:15.\nChunk 2: I will be leaving the Stansted Airport on Thursday.\nChunk 3: Book it for 3 people.\nChunk 4: I need to find a place to stay as well Can you help?", "streaming_reasoning": "C1 domain=train; goal=search; time+=09:15; destination+=find a train into cambridge that will arr. C2 day+=thursday. C3 goal=booking; party_size+=3 people. C4 domain=hotel.", "deep_reasoning": "Need domain=train, hotel; goal=search, booking; party_size=3 people; destination=find a train into cambridge that will arr; when=thursday, 09:15.", "answer": "What area, price range should I use for the search?", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to find a train into Cambridge that will arrive by 09:15.\nChunk 2: I will be leaving the Stansted Airport on Thursday.\nChunk 3: Book it for 3 people.\nChunk 4: I need to find a place to stay as well Can you help?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; time+=09:15; destination+=find a train into cambridge that will arr. C2 day+=thursday. C3 goal=booking; party_size+=3 people. C4 domain=hotel.\n\nDeep reasoning: Need domain=train, hotel; goal=search, booking; party_size=3 people; destination=find a train into cambridge that will arr; when=thursday, 09:15.\n\nAnswer: What area, price range should I use for the search?"}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a train into Cambridge that will arrive by 09:15.\nChunk 2: I will be leaving the Stansted Airport on Thursday.\nChunk 3: Book it for 3 people.\nChunk 4: I need to find a place to stay as well Can you help?", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 09:15; destination: find a train into cambridge that will arr. Next, day: thursday. Next, the goal is booking; party size: 3 people. Finally, the topic is hotel. In summary, The overall topic is hotel.. the goal is booking. time: 09:15; destination: find a train into cambridge that will arr.; day: thursday.; party size: 3 people..", "trace": "C1 domain=train; goal=search; time+=09:15; destination+=find a train into cambridge that will arr. C2 day+=thursday. C3 goal=booking; party_size+=3 people. C4 domain=hotel.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to find a train into Cambridge that will arrive by 09:15.", "streaming_reasoning": "Initially, the topic is train; the goal is search; time: 09:15; destination: find a train into cambridge that will arr..", "trace": "domain=train; goal=search; time+=09:15; destination+=find a train into cambridge that will arr."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be leaving the Stansted Airport on Thursday.", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Book it for 3 people.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 3 people..", "trace": "goal=booking; party_size+=3 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to find a place to stay as well Can you help?", "streaming_reasoning": "Finally, the topic is hotel..", "trace": "domain=hotel."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 3 people; destination is find a train into cambridge that will arr; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "What area, price range should I use for the search?", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, booking; party_size=3 people; destination=find a train into cambridge that will arr; when=thursday, 09:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001655", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My cat dissapeared after 14 years one day.\nChunk 2: He never came back.\nChunk 3: My first cat disaapeared 2 years ago after 14 years with him That's so sad.\nChunk 4: I just had a cat disappear, it's quite sad.\nChunk 5: Yea they like to leave when they are dying to try and heal but it is very depressing when they are just gone.", "streaming_reasoning": "C1 cause=14 years one day; need=encouragement. C2 support_signal=received. C3 emotion=sad; cause=14 years with him That's so; need=validation. C4 emotion=sad; cause=I just had a cat disappear, it's quite. C5 need=encouragement.", "deep_reasoning": "User feels sad after I just had a cat disappear, it's quite and needs encouragement.", "answer": "It makes sense to feel sad after I just had a cat disappear, it's quite. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: My cat dissapeared after 14 years one day.\nChunk 2: He never came back.\nChunk 3: My first cat disaapeared 2 years ago after 14 years with him That's so sad.\nChunk 4: I just had a cat disappear, it's quite sad.\nChunk 5: Yea they like to leave when they are dying to try and heal but it is very depressing when they are just gone."}, {"role": "assistant", "content": "Streaming reasoning: C1 cause=14 years one day; need=encouragement. C2 support_signal=received. C3 emotion=sad; cause=14 years with him That's so; need=validation. C4 emotion=sad; cause=I just had a cat disappear, it's quite. C5 need=encouragement.\n\nDeep reasoning: User feels sad after I just had a cat disappear, it's quite and needs encouragement.\n\nAnswer: It makes sense to feel sad after I just had a cat disappear, it's quite. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My cat dissapeared after 14 years one day.\nChunk 2: He never came back.\nChunk 3: My first cat disaapeared 2 years ago after 14 years with him That's so sad.\nChunk 4: I just had a cat disappear, it's quite sad.\nChunk 5: Yea they like to leave when they are dying to try and heal but it is very depressing when they are just gone.", "input_token_count": 69, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user mentions 14 years one day; the user needs encouragement. Next, the user signals support or acknowledgment. Next, the user expresses sad about 14 years with him That's so; the user needs validation. Next, the user expresses sad about I just had a cat disappear. Finally, the user needs encouragement.", "trace": "C1 cause=14 years one day; need=encouragement. C2 support_signal=received. C3 emotion=sad; cause=14 years with him That's so; need=validation. C4 emotion=sad; cause=I just had a cat disappear, it's quite. C5 need=encouragement.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "My cat dissapeared after 14 years one day.", "streaming_reasoning": "Initially, the user mentions 14 years one day; the user needs encouragement..", "trace": "cause=14 years one day; need=encouragement."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "He never came back.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "My first cat disaapeared 2 years ago after 14 years with him That's so sad.", "streaming_reasoning": "As more information arrives, the user expresses sad about 14 years with him That's so; the user needs validation..", "trace": "emotion=sad; cause=14 years with him That's so; need=validation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I just had a cat disappear, it's quite sad.", "streaming_reasoning": "As more information arrives, the user expresses sad about I just had a cat disappear.", "trace": "emotion=sad; cause=I just had a cat disappear, it's quite."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yea they like to leave when they are dying to try and heal but it is very depressing when they are just gone.", "streaming_reasoning": "Finally, the user needs encouragement..", "trace": "need=encouragement."}]}, "output": {"deep_reasoning": "User feels sad after I just had a cat disappear, it's quite and needs encouragement.", "answer": "It makes sense to feel sad after I just had a cat disappear, it's quite. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002476", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a cheap restaurant in the east part of town, please.\nChunk 2: Address and phone number, please.\nChunk 3: thank you good bye.\nChunk 4: Thanks so much Bye bye.", "streaming_reasoning": "C1 domain=restaurant; area+=east; price+=cheap. C2 goal=request_info; requested_info+=address, phone. C3 [SKIP: thanks_only]. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=request_info; area=east; price=cheap; requested_info=address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a cheap restaurant in the east part of town, please.\nChunk 2: Address and phone number, please.\nChunk 3: thank you good bye.\nChunk 4: Thanks so much Bye bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=east; price+=cheap. C2 goal=request_info; requested_info+=address, phone. C3 [SKIP: thanks_only]. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=request_info; area=east; price=cheap; requested_info=address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a cheap restaurant in the east part of town, please.\nChunk 2: Address and phone number, please.\nChunk 3: thank you good bye.\nChunk 4: Thanks so much Bye bye.", "input_token_count": 35, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: east; price: cheap. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: east; price: cheap.; requested information: address.", "trace": "C1 domain=restaurant; area+=east; price+=cheap. C2 goal=request_info; requested_info+=address, phone. C3 [SKIP: thanks_only]. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a cheap restaurant in the east part of town, please.", "streaming_reasoning": "Initially, the topic is restaurant; area: east; price: cheap..", "trace": "domain=restaurant; area+=east; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Address and phone number, please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "thank you good bye.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks so much Bye bye.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is east; price is cheap; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info; area=east; price=cheap; requested_info=address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000510", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Organize Pok•mon Cards.\nChunk 2: • Pok•mon cards • Storage container (like a binder, box, or catalog) • Card holder inserts (for binder; 2.5 in.\nChunk 3: (64mm by 89mm)) • Individual card sleeves (optional).", "streaming_reasoning": "C1 task=organize_pok_mon_cards. C2 step=pok_mon_cards_storage. C3 step=64mm_by_89mm_individual.", "deep_reasoning": "Procedure for Organize Pok mon Cards: Pok mon cards Storage container Card holder inserts (for binder;, ) Individual card sleeves.", "answer": "For Organize Pok mon Cards, follow the steps in order: Pok mon cards Storage container Card holder inserts (for binder;, ) Individual card sleeves.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Organize Pok•mon Cards.\nChunk 2: • Pok•mon cards • Storage container (like a binder, box, or catalog) • Card holder inserts (for binder; 2.5 in.\nChunk 3: (64mm by 89mm)) • Individual card sleeves (optional)."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=organize_pok_mon_cards. C2 step=pok_mon_cards_storage. C3 step=64mm_by_89mm_individual.\n\nDeep reasoning: Procedure for Organize Pok mon Cards: Pok mon cards Storage container Card holder inserts (for binder;, ) Individual card sleeves.\n\nAnswer: For Organize Pok mon Cards, follow the steps in order: Pok mon cards Storage container Card holder inserts (for binder;, ) Individual card sleeves."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Organize Pok•mon Cards.\nChunk 2: • Pok•mon cards • Storage container (like a binder, box, or catalog) • Card holder inserts (for binder; 2.5 in.\nChunk 3: (64mm by 89mm)) • Individual card sleeves (optional).", "input_token_count": 37, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, task: organize_pok_mon_cards. Next, step: pok_mon_cards_storage. Finally, step: 64mm_by_89mm_individual. In summary, task: organize_pok_mon_cards.; step: pok_mon_cards_storage., 64mm_by_89mm_individual..", "trace": "C1 task=organize_pok_mon_cards. C2 step=pok_mon_cards_storage. C3 step=64mm_by_89mm_individual.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Organize Pok•mon Cards.", "streaming_reasoning": "Initially, task: organize_pok_mon_cards..", "trace": "task=organize_pok_mon_cards."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• Pok•mon cards • Storage container (like a binder, box, or catalog) • Card holder inserts (for binder; 2.5 in.", "streaming_reasoning": "As more information arrives, step: pok_mon_cards_storage..", "trace": "step=pok_mon_cards_storage."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "(64mm by 89mm)) • Individual card sleeves (optional).", "streaming_reasoning": "Finally, step: 64mm_by_89mm_individual..", "trace": "step=64mm_by_89mm_individual."}]}, "output": {"deep_reasoning": "Procedure for Organize Pok mon Cards: Pok mon cards Storage container Card holder inserts (for binder;, ) Individual card sleeves.", "answer": "For Organize Pok mon Cards, follow the steps in order: Pok mon cards Storage container Card holder inserts (for binder;, ) Individual card sleeves."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003114", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I don't know where that is.\nChunk 2: The office is in front of you as you cross the quad.\nChunk 3: The signs in the hallway will tell you where you need to be.\nChunk 4: I think I can find it.\nChunk 5: You'll find it easily.\nChunk 6: Make sure you add the class and then we will look at the roll sheet later to make sure that you were added on.\nChunk 7: Thank you for letting me add your class.", "streaming_reasoning": "C1 casual_comment=don't. C2 casual_comment=office, front. C3 casual_comment=signs, hallway. C4 casual_comment=think, find. C5 casual_comment=you'll, find. C6 casual_comment=make, add. C7 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, I don't know where that is.\nChunk 2: The office is in front of you as you cross the quad.\nChunk 3: The signs in the hallway will tell you where you need to be.\nChunk 4: I think I can find it.\nChunk 5: You'll find it easily.\nChunk 6: Make sure you add the class and then we will look at the roll sheet later to make sure that you were added on.\nChunk 7: Thank you for letting me add your class."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=don't. C2 casual_comment=office, front. C3 casual_comment=signs, hallway. C4 casual_comment=think, find. C5 casual_comment=you'll, find. C6 casual_comment=make, add. C7 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I don't know where that is.\nChunk 2: The office is in front of you as you cross the quad.\nChunk 3: The signs in the hallway will tell you where you need to be.\nChunk 4: I think I can find it.\nChunk 5: You'll find it easily.\nChunk 6: Make sure you add the class and then we will look at the roll sheet later to make sure that you were added on.\nChunk 7: Thank you for letting me add your class.", "input_token_count": 88, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on don't. Next, the user comments on office. Next, the user comments on signs. Next, the user comments on think. Next, the user comments on you'll. Finally, the user comments on make.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=don't. C2 casual_comment=office, front. C3 casual_comment=signs, hallway. C4 casual_comment=think, find. C5 casual_comment=you'll, find. C6 casual_comment=make, add. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, I don't know where that is.", "streaming_reasoning": "Initially, the user comments on don't..", "trace": "casual_comment=don't."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The office is in front of you as you cross the quad.", "streaming_reasoning": "As more information arrives, the user comments on office.", "trace": "casual_comment=office, front."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The signs in the hallway will tell you where you need to be.", "streaming_reasoning": "As more information arrives, the user comments on signs.", "trace": "casual_comment=signs, hallway."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I think I can find it.", "streaming_reasoning": "As more information arrives, the user comments on think.", "trace": "casual_comment=think, find."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "You'll find it easily.", "streaming_reasoning": "As more information arrives, the user comments on you'll.", "trace": "casual_comment=you'll, find."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Make sure you add the class and then we will look at the roll sheet later to make sure that you were added on.", "streaming_reasoning": "As more information arrives, the user comments on make.", "trace": "casual_comment=make, add."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for letting me add your class.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002477", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should go to little saint mary's church and should leave after 05:45.\nChunk 3: I am departing from el shaddai.\nChunk 4: Can you provide me with what car will be picking me up and contact number Thank you.\nChunk 5: I think that is all I need today.", "streaming_reasoning": "C1 domain=taxi; goal=booking. C2 time+=05:45; destination+=little saint mary's church and should lea. C3 departure+=el shaddai. C4 intent=context_update. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi; goal=search, booking; destination=little saint mary's church and should lea; departure=el shaddai; when=05:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i want to book a taxi.\nChunk 2: The taxi should go to little saint mary's church and should leave after 05:45.\nChunk 3: I am departing from el shaddai.\nChunk 4: Can you provide me with what car will be picking me up and contact number Thank you.\nChunk 5: I think that is all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=booking. C2 time+=05:45; destination+=little saint mary's church and should lea. C3 departure+=el shaddai. C4 intent=context_update. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi; goal=search, booking; destination=little saint mary's church and should lea; departure=el shaddai; when=05:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should go to little saint mary's church and should leave after 05:45.\nChunk 3: I am departing from el shaddai.\nChunk 4: Can you provide me with what car will be picking me up and contact number Thank you.\nChunk 5: I think that is all I need today.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is booking. Next, time: 05:45; destination: little saint mary's church and should lea. Next, departure point: el shaddai. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is booking.. time: 05:45; destination: little saint mary's church and should lea.; departure point: el shaddai.; intent: context_update..", "trace": "C1 domain=taxi; goal=booking. C2 time+=05:45; destination+=little saint mary's church and should lea. C3 departure+=el shaddai. C4 intent=context_update. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i want to book a taxi.", "streaming_reasoning": "Initially, the topic is taxi; the goal is booking..", "trace": "domain=taxi; goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The taxi should go to little saint mary's church and should leave after 05:45.", "streaming_reasoning": "As more information arrives, time: 05:45; destination: little saint mary's church and should lea..", "trace": "time+=05:45; destination+=little saint mary's church and should lea."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am departing from el shaddai.", "streaming_reasoning": "As more information arrives, departure point: el shaddai..", "trace": "departure+=el shaddai."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you provide me with what car will be picking me up and contact number Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I think that is all I need today.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is little saint mary's church and should lea; departure point is el shaddai; timing is 05:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search, booking; destination=little saint mary's church and should lea; departure=el shaddai; when=05:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002478", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, no other preferences.\nChunk 2: What would you recommend?\nChunk 3: I prefer something a little more south.\nChunk 4: Ok, can you send me the address and area of Aylesbray lodge?\nChunk 5: I am also looking for a restaurant called royal spice.\nChunk 6: I'd like to book table at the royal spice for 6 people at 19:45 Tuesday.\nChunk 7: I want to find a guesthouse.\nChunk 8: The time is tuesday, 19:45.\nChunk 9: Please make a booking.\nChunk 10: No that's all I need Thank you!", "streaming_reasoning": "C1 goal=modify_constraint. C2 goal=recommendation. C3 area+=south. C4 goal=request_info; requested_info+=address. C5 domain=restaurant; goal=search. C6 goal=booking; time+=6, 19:45; day+=tuesday; party_size+=6 people. C7 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C8 intent=context_update. C9 intent=context_update. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel; goal=recommendation, request_info, search, booking; area=south; party_size=6 people; destination=find a guesthouse; requested_info=address; when=tuesday, 6, 19:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, no other preferences.\nChunk 2: What would you recommend?\nChunk 3: I prefer something a little more south.\nChunk 4: Ok, can you send me the address and area of Aylesbray lodge?\nChunk 5: I am also looking for a restaurant called royal spice.\nChunk 6: I'd like to book table at the royal spice for 6 people at 19:45 Tuesday.\nChunk 7: I want to find a guesthouse.\nChunk 8: The time is tuesday, 19:45.\nChunk 9: Please make a booking.\nChunk 10: No that's all I need Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=modify_constraint. C2 goal=recommendation. C3 area+=south. C4 goal=request_info; requested_info+=address. C5 domain=restaurant; goal=search. C6 goal=booking; time+=6, 19:45; day+=tuesday; party_size+=6 people. C7 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C8 intent=context_update. C9 intent=context_update. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel; goal=recommendation, request_info, search, booking; area=south; party_size=6 people; destination=find a guesthouse; requested_info=address; when=tuesday, 6, 19:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, no other preferences.\nChunk 2: What would you recommend?\nChunk 3: I prefer something a little more south.\nChunk 4: Ok, can you send me the address and area of Aylesbray lodge?\nChunk 5: I am also looking for a restaurant called royal spice.\nChunk 6: I'd like to book table at the royal spice for 6 people at 19:45 Tuesday.\nChunk 7: I want to find a guesthouse.\nChunk 8: The time is tuesday, 19:45.\nChunk 9: Please make a booking.\nChunk 10: No that's all I need Thank you!", "input_token_count": 96, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is modify constraint. Next, the goal is recommendation. Next, area: south. Next, the goal is request info; requested information: address. Next, the topic is restaurant; the goal is search. Next, the goal is booking; time: 6; day: tuesday; party size: 6 people. Next, the topic is hotel; hotel type: guesthouse; destination: find a guesthouse. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking. area: south.; requested information: address.; time: 6; day: tuesday; party size: 6 people.; hotel type: guesthouse; destination: find a guesthouse.; intent: context_update..", "trace": "C1 goal=modify_constraint. C2 goal=recommendation. C3 area+=south. C4 goal=request_info; requested_info+=address. C5 domain=restaurant; goal=search. C6 goal=booking; time+=6, 19:45; day+=tuesday; party_size+=6 people. C7 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C8 intent=context_update. C9 intent=context_update. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, no other preferences.", "streaming_reasoning": "Initially, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What would you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I prefer something a little more south.", "streaming_reasoning": "As more information arrives, area: south..", "trace": "area+=south."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Ok, can you send me the address and area of Aylesbray lodge?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I am also looking for a restaurant called royal spice.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'd like to book table at the royal spice for 6 people at 19:45 Tuesday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 6; day: tuesday; party size: 6 people..", "trace": "goal=booking; time+=6, 19:45; day+=tuesday; party_size+=6 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I want to find a guesthouse.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse; destination: find a guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "The time is tuesday, 19:45.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "No that's all I need Thank you!", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: area is south; party size is 6 people; destination is find a guesthouse; requested information is address; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=recommendation, request_info, search, booking; area=south; party_size=6 people; destination=find a guesthouse; requested_info=address; when=tuesday, 6, 19:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003120", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That's all right, I'm a beginner.\nChunk 2: I've just learnt how to play.\nChunk 3: Look, there's a chessboard.\nChunk 4: Those two men have already finished playing.\nChunk 5: You're a very good player.\nChunk 6: Not really, but once I won a prize So did I.\nChunk 7: I won a prize last week but it was a prize for beginners.", "streaming_reasoning": "C1 [SKIP: closing_only]. C2 casual_comment=i've, learnt. C3 casual_comment=look, there's. C4 casual_comment=those, two. C5 casual_comment=you're, very. C6 casual_comment=not, once. C7 casual_comment=won, prize.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: That's all right, I'm a beginner.\nChunk 2: I've just learnt how to play.\nChunk 3: Look, there's a chessboard.\nChunk 4: Those two men have already finished playing.\nChunk 5: You're a very good player.\nChunk 6: Not really, but once I won a prize So did I.\nChunk 7: I won a prize last week but it was a prize for beginners."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: closing_only]. C2 casual_comment=i've, learnt. C3 casual_comment=look, there's. C4 casual_comment=those, two. C5 casual_comment=you're, very. C6 casual_comment=not, once. C7 casual_comment=won, prize.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That's all right, I'm a beginner.\nChunk 2: I've just learnt how to play.\nChunk 3: Look, there's a chessboard.\nChunk 4: Those two men have already finished playing.\nChunk 5: You're a very good player.\nChunk 6: Not really, but once I won a prize So did I.\nChunk 7: I won a prize last week but it was a prize for beginners.", "input_token_count": 66, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on i've. Next, the user comments on look. Next, the user comments on those. Next, the user comments on you're. Next, the user comments on not. Finally, the user comments on won.  Some chunks were skipped because they contained closing_only.", "trace": "C1 [SKIP: closing_only]. C2 casual_comment=i've, learnt. C3 casual_comment=look, there's. C4 casual_comment=those, two. C5 casual_comment=you're, very. C6 casual_comment=not, once. C7 casual_comment=won, prize.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "That's all right, I'm a beginner.", "streaming_reasoning": "The content at C1 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I've just learnt how to play.", "streaming_reasoning": "As more information arrives, the user comments on i've.", "trace": "casual_comment=i've, learnt."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Look, there's a chessboard.", "streaming_reasoning": "As more information arrives, the user comments on look.", "trace": "casual_comment=look, there's."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Those two men have already finished playing.", "streaming_reasoning": "As more information arrives, the user comments on those.", "trace": "casual_comment=those, two."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "You're a very good player.", "streaming_reasoning": "As more information arrives, the user comments on you're.", "trace": "casual_comment=you're, very."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Not really, but once I won a prize So did I.", "streaming_reasoning": "As more information arrives, the user comments on not.", "trace": "casual_comment=not, once."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I won a prize last week but it was a prize for beginners.", "streaming_reasoning": "Finally, the user comments on won.", "trace": "casual_comment=won, prize."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002479", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: The east is OK, is that one a guesthouse style Oh well then.\nChunk 2: Can I ask what 4 star guesthouses with free parking are around?\nChunk 3: Alright, let's go with Rosa's Bed and Breakfast then, that's a guesthouse at least?\nChunk 4: I would like the reservation for 2 nights starting Tuesday.\nChunk 5: It will be for 8 people.\nChunk 6: That's all I needed Thank you Thank you.\nChunk 7: Have a good day.", "streaming_reasoning": "C1 domain=hotel; area+=east; hotel_type+=guesthouse. C2 goal=request_info; stars+=4 stars; amenities+=parking, free parking. C3 domain=restaurant; amenities+=breakfast. C4 goal=booking; time+=2; day+=tuesday; stay_length+=2 nights. C5 party_size+=8 people. C6 [SKIP: closing_only]. C7 intent=context_update.", "deep_reasoning": "Need domain=hotel, restaurant; goal=request_info, booking; area=east; party_size=8 people; stay_length=2 nights; stars=4 stars; amenities=parking, free parking, breakfast; when=tuesday, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: The east is OK, is that one a guesthouse style Oh well then.\nChunk 2: Can I ask what 4 star guesthouses with free parking are around?\nChunk 3: Alright, let's go with Rosa's Bed and Breakfast then, that's a guesthouse at least?\nChunk 4: I would like the reservation for 2 nights starting Tuesday.\nChunk 5: It will be for 8 people.\nChunk 6: That's all I needed Thank you Thank you.\nChunk 7: Have a good day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; area+=east; hotel_type+=guesthouse. C2 goal=request_info; stars+=4 stars; amenities+=parking, free parking. C3 domain=restaurant; amenities+=breakfast. C4 goal=booking; time+=2; day+=tuesday; stay_length+=2 nights. C5 party_size+=8 people. C6 [SKIP: closing_only]. C7 intent=context_update.\n\nDeep reasoning: Need domain=hotel, restaurant; goal=request_info, booking; area=east; party_size=8 people; stay_length=2 nights; stars=4 stars; amenities=parking, free parking, breakfast; when=tuesday, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: The east is OK, is that one a guesthouse style Oh well then.\nChunk 2: Can I ask what 4 star guesthouses with free parking are around?\nChunk 3: Alright, let's go with Rosa's Bed and Breakfast then, that's a guesthouse at least?\nChunk 4: I would like the reservation for 2 nights starting Tuesday.\nChunk 5: It will be for 8 people.\nChunk 6: That's all I needed Thank you Thank you.\nChunk 7: Have a good day.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; area: east; hotel type: guesthouse. Next, the goal is request info; star rating: 4 stars; amenities: parking. Next, the topic is restaurant; amenities: breakfast. Next, the goal is booking; time: 2; day: tuesday; stay length: 2 nights. Next, party size: 8 people. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. area: east; hotel type: guesthouse.; star rating: 4 stars; amenities: parking, breakfast.; time: 2; day: tuesday; stay length: 2 nights.; party size: 8 people.; intent: context_update..", "trace": "C1 domain=hotel; area+=east; hotel_type+=guesthouse. C2 goal=request_info; stars+=4 stars; amenities+=parking, free parking. C3 domain=restaurant; amenities+=breakfast. C4 goal=booking; time+=2; day+=tuesday; stay_length+=2 nights. C5 party_size+=8 people. C6 [SKIP: closing_only]. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "The east is OK, is that one a guesthouse style Oh well then.", "streaming_reasoning": "Initially, the topic is hotel; area: east; hotel type: guesthouse..", "trace": "domain=hotel; area+=east; hotel_type+=guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I ask what 4 star guesthouses with free parking are around?", "streaming_reasoning": "As more information arrives, the goal is request info; star rating: 4 stars; amenities: parking.", "trace": "goal=request_info; stars+=4 stars; amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Alright, let's go with Rosa's Bed and Breakfast then, that's a guesthouse at least?", "streaming_reasoning": "As more information arrives, the topic is restaurant; amenities: breakfast..", "trace": "domain=restaurant; amenities+=breakfast."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like the reservation for 2 nights starting Tuesday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 2; day: tuesday; stay length: 2 nights..", "trace": "goal=booking; time+=2; day+=tuesday; stay_length+=2 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It will be for 8 people.", "streaming_reasoning": "As more information arrives, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all I needed Thank you Thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a good day.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: area is east; party size is 8 people; stay length is 2 nights; star rating is 4 stars; amenities is parking; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=request_info, booking; area=east; party_size=8 people; stay_length=2 nights; stars=4 stars; amenities=parking, free parking, breakfast; when=tuesday, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002480", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a police station in Parkside.\nChunk 2: No.\nChunk 3: That's all I wanted to know.\nChunk 4: Thanks.", "streaming_reasoning": "C1 domain=train; goal=search. C2 [SKIP: acknowledgement_only]. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a police station in Parkside.\nChunk 2: No.\nChunk 3: That's all I wanted to know.\nChunk 4: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 [SKIP: acknowledgement_only]. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["too_many_skips"], "version": "v0.4.1", "quality_score": 0.95, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a police station in Parkside.\nChunk 2: No.\nChunk 3: That's all I wanted to know.\nChunk 4: Thanks.", "input_token_count": 25, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search.  Some chunks were skipped because they contained acknowledgement_only or closing_only or thanks_only. In summary, The overall topic is train. the goal is search..", "trace": "C1 domain=train; goal=search. C2 [SKIP: acknowledgement_only]. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a police station in Parkside.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No.", "streaming_reasoning": "The content at C2 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That's all I wanted to know.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need domain=train; goal=search; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 0.95, "quality_flags": ["too_many_skips"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002481", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a table for 2 at 13:45 Monday.\nChunk 2: Could you try one of those different places?\nChunk 3: I really need that day and time.\nChunk 4: How about on Wednesday, the same time for 2?\nChunk 5: I'm also needing a train that departs from Norwich and goes to Cambridge.\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 10:45.\nChunk 8: Please make a booking.\nChunk 9: Thank you so much Goodbye.", "streaming_reasoning": "C1 time+=2, 13:45; day+=monday. C2 goal=compare_alternative. C3 goal=search. C4 goal=recommendation; day+=wednesday. C5 domain=train; destination+=cambridge; departure+=norwich and goes. C6 domain=restaurant; destination+=find a restaurant. C7 time+=10:45. C8 goal=booking. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, restaurant; goal=compare_alternative, search, recommendation, booking; destination=cambridge, find a restaurant; departure=norwich and goes; when=monday, wednesday, 2, 13:45, 10:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a table for 2 at 13:45 Monday.\nChunk 2: Could you try one of those different places?\nChunk 3: I really need that day and time.\nChunk 4: How about on Wednesday, the same time for 2?\nChunk 5: I'm also needing a train that departs from Norwich and goes to Cambridge.\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 10:45.\nChunk 8: Please make a booking.\nChunk 9: Thank you so much Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=2, 13:45; day+=monday. C2 goal=compare_alternative. C3 goal=search. C4 goal=recommendation; day+=wednesday. C5 domain=train; destination+=cambridge; departure+=norwich and goes. C6 domain=restaurant; destination+=find a restaurant. C7 time+=10:45. C8 goal=booking. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=compare_alternative, search, recommendation, booking; destination=cambridge, find a restaurant; departure=norwich and goes; when=monday, wednesday, 2, 13:45, 10:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a table for 2 at 13:45 Monday.\nChunk 2: Could you try one of those different places?\nChunk 3: I really need that day and time.\nChunk 4: How about on Wednesday, the same time for 2?\nChunk 5: I'm also needing a train that departs from Norwich and goes to Cambridge.\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 10:45.\nChunk 8: Please make a booking.\nChunk 9: Thank you so much Goodbye.", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 2; day: monday. Next, the goal is compare alternative. Next, the goal is search. Next, the goal is recommendation; day: wednesday. Next, the topic is train; destination: cambridge; departure point: norwich and goes. Next, the topic is restaurant; destination: find a restaurant. Next, time: 10:45. Finally, the goal is booking.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is booking.. time: 2, 10:45.; day: monday., wednesday.; destination: cambridge, find a restaurant.; departure point: norwich and goes..", "trace": "C1 time+=2, 13:45; day+=monday. C2 goal=compare_alternative. C3 goal=search. C4 goal=recommendation; day+=wednesday. C5 domain=train; destination+=cambridge; departure+=norwich and goes. C6 domain=restaurant; destination+=find a restaurant. C7 time+=10:45. C8 goal=booking. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a table for 2 at 13:45 Monday.", "streaming_reasoning": "Initially, time: 2; day: monday..", "trace": "time+=2, 13:45; day+=monday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Could you try one of those different places?", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I really need that day and time.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "How about on Wednesday, the same time for 2?", "streaming_reasoning": "As more information arrives, the goal is recommendation; day: wednesday..", "trace": "goal=recommendation; day+=wednesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm also needing a train that departs from Norwich and goes to Cambridge.", "streaming_reasoning": "As more information arrives, the topic is train; destination: cambridge; departure point: norwich and goes..", "trace": "domain=train; destination+=cambridge; departure+=norwich and goes."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: find a restaurant..", "trace": "domain=restaurant; destination+=find a restaurant."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 10:45.", "streaming_reasoning": "As more information arrives, time: 10:45..", "trace": "time+=10:45."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you so much Goodbye.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of compare alternative. Key information: destination is cambridge; departure point is norwich and goes; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=compare_alternative, search, recommendation, booking; destination=cambridge, find a restaurant; departure=norwich and goes; when=monday, wednesday, 2, 13:45, 10:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002482", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sala Thong sounds good.\nChunk 2: Please make a booking for 2 at 11:45 on Monday.\nChunk 3: yeah i need a train too.\nChunk 4: I'll need to arrive by 11:00 and it should be going to london liverpool street.\nChunk 5: Let's pick something arriving between 11:00 and 10:30.\nChunk 6: It needs to depart from cambridge and leave on tuesday.\nChunk 7: I would like 2 tickets please.\nChunk 8: Thank you so much.\nChunk 9: The restaurant and train are all I need for now.\nChunk 10: Have a great day Goodbye.", "streaming_reasoning": "C1 acceptance=selected_option. C2 goal=booking; time+=2, 11:45; day+=monday. C3 domain=train; goal=search. C4 time+=11:00; amenities+=pool; destination+=arrive by 11:00 and it should be going to. C5 time+=10:30. C6 day+=tuesday; departure+=cambridge and leave on tuesday. C7 intent=context_update. C8 [SKIP: thanks_only]. C9 domain=restaurant. C10 intent=context_update.", "deep_reasoning": "Need domain=train, restaurant; goal=booking, search; amenities=pool; destination=arrive by 11:00 and it should be going to; departure=cambridge and leave on tuesday; when=monday, tuesday, 2, 11:45, 11:00, 10:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sala Thong sounds good.\nChunk 2: Please make a booking for 2 at 11:45 on Monday.\nChunk 3: yeah i need a train too.\nChunk 4: I'll need to arrive by 11:00 and it should be going to london liverpool street.\nChunk 5: Let's pick something arriving between 11:00 and 10:30.\nChunk 6: It needs to depart from cambridge and leave on tuesday.\nChunk 7: I would like 2 tickets please.\nChunk 8: Thank you so much.\nChunk 9: The restaurant and train are all I need for now.\nChunk 10: Have a great day Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 acceptance=selected_option. C2 goal=booking; time+=2, 11:45; day+=monday. C3 domain=train; goal=search. C4 time+=11:00; amenities+=pool; destination+=arrive by 11:00 and it should be going to. C5 time+=10:30. C6 day+=tuesday; departure+=cambridge and leave on tuesday. C7 intent=context_update. C8 [SKIP: thanks_only]. C9 domain=restaurant. C10 intent=context_update.\n\nDeep reasoning: Need domain=train, restaurant; goal=booking, search; amenities=pool; destination=arrive by 11:00 and it should be going to; departure=cambridge and leave on tuesday; when=monday, tuesday, 2, 11:45, 11:00, 10:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sala Thong sounds good.\nChunk 2: Please make a booking for 2 at 11:45 on Monday.\nChunk 3: yeah i need a train too.\nChunk 4: I'll need to arrive by 11:00 and it should be going to london liverpool street.\nChunk 5: Let's pick something arriving between 11:00 and 10:30.\nChunk 6: It needs to depart from cambridge and leave on tuesday.\nChunk 7: I would like 2 tickets please.\nChunk 8: Thank you so much.\nChunk 9: The restaurant and train are all I need for now.\nChunk 10: Have a great day Goodbye.", "input_token_count": 102, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, acceptance: selected_option. Next, the goal is booking; time: 2; day: monday. Next, the topic is train; the goal is search. Next, time: 11:00; amenities: pool; destination: arrive by 11:00 and it should be going to. Next, time: 10:30. Next, day: tuesday; departure point: cambridge and leave on tuesday. Next, intent: context_update. Next, the topic is restaurant. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant.. the goal is search.. acceptance: selected_option.; time: 2, 11:00, 10:30.; day: monday., tuesday; amenities: pool; destination: arrive by 11:00 and it should be going to.; departure point: cambridge and leave on tuesday.; intent: context_update..", "trace": "C1 acceptance=selected_option. C2 goal=booking; time+=2, 11:45; day+=monday. C3 domain=train; goal=search. C4 time+=11:00; amenities+=pool; destination+=arrive by 11:00 and it should be going to. C5 time+=10:30. C6 day+=tuesday; departure+=cambridge and leave on tuesday. C7 intent=context_update. C8 [SKIP: thanks_only]. C9 domain=restaurant. C10 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sala Thong sounds good.", "streaming_reasoning": "Initially, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Please make a booking for 2 at 11:45 on Monday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 2; day: monday..", "trace": "goal=booking; time+=2, 11:45; day+=monday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "yeah i need a train too.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll need to arrive by 11:00 and it should be going to london liverpool street.", "streaming_reasoning": "As more information arrives, time: 11:00; amenities: pool; destination: arrive by 11:00 and it should be going to..", "trace": "time+=11:00; amenities+=pool; destination+=arrive by 11:00 and it should be going to."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Let's pick something arriving between 11:00 and 10:30.", "streaming_reasoning": "As more information arrives, time: 10:30..", "trace": "time+=10:30."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It needs to depart from cambridge and leave on tuesday.", "streaming_reasoning": "As more information arrives, day: tuesday; departure point: cambridge and leave on tuesday..", "trace": "day+=tuesday; departure+=cambridge and leave on tuesday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I would like 2 tickets please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you so much.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "The restaurant and train are all I need for now.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Have a great day Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: amenities is pool; destination is arrive by 11:00 and it should be going to; departure point is cambridge and leave on tuesday; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=booking, search; amenities=pool; destination=arrive by 11:00 and it should be going to; departure=cambridge and leave on tuesday; when=monday, tuesday, 2, 11:45, 11:00, 10:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002484", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for a particular restaurant named Bedouin Can you help?\nChunk 2: Can you book me a table for 3 people at 20:00 on Wednesday?\nChunk 3: Great, thank you so much.\nChunk 4: That'll be all for today.\nChunk 5: Bye!", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 goal=booking; time+=3, 20:00; day+=wednesday; party_size+=3 people. C3 intent=context_update. C4 day+=today. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking; party_size=3 people; when=wednesday, today, 3, 20:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I'm looking for a particular restaurant named Bedouin Can you help?\nChunk 2: Can you book me a table for 3 people at 20:00 on Wednesday?\nChunk 3: Great, thank you so much.\nChunk 4: That'll be all for today.\nChunk 5: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 goal=booking; time+=3, 20:00; day+=wednesday; party_size+=3 people. C3 intent=context_update. C4 day+=today. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking; party_size=3 people; when=wednesday, today, 3, 20:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for a particular restaurant named Bedouin Can you help?\nChunk 2: Can you book me a table for 3 people at 20:00 on Wednesday?\nChunk 3: Great, thank you so much.\nChunk 4: That'll be all for today.\nChunk 5: Bye!", "input_token_count": 47, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, the goal is booking; time: 3; day: wednesday; party size: 3 people. Next, intent: context_update. Finally, day: today.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. time: 3; day: wednesday, today.; party size: 3 people.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search. C2 goal=booking; time+=3, 20:00; day+=wednesday; party_size+=3 people. C3 intent=context_update. C4 day+=today. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I'm looking for a particular restaurant named Bedouin Can you help?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you book me a table for 3 people at 20:00 on Wednesday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 3; day: wednesday; party size: 3 people..", "trace": "goal=booking; time+=3, 20:00; day+=wednesday; party_size+=3 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Great, thank you so much.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That'll be all for today.", "streaming_reasoning": "As more information arrives, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Bye!", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 3 people; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking; party_size=3 people; when=wednesday, today, 3, 20:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002485", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant serving basque food.\nChunk 2: I don't care about the price range yes, international food I don't care.\nChunk 3: Can I have the address please Thank you, goodbye Goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant serving basque food. C2 acceptance=selected_option. C3 goal=request_info; requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; destination=find a restaurant serving basque food; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a restaurant serving basque food.\nChunk 2: I don't care about the price range yes, international food I don't care.\nChunk 3: Can I have the address please Thank you, goodbye Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant serving basque food. C2 acceptance=selected_option. C3 goal=request_info; requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; destination=find a restaurant serving basque food; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant serving basque food.\nChunk 2: I don't care about the price range yes, international food I don't care.\nChunk 3: Can I have the address please Thank you, goodbye Goodbye.", "input_token_count": 38, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant serving basque food. Next, acceptance: selected_option. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. destination: find a restaurant serving basque food.; acceptance: selected_option.; requested information: address..", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant serving basque food. C2 acceptance=selected_option. C3 goal=request_info; requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a restaurant serving basque food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant serving basque food..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant serving basque food."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I don't care about the price range yes, international food I don't care.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I have the address please Thank you, goodbye Goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: destination is find a restaurant serving basque food; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; destination=find a restaurant serving basque food; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002486", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm trying to find a restaurant called The Slug and Lettuce.\nChunk 2: Do you know where that is?\nChunk 3: I'd like to book it for 3 people at 16:45 on Saturday.\nChunk 4: Could I get a reference number please?", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant called the slug and let. C2 goal=request_info. C3 goal=booking; time+=3, 16:45; day+=saturday; party_size+=3 people. C4 goal=request_info; requested_info+=reference_number.", "deep_reasoning": "Need domain=restaurant; goal=search, booking, request_info; party_size=3 people; destination=find a restaurant called the slug and let; requested_info=reference_number; when=saturday, 3, 16:45.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm trying to find a restaurant called The Slug and Lettuce.\nChunk 2: Do you know where that is?\nChunk 3: I'd like to book it for 3 people at 16:45 on Saturday.\nChunk 4: Could I get a reference number please?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant called the slug and let. C2 goal=request_info. C3 goal=booking; time+=3, 16:45; day+=saturday; party_size+=3 people. C4 goal=request_info; requested_info+=reference_number.\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, request_info; party_size=3 people; destination=find a restaurant called the slug and let; requested_info=reference_number; when=saturday, 3, 16:45.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm trying to find a restaurant called The Slug and Lettuce.\nChunk 2: Do you know where that is?\nChunk 3: I'd like to book it for 3 people at 16:45 on Saturday.\nChunk 4: Could I get a reference number please?", "input_token_count": 45, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant called the slug and let. Next, the goal is request info. Next, the goal is booking; time: 3; day: saturday; party size: 3 people. Finally, the goal is request info; requested information: reference_number. In summary, The overall topic is restaurant. the goal is request info. destination: find a restaurant called the slug and let.; time: 3; day: saturday; party size: 3 people.; requested information: reference_number..", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant called the slug and let. C2 goal=request_info. C3 goal=booking; time+=3, 16:45; day+=saturday; party_size+=3 people. C4 goal=request_info; requested_info+=reference_number.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm trying to find a restaurant called The Slug and Lettuce.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant called the slug and let..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant called the slug and let."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do you know where that is?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'd like to book it for 3 people at 16:45 on Saturday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 3; day: saturday; party size: 3 people..", "trace": "goal=booking; time+=3, 16:45; day+=saturday; party_size+=3 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could I get a reference number please?", "streaming_reasoning": "Finally, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 3 people; destination is find a restaurant called the slug and let; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, request_info; party_size=3 people; destination=find a restaurant called the slug and let; requested_info=reference_number; when=saturday, 3, 16:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002487", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No preference.\nChunk 2: Which one do you recommend?\nChunk 3: Thanks, I'm also looking for a train to cambridge departing birmingham new street.\nChunk 4: i want to leave friday, after 10.\nChunk 5: I will be going to cambridge.\nChunk 6: Yes, could you please book that for me.\nChunk 7: I need one ticket.\nChunk 8: That is all, have a great day.", "streaming_reasoning": "C1 goal=modify_constraint. C2 goal=recommendation. C3 domain=train; goal=search; destination+=cambridge departing birmingham new street. C4 time+=10; day+=friday; destination+=leave friday. C5 destination+=cambridge. C6 goal=confirm_booking; goal=confirm_booking. C7 intent=context_update. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=recommendation, search, booking, confirm_booking; destination=cambridge departing birmingham new street, leave friday, cambridge; when=friday, 10; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No preference.\nChunk 2: Which one do you recommend?\nChunk 3: Thanks, I'm also looking for a train to cambridge departing birmingham new street.\nChunk 4: i want to leave friday, after 10.\nChunk 5: I will be going to cambridge.\nChunk 6: Yes, could you please book that for me.\nChunk 7: I need one ticket.\nChunk 8: That is all, have a great day."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=modify_constraint. C2 goal=recommendation. C3 domain=train; goal=search; destination+=cambridge departing birmingham new street. C4 time+=10; day+=friday; destination+=leave friday. C5 destination+=cambridge. C6 goal=confirm_booking; goal=confirm_booking. C7 intent=context_update. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=recommendation, search, booking, confirm_booking; destination=cambridge departing birmingham new street, leave friday, cambridge; when=friday, 10; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No preference.\nChunk 2: Which one do you recommend?\nChunk 3: Thanks, I'm also looking for a train to cambridge departing birmingham new street.\nChunk 4: i want to leave friday, after 10.\nChunk 5: I will be going to cambridge.\nChunk 6: Yes, could you please book that for me.\nChunk 7: I need one ticket.\nChunk 8: That is all, have a great day.", "input_token_count": 68, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is modify constraint. Next, the goal is recommendation. Next, the topic is train; the goal is search; destination: cambridge departing birmingham new street. Next, time: 10; day: friday; destination: leave friday. Next, destination: cambridge. Next, the goal is confirm booking. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is confirm booking.. destination: cambridge departing birmingham new street., leave friday., cambridge.; time: 10; day: friday; intent: context_update..", "trace": "C1 goal=modify_constraint. C2 goal=recommendation. C3 domain=train; goal=search; destination+=cambridge departing birmingham new street. C4 time+=10; day+=friday; destination+=leave friday. C5 destination+=cambridge. C6 goal=confirm_booking; goal=confirm_booking. C7 intent=context_update. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No preference.", "streaming_reasoning": "Initially, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Which one do you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks, I'm also looking for a train to cambridge departing birmingham new street.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; destination: cambridge departing birmingham new street..", "trace": "domain=train; goal=search; destination+=cambridge departing birmingham new street."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "i want to leave friday, after 10.", "streaming_reasoning": "As more information arrives, time: 10; day: friday; destination: leave friday..", "trace": "time+=10; day+=friday; destination+=leave friday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will be going to cambridge.", "streaming_reasoning": "As more information arrives, destination: cambridge..", "trace": "destination+=cambridge."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, could you please book that for me.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need one ticket.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all, have a great day.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of recommendation. Key information: destination is cambridge departing birmingham new street; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=recommendation, search, booking, confirm_booking; destination=cambridge departing birmingham new street, leave friday, cambridge; when=friday, 10; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002488", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a italian restaurant.\nChunk 2: It should be in the south part of town That doesn't matter.\nChunk 3: Could you recommend something Sounds good.\nChunk 4: I need to book a reservation for 3 people.\nChunk 5: I need to book a table for the same group of people at 21:00 on the same day Great Thank you!\nChunk 6: Nope, that's all I needed Goodbye!", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=italian; destination+=find a italian restaurant. C2 area+=south. C3 goal=recommendation; acceptance=selected_option. C4 goal=booking; party_size+=3 people. C5 time+=21:00. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, booking; area=south; food=italian; party_size=3 people; destination=find a italian restaurant; when=21:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a italian restaurant.\nChunk 2: It should be in the south part of town That doesn't matter.\nChunk 3: Could you recommend something Sounds good.\nChunk 4: I need to book a reservation for 3 people.\nChunk 5: I need to book a table for the same group of people at 21:00 on the same day Great Thank you!\nChunk 6: Nope, that's all I needed Goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=italian; destination+=find a italian restaurant. C2 area+=south. C3 goal=recommendation; acceptance=selected_option. C4 goal=booking; party_size+=3 people. C5 time+=21:00. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, booking; area=south; food=italian; party_size=3 people; destination=find a italian restaurant; when=21:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a italian restaurant.\nChunk 2: It should be in the south part of town That doesn't matter.\nChunk 3: Could you recommend something Sounds good.\nChunk 4: I need to book a reservation for 3 people.\nChunk 5: I need to book a table for the same group of people at 21:00 on the same day Great Thank you!\nChunk 6: Nope, that's all I needed Goodbye!", "input_token_count": 74, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: italian; destination: find a italian restaurant. Next, area: south. Next, the goal is recommendation; acceptance: selected_option. Next, the goal is booking; party size: 3 people. Finally, time: 21:00.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. cuisine: italian; destination: find a italian restaurant.; area: south.; acceptance: selected_option.; party size: 3 people.; time: 21:00..", "trace": "C1 domain=restaurant; goal=search; cuisine+=italian; destination+=find a italian restaurant. C2 area+=south. C3 goal=recommendation; acceptance=selected_option. C4 goal=booking; party_size+=3 people. C5 time+=21:00. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a italian restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: italian; destination: find a italian restaurant..", "trace": "domain=restaurant; goal=search; cuisine+=italian; destination+=find a italian restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the south part of town That doesn't matter.", "streaming_reasoning": "As more information arrives, area: south..", "trace": "area+=south."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Could you recommend something Sounds good.", "streaming_reasoning": "As more information arrives, the goal is recommendation; acceptance: selected_option..", "trace": "goal=recommendation; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to book a reservation for 3 people.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 3 people..", "trace": "goal=booking; party_size+=3 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need to book a table for the same group of people at 21:00 on the same day Great Thank you!", "streaming_reasoning": "As more information arrives, time: 21:00..", "trace": "time+=21:00."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Nope, that's all I needed Goodbye!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; cuisine is italian; party size is 3 people; destination is find a italian restaurant; timing is 21:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, booking; area=south; food=italian; party_size=3 people; destination=find a italian restaurant; when=21:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002489", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: what are the two expensive indian restaurants?\nChunk 2: Could you please book a table at Sitar Tandoori for 4 people on Sunday?\nChunk 3: I would like the booking to be for 13:00.\nChunk 4: That's okay, maybe 12:00 will work Try that please?\nChunk 5: I want to find a restaurant.\nChunk 6: Please make a booking.\nChunk 7: Thank you for all your help.\nChunk 8: I have all the information I need Goodbye.", "streaming_reasoning": "C1 cuisine+=indian; price+=expensive. C2 goal=booking; time+=4; day+=sunday; party_size+=4 people. C3 time+=13:00; destination+=be for 13:00. C4 time+=12:00. C5 domain=restaurant; goal=search; destination+=find a restaurant. C6 intent=context_update. C7 [SKIP: thanks_only]. C8 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=booking, search; food=indian; price=expensive; party_size=4 people; destination=be for 13:00, find a restaurant; when=sunday, 4, 13:00, 12:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: what are the two expensive indian restaurants?\nChunk 2: Could you please book a table at Sitar Tandoori for 4 people on Sunday?\nChunk 3: I would like the booking to be for 13:00.\nChunk 4: That's okay, maybe 12:00 will work Try that please?\nChunk 5: I want to find a restaurant.\nChunk 6: Please make a booking.\nChunk 7: Thank you for all your help.\nChunk 8: I have all the information I need Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 cuisine+=indian; price+=expensive. C2 goal=booking; time+=4; day+=sunday; party_size+=4 people. C3 time+=13:00; destination+=be for 13:00. C4 time+=12:00. C5 domain=restaurant; goal=search; destination+=find a restaurant. C6 intent=context_update. C7 [SKIP: thanks_only]. C8 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=booking, search; food=indian; price=expensive; party_size=4 people; destination=be for 13:00, find a restaurant; when=sunday, 4, 13:00, 12:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: what are the two expensive indian restaurants?\nChunk 2: Could you please book a table at Sitar Tandoori for 4 people on Sunday?\nChunk 3: I would like the booking to be for 13:00.\nChunk 4: That's okay, maybe 12:00 will work Try that please?\nChunk 5: I want to find a restaurant.\nChunk 6: Please make a booking.\nChunk 7: Thank you for all your help.\nChunk 8: I have all the information I need Goodbye.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, cuisine: indian; price: expensive. Next, the goal is booking; time: 4; day: sunday; party size: 4 people. Next, time: 13:00; destination: be for 13:00. Next, time: 12:00. Next, the topic is restaurant; the goal is search; destination: find a restaurant. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is search. cuisine: indian; price: expensive.; time: 4, 13:00, 12:00.; day: sunday; party size: 4 people.; destination: be for 13:00., find a restaurant.; intent: context_update..", "trace": "C1 cuisine+=indian; price+=expensive. C2 goal=booking; time+=4; day+=sunday; party_size+=4 people. C3 time+=13:00; destination+=be for 13:00. C4 time+=12:00. C5 domain=restaurant; goal=search; destination+=find a restaurant. C6 intent=context_update. C7 [SKIP: thanks_only]. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "what are the two expensive indian restaurants?", "streaming_reasoning": "Initially, cuisine: indian; price: expensive..", "trace": "cuisine+=indian; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Could you please book a table at Sitar Tandoori for 4 people on Sunday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 4; day: sunday; party size: 4 people..", "trace": "goal=booking; time+=4; day+=sunday; party_size+=4 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like the booking to be for 13:00.", "streaming_reasoning": "As more information arrives, time: 13:00; destination: be for 13:00..", "trace": "time+=13:00; destination+=be for 13:00."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That's okay, maybe 12:00 will work Try that please?", "streaming_reasoning": "As more information arrives, time: 12:00..", "trace": "time+=12:00."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; destination: find a restaurant..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I have all the information I need Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: cuisine is indian; price is expensive; party size is 4 people; destination is be for 13:00; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=booking, search; food=indian; price=expensive; party_size=4 people; destination=be for 13:00, find a restaurant; when=sunday, 4, 13:00, 12:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002490", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am interested in a restaurant located in the north part of town that specializes in Indonesian food, please.\nChunk 2: what about italian food?\nChunk 3: Yes, may I have the address and phone number please thank you, goodbye.\nChunk 4: Bye.", "streaming_reasoning": "C1 domain=restaurant; area+=north. C2 goal=recommendation; cuisine+=italian. C3 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=recommendation, request_info; area=north; food=italian; requested_info=address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am interested in a restaurant located in the north part of town that specializes in Indonesian food, please.\nChunk 2: what about italian food?\nChunk 3: Yes, may I have the address and phone number please thank you, goodbye.\nChunk 4: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=north. C2 goal=recommendation; cuisine+=italian. C3 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=recommendation, request_info; area=north; food=italian; requested_info=address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am interested in a restaurant located in the north part of town that specializes in Indonesian food, please.\nChunk 2: what about italian food?\nChunk 3: Yes, may I have the address and phone number please thank you, goodbye.\nChunk 4: Bye.", "input_token_count": 45, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: north. Next, the goal is recommendation; cuisine: italian. Finally, the goal is request info; requested information: address; acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. area: north.; cuisine: italian.; requested information: address; acceptance: selected_option..", "trace": "C1 domain=restaurant; area+=north. C2 goal=recommendation; cuisine+=italian. C3 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am interested in a restaurant located in the north part of town that specializes in Indonesian food, please.", "streaming_reasoning": "Initially, the topic is restaurant; area: north..", "trace": "domain=restaurant; area+=north."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "what about italian food?", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: italian..", "trace": "goal=recommendation; cuisine+=italian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, may I have the address and phone number please thank you, goodbye.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=address, phone; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Bye.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: area is north; cuisine is italian; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=recommendation, request_info; area=north; food=italian; requested_info=address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002491", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Arrive by 10:30 in London Kings Cross.\nChunk 2: Yes please bookm it for me and I need the departure time Just one please.\nChunk 3: I also need a college to go to in the west That sounds great!\nChunk 4: What is their address Thank you!\nChunk 5: That will be all.", "streaming_reasoning": "C1 time+=10:30. C2 goal=confirm_booking; acceptance=selected_option. C3 domain=attraction; area+=west; destination+=go to in the west that sounds great!. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction; goal=search, confirm_booking, request_info; area=west; destination=go to in the west that sounds great!; requested_info=address; when=10:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Arrive by 10:30 in London Kings Cross.\nChunk 2: Yes please bookm it for me and I need the departure time Just one please.\nChunk 3: I also need a college to go to in the west That sounds great!\nChunk 4: What is their address Thank you!\nChunk 5: That will be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=10:30. C2 goal=confirm_booking; acceptance=selected_option. C3 domain=attraction; area+=west; destination+=go to in the west that sounds great!. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction; goal=search, confirm_booking, request_info; area=west; destination=go to in the west that sounds great!; requested_info=address; when=10:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Arrive by 10:30 in London Kings Cross.\nChunk 2: Yes please bookm it for me and I need the departure time Just one please.\nChunk 3: I also need a college to go to in the west That sounds great!\nChunk 4: What is their address Thank you!\nChunk 5: That will be all.", "input_token_count": 57, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 10:30. Next, the goal is confirm booking; acceptance: selected_option. Next, the topic is attraction; area: west; destination: go to in the west that sounds great!. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is request info. time: 10:30.; acceptance: selected_option.; area: west; destination: go to in the west that sounds great!.; requested information: address..", "trace": "C1 time+=10:30. C2 goal=confirm_booking; acceptance=selected_option. C3 domain=attraction; area+=west; destination+=go to in the west that sounds great!. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Arrive by 10:30 in London Kings Cross.", "streaming_reasoning": "Initially, time: 10:30..", "trace": "time+=10:30."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes please bookm it for me and I need the departure time Just one please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking; acceptance: selected_option..", "trace": "goal=confirm_booking; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need a college to go to in the west That sounds great!", "streaming_reasoning": "As more information arrives, the topic is attraction; area: west; destination: go to in the west that sounds great!..", "trace": "domain=attraction; area+=west; destination+=go to in the west that sounds great!."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is their address Thank you!", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That will be all.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is west; destination is go to in the west that sounds great!; requested information is address; timing is 10:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, confirm_booking, request_info; area=west; destination=go to in the west that sounds great!; requested_info=address; when=10:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002492", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you find me something cheap in the south part of town?\nChunk 2: I do not care about the type of food.\nChunk 3: Is there anything else?\nChunk 4: What is the address Thanks, good bye.", "streaming_reasoning": "C1 goal=search; area+=south; price+=cheap. C2 domain=restaurant. C3 goal=compare_alternative. C4 goal=request_info; requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=search, compare_alternative, request_info; area=south; price=cheap; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you find me something cheap in the south part of town?\nChunk 2: I do not care about the type of food.\nChunk 3: Is there anything else?\nChunk 4: What is the address Thanks, good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=south; price+=cheap. C2 domain=restaurant. C3 goal=compare_alternative. C4 goal=request_info; requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=search, compare_alternative, request_info; area=south; price=cheap; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you find me something cheap in the south part of town?\nChunk 2: I do not care about the type of food.\nChunk 3: Is there anything else?\nChunk 4: What is the address Thanks, good bye.", "input_token_count": 40, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: south; price: cheap. Next, the topic is restaurant. Next, the goal is compare alternative. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant.. the goal is request info. area: south; price: cheap.; requested information: address..", "trace": "C1 goal=search; area+=south; price+=cheap. C2 domain=restaurant. C3 goal=compare_alternative. C4 goal=request_info; requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you find me something cheap in the south part of town?", "streaming_reasoning": "Initially, the goal is search; area: south; price: cheap..", "trace": "goal=search; area+=south; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I do not care about the type of food.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Is there anything else?", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is the address Thanks, good bye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; price is cheap; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, compare_alternative, request_info; area=south; price=cheap; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002493", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please do and send me the reference number.\nChunk 2: I need it for 7 people for 3 nights starting on friday please.\nChunk 3: Can you also provide the address to an attraction in the town centre?\nChunk 4: I need help with taxi.\nChunk 5: The time is 21:30.\nChunk 6: My destination will be going from the Castle Galleries and going back to the Alexander bed and breakfast.\nChunk 7: That is all I need today Thank you.", "streaming_reasoning": "C1 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C2 goal=search; time+=7, 3; day+=friday; party_size+=7 people; stay_length+=3 nights. C3 domain=attraction; area+=centre; destination+=an attraction in the town centre; requested_info+=address. C4 domain=taxi. C5 time+=21:30. C6 domain=restaurant; amenities+=breakfast; destination+=the alexander bed and breakfast; departure+=the castle galleries and. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, taxi, restaurant; goal=request_info, search; area=centre; party_size=7 people; stay_length=3 nights; amenities=breakfast; destination=an attraction in the town centre, the alexander bed and breakfast; departure=the castle galleries and; requested_info=reference_number, address; when=friday, 7, 3, 21:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please do and send me the reference number.\nChunk 2: I need it for 7 people for 3 nights starting on friday please.\nChunk 3: Can you also provide the address to an attraction in the town centre?\nChunk 4: I need help with taxi.\nChunk 5: The time is 21:30.\nChunk 6: My destination will be going from the Castle Galleries and going back to the Alexander bed and breakfast.\nChunk 7: That is all I need today Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C2 goal=search; time+=7, 3; day+=friday; party_size+=7 people; stay_length+=3 nights. C3 domain=attraction; area+=centre; destination+=an attraction in the town centre; requested_info+=address. C4 domain=taxi. C5 time+=21:30. C6 domain=restaurant; amenities+=breakfast; destination+=the alexander bed and breakfast; departure+=the castle galleries and. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, taxi, restaurant; goal=request_info, search; area=centre; party_size=7 people; stay_length=3 nights; amenities=breakfast; destination=an attraction in the town centre, the alexander bed and breakfast; departure=the castle galleries and; requested_info=reference_number, address; when=friday, 7, 3, 21:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please do and send me the reference number.\nChunk 2: I need it for 7 people for 3 nights starting on friday please.\nChunk 3: Can you also provide the address to an attraction in the town centre?\nChunk 4: I need help with taxi.\nChunk 5: The time is 21:30.\nChunk 6: My destination will be going from the Castle Galleries and going back to the Alexander bed and breakfast.\nChunk 7: That is all I need today Thank you.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: reference_number; acceptance: selected_option. Next, the goal is search; time: 7; day: friday; party size: 7 people; stay length: 3 nights. Next, the topic is attraction; area: centre; destination: an attraction in the town centre; requested information: address. Next, the topic is taxi. Next, time: 21:30. Finally, the topic is restaurant; amenities: breakfast; destination: the alexander bed and breakfast; departure point: the castle galleries and.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is search. requested information: reference_number, address.; acceptance: selected_option.; time: 7, 21:30.; day: friday; party size: 7 people; stay length: 3 nights.; area: centre; destination: an attraction in the town centre, the alexander bed and breakfast; amenities: breakfast; departure point: the castle galleries and..", "trace": "C1 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C2 goal=search; time+=7, 3; day+=friday; party_size+=7 people; stay_length+=3 nights. C3 domain=attraction; area+=centre; destination+=an attraction in the town centre; requested_info+=address. C4 domain=taxi. C5 time+=21:30. C6 domain=restaurant; amenities+=breakfast; destination+=the alexander bed and breakfast; departure+=the castle galleries and. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please do and send me the reference number.", "streaming_reasoning": "Initially, the goal is request info; requested information: reference_number; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=reference_number; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need it for 7 people for 3 nights starting on friday please.", "streaming_reasoning": "As more information arrives, the goal is search; time: 7; day: friday; party size: 7 people; stay length: 3 nights..", "trace": "goal=search; time+=7, 3; day+=friday; party_size+=7 people; stay_length+=3 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you also provide the address to an attraction in the town centre?", "streaming_reasoning": "As more information arrives, the topic is attraction; area: centre; destination: an attraction in the town centre; requested information: address..", "trace": "domain=attraction; area+=centre; destination+=an attraction in the town centre; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need help with taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is 21:30.", "streaming_reasoning": "As more information arrives, time: 21:30..", "trace": "time+=21:30."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "My destination will be going from the Castle Galleries and going back to the Alexander bed and breakfast.", "streaming_reasoning": "As more information arrives, the topic is restaurant; amenities: breakfast; destination: the alexander bed and breakfast; departure point: the castle galleries and..", "trace": "domain=restaurant; amenities+=breakfast; destination+=the alexander bed and breakfast; departure+=the castle galleries and."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I need today Thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: area is centre; party size is 7 people; stay length is 3 nights; amenities is breakfast; destination is an attraction in the town centre; departure point is the castle galleries and; requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, taxi, restaurant; goal=request_info, search; area=centre; party_size=7 people; stay_length=3 nights; amenities=breakfast; destination=an attraction in the town centre, the alexander bed and breakfast; departure=the castle galleries and; requested_info=reference_number, address; when=friday, 7, 3, 21:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002494", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No thank you, but I would like the phone number please.\nChunk 2: I am also looking for a train.\nChunk 3: I'm leaving from Cambridge and going to peterborough.\nChunk 4: I am looking to leave Cambridge on Saturday.\nChunk 5: yes I need to arrive by 12:45, for 2 people.\nChunk 6: Thank you so much, you have been very helpful That is everything.\nChunk 7: Have a nice day, bye.", "streaming_reasoning": "C1 goal=request_info; requested_info+=phone. C2 domain=train; goal=search. C3 destination+=peterborough; departure+=cambridge and. C4 day+=saturday; destination+=leave cambridge on saturday. C5 time+=12:45, 2; party_size+=2 people; destination+=arrive by 12:45; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 intent=context_update.", "deep_reasoning": "Need domain=train; goal=request_info, search; party_size=2 people; destination=peterborough, leave cambridge on saturday, arrive by 12:45; departure=cambridge and; requested_info=phone; when=saturday, 12:45, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No thank you, but I would like the phone number please.\nChunk 2: I am also looking for a train.\nChunk 3: I'm leaving from Cambridge and going to peterborough.\nChunk 4: I am looking to leave Cambridge on Saturday.\nChunk 5: yes I need to arrive by 12:45, for 2 people.\nChunk 6: Thank you so much, you have been very helpful That is everything.\nChunk 7: Have a nice day, bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=phone. C2 domain=train; goal=search. C3 destination+=peterborough; departure+=cambridge and. C4 day+=saturday; destination+=leave cambridge on saturday. C5 time+=12:45, 2; party_size+=2 people; destination+=arrive by 12:45; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=request_info, search; party_size=2 people; destination=peterborough, leave cambridge on saturday, arrive by 12:45; departure=cambridge and; requested_info=phone; when=saturday, 12:45, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No thank you, but I would like the phone number please.\nChunk 2: I am also looking for a train.\nChunk 3: I'm leaving from Cambridge and going to peterborough.\nChunk 4: I am looking to leave Cambridge on Saturday.\nChunk 5: yes I need to arrive by 12:45, for 2 people.\nChunk 6: Thank you so much, you have been very helpful That is everything.\nChunk 7: Have a nice day, bye.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: phone. Next, the topic is train; the goal is search. Next, destination: peterborough; departure point: cambridge and. Next, day: saturday; destination: leave cambridge on saturday. Next, time: 12:45; party size: 2 people; destination: arrive by 12:45; acceptance: selected_option. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is search.. requested information: phone.; destination: peterborough, leave cambridge on saturday., arrive by 12:45; departure point: cambridge and.; day: saturday; time: 12:45; party size: 2 people; acceptance: selected_option.; intent: context_update..", "trace": "C1 goal=request_info; requested_info+=phone. C2 domain=train; goal=search. C3 destination+=peterborough; departure+=cambridge and. C4 day+=saturday; destination+=leave cambridge on saturday. C5 time+=12:45, 2; party_size+=2 people; destination+=arrive by 12:45; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No thank you, but I would like the phone number please.", "streaming_reasoning": "Initially, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also looking for a train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm leaving from Cambridge and going to peterborough.", "streaming_reasoning": "As more information arrives, destination: peterborough; departure point: cambridge and..", "trace": "destination+=peterborough; departure+=cambridge and."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am looking to leave Cambridge on Saturday.", "streaming_reasoning": "As more information arrives, day: saturday; destination: leave cambridge on saturday..", "trace": "day+=saturday; destination+=leave cambridge on saturday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "yes I need to arrive by 12:45, for 2 people.", "streaming_reasoning": "As more information arrives, time: 12:45; party size: 2 people; destination: arrive by 12:45; acceptance: selected_option..", "trace": "time+=12:45, 2; party_size+=2 people; destination+=arrive by 12:45; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you so much, you have been very helpful That is everything.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a nice day, bye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: party size is 2 people; destination is peterborough; departure point is cambridge and; requested information is phone; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search; party_size=2 people; destination=peterborough, leave cambridge on saturday, arrive by 12:45; departure=cambridge and; requested_info=phone; when=saturday, 12:45, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002495", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a cheap gastropub restaurant in the centre of town.\nChunk 2: How about something in the south and moderate price range?\nChunk 3: Sure let's try chinese food.\nChunk 4: I'll take Rice House, what's the postcode?\nChunk 5: That's all Thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; price+=cheap. C2 goal=recommendation; area+=south; price+=moderate. C3 cuisine+=chinese. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, request_info; area=centre, south; food=chinese; price=cheap, moderate; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a cheap gastropub restaurant in the centre of town.\nChunk 2: How about something in the south and moderate price range?\nChunk 3: Sure let's try chinese food.\nChunk 4: I'll take Rice House, what's the postcode?\nChunk 5: That's all Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; price+=cheap. C2 goal=recommendation; area+=south; price+=moderate. C3 cuisine+=chinese. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, request_info; area=centre, south; food=chinese; price=cheap, moderate; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a cheap gastropub restaurant in the centre of town.\nChunk 2: How about something in the south and moderate price range?\nChunk 3: Sure let's try chinese food.\nChunk 4: I'll take Rice House, what's the postcode?\nChunk 5: That's all Thank you.", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: cheap. Next, the goal is recommendation; area: south; price: moderate. Next, cuisine: chinese. Finally, the goal is request info; requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. area: centre, south; price: cheap., moderate.; cuisine: chinese.; requested information: postcode..", "trace": "C1 domain=restaurant; goal=search; area+=centre; price+=cheap. C2 goal=recommendation; area+=south; price+=moderate. C3 cuisine+=chinese. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a cheap gastropub restaurant in the centre of town.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: cheap..", "trace": "domain=restaurant; goal=search; area+=centre; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How about something in the south and moderate price range?", "streaming_reasoning": "As more information arrives, the goal is recommendation; area: south; price: moderate..", "trace": "goal=recommendation; area+=south; price+=moderate."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Sure let's try chinese food.", "streaming_reasoning": "As more information arrives, cuisine: chinese..", "trace": "cuisine+=chinese."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll take Rice House, what's the postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That's all Thank you.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; price is cheap; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, request_info; area=centre, south; food=chinese; price=cheap, moderate; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002497", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No specific area, but I would like it for Friday.\nChunk 2: I'd like to make reservations for 7 people at 11:15 on Friday please.\nChunk 3: I need help with train.\nChunk 4: The time is friday, 08:15.\nChunk 5: I'll be coming from Peterborough.\nChunk 6: All 7 of us will need tickets for the train.\nChunk 7: Yes, please include the reference number.\nChunk 8: Thank you, that is all for today Goodbye.", "streaming_reasoning": "C1 day+=friday. C2 time+=7, 11:15; party_size+=7 people; destination+=make reservations for 7 people at 11:15 o. C3 domain=train; goal=search. C4 [SKIP: repeated_information]. C5 intent=context_update. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; party_size=7 people; destination=make reservations for 7 people at 11:15 o; requested_info=reference_number; when=friday, 7, 11:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No specific area, but I would like it for Friday.\nChunk 2: I'd like to make reservations for 7 people at 11:15 on Friday please.\nChunk 3: I need help with train.\nChunk 4: The time is friday, 08:15.\nChunk 5: I'll be coming from Peterborough.\nChunk 6: All 7 of us will need tickets for the train.\nChunk 7: Yes, please include the reference number.\nChunk 8: Thank you, that is all for today Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=friday. C2 time+=7, 11:15; party_size+=7 people; destination+=make reservations for 7 people at 11:15 o. C3 domain=train; goal=search. C4 [SKIP: repeated_information]. C5 intent=context_update. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; party_size=7 people; destination=make reservations for 7 people at 11:15 o; requested_info=reference_number; when=friday, 7, 11:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No specific area, but I would like it for Friday.\nChunk 2: I'd like to make reservations for 7 people at 11:15 on Friday please.\nChunk 3: I need help with train.\nChunk 4: The time is friday, 08:15.\nChunk 5: I'll be coming from Peterborough.\nChunk 6: All 7 of us will need tickets for the train.\nChunk 7: Yes, please include the reference number.\nChunk 8: Thank you, that is all for today Goodbye.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, day: friday. Next, time: 7; party size: 7 people; destination: make reservations for 7 people at 11:15 o. Next, the topic is train; the goal is search. Next, intent: context_update. Next, intent: context_update. Finally, the goal is request info; requested information: reference_number; acceptance: selected_option.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is train. the goal is request info. day: friday.; time: 7; party size: 7 people; destination: make reservations for 7 people at 11:15 o.; intent: context_update.; requested information: reference_number; acceptance: selected_option..", "trace": "C1 day+=friday. C2 time+=7, 11:15; party_size+=7 people; destination+=make reservations for 7 people at 11:15 o. C3 domain=train; goal=search. C4 [SKIP: repeated_information]. C5 intent=context_update. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No specific area, but I would like it for Friday.", "streaming_reasoning": "Initially, day: friday..", "trace": "day+=friday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to make reservations for 7 people at 11:15 on Friday please.", "streaming_reasoning": "As more information arrives, time: 7; party size: 7 people; destination: make reservations for 7 people at 11:15 o..", "trace": "time+=7, 11:15; party_size+=7 people; destination+=make reservations for 7 people at 11:15 o."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is friday, 08:15.", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'll be coming from Peterborough.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "All 7 of us will need tickets for the train.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, please include the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=reference_number; acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you, that is all for today Goodbye.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 7 people; destination is make reservations for 7 people at 11:15 o; requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; party_size=7 people; destination=make reservations for 7 people at 11:15 o; requested_info=reference_number; when=friday, 7, 11:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002498", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am also interested in your local museums.\nChunk 2: Are there any in the south Sure.\nChunk 3: What is the entrance fee and phone number?\nChunk 4: I also need a place to stay.\nChunk 5: I am looking for a 4 star moderately priced place.\nChunk 6: Not really, but I prefer guesthouse type.\nChunk 7: As long as they have decent internet I'm fine No thank you.\nChunk 8: That's everything I needed.", "streaming_reasoning": "C1 intent=context_update. C2 area+=south. C3 goal=request_info; requested_info+=phone, entrance_fee. C4 domain=hotel; goal=search; destination+=stay. C5 price+=moderate; stars+=4 stars. C6 hotel_type+=guesthouse. C7 amenities+=internet. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=request_info, search; area=south; price=moderate; stars=4 stars; amenities=internet; destination=stay; requested_info=phone, entrance_fee; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am also interested in your local museums.\nChunk 2: Are there any in the south Sure.\nChunk 3: What is the entrance fee and phone number?\nChunk 4: I also need a place to stay.\nChunk 5: I am looking for a 4 star moderately priced place.\nChunk 6: Not really, but I prefer guesthouse type.\nChunk 7: As long as they have decent internet I'm fine No thank you.\nChunk 8: That's everything I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 area+=south. C3 goal=request_info; requested_info+=phone, entrance_fee. C4 domain=hotel; goal=search; destination+=stay. C5 price+=moderate; stars+=4 stars. C6 hotel_type+=guesthouse. C7 amenities+=internet. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info, search; area=south; price=moderate; stars=4 stars; amenities=internet; destination=stay; requested_info=phone, entrance_fee; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am also interested in your local museums.\nChunk 2: Are there any in the south Sure.\nChunk 3: What is the entrance fee and phone number?\nChunk 4: I also need a place to stay.\nChunk 5: I am looking for a 4 star moderately priced place.\nChunk 6: Not really, but I prefer guesthouse type.\nChunk 7: As long as they have decent internet I'm fine No thank you.\nChunk 8: That's everything I needed.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, area: south. Next, the goal is request info; requested information: phone. Next, the topic is hotel; the goal is search; destination: stay. Next, price: moderate; star rating: 4 stars. Next, hotel type: guesthouse. Finally, amenities: internet.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is search. intent: context_update.; area: south.; requested information: phone; destination: stay.; price: moderate; star rating: 4 stars.; hotel type: guesthouse.; amenities: internet..", "trace": "C1 intent=context_update. C2 area+=south. C3 goal=request_info; requested_info+=phone, entrance_fee. C4 domain=hotel; goal=search; destination+=stay. C5 price+=moderate; stars+=4 stars. C6 hotel_type+=guesthouse. C7 amenities+=internet. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am also interested in your local museums.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Are there any in the south Sure.", "streaming_reasoning": "As more information arrives, area: south..", "trace": "area+=south."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the entrance fee and phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, entrance_fee."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need a place to stay.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I am looking for a 4 star moderately priced place.", "streaming_reasoning": "As more information arrives, price: moderate; star rating: 4 stars..", "trace": "price+=moderate; stars+=4 stars."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Not really, but I prefer guesthouse type.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse..", "trace": "hotel_type+=guesthouse."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "As long as they have decent internet I'm fine No thank you.", "streaming_reasoning": "As more information arrives, amenities: internet..", "trace": "amenities+=internet."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's everything I needed.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: area is south; price is moderate; star rating is 4 stars; amenities is internet; destination is stay; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search; area=south; price=moderate; stars=4 stars; amenities=internet; destination=stay; requested_info=phone, entrance_fee; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002499", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: Can you tell me about some of the museums in Cambridge?\nChunk 3: Can you recommend one to me and give me the address?\nChunk 4: What is the entrance fee?\nChunk 5: Yes can you find a restaurant in the south that serves creative food?\nChunk 6: How about on that serves Mexican food?\nChunk 7: Yes, could I book it for 5 people at 12:00 on Wednesday, please?", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 goal=request_info. C3 goal=recommendation; destination+=me and give me the address; requested_info+=address. C4 requested_info+=entrance_fee. C5 domain=restaurant; goal=search; area+=south; acceptance=selected_option. C6 cuisine+=mexican. C7 goal=confirm_booking; time+=5, 12:00; day+=wednesday; party_size+=5 people; goal=confirm_booking.", "deep_reasoning": "Need domain=restaurant; goal=request_info, recommendation, search, booking, confirm_booking; area=south; food=mexican; party_size=5 people; destination=me and give me the address; requested_info=address, entrance_fee; when=wednesday, 5, 12:00.", "answer": "I can help with that and include the address, entrance fee once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi!\nChunk 2: Can you tell me about some of the museums in Cambridge?\nChunk 3: Can you recommend one to me and give me the address?\nChunk 4: What is the entrance fee?\nChunk 5: Yes can you find a restaurant in the south that serves creative food?\nChunk 6: How about on that serves Mexican food?\nChunk 7: Yes, could I book it for 5 people at 12:00 on Wednesday, please?"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 goal=request_info. C3 goal=recommendation; destination+=me and give me the address; requested_info+=address. C4 requested_info+=entrance_fee. C5 domain=restaurant; goal=search; area+=south; acceptance=selected_option. C6 cuisine+=mexican. C7 goal=confirm_booking; time+=5, 12:00; day+=wednesday; party_size+=5 people; goal=confirm_booking.\n\nDeep reasoning: Need domain=restaurant; goal=request_info, recommendation, search, booking, confirm_booking; area=south; food=mexican; party_size=5 people; destination=me and give me the address; requested_info=address, entrance_fee; when=wednesday, 5, 12:00.\n\nAnswer: I can help with that and include the address, entrance fee once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: Can you tell me about some of the museums in Cambridge?\nChunk 3: Can you recommend one to me and give me the address?\nChunk 4: What is the entrance fee?\nChunk 5: Yes can you find a restaurant in the south that serves creative food?\nChunk 6: How about on that serves Mexican food?\nChunk 7: Yes, could I book it for 5 people at 12:00 on Wednesday, please?", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, the goal is recommendation; destination: me and give me the address; requested information: address. Next, requested information: entrance_fee. Next, the topic is restaurant; the goal is search; area: south; acceptance: selected_option. Next, cuisine: mexican. Finally, the goal is confirm booking.; time: 5; day: wednesday; party size: 5 people.  Some chunks were skipped because they contained greeting_only. In summary, The overall topic is restaurant. the goal is confirm booking.. destination: me and give me the address; requested information: address., entrance_fee.; area: south; acceptance: selected_option.; cuisine: mexican.; time: 5; day: wednesday; party size: 5 people.", "trace": "C1 [SKIP: greeting_only]. C2 goal=request_info. C3 goal=recommendation; destination+=me and give me the address; requested_info+=address. C4 requested_info+=entrance_fee. C5 domain=restaurant; goal=search; area+=south; acceptance=selected_option. C6 cuisine+=mexican. C7 goal=confirm_booking; time+=5, 12:00; day+=wednesday; party_size+=5 people; goal=confirm_booking.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi!", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you tell me about some of the museums in Cambridge?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you recommend one to me and give me the address?", "streaming_reasoning": "As more information arrives, the goal is recommendation; destination: me and give me the address; requested information: address..", "trace": "goal=recommendation; destination+=me and give me the address; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is the entrance fee?", "streaming_reasoning": "As more information arrives, requested information: entrance_fee..", "trace": "requested_info+=entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes can you find a restaurant in the south that serves creative food?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; area: south; acceptance: selected_option..", "trace": "domain=restaurant; goal=search; area+=south; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "How about on that serves Mexican food?", "streaming_reasoning": "As more information arrives, cuisine: mexican..", "trace": "cuisine+=mexican."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, could I book it for 5 people at 12:00 on Wednesday, please?", "streaming_reasoning": "Finally, the goal is confirm booking.; time: 5; day: wednesday; party size: 5 people.", "trace": "goal=confirm_booking; time+=5, 12:00; day+=wednesday; party_size+=5 people; goal=confirm_booking."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is south; cuisine is mexican; party size is 5 people; destination is me and give me the address; requested information is address; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, entrance fee once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info, recommendation, search, booking, confirm_booking; area=south; food=mexican; party_size=5 people; destination=me and give me the address; requested_info=address, entrance_fee; when=wednesday, 5, 12:00."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000517", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Make Espresso Beverages With a French Press.\nChunk 2: • Caf• press pot, AKA Cafetiere or French press.\nChunk 3: These can be found in most department stores, kitchen departments, or coffee shops.\nChunk 4: • Immersion blender, sometimes called a stick blender.\nChunk 5: These can be found in most department stores.\nChunk 6: • Fresh, quality coffee • Milk or heavy cream • Saucepan.", "streaming_reasoning": "C1 task=make_espresso_beverages_with. C2 step=caf_press_pot_aka. C3 step=these_can_be_found. C4 step=immersion_blender_sometimes_called. C5 [SKIP: repeated_information]. C6 step=fresh_quality_coffee_milk.", "deep_reasoning": "Procedure for Make Espresso Beverages With a French Press: Caf press pot, AKA Cafetiere or French press, These can be found in most department stores, kitchen departments,, Immersion blender, sometimes called a stick blender, Fresh, quality coffee Milk or heavy cream Saucepan.", "answer": "For Make Espresso Beverages With a French Press, follow the steps in order: Caf press pot, AKA Cafetiere or French press, These can be found in most department stores, kitchen departments,, Immersion blender, sometimes called a stick blender, Fresh, quality coffee Milk or heavy cream Saucepan.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Make Espresso Beverages With a French Press.\nChunk 2: • Caf• press pot, AKA Cafetiere or French press.\nChunk 3: These can be found in most department stores, kitchen departments, or coffee shops.\nChunk 4: • Immersion blender, sometimes called a stick blender.\nChunk 5: These can be found in most department stores.\nChunk 6: • Fresh, quality coffee • Milk or heavy cream • Saucepan."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=make_espresso_beverages_with. C2 step=caf_press_pot_aka. C3 step=these_can_be_found. C4 step=immersion_blender_sometimes_called. C5 [SKIP: repeated_information]. C6 step=fresh_quality_coffee_milk.\n\nDeep reasoning: Procedure for Make Espresso Beverages With a French Press: Caf press pot, AKA Cafetiere or French press, These can be found in most department stores, kitchen departments,, Immersion blender, sometimes called a stick blender, Fresh, quality coffee Milk or heavy cream Saucepan.\n\nAnswer: For Make Espresso Beverages With a French Press, follow the steps in order: Caf press pot, AKA Cafetiere or French press, These can be found in most department stores, kitchen departments,, Immersion blender, sometimes called a stick blender, Fresh, quality coffee Milk or heavy cream Saucepan."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Make Espresso Beverages With a French Press.\nChunk 2: • Caf• press pot, AKA Cafetiere or French press.\nChunk 3: These can be found in most department stores, kitchen departments, or coffee shops.\nChunk 4: • Immersion blender, sometimes called a stick blender.\nChunk 5: These can be found in most department stores.\nChunk 6: • Fresh, quality coffee • Milk or heavy cream • Saucepan.", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, task: make_espresso_beverages_with. Next, step: caf_press_pot_aka. Next, step: these_can_be_found. Next, step: immersion_blender_sometimes_called. Finally, step: fresh_quality_coffee_milk.  Some chunks were skipped because they contained repeated_information. In summary, task: make_espresso_beverages_with.; step: caf_press_pot_aka., these_can_be_found., immersion_blender_sometimes_called., fresh_quality_coffee_milk..", "trace": "C1 task=make_espresso_beverages_with. C2 step=caf_press_pot_aka. C3 step=these_can_be_found. C4 step=immersion_blender_sometimes_called. C5 [SKIP: repeated_information]. C6 step=fresh_quality_coffee_milk.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Make Espresso Beverages With a French Press.", "streaming_reasoning": "Initially, task: make_espresso_beverages_with..", "trace": "task=make_espresso_beverages_with."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• Caf• press pot, AKA Cafetiere or French press.", "streaming_reasoning": "As more information arrives, step: caf_press_pot_aka..", "trace": "step=caf_press_pot_aka."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "These can be found in most department stores, kitchen departments, or coffee shops.", "streaming_reasoning": "As more information arrives, step: these_can_be_found..", "trace": "step=these_can_be_found."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "• Immersion blender, sometimes called a stick blender.", "streaming_reasoning": "As more information arrives, step: immersion_blender_sometimes_called..", "trace": "step=immersion_blender_sometimes_called."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "These can be found in most department stores.", "streaming_reasoning": "The content at C5 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "• Fresh, quality coffee • Milk or heavy cream • Saucepan.", "streaming_reasoning": "Finally, step: fresh_quality_coffee_milk..", "trace": "step=fresh_quality_coffee_milk."}]}, "output": {"deep_reasoning": "Procedure for Make Espresso Beverages With a French Press: Caf press pot, AKA Cafetiere or French press, These can be found in most department stores, kitchen departments,, Immersion blender, sometimes called a stick blender, Fresh, quality coffee Milk or heavy cream Saucepan.", "answer": "For Make Espresso Beverages With a French Press, follow the steps in order: Caf press pot, AKA Cafetiere or French press, These can be found in most department stores, kitchen departments,, Immersion blender, sometimes called a stick blender, Fresh, quality coffee Milk or heavy cream Saucepan."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002500", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I also would like it to be a guesthouse and have a 4 star rating.\nChunk 3: Does the Archway House have internet?\nChunk 4: What's the phone number there Great, thanks.\nChunk 5: Can I please also get the address?\nChunk 6: No that won't be necessary, that's all I needed Thank You!\nChunk 7: No, that's all Goodbye!", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 domain=hotel; hotel_type+=guesthouse; stars+=4 stars; destination+=be a guesthouse and have a 4 star rating. C3 amenities+=internet. C4 goal=request_info; requested_info+=phone. C5 requested_info+=address. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=request_info; stars=4 stars; amenities=internet; destination=be a guesthouse and have a 4 star rating; requested_info=phone, address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I also would like it to be a guesthouse and have a 4 star rating.\nChunk 3: Does the Archway House have internet?\nChunk 4: What's the phone number there Great, thanks.\nChunk 5: Can I please also get the address?\nChunk 6: No that won't be necessary, that's all I needed Thank You!\nChunk 7: No, that's all Goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 domain=hotel; hotel_type+=guesthouse; stars+=4 stars; destination+=be a guesthouse and have a 4 star rating. C3 amenities+=internet. C4 goal=request_info; requested_info+=phone. C5 requested_info+=address. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info; stars=4 stars; amenities=internet; destination=be a guesthouse and have a 4 star rating; requested_info=phone, address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I also would like it to be a guesthouse and have a 4 star rating.\nChunk 3: Does the Archway House have internet?\nChunk 4: What's the phone number there Great, thanks.\nChunk 5: Can I please also get the address?\nChunk 6: No that won't be necessary, that's all I needed Thank You!\nChunk 7: No, that's all Goodbye!", "input_token_count": 65, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse; star rating: 4 stars; destination: be a guesthouse and have a 4 star rating. Next, amenities: internet. Next, the goal is request info; requested information: phone. Finally, requested information: address.  Some chunks were skipped because they contained acknowledgement_only or closing_only. In summary, The overall topic is hotel. the goal is request info. hotel type: guesthouse; star rating: 4 stars; destination: be a guesthouse and have a 4 star rating.; amenities: internet.; requested information: phone., address..", "trace": "C1 [SKIP: acknowledgement_only]. C2 domain=hotel; hotel_type+=guesthouse; stars+=4 stars; destination+=be a guesthouse and have a 4 star rating. C3 amenities+=internet. C4 goal=request_info; requested_info+=phone. C5 requested_info+=address. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also would like it to be a guesthouse and have a 4 star rating.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse; star rating: 4 stars; destination: be a guesthouse and have a 4 star rating..", "trace": "domain=hotel; hotel_type+=guesthouse; stars+=4 stars; destination+=be a guesthouse and have a 4 star rating."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Does the Archway House have internet?", "streaming_reasoning": "As more information arrives, amenities: internet..", "trace": "amenities+=internet."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What's the phone number there Great, thanks.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I please also get the address?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No that won't be necessary, that's all I needed Thank You!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that's all Goodbye!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: star rating is 4 stars; amenities is internet; destination is be a guesthouse and have a 4 star rating; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info; stars=4 stars; amenities=internet; destination=be a guesthouse and have a 4 star rating; requested_info=phone, address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002501", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need free wifi and a 0 star rating please.\nChunk 2: Ok, then, is there one that is cheap and offers free parking instead?\nChunk 3: Ok, I will try again later.\nChunk 4: I want which ever one is close to town Sure.\nChunk 5: There will be 5 of us for 4 nights starting Monday.\nChunk 6: Perfect thanks so much for your help that was all I needed today.", "streaming_reasoning": "C1 goal=search; stars+=0 stars; amenities+=wifi. C2 goal=compare_alternative; price+=cheap; amenities+=parking, free parking. C3 intent=context_update. C4 destination+=town sure. C5 time+=5, 4; day+=monday; stay_length+=4 nights. C6 [SKIP: closing_only].", "deep_reasoning": "Need goal=search, compare_alternative; price=cheap; stay_length=4 nights; stars=0 stars; amenities=wifi, parking, free parking; destination=town sure; when=monday, 5, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also need free wifi and a 0 star rating please.\nChunk 2: Ok, then, is there one that is cheap and offers free parking instead?\nChunk 3: Ok, I will try again later.\nChunk 4: I want which ever one is close to town Sure.\nChunk 5: There will be 5 of us for 4 nights starting Monday.\nChunk 6: Perfect thanks so much for your help that was all I needed today."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; stars+=0 stars; amenities+=wifi. C2 goal=compare_alternative; price+=cheap; amenities+=parking, free parking. C3 intent=context_update. C4 destination+=town sure. C5 time+=5, 4; day+=monday; stay_length+=4 nights. C6 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search, compare_alternative; price=cheap; stay_length=4 nights; stars=0 stars; amenities=wifi, parking, free parking; destination=town sure; when=monday, 5, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need free wifi and a 0 star rating please.\nChunk 2: Ok, then, is there one that is cheap and offers free parking instead?\nChunk 3: Ok, I will try again later.\nChunk 4: I want which ever one is close to town Sure.\nChunk 5: There will be 5 of us for 4 nights starting Monday.\nChunk 6: Perfect thanks so much for your help that was all I needed today.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; star rating: 0 stars; amenities: wifi. Next, the goal is compare alternative; price: cheap; amenities: parking. Next, intent: context_update. Next, destination: town sure. Finally, time: 5; day: monday; stay length: 4 nights.  Some chunks were skipped because they contained closing_only. In summary, the goal is compare alternative. star rating: 0 stars; amenities: wifi., parking; price: cheap; intent: context_update.; destination: town sure.; time: 5; day: monday; stay length: 4 nights..", "trace": "C1 goal=search; stars+=0 stars; amenities+=wifi. C2 goal=compare_alternative; price+=cheap; amenities+=parking, free parking. C3 intent=context_update. C4 destination+=town sure. C5 time+=5, 4; day+=monday; stay_length+=4 nights. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also need free wifi and a 0 star rating please.", "streaming_reasoning": "Initially, the goal is search; star rating: 0 stars; amenities: wifi..", "trace": "goal=search; stars+=0 stars; amenities+=wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Ok, then, is there one that is cheap and offers free parking instead?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; price: cheap; amenities: parking.", "trace": "goal=compare_alternative; price+=cheap; amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Ok, I will try again later.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want which ever one is close to town Sure.", "streaming_reasoning": "As more information arrives, destination: town sure..", "trace": "destination+=town sure."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "There will be 5 of us for 4 nights starting Monday.", "streaming_reasoning": "As more information arrives, time: 5; day: monday; stay length: 4 nights..", "trace": "time+=5, 4; day+=monday; stay_length+=4 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Perfect thanks so much for your help that was all I needed today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search, compare_alternative; price=cheap; stay_length=4 nights; stars=0 stars; amenities=wifi, parking, free parking; destination=town sure; when=monday, 5, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003158", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I'm not sure.\nChunk 2: When you cross the quad, the office is right in front of you.\nChunk 3: Go inside and follow the signs to the correct line.\nChunk 4: Thanks.\nChunk 5: I understand what to do now.\nChunk 6: It should be easy to find.\nChunk 7: After you add the class, check with me in a few weeks to make sure that you are on my roll sheet That sounds good.", "streaming_reasoning": "C1 casual_comment=i'm, not. C2 casual_comment=cross, quad. C3 casual_comment=inside, follow. C4 [SKIP: thanks_only]. C5 casual_comment=understand, now. C6 casual_comment=easy, find. C7 casual_comment=add, class.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, I'm not sure.\nChunk 2: When you cross the quad, the office is right in front of you.\nChunk 3: Go inside and follow the signs to the correct line.\nChunk 4: Thanks.\nChunk 5: I understand what to do now.\nChunk 6: It should be easy to find.\nChunk 7: After you add the class, check with me in a few weeks to make sure that you are on my roll sheet That sounds good."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=i'm, not. C2 casual_comment=cross, quad. C3 casual_comment=inside, follow. C4 [SKIP: thanks_only]. C5 casual_comment=understand, now. C6 casual_comment=easy, find. C7 casual_comment=add, class.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I'm not sure.\nChunk 2: When you cross the quad, the office is right in front of you.\nChunk 3: Go inside and follow the signs to the correct line.\nChunk 4: Thanks.\nChunk 5: I understand what to do now.\nChunk 6: It should be easy to find.\nChunk 7: After you add the class, check with me in a few weeks to make sure that you are on my roll sheet That sounds good.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on i'm. Next, the user comments on cross. Next, the user comments on inside. Next, the user comments on understand. Next, the user comments on easy. Finally, the user comments on add.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=i'm, not. C2 casual_comment=cross, quad. C3 casual_comment=inside, follow. C4 [SKIP: thanks_only]. C5 casual_comment=understand, now. C6 casual_comment=easy, find. C7 casual_comment=add, class.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, I'm not sure.", "streaming_reasoning": "Initially, the user comments on i'm.", "trace": "casual_comment=i'm, not."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "When you cross the quad, the office is right in front of you.", "streaming_reasoning": "As more information arrives, the user comments on cross.", "trace": "casual_comment=cross, quad."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Go inside and follow the signs to the correct line.", "streaming_reasoning": "As more information arrives, the user comments on inside.", "trace": "casual_comment=inside, follow."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I understand what to do now.", "streaming_reasoning": "As more information arrives, the user comments on understand.", "trace": "casual_comment=understand, now."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It should be easy to find.", "streaming_reasoning": "As more information arrives, the user comments on easy.", "trace": "casual_comment=easy, find."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "After you add the class, check with me in a few weeks to make sure that you are on my roll sheet That sounds good.", "streaming_reasoning": "Finally, the user comments on add.", "trace": "casual_comment=add, class."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002502", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My wallet was stolen.\nChunk 2: Can I get some help Thank you goodbye.", "streaming_reasoning": "C1 intent=context_update. C2 goal=request_info.", "deep_reasoning": "Need goal=search, request_info.", "answer": "Got it. I will use those details and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: My wallet was stolen.\nChunk 2: Can I get some help Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=request_info.\n\nDeep reasoning: Need goal=search, request_info.\n\nAnswer: Got it. I will use those details and move the task forward."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My wallet was stolen.\nChunk 2: Can I get some help Thank you goodbye.", "input_token_count": 16, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Finally, the goal is request info. In summary, the goal is request info.. intent: context_update..", "trace": "C1 intent=context_update. C2 goal=request_info.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "My wallet was stolen.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I get some help Thank you goodbye.", "streaming_reasoning": "Finally, the goal is request info..", "trace": "goal=request_info."}]}, "output": {"deep_reasoning": "Need goal=search, request_info.", "answer": "Got it. I will use those details and move the task forward."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002503", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train departing from london kings cross.\nChunk 2: I would like to go to Cambridge, after 11:15.\nChunk 3: I want to leave on Monday.\nChunk 4: Actually, can I have the price, and the travel time please?\nChunk 5: Great that's all the info I need, thank you for your help today.", "streaming_reasoning": "C1 domain=train; goal=search; departure+=london kings cross. C2 time+=11:15; destination+=go to cambridge. C3 day+=monday; destination+=leave on monday. C4 goal=request_info; requested_info+=travel_time. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=go to cambridge, leave on monday; departure=london kings cross; requested_info=travel_time; when=monday, 11:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a train departing from london kings cross.\nChunk 2: I would like to go to Cambridge, after 11:15.\nChunk 3: I want to leave on Monday.\nChunk 4: Actually, can I have the price, and the travel time please?\nChunk 5: Great that's all the info I need, thank you for your help today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; departure+=london kings cross. C2 time+=11:15; destination+=go to cambridge. C3 day+=monday; destination+=leave on monday. C4 goal=request_info; requested_info+=travel_time. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=go to cambridge, leave on monday; departure=london kings cross; requested_info=travel_time; when=monday, 11:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train departing from london kings cross.\nChunk 2: I would like to go to Cambridge, after 11:15.\nChunk 3: I want to leave on Monday.\nChunk 4: Actually, can I have the price, and the travel time please?\nChunk 5: Great that's all the info I need, thank you for your help today.", "input_token_count": 61, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; departure point: london kings cross. Next, time: 11:15; destination: go to cambridge. Next, day: monday; destination: leave on monday. Finally, the goal is request info; requested information: travel_time.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. departure point: london kings cross.; time: 11:15; destination: go to cambridge., leave on monday.; day: monday; requested information: travel_time..", "trace": "C1 domain=train; goal=search; departure+=london kings cross. C2 time+=11:15; destination+=go to cambridge. C3 day+=monday; destination+=leave on monday. C4 goal=request_info; requested_info+=travel_time. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a train departing from london kings cross.", "streaming_reasoning": "Initially, the topic is train; the goal is search; departure point: london kings cross..", "trace": "domain=train; goal=search; departure+=london kings cross."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to go to Cambridge, after 11:15.", "streaming_reasoning": "As more information arrives, time: 11:15; destination: go to cambridge..", "trace": "time+=11:15; destination+=go to cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to leave on Monday.", "streaming_reasoning": "As more information arrives, day: monday; destination: leave on monday..", "trace": "day+=monday; destination+=leave on monday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Actually, can I have the price, and the travel time please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Great that's all the info I need, thank you for your help today.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is go to cambridge; departure point is london kings cross; requested information is travel_time; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=go to cambridge, leave on monday; departure=london kings cross; requested_info=travel_time; when=monday, 11:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001680", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I was sad when the truck I wasnted had been sold.\nChunk 2: I was so sad when the truck I wanted was sold.\nChunk 3: Oh no, that is not cool.\nChunk 4: no it was sad, i had been working to get the money up for it.", "streaming_reasoning": "C1 emotion=sad; cause=the truck I wasnted had been sold; need=validation. C2 emotion=sad; cause=the truck I wanted was sold. C3 support_signal=received. C4 emotion=sad; cause=no it was , i had been working to get the money.", "deep_reasoning": "User feels sad after no it was , i had been working to get the money and needs validation.", "answer": "It makes sense to feel sad after no it was, i had been working to get the money. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I was sad when the truck I wasnted had been sold.\nChunk 2: I was so sad when the truck I wanted was sold.\nChunk 3: Oh no, that is not cool.\nChunk 4: no it was sad, i had been working to get the money up for it."}, {"role": "assistant", "content": "Streaming reasoning: C1 emotion=sad; cause=the truck I wasnted had been sold; need=validation. C2 emotion=sad; cause=the truck I wanted was sold. C3 support_signal=received. C4 emotion=sad; cause=no it was , i had been working to get the money.\n\nDeep reasoning: User feels sad after no it was , i had been working to get the money and needs validation.\n\nAnswer: It makes sense to feel sad after no it was, i had been working to get the money. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I was sad when the truck I wasnted had been sold.\nChunk 2: I was so sad when the truck I wanted was sold.\nChunk 3: Oh no, that is not cool.\nChunk 4: no it was sad, i had been working to get the money up for it.", "input_token_count": 51, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user expresses sad about the truck I wasnted had been sold; the user needs validation. Next, the user expresses sad about the truck I wanted was sold. Next, the user signals support or acknowledgment. Finally, the user expresses sad about no it was.", "trace": "C1 emotion=sad; cause=the truck I wasnted had been sold; need=validation. C2 emotion=sad; cause=the truck I wanted was sold. C3 support_signal=received. C4 emotion=sad; cause=no it was , i had been working to get the money.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I was sad when the truck I wasnted had been sold.", "streaming_reasoning": "Initially, the user expresses sad about the truck I wasnted had been sold; the user needs validation..", "trace": "emotion=sad; cause=the truck I wasnted had been sold; need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I was so sad when the truck I wanted was sold.", "streaming_reasoning": "As more information arrives, the user expresses sad about the truck I wanted was sold..", "trace": "emotion=sad; cause=the truck I wanted was sold."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Oh no, that is not cool.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "no it was sad, i had been working to get the money up for it.", "streaming_reasoning": "Finally, the user expresses sad about no it was.", "trace": "emotion=sad; cause=no it was , i had been working to get the money."}]}, "output": {"deep_reasoning": "User feels sad after no it was , i had been working to get the money and needs validation.", "answer": "It makes sense to feel sad after no it was, i had been working to get the money. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002504", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No thanks, but could i get their postcode Thank you!\nChunk 2: I also would like information about a train, please, leaving Cambridge after 21:00.\nChunk 3: I am going to Leicester Perfect.\nChunk 4: Can you get me 4 seats on that one?\nChunk 5: Thank you for your help!\nChunk 6: Nothing else, thank you.\nChunk 7: Have a great day.", "streaming_reasoning": "C1 goal=request_info; requested_info+=postcode. C2 domain=train; time+=21:00. C3 destination+=leicester perfect; acceptance=selected_option. C4 goal=search. C5 [SKIP: thanks_only]. C6 goal=compare_alternative. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=request_info, search, compare_alternative; destination=leicester perfect; requested_info=postcode; when=21:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No thanks, but could i get their postcode Thank you!\nChunk 2: I also would like information about a train, please, leaving Cambridge after 21:00.\nChunk 3: I am going to Leicester Perfect.\nChunk 4: Can you get me 4 seats on that one?\nChunk 5: Thank you for your help!\nChunk 6: Nothing else, thank you.\nChunk 7: Have a great day."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=postcode. C2 domain=train; time+=21:00. C3 destination+=leicester perfect; acceptance=selected_option. C4 goal=search. C5 [SKIP: thanks_only]. C6 goal=compare_alternative. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search, compare_alternative; destination=leicester perfect; requested_info=postcode; when=21:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No thanks, but could i get their postcode Thank you!\nChunk 2: I also would like information about a train, please, leaving Cambridge after 21:00.\nChunk 3: I am going to Leicester Perfect.\nChunk 4: Can you get me 4 seats on that one?\nChunk 5: Thank you for your help!\nChunk 6: Nothing else, thank you.\nChunk 7: Have a great day.", "input_token_count": 66, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: postcode. Next, the topic is train; time: 21:00. Next, destination: leicester perfect; acceptance: selected_option. Next, the goal is search. Finally, the goal is compare alternative.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is compare alternative.. requested information: postcode.; time: 21:00.; destination: leicester perfect; acceptance: selected_option..", "trace": "C1 goal=request_info; requested_info+=postcode. C2 domain=train; time+=21:00. C3 destination+=leicester perfect; acceptance=selected_option. C4 goal=search. C5 [SKIP: thanks_only]. C6 goal=compare_alternative. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No thanks, but could i get their postcode Thank you!", "streaming_reasoning": "Initially, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also would like information about a train, please, leaving Cambridge after 21:00.", "streaming_reasoning": "As more information arrives, the topic is train; time: 21:00..", "trace": "domain=train; time+=21:00."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am going to Leicester Perfect.", "streaming_reasoning": "As more information arrives, destination: leicester perfect; acceptance: selected_option..", "trace": "destination+=leicester perfect; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you get me 4 seats on that one?", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you for your help!", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Nothing else, thank you.", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: destination is leicester perfect; requested information is postcode; timing is 21:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search, compare_alternative; destination=leicester perfect; requested_info=postcode; when=21:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002505", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help finding a restaurant please.\nChunk 2: I would really like to find someplace serving thai in the centre of town.\nChunk 3: Yes, I need a table for 4 people at 19:30 on Sunday.\nChunk 4: No, that is all thanks Good bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 area+=centre; cuisine+=thai; destination+=find someplace serving thai in the centre. C3 time+=4, 19:30; day+=sunday; party_size+=4 people; acceptance=selected_option. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search; area=centre; food=thai; party_size=4 people; destination=find someplace serving thai in the centre; when=sunday, 4, 19:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need help finding a restaurant please.\nChunk 2: I would really like to find someplace serving thai in the centre of town.\nChunk 3: Yes, I need a table for 4 people at 19:30 on Sunday.\nChunk 4: No, that is all thanks Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 area+=centre; cuisine+=thai; destination+=find someplace serving thai in the centre. C3 time+=4, 19:30; day+=sunday; party_size+=4 people; acceptance=selected_option. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search; area=centre; food=thai; party_size=4 people; destination=find someplace serving thai in the centre; when=sunday, 4, 19:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help finding a restaurant please.\nChunk 2: I would really like to find someplace serving thai in the centre of town.\nChunk 3: Yes, I need a table for 4 people at 19:30 on Sunday.\nChunk 4: No, that is all thanks Good bye.", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, area: centre; cuisine: thai; destination: find someplace serving thai in the centre. Finally, time: 4; day: sunday; party size: 4 people; acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is search.. area: centre; cuisine: thai; destination: find someplace serving thai in the centre.; time: 4; day: sunday; party size: 4 people; acceptance: selected_option..", "trace": "C1 domain=restaurant; goal=search. C2 area+=centre; cuisine+=thai; destination+=find someplace serving thai in the centre. C3 time+=4, 19:30; day+=sunday; party_size+=4 people; acceptance=selected_option. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need help finding a restaurant please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would really like to find someplace serving thai in the centre of town.", "streaming_reasoning": "As more information arrives, area: centre; cuisine: thai; destination: find someplace serving thai in the centre..", "trace": "area+=centre; cuisine+=thai; destination+=find someplace serving thai in the centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I need a table for 4 people at 19:30 on Sunday.", "streaming_reasoning": "As more information arrives, time: 4; day: sunday; party size: 4 people; acceptance: selected_option..", "trace": "time+=4, 19:30; day+=sunday; party_size+=4 people; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, that is all thanks Good bye.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is thai; party size is 4 people; destination is find someplace serving thai in the centre; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search; area=centre; food=thai; party_size=4 people; destination=find someplace serving thai in the centre; when=sunday, 4, 19:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002506", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hospital in town.\nChunk 2: The hospital should have the hepatobillary and gastrointestinal surgery regional referral centre department.\nChunk 3: I need the address, postcode, and phone number.\nChunk 4: Great, thanks for your help That was all.\nChunk 5: Thanks.", "streaming_reasoning": "C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 area+=centre. C3 goal=request_info; requested_info+=address, phone, postcode. C4 [SKIP: thanks_only]. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hospital; goal=search, request_info; area=centre; destination=find a hospital in town; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a hospital in town.\nChunk 2: The hospital should have the hepatobillary and gastrointestinal surgery regional referral centre department.\nChunk 3: I need the address, postcode, and phone number.\nChunk 4: Great, thanks for your help That was all.\nChunk 5: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 area+=centre. C3 goal=request_info; requested_info+=address, phone, postcode. C4 [SKIP: thanks_only]. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; area=centre; destination=find a hospital in town; requested_info=address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hospital in town.\nChunk 2: The hospital should have the hepatobillary and gastrointestinal surgery regional referral centre department.\nChunk 3: I need the address, postcode, and phone number.\nChunk 4: Great, thanks for your help That was all.\nChunk 5: Thanks.", "input_token_count": 48, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital in town. Next, area: centre. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hospital. the goal is request info. destination: find a hospital in town.; area: centre.; requested information: address.", "trace": "C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 area+=centre. C3 goal=request_info; requested_info+=address, phone, postcode. C4 [SKIP: thanks_only]. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a hospital in town.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital in town..", "trace": "domain=hospital; goal=search; destination+=find a hospital in town."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The hospital should have the hepatobillary and gastrointestinal surgery regional referral centre department.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need the address, postcode, and phone number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Great, thanks for your help That was all.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: area is centre; destination is find a hospital in town; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; area=centre; destination=find a hospital in town; requested_info=address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002507", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is this located in the centre area?\nChunk 2: OK, I don't need a table right now, but I do need the address and postcode of the Curry Garden, please.\nChunk 3: Can you tell me about a local swimming pool in town?\nChunk 4: The north please, can I get the phone number, address, and area?\nChunk 5: I need help with taxi.\nChunk 6: The time is 12:00.\nChunk 7: That's everything I needed.\nChunk 8: Thank you so much for your help!", "streaming_reasoning": "C1 area+=centre. C2 goal=request_info; requested_info+=address, postcode. C3 amenities+=pool. C4 area+=north; requested_info+=phone. C5 domain=taxi. C6 time+=12:00. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi; goal=search, request_info; area=centre, north; amenities=pool; requested_info=address, postcode, phone; when=12:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Is this located in the centre area?\nChunk 2: OK, I don't need a table right now, but I do need the address and postcode of the Curry Garden, please.\nChunk 3: Can you tell me about a local swimming pool in town?\nChunk 4: The north please, can I get the phone number, address, and area?\nChunk 5: I need help with taxi.\nChunk 6: The time is 12:00.\nChunk 7: That's everything I needed.\nChunk 8: Thank you so much for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre. C2 goal=request_info; requested_info+=address, postcode. C3 amenities+=pool. C4 area+=north; requested_info+=phone. C5 domain=taxi. C6 time+=12:00. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi; goal=search, request_info; area=centre, north; amenities=pool; requested_info=address, postcode, phone; when=12:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is this located in the centre area?\nChunk 2: OK, I don't need a table right now, but I do need the address and postcode of the Curry Garden, please.\nChunk 3: Can you tell me about a local swimming pool in town?\nChunk 4: The north please, can I get the phone number, address, and area?\nChunk 5: I need help with taxi.\nChunk 6: The time is 12:00.\nChunk 7: That's everything I needed.\nChunk 8: Thank you so much for your help!", "input_token_count": 88, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: centre. Next, the goal is request info; requested information: address. Next, amenities: pool. Next, area: north; requested information: phone. Next, the topic is taxi. Finally, time: 12:00.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi.. the goal is request info. area: centre., north; requested information: address, phone.; amenities: pool.; time: 12:00..", "trace": "C1 area+=centre. C2 goal=request_info; requested_info+=address, postcode. C3 amenities+=pool. C4 area+=north; requested_info+=phone. C5 domain=taxi. C6 time+=12:00. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Is this located in the centre area?", "streaming_reasoning": "Initially, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "OK, I don't need a table right now, but I do need the address and postcode of the Curry Garden, please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you tell me about a local swimming pool in town?", "streaming_reasoning": "As more information arrives, amenities: pool..", "trace": "amenities+=pool."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The north please, can I get the phone number, address, and area?", "streaming_reasoning": "As more information arrives, area: north; requested information: phone..", "trace": "area+=north; requested_info+=phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need help with taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 12:00.", "streaming_reasoning": "As more information arrives, time: 12:00..", "trace": "time+=12:00."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's everything I needed.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you so much for your help!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: area is centre; amenities is pool; requested information is address; timing is 12:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search, request_info; area=centre, north; amenities=pool; requested_info=address, postcode, phone; when=12:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002508", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant near the centre, moderate priced, please.\nChunk 2: I would like british food please That sounds great.\nChunk 3: Can you book a table for 8 people on Friday at 13:30?\nChunk 4: I am looking for places to go in town.\nChunk 5: The attraction should be in the type of museum and should be in the same area as the restaurant.\nChunk 6: Yes.\nChunk 7: May I have the number and address?\nChunk 8: That is everything thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 cuisine+=british. C3 goal=booking; time+=8, 13:30; day+=friday; party_size+=8 people. C4 destination+=go in town. C5 domain=attraction; goal=modify_constraint. C6 goal=confirm_booking. C7 goal=request_info; requested_info+=address. C8 intent=context_update.", "deep_reasoning": "Need domain=restaurant, attraction; goal=search, booking, modify_constraint, request_info; area=centre; food=british; price=moderate; party_size=8 people; destination=go in town; requested_info=address; when=friday, 8, 13:30.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant near the centre, moderate priced, please.\nChunk 2: I would like british food please That sounds great.\nChunk 3: Can you book a table for 8 people on Friday at 13:30?\nChunk 4: I am looking for places to go in town.\nChunk 5: The attraction should be in the type of museum and should be in the same area as the restaurant.\nChunk 6: Yes.\nChunk 7: May I have the number and address?\nChunk 8: That is everything thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 cuisine+=british. C3 goal=booking; time+=8, 13:30; day+=friday; party_size+=8 people. C4 destination+=go in town. C5 domain=attraction; goal=modify_constraint. C6 goal=confirm_booking. C7 goal=request_info; requested_info+=address. C8 intent=context_update.\n\nDeep reasoning: Need domain=restaurant, attraction; goal=search, booking, modify_constraint, request_info; area=centre; food=british; price=moderate; party_size=8 people; destination=go in town; requested_info=address; when=friday, 8, 13:30.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant near the centre, moderate priced, please.\nChunk 2: I would like british food please That sounds great.\nChunk 3: Can you book a table for 8 people on Friday at 13:30?\nChunk 4: I am looking for places to go in town.\nChunk 5: The attraction should be in the type of museum and should be in the same area as the restaurant.\nChunk 6: Yes.\nChunk 7: May I have the number and address?\nChunk 8: That is everything thank you.", "input_token_count": 91, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: moderate. Next, cuisine: british. Next, the goal is booking; time: 8; day: friday; party size: 8 people. Next, destination: go in town. Next, the topic is attraction; the goal is modify constraint. Next, the goal is confirm booking. Next, the goal is request info; requested information: address. Finally, intent: context_update. In summary, The overall topic is attraction. the goal is request info. area: centre; price: moderate.; cuisine: british.; time: 8; day: friday; party size: 8 people.; destination: go in town.; requested information: address.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 cuisine+=british. C3 goal=booking; time+=8, 13:30; day+=friday; party_size+=8 people. C4 destination+=go in town. C5 domain=attraction; goal=modify_constraint. C6 goal=confirm_booking. C7 goal=request_info; requested_info+=address. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant near the centre, moderate priced, please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: moderate..", "trace": "domain=restaurant; goal=search; area+=centre; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like british food please That sounds great.", "streaming_reasoning": "As more information arrives, cuisine: british..", "trace": "cuisine+=british."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you book a table for 8 people on Friday at 13:30?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 8; day: friday; party size: 8 people..", "trace": "goal=booking; time+=8, 13:30; day+=friday; party_size+=8 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am looking for places to go in town.", "streaming_reasoning": "As more information arrives, destination: go in town..", "trace": "destination+=go in town."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The attraction should be in the type of museum and should be in the same area as the restaurant.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is modify constraint..", "trace": "domain=attraction; goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "May I have the number and address?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is everything thank you.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is british; price is moderate; party size is 8 people; destination is go in town; requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant, attraction; goal=search, booking, modify_constraint, request_info; area=centre; food=british; price=moderate; party_size=8 people; destination=go in town; requested_info=address; when=friday, 8, 13:30."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002509", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train departing for Cambridge after 8:15am.\nChunk 2: No thank you, I would like a train that is leaving on Thursday and departing from Kings Lynn.\nChunk 3: I need help with train.\nChunk 4: The time is 8:15.\nChunk 5: I also need the travel time.\nChunk 6: I also need the price Thank you.\nChunk 7: That is all I needed.", "streaming_reasoning": "C1 domain=train; goal=search; time+=8:15am. C2 day+=thursday; departure+=kings lynn. C3 intent=context_update. C4 time+=8:15. C5 goal=request_info; requested_info+=travel_time. C6 requested_info+=price. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; departure=kings lynn; requested_info=travel_time, price; when=thursday, 8:15am, 8:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a train departing for Cambridge after 8:15am.\nChunk 2: No thank you, I would like a train that is leaving on Thursday and departing from Kings Lynn.\nChunk 3: I need help with train.\nChunk 4: The time is 8:15.\nChunk 5: I also need the travel time.\nChunk 6: I also need the price Thank you.\nChunk 7: That is all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; time+=8:15am. C2 day+=thursday; departure+=kings lynn. C3 intent=context_update. C4 time+=8:15. C5 goal=request_info; requested_info+=travel_time. C6 requested_info+=price. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; departure=kings lynn; requested_info=travel_time, price; when=thursday, 8:15am, 8:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train departing for Cambridge after 8:15am.\nChunk 2: No thank you, I would like a train that is leaving on Thursday and departing from Kings Lynn.\nChunk 3: I need help with train.\nChunk 4: The time is 8:15.\nChunk 5: I also need the travel time.\nChunk 6: I also need the price Thank you.\nChunk 7: That is all I needed.", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 8:15am. Next, day: thursday; departure point: kings lynn. Next, intent: context_update. Next, time: 8:15. Next, the goal is request info; requested information: travel_time. Finally, requested information: price.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. time: 8:15am., 8:15.; day: thursday; departure point: kings lynn.; intent: context_update.; requested information: travel_time., price..", "trace": "C1 domain=train; goal=search; time+=8:15am. C2 day+=thursday; departure+=kings lynn. C3 intent=context_update. C4 time+=8:15. C5 goal=request_info; requested_info+=travel_time. C6 requested_info+=price. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a train departing for Cambridge after 8:15am.", "streaming_reasoning": "Initially, the topic is train; the goal is search; time: 8:15am..", "trace": "domain=train; goal=search; time+=8:15am."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No thank you, I would like a train that is leaving on Thursday and departing from Kings Lynn.", "streaming_reasoning": "As more information arrives, day: thursday; departure point: kings lynn..", "trace": "day+=thursday; departure+=kings lynn."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is 8:15.", "streaming_reasoning": "As more information arrives, time: 8:15..", "trace": "time+=8:15."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the travel time.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need the price Thank you.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I needed.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: departure point is kings lynn; requested information is travel_time; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; departure=kings lynn; requested_info=travel_time, price; when=thursday, 8:15am, 8:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002510", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a hotel with free parking.\nChunk 2: I do prefer that it be expensive and include wifi.\nChunk 3: Location does not matter.\nChunk 4: Yes, I would like to book that for five nights starting Wednesday and for eight people.\nChunk 5: I'm also looking for a nightclub to go to located in the centre.\nChunk 6: Can I get the address and phone number for the nightclub with an entrance fee of 4 pounds?\nChunk 7: Nope, you have been great!", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking. C2 price+=expensive; amenities+=wifi. C3 goal=modify_constraint. C4 goal=confirm_booking; day+=wednesday; party_size+=8 people; goal=confirm_booking. C5 area+=centre; destination+=go to located in the centre. C6 goal=request_info; requested_info+=address, phone, entrance_fee. C7 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=search, booking, confirm_booking, request_info; area=centre; price=expensive; party_size=8 people; amenities=parking, free parking, wifi; destination=go to located in the centre; requested_info=address, phone, entrance_fee; when=wednesday.", "answer": "I can help with that and include the address, phone, entrance fee once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a hotel with free parking.\nChunk 2: I do prefer that it be expensive and include wifi.\nChunk 3: Location does not matter.\nChunk 4: Yes, I would like to book that for five nights starting Wednesday and for eight people.\nChunk 5: I'm also looking for a nightclub to go to located in the centre.\nChunk 6: Can I get the address and phone number for the nightclub with an entrance fee of 4 pounds?\nChunk 7: Nope, you have been great!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking. C2 price+=expensive; amenities+=wifi. C3 goal=modify_constraint. C4 goal=confirm_booking; day+=wednesday; party_size+=8 people; goal=confirm_booking. C5 area+=centre; destination+=go to located in the centre. C6 goal=request_info; requested_info+=address, phone, entrance_fee. C7 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=search, booking, confirm_booking, request_info; area=centre; price=expensive; party_size=8 people; amenities=parking, free parking, wifi; destination=go to located in the centre; requested_info=address, phone, entrance_fee; when=wednesday.\n\nAnswer: I can help with that and include the address, phone, entrance fee once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a hotel with free parking.\nChunk 2: I do prefer that it be expensive and include wifi.\nChunk 3: Location does not matter.\nChunk 4: Yes, I would like to book that for five nights starting Wednesday and for eight people.\nChunk 5: I'm also looking for a nightclub to go to located in the centre.\nChunk 6: Can I get the address and phone number for the nightclub with an entrance fee of 4 pounds?\nChunk 7: Nope, you have been great!", "input_token_count": 89, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; amenities: parking. Next, price: expensive; amenities: wifi. Next, the goal is modify constraint. Next, the goal is confirm booking.; day: wednesday; party size: 8 people. Next, area: centre; destination: go to located in the centre. Next, the goal is request info; requested information: address. Finally, intent: context_update. In summary, The overall topic is hotel. the goal is request info. hotel type: hotel; amenities: parking, wifi.; price: expensive; day: wednesday; party size: 8 people; area: centre; destination: go to located in the centre.; requested information: address; intent: context_update..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking. C2 price+=expensive; amenities+=wifi. C3 goal=modify_constraint. C4 goal=confirm_booking; day+=wednesday; party_size+=8 people; goal=confirm_booking. C5 area+=centre; destination+=go to located in the centre. C6 goal=request_info; requested_info+=address, phone, entrance_fee. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a hotel with free parking.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; amenities: parking.", "trace": "domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I do prefer that it be expensive and include wifi.", "streaming_reasoning": "As more information arrives, price: expensive; amenities: wifi..", "trace": "price+=expensive; amenities+=wifi."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Location does not matter.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I would like to book that for five nights starting Wednesday and for eight people.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; day: wednesday; party size: 8 people.", "trace": "goal=confirm_booking; day+=wednesday; party_size+=8 people; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm also looking for a nightclub to go to located in the centre.", "streaming_reasoning": "As more information arrives, area: centre; destination: go to located in the centre..", "trace": "area+=centre; destination+=go to located in the centre."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I get the address and phone number for the nightclub with an entrance fee of 4 pounds?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, entrance_fee."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Nope, you have been great!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; price is expensive; party size is 8 people; amenities is parking; destination is go to located in the centre; requested information is address; timing is wednesday.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone, entrance fee once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, confirm_booking, request_info; area=centre; price=expensive; party_size=8 people; amenities=parking, free parking, wifi; destination=go to located in the centre; requested_info=address, phone, entrance_fee; when=wednesday."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002511", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It will be 3 nights for 8 people.\nChunk 2: Can we please try for 2 nights?\nChunk 3: What museums do you have in the centre That sounds good.\nChunk 4: Can you tell me what the entrance fee is?\nChunk 5: Thanks.\nChunk 6: Can I also have the address and postcode?\nChunk 7: No, you've been a great help.\nChunk 8: Thank you for your time Goodbye.", "streaming_reasoning": "C1 party_size+=8 people; stay_length+=3 nights. C2 stay_length+=2 nights. C3 area+=centre; acceptance=selected_option. C4 goal=request_info; requested_info+=entrance_fee. C5 [SKIP: thanks_only]. C6 requested_info+=address, postcode. C7 goal=search. C8 [SKIP: thanks_only].", "deep_reasoning": "Need goal=request_info, search; area=centre; party_size=8 people; stay_length=3 nights, 2 nights; requested_info=entrance_fee, address, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: It will be 3 nights for 8 people.\nChunk 2: Can we please try for 2 nights?\nChunk 3: What museums do you have in the centre That sounds good.\nChunk 4: Can you tell me what the entrance fee is?\nChunk 5: Thanks.\nChunk 6: Can I also have the address and postcode?\nChunk 7: No, you've been a great help.\nChunk 8: Thank you for your time Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 party_size+=8 people; stay_length+=3 nights. C2 stay_length+=2 nights. C3 area+=centre; acceptance=selected_option. C4 goal=request_info; requested_info+=entrance_fee. C5 [SKIP: thanks_only]. C6 requested_info+=address, postcode. C7 goal=search. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=request_info, search; area=centre; party_size=8 people; stay_length=3 nights, 2 nights; requested_info=entrance_fee, address, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It will be 3 nights for 8 people.\nChunk 2: Can we please try for 2 nights?\nChunk 3: What museums do you have in the centre That sounds good.\nChunk 4: Can you tell me what the entrance fee is?\nChunk 5: Thanks.\nChunk 6: Can I also have the address and postcode?\nChunk 7: No, you've been a great help.\nChunk 8: Thank you for your time Goodbye.", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, party size: 8 people; stay length: 3 nights. Next, stay length: 2 nights. Next, area: centre; acceptance: selected_option. Next, the goal is request info; requested information: entrance_fee. Next, requested information: address. Finally, the goal is search.  Some chunks were skipped because they contained thanks_only. In summary, the goal is search.. party size: 8 people; stay length: 3 nights., 2 nights.; area: centre; acceptance: selected_option.; requested information: entrance_fee., address.", "trace": "C1 party_size+=8 people; stay_length+=3 nights. C2 stay_length+=2 nights. C3 area+=centre; acceptance=selected_option. C4 goal=request_info; requested_info+=entrance_fee. C5 [SKIP: thanks_only]. C6 requested_info+=address, postcode. C7 goal=search. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "It will be 3 nights for 8 people.", "streaming_reasoning": "Initially, party size: 8 people; stay length: 3 nights..", "trace": "party_size+=8 people; stay_length+=3 nights."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can we please try for 2 nights?", "streaming_reasoning": "As more information arrives, stay length: 2 nights..", "trace": "stay_length+=2 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What museums do you have in the centre That sounds good.", "streaming_reasoning": "As more information arrives, area: centre; acceptance: selected_option..", "trace": "area+=centre; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you tell me what the entrance fee is?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I also have the address and postcode?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, you've been a great help.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for your time Goodbye.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=request_info, search; area=centre; party_size=8 people; stay_length=3 nights, 2 nights; requested_info=entrance_fee, address, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002512", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find a concert hall?\nChunk 2: I need a concerthall on the west area of town.\nChunk 3: Yes, I would consider a museum.\nChunk 4: Can you make a recommendation and please provide the entrance fee, phone number, and postcode.", "streaming_reasoning": "C1 goal=search. C2 area+=west. C3 domain=attraction; acceptance=selected_option. C4 goal=request_info; requested_info+=phone, postcode, entrance_fee, recommendation.", "deep_reasoning": "Need domain=attraction; goal=search, request_info; area=west; requested_info=phone, postcode, entrance_fee, recommendation.", "answer": "I can help with that and include the phone, postcode, entrance fee, recommendation once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you help me find a concert hall?\nChunk 2: I need a concerthall on the west area of town.\nChunk 3: Yes, I would consider a museum.\nChunk 4: Can you make a recommendation and please provide the entrance fee, phone number, and postcode."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 area+=west. C3 domain=attraction; acceptance=selected_option. C4 goal=request_info; requested_info+=phone, postcode, entrance_fee, recommendation.\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; area=west; requested_info=phone, postcode, entrance_fee, recommendation.\n\nAnswer: I can help with that and include the phone, postcode, entrance fee, recommendation once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find a concert hall?\nChunk 2: I need a concerthall on the west area of town.\nChunk 3: Yes, I would consider a museum.\nChunk 4: Can you make a recommendation and please provide the entrance fee, phone number, and postcode.", "input_token_count": 47, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, area: west. Next, the topic is attraction; acceptance: selected_option. Finally, the goal is request info; requested information: phone. In summary, The overall topic is attraction. the goal is request info. area: west.; acceptance: selected_option.; requested information: phone.", "trace": "C1 goal=search. C2 area+=west. C3 domain=attraction; acceptance=selected_option. C4 goal=request_info; requested_info+=phone, postcode, entrance_fee, recommendation.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you help me find a concert hall?", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need a concerthall on the west area of town.", "streaming_reasoning": "As more information arrives, area: west..", "trace": "area+=west."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I would consider a museum.", "streaming_reasoning": "As more information arrives, the topic is attraction; acceptance: selected_option..", "trace": "domain=attraction; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you make a recommendation and please provide the entrance fee, phone number, and postcode.", "streaming_reasoning": "Finally, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode, entrance_fee, recommendation."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is west; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, postcode, entrance fee, recommendation once I find the matching option.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; area=west; requested_info=phone, postcode, entrance_fee, recommendation."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002513", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you find me a guesthouse that includes wi-fi?\nChunk 2: Not a particular area, but I would like free parking.\nChunk 3: It is for 3 people.\nChunk 4: The time is thursday.\nChunk 5: I also need the price No thank you.\nChunk 6: Thank you for the reference number 7QVODJMI Goodbye.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=guesthouse. C2 amenities+=parking, free parking. C3 party_size+=3 people. C4 day+=thursday. C5 requested_info+=price. C6 goal=request_info; requested_info+=reference_number.", "deep_reasoning": "Need domain=hotel; goal=search, request_info; party_size=3 people; amenities=parking, free parking; requested_info=price, reference_number; when=thursday.", "answer": "I can help with that and include the price, reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you find me a guesthouse that includes wi-fi?\nChunk 2: Not a particular area, but I would like free parking.\nChunk 3: It is for 3 people.\nChunk 4: The time is thursday.\nChunk 5: I also need the price No thank you.\nChunk 6: Thank you for the reference number 7QVODJMI Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=guesthouse. C2 amenities+=parking, free parking. C3 party_size+=3 people. C4 day+=thursday. C5 requested_info+=price. C6 goal=request_info; requested_info+=reference_number.\n\nDeep reasoning: Need domain=hotel; goal=search, request_info; party_size=3 people; amenities=parking, free parking; requested_info=price, reference_number; when=thursday.\n\nAnswer: I can help with that and include the price, reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you find me a guesthouse that includes wi-fi?\nChunk 2: Not a particular area, but I would like free parking.\nChunk 3: It is for 3 people.\nChunk 4: The time is thursday.\nChunk 5: I also need the price No thank you.\nChunk 6: Thank you for the reference number 7QVODJMI Goodbye.", "input_token_count": 56, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse. Next, amenities: parking. Next, party size: 3 people. Next, day: thursday. Next, requested information: price. Finally, the goal is request info; requested information: reference_number. In summary, The overall topic is hotel. the goal is request info. hotel type: guesthouse.; amenities: parking; party size: 3 people.; day: thursday.; requested information: price., reference_number..", "trace": "C1 domain=hotel; goal=search; hotel_type+=guesthouse. C2 amenities+=parking, free parking. C3 party_size+=3 people. C4 day+=thursday. C5 requested_info+=price. C6 goal=request_info; requested_info+=reference_number.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you find me a guesthouse that includes wi-fi?", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Not a particular area, but I would like free parking.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 3 people.", "streaming_reasoning": "As more information arrives, party size: 3 people..", "trace": "party_size+=3 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is thursday.", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the price No thank you.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for the reference number 7QVODJMI Goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 3 people; amenities is parking; requested information is price; timing is thursday.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the price, reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info; party_size=3 people; amenities=parking, free parking; requested_info=price, reference_number; when=thursday."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002514", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a moderate priced place to stay with free wifi.\nChunk 2: I am not sure what day, I am just researching now.\nChunk 3: I would like to have a 4 star hotel.\nChunk 4: Are there any options?\nChunk 5: I do not have a preference on area.\nChunk 6: does it have wifi?\nChunk 7: The time is thursday, 1, 3.\nChunk 8: Please make a booking.\nChunk 9: Yes, I need a train to peterbourough on Sunday.", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=moderate; amenities+=wifi; destination+=stay with free wifi. C2 goal=modify_constraint. C3 hotel_type+=hotel; stars+=4 stars; destination+=have a 4 star hotel. C4 goal=request_info. C5 goal=modify_constraint. C6 goal=request_info. C7 time+=1, 3; day+=thursday. C8 goal=booking. C9 domain=train; day+=sunday; destination+=peterbourough on sunday; goal=confirm_booking.", "deep_reasoning": "Need domain=hotel, train; goal=search, booking; price=moderate; stars=4 stars; amenities=wifi; destination=stay with free wifi, have a 4 star hotel, peterbourough on sunday; when=thursday, sunday, 1, 3.", "answer": "What area, guests should I use for the search?", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a moderate priced place to stay with free wifi.\nChunk 2: I am not sure what day, I am just researching now.\nChunk 3: I would like to have a 4 star hotel.\nChunk 4: Are there any options?\nChunk 5: I do not have a preference on area.\nChunk 6: does it have wifi?\nChunk 7: The time is thursday, 1, 3.\nChunk 8: Please make a booking.\nChunk 9: Yes, I need a train to peterbourough on Sunday."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=moderate; amenities+=wifi; destination+=stay with free wifi. C2 goal=modify_constraint. C3 hotel_type+=hotel; stars+=4 stars; destination+=have a 4 star hotel. C4 goal=request_info. C5 goal=modify_constraint. C6 goal=request_info. C7 time+=1, 3; day+=thursday. C8 goal=booking. C9 domain=train; day+=sunday; destination+=peterbourough on sunday; goal=confirm_booking.\n\nDeep reasoning: Need domain=hotel, train; goal=search, booking; price=moderate; stars=4 stars; amenities=wifi; destination=stay with free wifi, have a 4 star hotel, peterbourough on sunday; when=thursday, sunday, 1, 3.\n\nAnswer: What area, guests should I use for the search?"}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a moderate priced place to stay with free wifi.\nChunk 2: I am not sure what day, I am just researching now.\nChunk 3: I would like to have a 4 star hotel.\nChunk 4: Are there any options?\nChunk 5: I do not have a preference on area.\nChunk 6: does it have wifi?\nChunk 7: The time is thursday, 1, 3.\nChunk 8: Please make a booking.\nChunk 9: Yes, I need a train to peterbourough on Sunday.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: moderate; amenities: wifi; destination: stay with free wifi. Next, the goal is modify constraint. Next, hotel type: hotel; star rating: 4 stars; destination: have a 4 star hotel. Next, the goal is request info. Next, the goal is modify constraint. Next, the goal is request info. Next, time: 1; day: thursday. Next, the goal is booking. Finally, the topic is train; the goal is confirm booking.; day: sunday; destination: peterbourough on sunday. In summary, The overall topic is train. the goal is confirm booking.. price: moderate; amenities: wifi; destination: stay with free wifi., have a 4 star hotel., peterbourough on sunday; hotel type: hotel; star rating: 4 stars; time: 1; day: thursday., sunday.", "trace": "C1 domain=hotel; goal=search; price+=moderate; amenities+=wifi; destination+=stay with free wifi. C2 goal=modify_constraint. C3 hotel_type+=hotel; stars+=4 stars; destination+=have a 4 star hotel. C4 goal=request_info. C5 goal=modify_constraint. C6 goal=request_info. C7 time+=1, 3; day+=thursday. C8 goal=booking. C9 domain=train; day+=sunday; destination+=peterbourough on sunday; goal=confirm_booking.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a moderate priced place to stay with free wifi.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: moderate; amenities: wifi; destination: stay with free wifi..", "trace": "domain=hotel; goal=search; price+=moderate; amenities+=wifi; destination+=stay with free wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am not sure what day, I am just researching now.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to have a 4 star hotel.", "streaming_reasoning": "As more information arrives, hotel type: hotel; star rating: 4 stars; destination: have a 4 star hotel..", "trace": "hotel_type+=hotel; stars+=4 stars; destination+=have a 4 star hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Are there any options?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I do not have a preference on area.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "does it have wifi?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is thursday, 1, 3.", "streaming_reasoning": "As more information arrives, time: 1; day: thursday..", "trace": "time+=1, 3; day+=thursday."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Yes, I need a train to peterbourough on Sunday.", "streaming_reasoning": "Finally, the topic is train; the goal is confirm booking.; day: sunday; destination: peterbourough on sunday.", "trace": "domain=train; day+=sunday; destination+=peterbourough on sunday; goal=confirm_booking."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is moderate; star rating is 4 stars; amenities is wifi; destination is stay with free wifi; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "What area, guests should I use for the search?", "deep_reasoning_trace": "Need domain=hotel, train; goal=search, booking; price=moderate; stars=4 stars; amenities=wifi; destination=stay with free wifi, have a 4 star hotel, peterbourough on sunday; when=thursday, sunday, 1, 3."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002515", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you book the hotel for 8 people for 2 nights starting Monday?\nChunk 2: Looking for places to go in the same area as the hotel, possibly a concerthall.\nChunk 3: Well I guess that's where I'll be then.\nChunk 4: Can you tell me the address and entrance fee?\nChunk 5: Yes, I also need a taxi to leave the attraction please To my hotel.\nChunk 6: I want to leave the attraction by 08:45 please.\nChunk 7: That is all I needed.\nChunk 8: You were very helpful.", "streaming_reasoning": "C1 domain=hotel; goal=booking; time+=8, 2; day+=monday; party_size+=8 people; stay_length+=2 nights; hotel_type+=hotel. C2 goal=modify_constraint; destination+=go in the same area as the hotel. C3 intent=context_update. C4 goal=request_info; requested_info+=address, entrance_fee. C5 domain=attraction; destination+=leave the attraction please to my hotel; goal=confirm_booking. C6 [SKIP: repeated_information]. C7 [SKIP: closing_only]. C8 intent=context_update.", "deep_reasoning": "Need domain=hotel, taxi, attraction; goal=booking, search, modify_constraint, request_info; party_size=8 people; stay_length=2 nights; destination=go in the same area as the hotel, leave the attraction please to my hotel; requested_info=address, entrance_fee; when=monday, 8, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Could you book the hotel for 8 people for 2 nights starting Monday?\nChunk 2: Looking for places to go in the same area as the hotel, possibly a concerthall.\nChunk 3: Well I guess that's where I'll be then.\nChunk 4: Can you tell me the address and entrance fee?\nChunk 5: Yes, I also need a taxi to leave the attraction please To my hotel.\nChunk 6: I want to leave the attraction by 08:45 please.\nChunk 7: That is all I needed.\nChunk 8: You were very helpful."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=booking; time+=8, 2; day+=monday; party_size+=8 people; stay_length+=2 nights; hotel_type+=hotel. C2 goal=modify_constraint; destination+=go in the same area as the hotel. C3 intent=context_update. C4 goal=request_info; requested_info+=address, entrance_fee. C5 domain=attraction; destination+=leave the attraction please to my hotel; goal=confirm_booking. C6 [SKIP: repeated_information]. C7 [SKIP: closing_only]. C8 intent=context_update.\n\nDeep reasoning: Need domain=hotel, taxi, attraction; goal=booking, search, modify_constraint, request_info; party_size=8 people; stay_length=2 nights; destination=go in the same area as the hotel, leave the attraction please to my hotel; requested_info=address, entrance_fee; when=monday, 8, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you book the hotel for 8 people for 2 nights starting Monday?\nChunk 2: Looking for places to go in the same area as the hotel, possibly a concerthall.\nChunk 3: Well I guess that's where I'll be then.\nChunk 4: Can you tell me the address and entrance fee?\nChunk 5: Yes, I also need a taxi to leave the attraction please To my hotel.\nChunk 6: I want to leave the attraction by 08:45 please.\nChunk 7: That is all I needed.\nChunk 8: You were very helpful.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is booking; time: 8; day: monday; party size: 8 people; stay length: 2 nights; hotel type: hotel. Next, the goal is modify constraint; destination: go in the same area as the hotel. Next, intent: context_update. Next, the goal is request info; requested information: address. Next, the topic is attraction; the goal is confirm booking.; destination: leave the attraction please to my hotel. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is attraction. the goal is confirm booking.. time: 8; day: monday; party size: 8 people; stay length: 2 nights; hotel type: hotel.; destination: go in the same area as the hotel., leave the attraction please to my hotel; intent: context_update.; requested information: address.", "trace": "C1 domain=hotel; goal=booking; time+=8, 2; day+=monday; party_size+=8 people; stay_length+=2 nights; hotel_type+=hotel. C2 goal=modify_constraint; destination+=go in the same area as the hotel. C3 intent=context_update. C4 goal=request_info; requested_info+=address, entrance_fee. C5 domain=attraction; destination+=leave the attraction please to my hotel; goal=confirm_booking. C6 [SKIP: repeated_information]. C7 [SKIP: closing_only]. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Could you book the hotel for 8 people for 2 nights starting Monday?", "streaming_reasoning": "Initially, the topic is hotel; the goal is booking; time: 8; day: monday; party size: 8 people; stay length: 2 nights; hotel type: hotel..", "trace": "domain=hotel; goal=booking; time+=8, 2; day+=monday; party_size+=8 people; stay_length+=2 nights; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Looking for places to go in the same area as the hotel, possibly a concerthall.", "streaming_reasoning": "As more information arrives, the goal is modify constraint; destination: go in the same area as the hotel..", "trace": "goal=modify_constraint; destination+=go in the same area as the hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Well I guess that's where I'll be then.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you tell me the address and entrance fee?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, I also need a taxi to leave the attraction please To my hotel.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is confirm booking.; destination: leave the attraction please to my hotel.", "trace": "domain=attraction; destination+=leave the attraction please to my hotel; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to leave the attraction by 08:45 please.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I needed.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "You were very helpful.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: party size is 8 people; stay length is 2 nights; destination is go in the same area as the hotel; requested information is address; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, taxi, attraction; goal=booking, search, modify_constraint, request_info; party_size=8 people; stay_length=2 nights; destination=go in the same area as the hotel, leave the attraction please to my hotel; requested_info=address, entrance_fee; when=monday, 8, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002516", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I'm looking for a college to visit.\nChunk 2: the centre around the same area as the restaurant do you have any suggestions?\nChunk 3: That's a great suggestion.\nChunk 4: Thanks.\nChunk 5: I will also need a taxi between the college and the restaurant, please.\nChunk 6: I just need it to arrive by 12:15 for the reservation.\nChunk 7: Thank you so much!, Have a great Day!\nChunk 8: Thank you good bye.", "streaming_reasoning": "C1 domain=attraction; goal=search; destination+=visit; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; area+=centre. C3 intent=context_update. C4 [SKIP: thanks_only]. C5 domain=taxi. C6 goal=booking; time+=12:15; destination+=arrive by 12:15 for the reservation. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, restaurant, taxi; goal=search, modify_constraint, booking; area=centre; destination=visit, arrive by 12:15 for the reservation; when=12:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I'm looking for a college to visit.\nChunk 2: the centre around the same area as the restaurant do you have any suggestions?\nChunk 3: That's a great suggestion.\nChunk 4: Thanks.\nChunk 5: I will also need a taxi between the college and the restaurant, please.\nChunk 6: I just need it to arrive by 12:15 for the reservation.\nChunk 7: Thank you so much!, Have a great Day!\nChunk 8: Thank you good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search; destination+=visit; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; area+=centre. C3 intent=context_update. C4 [SKIP: thanks_only]. C5 domain=taxi. C6 goal=booking; time+=12:15; destination+=arrive by 12:15 for the reservation. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, restaurant, taxi; goal=search, modify_constraint, booking; area=centre; destination=visit, arrive by 12:15 for the reservation; when=12:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I'm looking for a college to visit.\nChunk 2: the centre around the same area as the restaurant do you have any suggestions?\nChunk 3: That's a great suggestion.\nChunk 4: Thanks.\nChunk 5: I will also need a taxi between the college and the restaurant, please.\nChunk 6: I just need it to arrive by 12:15 for the reservation.\nChunk 7: Thank you so much!, Have a great Day!\nChunk 8: Thank you good bye.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; destination: visit; acceptance: selected_option. Next, the topic is restaurant; the goal is modify constraint; area: centre. Next, intent: context_update. Next, the topic is taxi. Finally, the goal is booking; time: 12:15; destination: arrive by 12:15 for the reservation.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is taxi.. the goal is booking. destination: visit, arrive by 12:15 for the reservation.; acceptance: selected_option.; area: centre.; intent: context_update.; time: 12:15.", "trace": "C1 domain=attraction; goal=search; destination+=visit; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; area+=centre. C3 intent=context_update. C4 [SKIP: thanks_only]. C5 domain=taxi. C6 goal=booking; time+=12:15; destination+=arrive by 12:15 for the reservation. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I'm looking for a college to visit.", "streaming_reasoning": "Initially, the topic is attraction; the goal is search; destination: visit; acceptance: selected_option..", "trace": "domain=attraction; goal=search; destination+=visit; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "the centre around the same area as the restaurant do you have any suggestions?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint; area: centre..", "trace": "domain=restaurant; goal=modify_constraint; area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That's a great suggestion.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will also need a taxi between the college and the restaurant, please.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I just need it to arrive by 12:15 for the reservation.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 12:15; destination: arrive by 12:15 for the reservation..", "trace": "goal=booking; time+=12:15; destination+=arrive by 12:15 for the reservation."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you so much!, Have a great Day!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you good bye.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; destination is visit; timing is 12:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant, taxi; goal=search, modify_constraint, booking; area=centre; destination=visit, arrive by 12:15 for the reservation; when=12:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001690", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ive been doing quite well for myself the past few months and things have been going well so im happy.\nChunk 2: The past few months have been going quite well, im happy with how things have gone.\nChunk 3: good to hear that, what is interesting.\nChunk 4: Things have just been going how i planned and im pretty stress free so its been nice for once.", "streaming_reasoning": "C1 emotion=happy; need=celebration. C2 emotion=happy. C3 support_signal=received. C4 emotion=stressed; cause=Things have just been going how i planned and im pretty stress; need=validation.", "deep_reasoning": "User feels stressed after Things have just been going how i planned and im pretty stress and needs validation.", "answer": "It makes sense to feel stressed after Things have just been going how i planned and im pretty stress. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Ive been doing quite well for myself the past few months and things have been going well so im happy.\nChunk 2: The past few months have been going quite well, im happy with how things have gone.\nChunk 3: good to hear that, what is interesting.\nChunk 4: Things have just been going how i planned and im pretty stress free so its been nice for once."}, {"role": "assistant", "content": "Streaming reasoning: C1 emotion=happy; need=celebration. C2 emotion=happy. C3 support_signal=received. C4 emotion=stressed; cause=Things have just been going how i planned and im pretty stress; need=validation.\n\nDeep reasoning: User feels stressed after Things have just been going how i planned and im pretty stress and needs validation.\n\nAnswer: It makes sense to feel stressed after Things have just been going how i planned and im pretty stress. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ive been doing quite well for myself the past few months and things have been going well so im happy.\nChunk 2: The past few months have been going quite well, im happy with how things have gone.\nChunk 3: good to hear that, what is interesting.\nChunk 4: Things have just been going how i planned and im pretty stress free so its been nice for once.", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user expresses happy; the user needs celebration. Next, the user expresses happy. Next, the user signals support or acknowledgment. Finally, the user expresses stressed about Things have just been going how i planned and im pretty stress; the user needs validation.", "trace": "C1 emotion=happy; need=celebration. C2 emotion=happy. C3 support_signal=received. C4 emotion=stressed; cause=Things have just been going how i planned and im pretty stress; need=validation.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Ive been doing quite well for myself the past few months and things have been going well so im happy.", "streaming_reasoning": "Initially, the user expresses happy; the user needs celebration..", "trace": "emotion=happy; need=celebration."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The past few months have been going quite well, im happy with how things have gone.", "streaming_reasoning": "As more information arrives, the user expresses happy..", "trace": "emotion=happy."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "good to hear that, what is interesting.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Things have just been going how i planned and im pretty stress free so its been nice for once.", "streaming_reasoning": "Finally, the user expresses stressed about Things have just been going how i planned and im pretty stress; the user needs validation..", "trace": "emotion=stressed; cause=Things have just been going how i planned and im pretty stress; need=validation."}]}, "output": {"deep_reasoning": "User feels stressed after Things have just been going how i planned and im pretty stress and needs validation.", "answer": "It makes sense to feel stressed after Things have just been going how i planned and im pretty stress. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000523", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Brew White Tea.\nChunk 2: • Loose leaf white tea (two teaspoons per cup) • Water.\nChunk 3: filtered if possible • A kettle • Cups • A strainer • A clock to determine steeping time.", "streaming_reasoning": "C1 task=brew_white_tea. C2 step=loose_leaf_white_tea. C3 step=filtered_if_possible_a.", "deep_reasoning": "Procedure for Brew White Tea: Loose leaf white tea Water, filtered if possible A kettle Cups A strainer A clock.", "answer": "For Brew White Tea, follow the steps in order: Loose leaf white tea Water, filtered if possible A kettle Cups A strainer A clock.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Brew White Tea.\nChunk 2: • Loose leaf white tea (two teaspoons per cup) • Water.\nChunk 3: filtered if possible • A kettle • Cups • A strainer • A clock to determine steeping time."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=brew_white_tea. C2 step=loose_leaf_white_tea. C3 step=filtered_if_possible_a.\n\nDeep reasoning: Procedure for Brew White Tea: Loose leaf white tea Water, filtered if possible A kettle Cups A strainer A clock.\n\nAnswer: For Brew White Tea, follow the steps in order: Loose leaf white tea Water, filtered if possible A kettle Cups A strainer A clock."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Brew White Tea.\nChunk 2: • Loose leaf white tea (two teaspoons per cup) • Water.\nChunk 3: filtered if possible • A kettle • Cups • A strainer • A clock to determine steeping time.", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, task: brew_white_tea. Next, step: loose_leaf_white_tea. Finally, step: filtered_if_possible_a. In summary, task: brew_white_tea.; step: loose_leaf_white_tea., filtered_if_possible_a..", "trace": "C1 task=brew_white_tea. C2 step=loose_leaf_white_tea. C3 step=filtered_if_possible_a.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Brew White Tea.", "streaming_reasoning": "Initially, task: brew_white_tea..", "trace": "task=brew_white_tea."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• Loose leaf white tea (two teaspoons per cup) • Water.", "streaming_reasoning": "As more information arrives, step: loose_leaf_white_tea..", "trace": "step=loose_leaf_white_tea."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "filtered if possible • A kettle • Cups • A strainer • A clock to determine steeping time.", "streaming_reasoning": "Finally, step: filtered_if_possible_a..", "trace": "step=filtered_if_possible_a."}]}, "output": {"deep_reasoning": "Procedure for Brew White Tea: Loose leaf white tea Water, filtered if possible A kettle Cups A strainer A clock.", "answer": "For Brew White Tea, follow the steps in order: Loose leaf white tea Water, filtered if possible A kettle Cups A strainer A clock."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002518", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I prefer a nightclub in the centre area.\nChunk 2: The Fez sounds great.\nChunk 3: Can I get their phone number?\nChunk 4: Can you help me find a train going to Ely on Monday?\nChunk 5: I would need to leave cambridge after 13:15 on Monday, please.\nChunk 6: For now, can you just give me the price and travel time of TR5167?\nChunk 7: I think that is all I need to know for now Thank you.", "streaming_reasoning": "C1 area+=centre. C2 intent=context_update. C3 goal=request_info; requested_info+=phone. C4 domain=train; goal=search; day+=monday; destination+=ely on monday. C5 time+=13:15; destination+=leave cambridge after 13:15 on monday. C6 requested_info+=travel_time, price. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=request_info, search; area=centre; destination=ely on monday, leave cambridge after 13:15 on monday; requested_info=phone, travel_time, price; when=monday, 13:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I prefer a nightclub in the centre area.\nChunk 2: The Fez sounds great.\nChunk 3: Can I get their phone number?\nChunk 4: Can you help me find a train going to Ely on Monday?\nChunk 5: I would need to leave cambridge after 13:15 on Monday, please.\nChunk 6: For now, can you just give me the price and travel time of TR5167?\nChunk 7: I think that is all I need to know for now Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre. C2 intent=context_update. C3 goal=request_info; requested_info+=phone. C4 domain=train; goal=search; day+=monday; destination+=ely on monday. C5 time+=13:15; destination+=leave cambridge after 13:15 on monday. C6 requested_info+=travel_time, price. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search; area=centre; destination=ely on monday, leave cambridge after 13:15 on monday; requested_info=phone, travel_time, price; when=monday, 13:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I prefer a nightclub in the centre area.\nChunk 2: The Fez sounds great.\nChunk 3: Can I get their phone number?\nChunk 4: Can you help me find a train going to Ely on Monday?\nChunk 5: I would need to leave cambridge after 13:15 on Monday, please.\nChunk 6: For now, can you just give me the price and travel time of TR5167?\nChunk 7: I think that is all I need to know for now Thank you.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: centre. Next, intent: context_update. Next, the goal is request info; requested information: phone. Next, the topic is train; the goal is search; day: monday; destination: ely on monday. Next, time: 13:15; destination: leave cambridge after 13:15 on monday. Finally, requested information: travel_time.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is search. area: centre.; intent: context_update.; requested information: phone., travel_time; day: monday; destination: ely on monday., leave cambridge after 13:15 on monday.; time: 13:15.", "trace": "C1 area+=centre. C2 intent=context_update. C3 goal=request_info; requested_info+=phone. C4 domain=train; goal=search; day+=monday; destination+=ely on monday. C5 time+=13:15; destination+=leave cambridge after 13:15 on monday. C6 requested_info+=travel_time, price. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I prefer a nightclub in the centre area.", "streaming_reasoning": "Initially, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The Fez sounds great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I get their phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you help me find a train going to Ely on Monday?", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: monday; destination: ely on monday..", "trace": "domain=train; goal=search; day+=monday; destination+=ely on monday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would need to leave cambridge after 13:15 on Monday, please.", "streaming_reasoning": "As more information arrives, time: 13:15; destination: leave cambridge after 13:15 on monday..", "trace": "time+=13:15; destination+=leave cambridge after 13:15 on monday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "For now, can you just give me the price and travel time of TR5167?", "streaming_reasoning": "As more information arrives, requested information: travel_time.", "trace": "requested_info+=travel_time, price."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I think that is all I need to know for now Thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: area is centre; destination is ely on monday; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search; area=centre; destination=ely on monday, leave cambridge after 13:15 on monday; requested_info=phone, travel_time, price; when=monday, 13:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002519", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok book for 1 please.\nChunk 2: I also need a hotel in the west and should be in the moderate price range.\nChunk 3: The hotel should have a star of 3.\nChunk 4: Yes, for 2 people for 3 nights On Saturday please.\nChunk 5: Awesome, thanks so much for your help!\nChunk 6: That is all I needed, have a good day.", "streaming_reasoning": "C1 goal=booking. C2 domain=hotel; goal=search; area+=west; price+=moderate; hotel_type+=hotel; requested_info+=price. C3 intent=context_update. C4 day+=saturday; party_size+=2 people; stay_length+=3 nights; goal=confirm_booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=booking, search; area=west; price=moderate; party_size=2 people; stay_length=3 nights; requested_info=price; when=saturday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Ok book for 1 please.\nChunk 2: I also need a hotel in the west and should be in the moderate price range.\nChunk 3: The hotel should have a star of 3.\nChunk 4: Yes, for 2 people for 3 nights On Saturday please.\nChunk 5: Awesome, thanks so much for your help!\nChunk 6: That is all I needed, have a good day."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking. C2 domain=hotel; goal=search; area+=west; price+=moderate; hotel_type+=hotel; requested_info+=price. C3 intent=context_update. C4 day+=saturday; party_size+=2 people; stay_length+=3 nights; goal=confirm_booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=booking, search; area=west; price=moderate; party_size=2 people; stay_length=3 nights; requested_info=price; when=saturday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok book for 1 please.\nChunk 2: I also need a hotel in the west and should be in the moderate price range.\nChunk 3: The hotel should have a star of 3.\nChunk 4: Yes, for 2 people for 3 nights On Saturday please.\nChunk 5: Awesome, thanks so much for your help!\nChunk 6: That is all I needed, have a good day.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking. Next, the topic is hotel; the goal is search; area: west; price: moderate; hotel type: hotel; requested information: price. Next, intent: context_update. Finally, the goal is confirm booking.; day: saturday; party size: 2 people; stay length: 3 nights.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is confirm booking.. area: west; price: moderate; hotel type: hotel; requested information: price.; intent: context_update.; day: saturday; party size: 2 people; stay length: 3 nights.", "trace": "C1 goal=booking. C2 domain=hotel; goal=search; area+=west; price+=moderate; hotel_type+=hotel; requested_info+=price. C3 intent=context_update. C4 day+=saturday; party_size+=2 people; stay_length+=3 nights; goal=confirm_booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Ok book for 1 please.", "streaming_reasoning": "Initially, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need a hotel in the west and should be in the moderate price range.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; area: west; price: moderate; hotel type: hotel; requested information: price..", "trace": "domain=hotel; goal=search; area+=west; price+=moderate; hotel_type+=hotel; requested_info+=price."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The hotel should have a star of 3.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, for 2 people for 3 nights On Saturday please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; day: saturday; party size: 2 people; stay length: 3 nights.", "trace": "day+=saturday; party_size+=2 people; stay_length+=3 nights; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Awesome, thanks so much for your help!", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all I needed, have a good day.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: area is west; price is moderate; party size is 2 people; stay length is 3 nights; requested information is price; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, search; area=west; price=moderate; party_size=2 people; stay_length=3 nights; requested_info=price; when=saturday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002520", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello I am looking for a college, can you help me?\nChunk 2: Do you have any in the centre Sure!\nChunk 3: Which one do you recommend?\nChunk 4: What is the phone number and postcode for that one?\nChunk 5: Could I get the complete address please?\nChunk 6: No, you have helped me Thank you!", "streaming_reasoning": "C1 domain=attraction; goal=search. C2 area+=centre. C3 goal=recommendation. C4 goal=request_info; requested_info+=phone, postcode. C5 requested_info+=address. C6 goal=modify_constraint.", "deep_reasoning": "Need domain=attraction; goal=search, recommendation, request_info; area=centre; requested_info=phone, postcode, address.", "answer": "I can help with that and include the phone, postcode, address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello I am looking for a college, can you help me?\nChunk 2: Do you have any in the centre Sure!\nChunk 3: Which one do you recommend?\nChunk 4: What is the phone number and postcode for that one?\nChunk 5: Could I get the complete address please?\nChunk 6: No, you have helped me Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search. C2 area+=centre. C3 goal=recommendation. C4 goal=request_info; requested_info+=phone, postcode. C5 requested_info+=address. C6 goal=modify_constraint.\n\nDeep reasoning: Need domain=attraction; goal=search, recommendation, request_info; area=centre; requested_info=phone, postcode, address.\n\nAnswer: I can help with that and include the phone, postcode, address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello I am looking for a college, can you help me?\nChunk 2: Do you have any in the centre Sure!\nChunk 3: Which one do you recommend?\nChunk 4: What is the phone number and postcode for that one?\nChunk 5: Could I get the complete address please?\nChunk 6: No, you have helped me Thank you!", "input_token_count": 60, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search. Next, area: centre. Next, the goal is recommendation. Next, the goal is request info; requested information: phone. Next, requested information: address. Finally, the goal is modify constraint. In summary, The overall topic is attraction. the goal is modify constraint.. area: centre.; requested information: phone, address..", "trace": "C1 domain=attraction; goal=search. C2 area+=centre. C3 goal=recommendation. C4 goal=request_info; requested_info+=phone, postcode. C5 requested_info+=address. C6 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello I am looking for a college, can you help me?", "streaming_reasoning": "Initially, the topic is attraction; the goal is search..", "trace": "domain=attraction; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do you have any in the centre Sure!", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Which one do you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is the phone number and postcode for that one?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Could I get the complete address please?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, you have helped me Thank you!", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, postcode, address once I find the matching option.", "deep_reasoning_trace": "Need domain=attraction; goal=search, recommendation, request_info; area=centre; requested_info=phone, postcode, address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002521", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm also wanting to stay at the Alpha-Milton Guest House.\nChunk 2: Can you help with that?\nChunk 3: Yes.\nChunk 4: Three nights, from Wednesday 8 people Thank you.\nChunk 5: I also need a taxi two commute between the hotel and restaurant.\nChunk 6: I need to arrive at the restaurant in time for our reservation.\nChunk 7: Wouldn't want to miss my booked time.\nChunk 8: Our reservations are for 11:15.\nChunk 9: No thanks That does it.\nChunk 10: Have a good night.\nChunk 11: Bye.", "streaming_reasoning": "C1 domain=hotel; hotel_type+=guesthouse; destination+=stay at the alpha-milton guest house. C2 goal=search. C3 [SKIP: acknowledgement_only]. C4 day+=wednesday; party_size+=8 people. C5 domain=taxi; hotel_type+=hotel. C6 goal=booking; destination+=arrive at the restaurant in time for our. C7 intent=context_update. C8 time+=11:15. C9 [SKIP: thanks_only]. C10 intent=context_update. C11 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant, taxi; goal=search, booking; party_size=8 people; destination=stay at the alpha-milton guest house, arrive at the restaurant in time for our; when=wednesday, 11:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm also wanting to stay at the Alpha-Milton Guest House.\nChunk 2: Can you help with that?\nChunk 3: Yes.\nChunk 4: Three nights, from Wednesday 8 people Thank you.\nChunk 5: I also need a taxi two commute between the hotel and restaurant.\nChunk 6: I need to arrive at the restaurant in time for our reservation.\nChunk 7: Wouldn't want to miss my booked time.\nChunk 8: Our reservations are for 11:15.\nChunk 9: No thanks That does it.\nChunk 10: Have a good night.\nChunk 11: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=guesthouse; destination+=stay at the alpha-milton guest house. C2 goal=search. C3 [SKIP: acknowledgement_only]. C4 day+=wednesday; party_size+=8 people. C5 domain=taxi; hotel_type+=hotel. C6 goal=booking; destination+=arrive at the restaurant in time for our. C7 intent=context_update. C8 time+=11:15. C9 [SKIP: thanks_only]. C10 intent=context_update. C11 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant, taxi; goal=search, booking; party_size=8 people; destination=stay at the alpha-milton guest house, arrive at the restaurant in time for our; when=wednesday, 11:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm also wanting to stay at the Alpha-Milton Guest House.\nChunk 2: Can you help with that?\nChunk 3: Yes.\nChunk 4: Three nights, from Wednesday 8 people Thank you.\nChunk 5: I also need a taxi two commute between the hotel and restaurant.\nChunk 6: I need to arrive at the restaurant in time for our reservation.\nChunk 7: Wouldn't want to miss my booked time.\nChunk 8: Our reservations are for 11:15.\nChunk 9: No thanks That does it.\nChunk 10: Have a good night.\nChunk 11: Bye.", "input_token_count": 93, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse; destination: stay at the alpha-milton guest house. Next, the goal is search. Next, day: wednesday; party size: 8 people. Next, the topic is taxi; hotel type: hotel. Next, the goal is booking; destination: arrive at the restaurant in time for our. Next, intent: context_update. Next, time: 11:15. Finally, intent: context_update.  Some chunks were skipped because they contained acknowledgement_only or closing_only or thanks_only. In summary, The overall topic is taxi. the goal is booking. hotel type: guesthouse, hotel.; destination: stay at the alpha-milton guest house., arrive at the restaurant in time for our.; day: wednesday; party size: 8 people.; intent: context_update.; time: 11:15..", "trace": "C1 domain=hotel; hotel_type+=guesthouse; destination+=stay at the alpha-milton guest house. C2 goal=search. C3 [SKIP: acknowledgement_only]. C4 day+=wednesday; party_size+=8 people. C5 domain=taxi; hotel_type+=hotel. C6 goal=booking; destination+=arrive at the restaurant in time for our. C7 intent=context_update. C8 time+=11:15. C9 [SKIP: thanks_only]. C10 intent=context_update. C11 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm also wanting to stay at the Alpha-Milton Guest House.", "streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse; destination: stay at the alpha-milton guest house..", "trace": "domain=hotel; hotel_type+=guesthouse; destination+=stay at the alpha-milton guest house."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you help with that?", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes.", "streaming_reasoning": "The content at C3 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Three nights, from Wednesday 8 people Thank you.", "streaming_reasoning": "As more information arrives, day: wednesday; party size: 8 people..", "trace": "day+=wednesday; party_size+=8 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need a taxi two commute between the hotel and restaurant.", "streaming_reasoning": "As more information arrives, the topic is taxi; hotel type: hotel..", "trace": "domain=taxi; hotel_type+=hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need to arrive at the restaurant in time for our reservation.", "streaming_reasoning": "As more information arrives, the goal is booking; destination: arrive at the restaurant in time for our..", "trace": "goal=booking; destination+=arrive at the restaurant in time for our."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Wouldn't want to miss my booked time.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Our reservations are for 11:15.", "streaming_reasoning": "As more information arrives, time: 11:15..", "trace": "time+=11:15."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No thanks That does it.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Have a good night.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Bye.", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 8 people; destination is stay at the alpha-milton guest house; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant, taxi; goal=search, booking; party_size=8 people; destination=stay at the alpha-milton guest house, arrive at the restaurant in time for our; when=wednesday, 11:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002522", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please and provide me with the reference number as well.\nChunk 2: I need place to stay with free wifi It doesn't matter.\nChunk 3: I like 4 star guesthouses though.\nChunk 4: I'd prefer something in the moderate price range That sounds good.\nChunk 5: Can I get that for 8 people for 4 nights starting Thursday Thank you!\nChunk 6: That is all that I need!", "streaming_reasoning": "C1 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C2 domain=hotel; goal=search; amenities+=wifi; destination+=stay with free wifi it doesn't matter. C3 hotel_type+=guesthouse; stars+=4 stars. C4 price+=moderate; acceptance=selected_option. C5 time+=8, 4; day+=thursday; party_size+=8 people; stay_length+=4 nights. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=request_info, search; price=moderate; party_size=8 people; stay_length=4 nights; stars=4 stars; amenities=wifi; destination=stay with free wifi it doesn't matter; requested_info=reference_number; when=thursday, 8, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please and provide me with the reference number as well.\nChunk 2: I need place to stay with free wifi It doesn't matter.\nChunk 3: I like 4 star guesthouses though.\nChunk 4: I'd prefer something in the moderate price range That sounds good.\nChunk 5: Can I get that for 8 people for 4 nights starting Thursday Thank you!\nChunk 6: That is all that I need!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C2 domain=hotel; goal=search; amenities+=wifi; destination+=stay with free wifi it doesn't matter. C3 hotel_type+=guesthouse; stars+=4 stars. C4 price+=moderate; acceptance=selected_option. C5 time+=8, 4; day+=thursday; party_size+=8 people; stay_length+=4 nights. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info, search; price=moderate; party_size=8 people; stay_length=4 nights; stars=4 stars; amenities=wifi; destination=stay with free wifi it doesn't matter; requested_info=reference_number; when=thursday, 8, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please and provide me with the reference number as well.\nChunk 2: I need place to stay with free wifi It doesn't matter.\nChunk 3: I like 4 star guesthouses though.\nChunk 4: I'd prefer something in the moderate price range That sounds good.\nChunk 5: Can I get that for 8 people for 4 nights starting Thursday Thank you!\nChunk 6: That is all that I need!", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: reference_number; acceptance: selected_option. Next, the topic is hotel; the goal is search; amenities: wifi; destination: stay with free wifi it doesn't matter. Next, hotel type: guesthouse; star rating: 4 stars. Next, price: moderate; acceptance: selected_option. Finally, time: 8; day: thursday; party size: 8 people; stay length: 4 nights.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is search. requested information: reference_number; acceptance: selected_option.; amenities: wifi; destination: stay with free wifi it doesn't matter.; hotel type: guesthouse; star rating: 4 stars.; price: moderate; time: 8; day: thursday; party size: 8 people; stay length: 4 nights..", "trace": "C1 goal=request_info; requested_info+=reference_number; acceptance=selected_option. C2 domain=hotel; goal=search; amenities+=wifi; destination+=stay with free wifi it doesn't matter. C3 hotel_type+=guesthouse; stars+=4 stars. C4 price+=moderate; acceptance=selected_option. C5 time+=8, 4; day+=thursday; party_size+=8 people; stay_length+=4 nights. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please and provide me with the reference number as well.", "streaming_reasoning": "Initially, the goal is request info; requested information: reference_number; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=reference_number; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need place to stay with free wifi It doesn't matter.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; amenities: wifi; destination: stay with free wifi it doesn't matter..", "trace": "domain=hotel; goal=search; amenities+=wifi; destination+=stay with free wifi it doesn't matter."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I like 4 star guesthouses though.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse; star rating: 4 stars..", "trace": "hotel_type+=guesthouse; stars+=4 stars."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd prefer something in the moderate price range That sounds good.", "streaming_reasoning": "As more information arrives, price: moderate; acceptance: selected_option..", "trace": "price+=moderate; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get that for 8 people for 4 nights starting Thursday Thank you!", "streaming_reasoning": "As more information arrives, time: 8; day: thursday; party size: 8 people; stay length: 4 nights..", "trace": "time+=8, 4; day+=thursday; party_size+=8 people; stay_length+=4 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all that I need!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: price is moderate; party size is 8 people; stay length is 4 nights; star rating is 4 stars; amenities is wifi; destination is stay with free wifi it doesn't matter; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search; price=moderate; party_size=8 people; stay_length=4 nights; stars=4 stars; amenities=wifi; destination=stay with free wifi it doesn't matter; requested_info=reference_number; when=thursday, 8, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002523", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure, I'll try it.\nChunk 2: Can I get their phone number and post code?\nChunk 3: Great I also need a place to stay that is a guesthouse that includes free parking.\nChunk 4: Any location is fine, but I would prefer something that is in the expensive price range.\nChunk 5: Okay, I guess it'll save me some dough if I try for a place that's more moderately priced.\nChunk 6: Any of them will do.\nChunk 7: Pick your favorite and let me know what area they're in, and their postcode and how many stars they have Thank you.\nChunk 8: That is all I need today.", "streaming_reasoning": "C1 intent=context_update. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=hotel; goal=search; hotel_type+=guesthouse; amenities+=parking, free parking; destination+=stay that is a guesthouse that includes f. C4 price+=expensive. C5 price+=moderate. C6 intent=context_update. C7 goal=recommendation. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=request_info, search, recommendation; price=expensive, moderate; amenities=parking, free parking; destination=stay that is a guesthouse that includes f; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sure, I'll try it.\nChunk 2: Can I get their phone number and post code?\nChunk 3: Great I also need a place to stay that is a guesthouse that includes free parking.\nChunk 4: Any location is fine, but I would prefer something that is in the expensive price range.\nChunk 5: Okay, I guess it'll save me some dough if I try for a place that's more moderately priced.\nChunk 6: Any of them will do.\nChunk 7: Pick your favorite and let me know what area they're in, and their postcode and how many stars they have Thank you.\nChunk 8: That is all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=hotel; goal=search; hotel_type+=guesthouse; amenities+=parking, free parking; destination+=stay that is a guesthouse that includes f. C4 price+=expensive. C5 price+=moderate. C6 intent=context_update. C7 goal=recommendation. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info, search, recommendation; price=expensive, moderate; amenities=parking, free parking; destination=stay that is a guesthouse that includes f; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure, I'll try it.\nChunk 2: Can I get their phone number and post code?\nChunk 3: Great I also need a place to stay that is a guesthouse that includes free parking.\nChunk 4: Any location is fine, but I would prefer something that is in the expensive price range.\nChunk 5: Okay, I guess it'll save me some dough if I try for a place that's more moderately priced.\nChunk 6: Any of them will do.\nChunk 7: Pick your favorite and let me know what area they're in, and their postcode and how many stars they have Thank you.\nChunk 8: That is all I need today.", "input_token_count": 112, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is request info; requested information: phone. Next, the topic is hotel; the goal is search; hotel type: guesthouse; amenities: parking; destination: stay that is a guesthouse that includes f. Next, price: expensive. Next, price: moderate. Next, intent: context_update. Finally, the goal is recommendation.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is recommendation.. intent: context_update.; requested information: phone; hotel type: guesthouse; amenities: parking; destination: stay that is a guesthouse that includes f.; price: expensive., moderate..", "trace": "C1 intent=context_update. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=hotel; goal=search; hotel_type+=guesthouse; amenities+=parking, free parking; destination+=stay that is a guesthouse that includes f. C4 price+=expensive. C5 price+=moderate. C6 intent=context_update. C7 goal=recommendation. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sure, I'll try it.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I get their phone number and post code?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Great I also need a place to stay that is a guesthouse that includes free parking.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: guesthouse; amenities: parking; destination: stay that is a guesthouse that includes f..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; amenities+=parking, free parking; destination+=stay that is a guesthouse that includes f."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Any location is fine, but I would prefer something that is in the expensive price range.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Okay, I guess it'll save me some dough if I try for a place that's more moderately priced.", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Any of them will do.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Pick your favorite and let me know what area they're in, and their postcode and how many stars they have Thank you.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all I need today.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: price is expensive; amenities is parking; destination is stay that is a guesthouse that includes f; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search, recommendation; price=expensive, moderate; amenities=parking, free parking; destination=stay that is a guesthouse that includes f; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002524", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I am also looking for a restaurant in the same area as the Ballare.\nChunk 2: Do you have any modern glodal ones How about International?\nChunk 3: I don't need a reservation but I do need the address, phone number and price range.\nChunk 4: and what is their phone number?\nChunk 5: No thank you that will be all.", "streaming_reasoning": "C1 domain=restaurant; goal=modify_constraint; acceptance=selected_option. C2 goal=recommendation. C3 goal=request_info; requested_info+=address, phone, price. C4 [SKIP: repeated_information]. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, modify_constraint, recommendation, booking, request_info; requested_info=address, phone, price; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I am also looking for a restaurant in the same area as the Ballare.\nChunk 2: Do you have any modern glodal ones How about International?\nChunk 3: I don't need a reservation but I do need the address, phone number and price range.\nChunk 4: and what is their phone number?\nChunk 5: No thank you that will be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=modify_constraint; acceptance=selected_option. C2 goal=recommendation. C3 goal=request_info; requested_info+=address, phone, price. C4 [SKIP: repeated_information]. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, modify_constraint, recommendation, booking, request_info; requested_info=address, phone, price; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I am also looking for a restaurant in the same area as the Ballare.\nChunk 2: Do you have any modern glodal ones How about International?\nChunk 3: I don't need a reservation but I do need the address, phone number and price range.\nChunk 4: and what is their phone number?\nChunk 5: No thank you that will be all.", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is modify constraint; acceptance: selected_option. Next, the goal is recommendation. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is restaurant. the goal is request info. acceptance: selected_option.; requested information: address.", "trace": "C1 domain=restaurant; goal=modify_constraint; acceptance=selected_option. C2 goal=recommendation. C3 goal=request_info; requested_info+=address, phone, price. C4 [SKIP: repeated_information]. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I am also looking for a restaurant in the same area as the Ballare.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is modify constraint; acceptance: selected_option..", "trace": "domain=restaurant; goal=modify_constraint; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do you have any modern glodal ones How about International?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I don't need a reservation but I do need the address, phone number and price range.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "and what is their phone number?", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No thank you that will be all.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, modify_constraint, recommendation, booking, request_info; requested_info=address, phone, price; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002525", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yeah, I need a train on Sunday Departing from Cambridge.\nChunk 2: The train should go to Bishops Stortford and leave after 14:45.\nChunk 3: Can you tell me the travel time first?\nChunk 4: That sounds great, that's all I wanted to know.\nChunk 5: That should be all Thank you!", "streaming_reasoning": "C1 domain=train; goal=search; day+=sunday; departure+=cambridge. C2 time+=14:45; destination+=bishops stortford and leave after 14:45. C3 goal=request_info; requested_info+=travel_time. C4 [SKIP: closing_only]. C5 intent=context_update.", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=bishops stortford and leave after 14:45; departure=cambridge; requested_info=travel_time; when=sunday, 14:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yeah, I need a train on Sunday Departing from Cambridge.\nChunk 2: The train should go to Bishops Stortford and leave after 14:45.\nChunk 3: Can you tell me the travel time first?\nChunk 4: That sounds great, that's all I wanted to know.\nChunk 5: That should be all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=sunday; departure+=cambridge. C2 time+=14:45; destination+=bishops stortford and leave after 14:45. C3 goal=request_info; requested_info+=travel_time. C4 [SKIP: closing_only]. C5 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=bishops stortford and leave after 14:45; departure=cambridge; requested_info=travel_time; when=sunday, 14:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yeah, I need a train on Sunday Departing from Cambridge.\nChunk 2: The train should go to Bishops Stortford and leave after 14:45.\nChunk 3: Can you tell me the travel time first?\nChunk 4: That sounds great, that's all I wanted to know.\nChunk 5: That should be all Thank you!", "input_token_count": 55, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: sunday; departure point: cambridge. Next, time: 14:45; destination: bishops stortford and leave after 14:45. Next, the goal is request info; requested information: travel_time. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. day: sunday; departure point: cambridge.; time: 14:45; destination: bishops stortford and leave after 14:45.; requested information: travel_time.; intent: context_update..", "trace": "C1 domain=train; goal=search; day+=sunday; departure+=cambridge. C2 time+=14:45; destination+=bishops stortford and leave after 14:45. C3 goal=request_info; requested_info+=travel_time. C4 [SKIP: closing_only]. C5 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yeah, I need a train on Sunday Departing from Cambridge.", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: sunday; departure point: cambridge..", "trace": "domain=train; goal=search; day+=sunday; departure+=cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The train should go to Bishops Stortford and leave after 14:45.", "streaming_reasoning": "As more information arrives, time: 14:45; destination: bishops stortford and leave after 14:45..", "trace": "time+=14:45; destination+=bishops stortford and leave after 14:45."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you tell me the travel time first?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That sounds great, that's all I wanted to know.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That should be all Thank you!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is bishops stortford and leave after 14:45; departure point is cambridge; requested information is travel_time; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=bishops stortford and leave after 14:45; departure=cambridge; requested_info=travel_time; when=sunday, 14:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002526", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant that serves Thai food and is in the expensive price range.\nChunk 2: what is the address and phone number?\nChunk 3: Thank you good bye.\nChunk 4: No further assistance needed Goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=thai; price+=expensive. C2 goal=request_info; requested_info+=address, phone. C3 [SKIP: thanks_only]. C4 goal=modify_constraint.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; food=thai; price=expensive; requested_info=address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant that serves Thai food and is in the expensive price range.\nChunk 2: what is the address and phone number?\nChunk 3: Thank you good bye.\nChunk 4: No further assistance needed Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=thai; price+=expensive. C2 goal=request_info; requested_info+=address, phone. C3 [SKIP: thanks_only]. C4 goal=modify_constraint.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; food=thai; price=expensive; requested_info=address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant that serves Thai food and is in the expensive price range.\nChunk 2: what is the address and phone number?\nChunk 3: Thank you good bye.\nChunk 4: No further assistance needed Goodbye.", "input_token_count": 41, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: thai; price: expensive. Next, the goal is request info; requested information: address. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is modify constraint.. cuisine: thai; price: expensive.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; cuisine+=thai; price+=expensive. C2 goal=request_info; requested_info+=address, phone. C3 [SKIP: thanks_only]. C4 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant that serves Thai food and is in the expensive price range.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: thai; price: expensive..", "trace": "domain=restaurant; goal=search; cuisine+=thai; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "what is the address and phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you good bye.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No further assistance needed Goodbye.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is thai; price is expensive; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; food=thai; price=expensive; requested_info=address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001699", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I get wistful remembering my high school days.\nChunk 2: find myself thinking a lot about my teen years and early twenties.\nChunk 3: The friends I had then and the fun we had.\nChunk 4: That is where I am still at, I am scared I will have regrets when I get older I don'.", "streaming_reasoning": "C1 need=validation. C2 cause=my teen years and early twenties; need=encouragement. C3 support_signal=received. C4 emotion=anxious; cause=older I don'; need=reassurance.", "deep_reasoning": "User feels anxious after older I don' and needs reassurance.", "answer": "It makes sense to feel anxious after older I don'. Slow down, check what is actually known, and take one small step before deciding what comes next.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I get wistful remembering my high school days.\nChunk 2: find myself thinking a lot about my teen years and early twenties.\nChunk 3: The friends I had then and the fun we had.\nChunk 4: That is where I am still at, I am scared I will have regrets when I get older I don'."}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 cause=my teen years and early twenties; need=encouragement. C3 support_signal=received. C4 emotion=anxious; cause=older I don'; need=reassurance.\n\nDeep reasoning: User feels anxious after older I don' and needs reassurance.\n\nAnswer: It makes sense to feel anxious after older I don'. Slow down, check what is actually known, and take one small step before deciding what comes next."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I get wistful remembering my high school days.\nChunk 2: find myself thinking a lot about my teen years and early twenties.\nChunk 3: The friends I had then and the fun we had.\nChunk 4: That is where I am still at, I am scared I will have regrets when I get older I don'.", "input_token_count": 58, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user mentions my teen years and early twenties; the user needs encouragement. Next, the user signals support or acknowledgment. Finally, the user expresses anxious about older I don'; the user needs reassurance.", "trace": "C1 need=validation. C2 cause=my teen years and early twenties; need=encouragement. C3 support_signal=received. C4 emotion=anxious; cause=older I don'; need=reassurance.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I get wistful remembering my high school days.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "find myself thinking a lot about my teen years and early twenties.", "streaming_reasoning": "As more information arrives, the user mentions my teen years and early twenties; the user needs encouragement..", "trace": "cause=my teen years and early twenties; need=encouragement."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The friends I had then and the fun we had.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That is where I am still at, I am scared I will have regrets when I get older I don'.", "streaming_reasoning": "Finally, the user expresses anxious about older I don'; the user needs reassurance..", "trace": "emotion=anxious; cause=older I don'; need=reassurance."}]}, "output": {"deep_reasoning": "User feels anxious after older I don' and needs reassurance.", "answer": "It makes sense to feel anxious after older I don'. Slow down, check what is actually known, and take one small step before deciding what comes next."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002527", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm also looking for a museum in the east Any recommendations?\nChunk 2: Yes, can I have more information about the Cambridge Museum of Tech?\nChunk 3: What is their address?\nChunk 4: Can I also get a phone number and postcode for the museum?\nChunk 5: sorry, what is the address?\nChunk 6: That's all thank you for your help.\nChunk 7: No that is it Thank you.", "streaming_reasoning": "C1 domain=attraction; goal=search; area+=east. C2 goal=request_info; acceptance=selected_option. C3 requested_info+=address. C4 requested_info+=phone, postcode. C5 goal=request_info. C6 [SKIP: closing_only]. C7 [SKIP: repeated_information].", "deep_reasoning": "Need domain=attraction; goal=search, request_info; area=east; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm also looking for a museum in the east Any recommendations?\nChunk 2: Yes, can I have more information about the Cambridge Museum of Tech?\nChunk 3: What is their address?\nChunk 4: Can I also get a phone number and postcode for the museum?\nChunk 5: sorry, what is the address?\nChunk 6: That's all thank you for your help.\nChunk 7: No that is it Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search; area+=east. C2 goal=request_info; acceptance=selected_option. C3 requested_info+=address. C4 requested_info+=phone, postcode. C5 goal=request_info. C6 [SKIP: closing_only]. C7 [SKIP: repeated_information].\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; area=east; requested_info=address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm also looking for a museum in the east Any recommendations?\nChunk 2: Yes, can I have more information about the Cambridge Museum of Tech?\nChunk 3: What is their address?\nChunk 4: Can I also get a phone number and postcode for the museum?\nChunk 5: sorry, what is the address?\nChunk 6: That's all thank you for your help.\nChunk 7: No that is it Thank you.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; area: east. Next, the goal is request info; acceptance: selected_option. Next, requested information: address. Next, requested information: phone. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is attraction. the goal is request info.. area: east.; acceptance: selected_option.; requested information: address., phone.", "trace": "C1 domain=attraction; goal=search; area+=east. C2 goal=request_info; acceptance=selected_option. C3 requested_info+=address. C4 requested_info+=phone, postcode. C5 goal=request_info. C6 [SKIP: closing_only]. C7 [SKIP: repeated_information].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm also looking for a museum in the east Any recommendations?", "streaming_reasoning": "Initially, the topic is attraction; the goal is search; area: east..", "trace": "domain=attraction; goal=search; area+=east."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, can I have more information about the Cambridge Museum of Tech?", "streaming_reasoning": "As more information arrives, the goal is request info; acceptance: selected_option..", "trace": "goal=request_info; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is their address?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I also get a phone number and postcode for the museum?", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "sorry, what is the address?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all thank you for your help.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No that is it Thank you.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is east; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; area=east; requested_info=address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002528", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you please get me the entrance fee, address and phone number for these Thank you.\nChunk 2: I also need a train to Cambridge, arriving by 19:15.\nChunk 3: It will be on friday and I only need 1 ticket for myself.\nChunk 4: I will be leaving from Kings Lynn.\nChunk 5: I will be traveling on Friday.\nChunk 6: No thank you that will be all!\nChunk 7: Bye!", "streaming_reasoning": "C1 goal=request_info; requested_info+=address, phone, entrance_fee. C2 domain=train; time+=19:15; destination+=cambridge. C3 day+=friday. C4 intent=context_update. C5 intent=context_update. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=cambridge; requested_info=address, phone, entrance_fee; when=friday, 19:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you please get me the entrance fee, address and phone number for these Thank you.\nChunk 2: I also need a train to Cambridge, arriving by 19:15.\nChunk 3: It will be on friday and I only need 1 ticket for myself.\nChunk 4: I will be leaving from Kings Lynn.\nChunk 5: I will be traveling on Friday.\nChunk 6: No thank you that will be all!\nChunk 7: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address, phone, entrance_fee. C2 domain=train; time+=19:15; destination+=cambridge. C3 day+=friday. C4 intent=context_update. C5 intent=context_update. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=cambridge; requested_info=address, phone, entrance_fee; when=friday, 19:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you please get me the entrance fee, address and phone number for these Thank you.\nChunk 2: I also need a train to Cambridge, arriving by 19:15.\nChunk 3: It will be on friday and I only need 1 ticket for myself.\nChunk 4: I will be leaving from Kings Lynn.\nChunk 5: I will be traveling on Friday.\nChunk 6: No thank you that will be all!\nChunk 7: Bye!", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the topic is train; time: 19:15; destination: cambridge. Next, day: friday. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. requested information: address; time: 19:15; destination: cambridge.; day: friday.; intent: context_update..", "trace": "C1 goal=request_info; requested_info+=address, phone, entrance_fee. C2 domain=train; time+=19:15; destination+=cambridge. C3 day+=friday. C4 intent=context_update. C5 intent=context_update. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you please get me the entrance fee, address and phone number for these Thank you.", "streaming_reasoning": "Initially, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, entrance_fee."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need a train to Cambridge, arriving by 19:15.", "streaming_reasoning": "As more information arrives, the topic is train; time: 19:15; destination: cambridge..", "trace": "domain=train; time+=19:15; destination+=cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It will be on friday and I only need 1 ticket for myself.", "streaming_reasoning": "As more information arrives, day: friday..", "trace": "day+=friday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I will be leaving from Kings Lynn.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will be traveling on Friday.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No thank you that will be all!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Bye!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge; requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=cambridge; requested_info=address, phone, entrance_fee; when=friday, 19:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002529", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I need a train going to Cambridge leaving after 19:15.\nChunk 3: I would like to leave on saturday.\nChunk 4: The 21:54 one, what's it's ID and travel time?\nChunk 5: What's the arrival time for that Okay thank you.\nChunk 6: That will be fine.\nChunk 7: No, that is all.\nChunk 8: have a nice day.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=search; time+=19:15; destination+=cambridge leaving after 19:15. C3 day+=saturday; destination+=leave on saturday. C4 goal=request_info; time+=21:54; requested_info+=travel_time. C5 intent=context_update. C6 acceptance=selected_option. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=cambridge leaving after 19:15, leave on saturday; requested_info=travel_time; when=saturday, 19:15, 21:54; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I need a train going to Cambridge leaving after 19:15.\nChunk 3: I would like to leave on saturday.\nChunk 4: The 21:54 one, what's it's ID and travel time?\nChunk 5: What's the arrival time for that Okay thank you.\nChunk 6: That will be fine.\nChunk 7: No, that is all.\nChunk 8: have a nice day."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=search; time+=19:15; destination+=cambridge leaving after 19:15. C3 day+=saturday; destination+=leave on saturday. C4 goal=request_info; time+=21:54; requested_info+=travel_time. C5 intent=context_update. C6 acceptance=selected_option. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=cambridge leaving after 19:15, leave on saturday; requested_info=travel_time; when=saturday, 19:15, 21:54; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I need a train going to Cambridge leaving after 19:15.\nChunk 3: I would like to leave on saturday.\nChunk 4: The 21:54 one, what's it's ID and travel time?\nChunk 5: What's the arrival time for that Okay thank you.\nChunk 6: That will be fine.\nChunk 7: No, that is all.\nChunk 8: have a nice day.", "input_token_count": 66, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 19:15; destination: cambridge leaving after 19:15. Next, day: saturday; destination: leave on saturday. Next, the goal is request info; time: 21:54; requested information: travel_time. Next, intent: context_update. Finally, acceptance: selected_option.  Some chunks were skipped because they contained acknowledgement_only or closing_only. In summary, The overall topic is train. the goal is request info. time: 19:15, 21:54; destination: cambridge leaving after 19:15., leave on saturday.; day: saturday; requested information: travel_time.; intent: context_update.; acceptance: selected_option..", "trace": "C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=search; time+=19:15; destination+=cambridge leaving after 19:15. C3 day+=saturday; destination+=leave on saturday. C4 goal=request_info; time+=21:54; requested_info+=travel_time. C5 intent=context_update. C6 acceptance=selected_option. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need a train going to Cambridge leaving after 19:15.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; time: 19:15; destination: cambridge leaving after 19:15..", "trace": "domain=train; goal=search; time+=19:15; destination+=cambridge leaving after 19:15."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to leave on saturday.", "streaming_reasoning": "As more information arrives, day: saturday; destination: leave on saturday..", "trace": "day+=saturday; destination+=leave on saturday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The 21:54 one, what's it's ID and travel time?", "streaming_reasoning": "As more information arrives, the goal is request info; time: 21:54; requested information: travel_time..", "trace": "goal=request_info; time+=21:54; requested_info+=travel_time."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What's the arrival time for that Okay thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That will be fine.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that is all.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "have a nice day.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge leaving after 19:15; requested information is travel_time; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=cambridge leaving after 19:15, leave on saturday; requested_info=travel_time; when=saturday, 19:15, 21:54; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002530", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a expensive restaurant.\nChunk 2: It should be in the centre part of town.\nChunk 3: It is for 7 people.\nChunk 4: The time is tuesday, 7, 13:15.\nChunk 5: Could we try for Tuesday at 12:15 please.\nChunk 6: Yes, I'm looking for a particular attraction called Whale of a Time.\nChunk 7: Do you have any information on it?\nChunk 8: Could I have the postcode, address, and entrance fee?\nChunk 9: Yes, can you book me a taxi between those two?\nChunk 10: I'd like to arrive at the restaurant in time for my reservation please.\nChunk 11: No, that should do it, thanks!", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=expensive; destination+=find a expensive restaurant. C2 area+=centre. C3 party_size+=7 people. C4 time+=7, 13:15; day+=tuesday. C5 time+=12:15. C6 domain=attraction; acceptance=selected_option. C7 goal=request_info. C8 goal=request_info; requested_info+=address, postcode, entrance_fee. C9 domain=taxi; goal=confirm_booking; goal=confirm_booking. C10 destination+=arrive at the restaurant in time for my r. C11 goal=modify_constraint.", "deep_reasoning": "Need domain=restaurant, attraction, taxi; goal=search, request_info, booking, confirm_booking; area=centre; price=expensive; party_size=7 people; destination=find a expensive restaurant, arrive at the restaurant in time for my r; requested_info=address, postcode, entrance_fee; when=tuesday, 7, 13:15, 12:15.", "answer": "I can help with that and include the address, postcode, entrance fee once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a expensive restaurant.\nChunk 2: It should be in the centre part of town.\nChunk 3: It is for 7 people.\nChunk 4: The time is tuesday, 7, 13:15.\nChunk 5: Could we try for Tuesday at 12:15 please.\nChunk 6: Yes, I'm looking for a particular attraction called Whale of a Time.\nChunk 7: Do you have any information on it?\nChunk 8: Could I have the postcode, address, and entrance fee?\nChunk 9: Yes, can you book me a taxi between those two?\nChunk 10: I'd like to arrive at the restaurant in time for my reservation please.\nChunk 11: No, that should do it, thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=expensive; destination+=find a expensive restaurant. C2 area+=centre. C3 party_size+=7 people. C4 time+=7, 13:15; day+=tuesday. C5 time+=12:15. C6 domain=attraction; acceptance=selected_option. C7 goal=request_info. C8 goal=request_info; requested_info+=address, postcode, entrance_fee. C9 domain=taxi; goal=confirm_booking; goal=confirm_booking. C10 destination+=arrive at the restaurant in time for my r. C11 goal=modify_constraint.\n\nDeep reasoning: Need domain=restaurant, attraction, taxi; goal=search, request_info, booking, confirm_booking; area=centre; price=expensive; party_size=7 people; destination=find a expensive restaurant, arrive at the restaurant in time for my r; requested_info=address, postcode, entrance_fee; when=tuesday, 7, 13:15, 12:15.\n\nAnswer: I can help with that and include the address, postcode, entrance fee once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a expensive restaurant.\nChunk 2: It should be in the centre part of town.\nChunk 3: It is for 7 people.\nChunk 4: The time is tuesday, 7, 13:15.\nChunk 5: Could we try for Tuesday at 12:15 please.\nChunk 6: Yes, I'm looking for a particular attraction called Whale of a Time.\nChunk 7: Do you have any information on it?\nChunk 8: Could I have the postcode, address, and entrance fee?\nChunk 9: Yes, can you book me a taxi between those two?\nChunk 10: I'd like to arrive at the restaurant in time for my reservation please.\nChunk 11: No, that should do it, thanks!", "input_token_count": 116, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: expensive; destination: find a expensive restaurant. Next, area: centre. Next, party size: 7 people. Next, time: 7; day: tuesday. Next, time: 12:15. Next, the topic is attraction; acceptance: selected_option. Next, the goal is request info. Next, the goal is request info; requested information: address. Next, the topic is taxi; the goal is confirm booking. Next, destination: arrive at the restaurant in time for my r. Finally, the goal is modify constraint. In summary, The overall topic is taxi. the goal is modify constraint.. price: expensive; destination: find a expensive restaurant., arrive at the restaurant in time for my r.; area: centre.; party size: 7 people.; time: 7, 12:15.; day: tuesday.; acceptance: selected_option.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; price+=expensive; destination+=find a expensive restaurant. C2 area+=centre. C3 party_size+=7 people. C4 time+=7, 13:15; day+=tuesday. C5 time+=12:15. C6 domain=attraction; acceptance=selected_option. C7 goal=request_info. C8 goal=request_info; requested_info+=address, postcode, entrance_fee. C9 domain=taxi; goal=confirm_booking; goal=confirm_booking. C10 destination+=arrive at the restaurant in time for my r. C11 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a expensive restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: expensive; destination: find a expensive restaurant..", "trace": "domain=restaurant; goal=search; price+=expensive; destination+=find a expensive restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 7 people.", "streaming_reasoning": "As more information arrives, party size: 7 people..", "trace": "party_size+=7 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is tuesday, 7, 13:15.", "streaming_reasoning": "As more information arrives, time: 7; day: tuesday..", "trace": "time+=7, 13:15; day+=tuesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Could we try for Tuesday at 12:15 please.", "streaming_reasoning": "As more information arrives, time: 12:15..", "trace": "time+=12:15."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, I'm looking for a particular attraction called Whale of a Time.", "streaming_reasoning": "As more information arrives, the topic is attraction; acceptance: selected_option..", "trace": "domain=attraction; acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Do you have any information on it?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Could I have the postcode, address, and entrance fee?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode, entrance_fee."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Yes, can you book me a taxi between those two?", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is confirm booking..", "trace": "domain=taxi; goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "I'd like to arrive at the restaurant in time for my reservation please.", "streaming_reasoning": "As more information arrives, destination: arrive at the restaurant in time for my r..", "trace": "destination+=arrive at the restaurant in time for my r."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "No, that should do it, thanks!", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is expensive; party size is 7 people; destination is find a expensive restaurant; requested information is address; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, postcode, entrance fee once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant, attraction, taxi; goal=search, request_info, booking, confirm_booking; area=centre; price=expensive; party_size=7 people; destination=find a expensive restaurant, arrive at the restaurant in time for my r; requested_info=address, postcode, entrance_fee; when=tuesday, 7, 13:15, 12:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002532", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any multiple sports in the centre of town?\nChunk 2: Well, how about a theatre then?\nChunk 3: I need the phone number.\nChunk 4: I'm not sure yet.\nChunk 5: Which one do you recommend?\nChunk 6: Yes, I need the entrance fee and phone number?\nChunk 7: No thanks, that is all the information I need.\nChunk 8: Thank you for your time.", "streaming_reasoning": "C1 area+=centre; type+=sports. C2 domain=attraction; goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 goal=modify_constraint. C5 goal=request_info. C6 requested_info+=entrance_fee; acceptance=selected_option. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction; goal=recommendation, search, request_info; area=centre; requested_info=phone, entrance_fee; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Are there any multiple sports in the centre of town?\nChunk 2: Well, how about a theatre then?\nChunk 3: I need the phone number.\nChunk 4: I'm not sure yet.\nChunk 5: Which one do you recommend?\nChunk 6: Yes, I need the entrance fee and phone number?\nChunk 7: No thanks, that is all the information I need.\nChunk 8: Thank you for your time."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre; type+=sports. C2 domain=attraction; goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 goal=modify_constraint. C5 goal=request_info. C6 requested_info+=entrance_fee; acceptance=selected_option. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction; goal=recommendation, search, request_info; area=centre; requested_info=phone, entrance_fee; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any multiple sports in the centre of town?\nChunk 2: Well, how about a theatre then?\nChunk 3: I need the phone number.\nChunk 4: I'm not sure yet.\nChunk 5: Which one do you recommend?\nChunk 6: Yes, I need the entrance fee and phone number?\nChunk 7: No thanks, that is all the information I need.\nChunk 8: Thank you for your time.", "input_token_count": 69, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: centre; type: sports. Next, the topic is attraction; the goal is recommendation. Next, the goal is request info; requested information: phone. Next, the goal is modify constraint. Next, the goal is request info. Finally, requested information: entrance_fee; acceptance: selected_option.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction. the goal is request info.. area: centre; type: sports.; requested information: phone., entrance_fee; acceptance: selected_option..", "trace": "C1 area+=centre; type+=sports. C2 domain=attraction; goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 goal=modify_constraint. C5 goal=request_info. C6 requested_info+=entrance_fee; acceptance=selected_option. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Are there any multiple sports in the centre of town?", "streaming_reasoning": "Initially, area: centre; type: sports..", "trace": "area+=centre; type+=sports."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Well, how about a theatre then?", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is recommendation..", "trace": "domain=attraction; goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need the phone number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm not sure yet.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Which one do you recommend?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, I need the entrance fee and phone number?", "streaming_reasoning": "As more information arrives, requested information: entrance_fee; acceptance: selected_option..", "trace": "requested_info+=entrance_fee; acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No thanks, that is all the information I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for your time.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of recommendation. Key information: area is centre; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=recommendation, search, request_info; area=centre; requested_info=phone, entrance_fee; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002533", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I am looking for a restaurant name taj tandoori.\nChunk 2: I would like to book a table for 8 people on Sunday at 19:30 Thanks so much.\nChunk 3: I think that's all I needed.\nChunk 4: Have a great day.\nChunk 5: Bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 goal=booking; time+=8, 19:30; day+=sunday; party_size+=8 people. C3 [SKIP: closing_only]. C4 [SKIP: closing_only]. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking; party_size=8 people; when=sunday, 8, 19:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, I am looking for a restaurant name taj tandoori.\nChunk 2: I would like to book a table for 8 people on Sunday at 19:30 Thanks so much.\nChunk 3: I think that's all I needed.\nChunk 4: Have a great day.\nChunk 5: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 goal=booking; time+=8, 19:30; day+=sunday; party_size+=8 people. C3 [SKIP: closing_only]. C4 [SKIP: closing_only]. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking; party_size=8 people; when=sunday, 8, 19:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I am looking for a restaurant name taj tandoori.\nChunk 2: I would like to book a table for 8 people on Sunday at 19:30 Thanks so much.\nChunk 3: I think that's all I needed.\nChunk 4: Have a great day.\nChunk 5: Bye.", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Finally, the goal is booking; time: 8; day: sunday; party size: 8 people.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. time: 8; day: sunday; party size: 8 people..", "trace": "C1 domain=restaurant; goal=search. C2 goal=booking; time+=8, 19:30; day+=sunday; party_size+=8 people. C3 [SKIP: closing_only]. C4 [SKIP: closing_only]. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, I am looking for a restaurant name taj tandoori.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to book a table for 8 people on Sunday at 19:30 Thanks so much.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 8; day: sunday; party size: 8 people..", "trace": "goal=booking; time+=8, 19:30; day+=sunday; party_size+=8 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I think that's all I needed.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Bye.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 8 people; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking; party_size=8 people; when=sunday, 8, 19:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000526", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Be a Sophisticated and Cultured Male.\nChunk 2: • Thoughtful use of money.\nChunk 3: • Free Time (to determine your qualities) • An education (be it formal or social) • Confidence.", "streaming_reasoning": "C1 task=be_a_sophisticated_and. C2 step=thoughtful_use_of_money. C3 step=free_time_to_determine.", "deep_reasoning": "Procedure for Be a Sophisticated and Cultured Male: Thoughtful use of money, Free Time An education Confidence.", "answer": "For Be a Sophisticated and Cultured Male, follow the steps in order: Thoughtful use of money, Free Time An education Confidence.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Be a Sophisticated and Cultured Male.\nChunk 2: • Thoughtful use of money.\nChunk 3: • Free Time (to determine your qualities) • An education (be it formal or social) • Confidence."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=be_a_sophisticated_and. C2 step=thoughtful_use_of_money. C3 step=free_time_to_determine.\n\nDeep reasoning: Procedure for Be a Sophisticated and Cultured Male: Thoughtful use of money, Free Time An education Confidence.\n\nAnswer: For Be a Sophisticated and Cultured Male, follow the steps in order: Thoughtful use of money, Free Time An education Confidence."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Be a Sophisticated and Cultured Male.\nChunk 2: • Thoughtful use of money.\nChunk 3: • Free Time (to determine your qualities) • An education (be it formal or social) • Confidence.", "input_token_count": 31, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, task: be_a_sophisticated_and. Next, step: thoughtful_use_of_money. Finally, step: free_time_to_determine. In summary, task: be_a_sophisticated_and.; step: thoughtful_use_of_money., free_time_to_determine..", "trace": "C1 task=be_a_sophisticated_and. C2 step=thoughtful_use_of_money. C3 step=free_time_to_determine.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Be a Sophisticated and Cultured Male.", "streaming_reasoning": "Initially, task: be_a_sophisticated_and..", "trace": "task=be_a_sophisticated_and."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• Thoughtful use of money.", "streaming_reasoning": "As more information arrives, step: thoughtful_use_of_money..", "trace": "step=thoughtful_use_of_money."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "• Free Time (to determine your qualities) • An education (be it formal or social) • Confidence.", "streaming_reasoning": "Finally, step: free_time_to_determine..", "trace": "step=free_time_to_determine."}]}, "output": {"deep_reasoning": "Procedure for Be a Sophisticated and Cultured Male: Thoughtful use of money, Free Time An education Confidence.", "answer": "For Be a Sophisticated and Cultured Male, follow the steps in order: Thoughtful use of money, Free Time An education Confidence."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003190", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: You need to stop smoking, and make sure that you get 30 minutes of exercise every day.\nChunk 2: Can I have a glass of wine now and then?\nChunk 3: As long as you don ' t overdo it, a glass of wine a day should be OK.\nChunk 4: Would you care for something to drink, Mr. Stone?\nChunk 5: No, thank you, Mrs. Carter.\nChunk 6: I'm fine for now.", "streaming_reasoning": "C1 casual_comment=stop, smoking. C2 question=true. C3 casual_comment=long, don. C4 question=true. C5 [SKIP: thanks_only]. C6 casual_comment=i'm, fine.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: You need to stop smoking, and make sure that you get 30 minutes of exercise every day.\nChunk 2: Can I have a glass of wine now and then?\nChunk 3: As long as you don ' t overdo it, a glass of wine a day should be OK.\nChunk 4: Would you care for something to drink, Mr. Stone?\nChunk 5: No, thank you, Mrs. Carter.\nChunk 6: I'm fine for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=stop, smoking. C2 question=true. C3 casual_comment=long, don. C4 question=true. C5 [SKIP: thanks_only]. C6 casual_comment=i'm, fine.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: You need to stop smoking, and make sure that you get 30 minutes of exercise every day.\nChunk 2: Can I have a glass of wine now and then?\nChunk 3: As long as you don ' t overdo it, a glass of wine a day should be OK.\nChunk 4: Would you care for something to drink, Mr. Stone?\nChunk 5: No, thank you, Mrs. Carter.\nChunk 6: I'm fine for now.", "input_token_count": 74, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on stop. Next, the input provides additional context about question=true. Next, the user comments on long. Next, the input provides additional context about question=true. Finally, the user comments on i'm.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=stop, smoking. C2 question=true. C3 casual_comment=long, don. C4 question=true. C5 [SKIP: thanks_only]. C6 casual_comment=i'm, fine.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "You need to stop smoking, and make sure that you get 30 minutes of exercise every day.", "streaming_reasoning": "Initially, the user comments on stop.", "trace": "casual_comment=stop, smoking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I have a glass of wine now and then?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "As long as you don ' t overdo it, a glass of wine a day should be OK.", "streaming_reasoning": "As more information arrives, the user comments on long.", "trace": "casual_comment=long, don."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Would you care for something to drink, Mr. Stone?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, thank you, Mrs. Carter.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'm fine for now.", "streaming_reasoning": "Finally, the user comments on i'm.", "trace": "casual_comment=i'm, fine."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001705", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Back when I was in school, i studied really well for an important exam.\nChunk 2: But, still I was so much worried about my test test results.\nChunk 3: I think small things make me worried.\nChunk 4: Small things like what?\nChunk 5: Back in school, I studied a lot for an important exam.\nChunk 6: But, still I was very much worried about my test results.", "streaming_reasoning": "C1 cause=in school, i studied really well for an important exam; need=encouragement. C2 emotion=worried; cause=my test test results; need=reassurance. C3 emotion=worried; cause=I think small things make me. C4 [SKIP: repeated_information]. C5 support_signal=received. C6 emotion=worried; cause=my test results.", "deep_reasoning": "User feels worried after my test results and needs reassurance.", "answer": "It makes sense to feel worried after my test results. Slow down, check what is actually known, and take one small step before deciding what comes next.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Back when I was in school, i studied really well for an important exam.\nChunk 2: But, still I was so much worried about my test test results.\nChunk 3: I think small things make me worried.\nChunk 4: Small things like what?\nChunk 5: Back in school, I studied a lot for an important exam.\nChunk 6: But, still I was very much worried about my test results."}, {"role": "assistant", "content": "Streaming reasoning: C1 cause=in school, i studied really well for an important exam; need=encouragement. C2 emotion=worried; cause=my test test results; need=reassurance. C3 emotion=worried; cause=I think small things make me. C4 [SKIP: repeated_information]. C5 support_signal=received. C6 emotion=worried; cause=my test results.\n\nDeep reasoning: User feels worried after my test results and needs reassurance.\n\nAnswer: It makes sense to feel worried after my test results. Slow down, check what is actually known, and take one small step before deciding what comes next."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Back when I was in school, i studied really well for an important exam.\nChunk 2: But, still I was so much worried about my test test results.\nChunk 3: I think small things make me worried.\nChunk 4: Small things like what?\nChunk 5: Back in school, I studied a lot for an important exam.\nChunk 6: But, still I was very much worried about my test results.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user mentions in school; the user needs encouragement. Next, the user expresses worried about my test test results; the user needs reassurance. Next, the user expresses worried about I think small things make me. Next, the user signals support or acknowledgment. Finally, the user expresses worried about my test results.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 cause=in school, i studied really well for an important exam; need=encouragement. C2 emotion=worried; cause=my test test results; need=reassurance. C3 emotion=worried; cause=I think small things make me. C4 [SKIP: repeated_information]. C5 support_signal=received. C6 emotion=worried; cause=my test results.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Back when I was in school, i studied really well for an important exam.", "streaming_reasoning": "Initially, the user mentions in school; the user needs encouragement..", "trace": "cause=in school, i studied really well for an important exam; need=encouragement."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "But, still I was so much worried about my test test results.", "streaming_reasoning": "As more information arrives, the user expresses worried about my test test results; the user needs reassurance..", "trace": "emotion=worried; cause=my test test results; need=reassurance."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I think small things make me worried.", "streaming_reasoning": "As more information arrives, the user expresses worried about I think small things make me..", "trace": "emotion=worried; cause=I think small things make me."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Small things like what?", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Back in school, I studied a lot for an important exam.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "But, still I was very much worried about my test results.", "streaming_reasoning": "Finally, the user expresses worried about my test results..", "trace": "emotion=worried; cause=my test results."}]}, "output": {"deep_reasoning": "User feels worried after my test results and needs reassurance.", "answer": "It makes sense to feel worried after my test results. Slow down, check what is actually known, and take one small step before deciding what comes next."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002534", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to find a restaurant that serves swiss food.\nChunk 2: Is there any restaurants that serve Vietnamese food What's the address Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant that serves swiss food. C2 goal=request_info; requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; destination=find a restaurant that serves swiss food; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like to find a restaurant that serves swiss food.\nChunk 2: Is there any restaurants that serve Vietnamese food What's the address Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant that serves swiss food. C2 goal=request_info; requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; destination=find a restaurant that serves swiss food; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to find a restaurant that serves swiss food.\nChunk 2: Is there any restaurants that serve Vietnamese food What's the address Thank you, goodbye.", "input_token_count": 28, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant that serves swiss food. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. destination: find a restaurant that serves swiss food.; requested information: address..", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant that serves swiss food. C2 goal=request_info; requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like to find a restaurant that serves swiss food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant that serves swiss food..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant that serves swiss food."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there any restaurants that serve Vietnamese food What's the address Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: destination is find a restaurant that serves swiss food; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; destination=find a restaurant that serves swiss food; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002535", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Okay what about spanish cuisine then Please.\nChunk 2: I need a reservation for 8 people at 12:45 on Sunday.\nChunk 3: Yes, I would also like a hotel with free wifi in the moderate price range.\nChunk 4: no, it should be a guesthouse though.\nChunk 5: Yes for 8 for 3 nights starting sunday.\nChunk 6: No that is all the help I need today Thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=recommendation. C2 goal=booking; time+=8, 12:45; day+=sunday; party_size+=8 people. C3 domain=hotel; price+=moderate; hotel_type+=hotel; amenities+=wifi; goal=confirm_booking. C4 hotel_type+=guesthouse. C5 time+=3; stay_length+=3 nights; goal=confirm_booking. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel; goal=recommendation, search, booking; price=moderate; party_size=8 people; stay_length=3 nights; amenities=wifi; when=sunday, 8, 12:45, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Okay what about spanish cuisine then Please.\nChunk 2: I need a reservation for 8 people at 12:45 on Sunday.\nChunk 3: Yes, I would also like a hotel with free wifi in the moderate price range.\nChunk 4: no, it should be a guesthouse though.\nChunk 5: Yes for 8 for 3 nights starting sunday.\nChunk 6: No that is all the help I need today Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=recommendation. C2 goal=booking; time+=8, 12:45; day+=sunday; party_size+=8 people. C3 domain=hotel; price+=moderate; hotel_type+=hotel; amenities+=wifi; goal=confirm_booking. C4 hotel_type+=guesthouse. C5 time+=3; stay_length+=3 nights; goal=confirm_booking. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel; goal=recommendation, search, booking; price=moderate; party_size=8 people; stay_length=3 nights; amenities=wifi; when=sunday, 8, 12:45, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Okay what about spanish cuisine then Please.\nChunk 2: I need a reservation for 8 people at 12:45 on Sunday.\nChunk 3: Yes, I would also like a hotel with free wifi in the moderate price range.\nChunk 4: no, it should be a guesthouse though.\nChunk 5: Yes for 8 for 3 nights starting sunday.\nChunk 6: No that is all the help I need today Thank you.", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is recommendation. Next, the goal is booking; time: 8; day: sunday; party size: 8 people. Next, the topic is hotel; the goal is confirm booking.; price: moderate; hotel type: hotel; amenities: wifi. Next, hotel type: guesthouse. Finally, the goal is confirm booking.; time: 3; stay length: 3 nights.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is confirm booking.. time: 8, 3; day: sunday; party size: 8 people.; price: moderate; hotel type: hotel, guesthouse.; amenities: wifi; stay length: 3 nights.", "trace": "C1 domain=restaurant; goal=recommendation. C2 goal=booking; time+=8, 12:45; day+=sunday; party_size+=8 people. C3 domain=hotel; price+=moderate; hotel_type+=hotel; amenities+=wifi; goal=confirm_booking. C4 hotel_type+=guesthouse. C5 time+=3; stay_length+=3 nights; goal=confirm_booking. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Okay what about spanish cuisine then Please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is recommendation..", "trace": "domain=restaurant; goal=recommendation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need a reservation for 8 people at 12:45 on Sunday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 8; day: sunday; party size: 8 people..", "trace": "goal=booking; time+=8, 12:45; day+=sunday; party_size+=8 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I would also like a hotel with free wifi in the moderate price range.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is confirm booking.; price: moderate; hotel type: hotel; amenities: wifi.", "trace": "domain=hotel; price+=moderate; hotel_type+=hotel; amenities+=wifi; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "no, it should be a guesthouse though.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse..", "trace": "hotel_type+=guesthouse."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes for 8 for 3 nights starting sunday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 3; stay length: 3 nights.", "trace": "time+=3; stay_length+=3 nights; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No that is all the help I need today Thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: price is moderate; party size is 8 people; stay length is 3 nights; amenities is wifi; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=recommendation, search, booking; price=moderate; party_size=8 people; stay_length=3 nights; amenities=wifi; when=sunday, 8, 12:45, 3; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002536", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need one ticket please and for leaving at 16:15,thank you.\nChunk 2: Yes, that's mostly right, but it should be after 16:15, please.\nChunk 3: Yes, please book it for one person and provide the reference number.\nChunk 4: Could you help me book a hotel called el shaddai?\nChunk 5: Right now I just need their phone number and to know if they have internet or not please Thank you!\nChunk 6: That's all for me Goodbye!", "streaming_reasoning": "C1 goal=search; time+=16:15. C2 acceptance=selected_option. C3 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C4 domain=hotel; hotel_type+=hotel. C5 amenities+=internet; destination+=know if they have internet or not please; requested_info+=phone. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking, request_info, confirm_booking; amenities=internet; destination=know if they have internet or not please; requested_info=reference_number, phone; when=16:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need one ticket please and for leaving at 16:15,thank you.\nChunk 2: Yes, that's mostly right, but it should be after 16:15, please.\nChunk 3: Yes, please book it for one person and provide the reference number.\nChunk 4: Could you help me book a hotel called el shaddai?\nChunk 5: Right now I just need their phone number and to know if they have internet or not please Thank you!\nChunk 6: That's all for me Goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; time+=16:15. C2 acceptance=selected_option. C3 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C4 domain=hotel; hotel_type+=hotel. C5 amenities+=internet; destination+=know if they have internet or not please; requested_info+=phone. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking, request_info, confirm_booking; amenities=internet; destination=know if they have internet or not please; requested_info=reference_number, phone; when=16:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need one ticket please and for leaving at 16:15,thank you.\nChunk 2: Yes, that's mostly right, but it should be after 16:15, please.\nChunk 3: Yes, please book it for one person and provide the reference number.\nChunk 4: Could you help me book a hotel called el shaddai?\nChunk 5: Right now I just need their phone number and to know if they have internet or not please Thank you!\nChunk 6: That's all for me Goodbye!", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; time: 16:15. Next, acceptance: selected_option. Next, the goal is confirm booking.; requested information: reference_number. Next, the topic is hotel; hotel type: hotel. Finally, amenities: internet; destination: know if they have internet or not please; requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is confirm booking.. time: 16:15.; acceptance: selected_option.; requested information: reference_number, phone.; hotel type: hotel.; amenities: internet; destination: know if they have internet or not please.", "trace": "C1 goal=search; time+=16:15. C2 acceptance=selected_option. C3 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C4 domain=hotel; hotel_type+=hotel. C5 amenities+=internet; destination+=know if they have internet or not please; requested_info+=phone. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need one ticket please and for leaving at 16:15,thank you.", "streaming_reasoning": "Initially, the goal is search; time: 16:15..", "trace": "goal=search; time+=16:15."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, that's mostly right, but it should be after 16:15, please.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, please book it for one person and provide the reference number.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you help me book a hotel called el shaddai?", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel..", "trace": "domain=hotel; hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Right now I just need their phone number and to know if they have internet or not please Thank you!", "streaming_reasoning": "As more information arrives, amenities: internet; destination: know if they have internet or not please; requested information: phone..", "trace": "amenities+=internet; destination+=know if they have internet or not please; requested_info+=phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all for me Goodbye!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: amenities is internet; destination is know if they have internet or not please; requested information is reference_number; timing is 16:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, request_info, confirm_booking; amenities=internet; destination=know if they have internet or not please; requested_info=reference_number, phone; when=16:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002537", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant serving modern american food in the moderate price range.\nChunk 2: Yes how about Turkish then?\nChunk 3: yes i reserve to Anatolia restaurant I'm sorry.\nChunk 4: I don't actually need to reserve at this time.\nChunk 5: I just need the phone number and address if you could provide that.\nChunk 6: No.\nChunk 7: That would be it Thanks a lot Goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=moderate. C2 goal=recommendation; cuisine+=turkish; acceptance=selected_option. C3 goal=booking; destination+=anatolia restaurant i'm sorry; goal=confirm_booking. C4 destination+=reserve at this time. C5 goal=request_info; requested_info+=address, phone. C6 goal=modify_constraint. C7 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, booking, request_info; food=turkish; price=moderate; destination=anatolia restaurant i'm sorry, reserve at this time; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant serving modern american food in the moderate price range.\nChunk 2: Yes how about Turkish then?\nChunk 3: yes i reserve to Anatolia restaurant I'm sorry.\nChunk 4: I don't actually need to reserve at this time.\nChunk 5: I just need the phone number and address if you could provide that.\nChunk 6: No.\nChunk 7: That would be it Thanks a lot Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=moderate. C2 goal=recommendation; cuisine+=turkish; acceptance=selected_option. C3 goal=booking; destination+=anatolia restaurant i'm sorry; goal=confirm_booking. C4 destination+=reserve at this time. C5 goal=request_info; requested_info+=address, phone. C6 goal=modify_constraint. C7 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, booking, request_info; food=turkish; price=moderate; destination=anatolia restaurant i'm sorry, reserve at this time; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant serving modern american food in the moderate price range.\nChunk 2: Yes how about Turkish then?\nChunk 3: yes i reserve to Anatolia restaurant I'm sorry.\nChunk 4: I don't actually need to reserve at this time.\nChunk 5: I just need the phone number and address if you could provide that.\nChunk 6: No.\nChunk 7: That would be it Thanks a lot Goodbye.", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate. Next, the goal is recommendation; cuisine: turkish; acceptance: selected_option. Next, the goal is confirm booking.; destination: anatolia restaurant i'm sorry. Next, destination: reserve at this time. Next, the goal is request info; requested information: address. Next, the goal is modify constraint. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is modify constraint.. price: moderate.; cuisine: turkish; acceptance: selected_option.; destination: anatolia restaurant i'm sorry, reserve at this time.; requested information: address; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; price+=moderate. C2 goal=recommendation; cuisine+=turkish; acceptance=selected_option. C3 goal=booking; destination+=anatolia restaurant i'm sorry; goal=confirm_booking. C4 destination+=reserve at this time. C5 goal=request_info; requested_info+=address, phone. C6 goal=modify_constraint. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant serving modern american food in the moderate price range.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate..", "trace": "domain=restaurant; goal=search; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes how about Turkish then?", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: turkish; acceptance: selected_option..", "trace": "goal=recommendation; cuisine+=turkish; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "yes i reserve to Anatolia restaurant I'm sorry.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; destination: anatolia restaurant i'm sorry.", "trace": "goal=booking; destination+=anatolia restaurant i'm sorry; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't actually need to reserve at this time.", "streaming_reasoning": "As more information arrives, destination: reserve at this time..", "trace": "destination+=reserve at this time."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I just need the phone number and address if you could provide that.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That would be it Thanks a lot Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is turkish; price is moderate; destination is anatolia restaurant i'm sorry; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, booking, request_info; food=turkish; price=moderate; destination=anatolia restaurant i'm sorry, reserve at this time; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003195", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Your muscles are a spectacle!\nChunk 2: Thank you.That ' s the result of exercise.By the way, do you work out?\nChunk 3: No, but I am starting working out from now on.", "streaming_reasoning": "C1 casual_comment=muscles, spectacle. C2 [SKIP: thanks_only]. C3 casual_comment=starting, working.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Your muscles are a spectacle!\nChunk 2: Thank you.That ' s the result of exercise.By the way, do you work out?\nChunk 3: No, but I am starting working out from now on."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=muscles, spectacle. C2 [SKIP: thanks_only]. C3 casual_comment=starting, working.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Your muscles are a spectacle!\nChunk 2: Thank you.That ' s the result of exercise.By the way, do you work out?\nChunk 3: No, but I am starting working out from now on.", "input_token_count": 36, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on muscles. Finally, the user comments on starting.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=muscles, spectacle. C2 [SKIP: thanks_only]. C3 casual_comment=starting, working.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Your muscles are a spectacle!", "streaming_reasoning": "Initially, the user comments on muscles.", "trace": "casual_comment=muscles, spectacle."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thank you.That ' s the result of exercise.By the way, do you work out?", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, but I am starting working out from now on.", "streaming_reasoning": "Finally, the user comments on starting.", "trace": "casual_comment=starting, working."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002538", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a place to stay that includes free parking, my price range is on the expensive end.\nChunk 2: Yes, I'm thinking I'd like it to be in the north Does that help?\nChunk 3: What about any in the cheap range?\nChunk 4: Yes, can you please book it for 5 people and 5 nights starting from thursday?\nChunk 5: Thank you that is all I need, goodbye.", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=expensive; amenities+=parking, free parking; destination+=stay that includes free parking. C2 area+=north; acceptance=selected_option. C3 goal=recommendation; price+=cheap. C4 goal=confirm_booking; time+=5; day+=thursday; party_size+=5 people; stay_length+=5 nights; goal=confirm_booking. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, recommendation, booking, confirm_booking; area=north; price=expensive, cheap; party_size=5 people; stay_length=5 nights; amenities=parking, free parking; destination=stay that includes free parking; when=thursday, 5; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a place to stay that includes free parking, my price range is on the expensive end.\nChunk 2: Yes, I'm thinking I'd like it to be in the north Does that help?\nChunk 3: What about any in the cheap range?\nChunk 4: Yes, can you please book it for 5 people and 5 nights starting from thursday?\nChunk 5: Thank you that is all I need, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=expensive; amenities+=parking, free parking; destination+=stay that includes free parking. C2 area+=north; acceptance=selected_option. C3 goal=recommendation; price+=cheap. C4 goal=confirm_booking; time+=5; day+=thursday; party_size+=5 people; stay_length+=5 nights; goal=confirm_booking. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, recommendation, booking, confirm_booking; area=north; price=expensive, cheap; party_size=5 people; stay_length=5 nights; amenities=parking, free parking; destination=stay that includes free parking; when=thursday, 5; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a place to stay that includes free parking, my price range is on the expensive end.\nChunk 2: Yes, I'm thinking I'd like it to be in the north Does that help?\nChunk 3: What about any in the cheap range?\nChunk 4: Yes, can you please book it for 5 people and 5 nights starting from thursday?\nChunk 5: Thank you that is all I need, goodbye.", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: expensive; amenities: parking; destination: stay that includes free parking. Next, area: north; acceptance: selected_option. Next, the goal is recommendation; price: cheap. Finally, the goal is confirm booking.; time: 5; day: thursday; party size: 5 people; stay length: 5 nights.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is confirm booking.. price: expensive, cheap.; amenities: parking; destination: stay that includes free parking.; area: north; acceptance: selected_option.; time: 5; day: thursday; party size: 5 people; stay length: 5 nights.", "trace": "C1 domain=hotel; goal=search; price+=expensive; amenities+=parking, free parking; destination+=stay that includes free parking. C2 area+=north; acceptance=selected_option. C3 goal=recommendation; price+=cheap. C4 goal=confirm_booking; time+=5; day+=thursday; party_size+=5 people; stay_length+=5 nights; goal=confirm_booking. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a place to stay that includes free parking, my price range is on the expensive end.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: expensive; amenities: parking; destination: stay that includes free parking..", "trace": "domain=hotel; goal=search; price+=expensive; amenities+=parking, free parking; destination+=stay that includes free parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I'm thinking I'd like it to be in the north Does that help?", "streaming_reasoning": "As more information arrives, area: north; acceptance: selected_option..", "trace": "area+=north; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What about any in the cheap range?", "streaming_reasoning": "As more information arrives, the goal is recommendation; price: cheap..", "trace": "goal=recommendation; price+=cheap."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, can you please book it for 5 people and 5 nights starting from thursday?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 5; day: thursday; party size: 5 people; stay length: 5 nights.", "trace": "goal=confirm_booking; time+=5; day+=thursday; party_size+=5 people; stay_length+=5 nights; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you that is all I need, goodbye.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; price is expensive; party size is 5 people; stay length is 5 nights; amenities is parking; destination is stay that includes free parking; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, recommendation, booking, confirm_booking; area=north; price=expensive, cheap; party_size=5 people; stay_length=5 nights; amenities=parking, free parking; destination=stay that includes free parking; when=thursday, 5; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003202", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sorry, madam.\nChunk 2: You have to wait your turn.\nChunk 3: The parking lot is full Unbelievable!\nChunk 4: Parking in this city is such a nightmare!\nChunk 5: Madam, patience is a virtue Oh, gosh!\nChunk 6: I have to go to the restroom so bad!\nChunk 7: I can't bear it anymore!\nChunk 8: I'm sure a spot will open up soon.", "streaming_reasoning": "C1 [SKIP: low_information]. C2 casual_comment=wait, turn. C3 casual_comment=parking, lot. C4 casual_comment=parking, city. C5 casual_comment=madam, patience. C6 leaving_reason=needs_to_go. C7 schedule_conflict=true. C8 casual_comment=i'm, spot.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sorry, madam.\nChunk 2: You have to wait your turn.\nChunk 3: The parking lot is full Unbelievable!\nChunk 4: Parking in this city is such a nightmare!\nChunk 5: Madam, patience is a virtue Oh, gosh!\nChunk 6: I have to go to the restroom so bad!\nChunk 7: I can't bear it anymore!\nChunk 8: I'm sure a spot will open up soon."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: low_information]. C2 casual_comment=wait, turn. C3 casual_comment=parking, lot. C4 casual_comment=parking, city. C5 casual_comment=madam, patience. C6 leaving_reason=needs_to_go. C7 schedule_conflict=true. C8 casual_comment=i'm, spot.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sorry, madam.\nChunk 2: You have to wait your turn.\nChunk 3: The parking lot is full Unbelievable!\nChunk 4: Parking in this city is such a nightmare!\nChunk 5: Madam, patience is a virtue Oh, gosh!\nChunk 6: I have to go to the restroom so bad!\nChunk 7: I can't bear it anymore!\nChunk 8: I'm sure a spot will open up soon.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on wait. Next, the user comments on parking. Next, the user comments on parking. Next, the user comments on madam. Next, leaving reason: needs_to_go. Next, schedule conflict: true. Finally, the user comments on i'm.  Some chunks were skipped because they contained low_information. In summary, leaving reason: needs_to_go.; schedule conflict: true..", "trace": "C1 [SKIP: low_information]. C2 casual_comment=wait, turn. C3 casual_comment=parking, lot. C4 casual_comment=parking, city. C5 casual_comment=madam, patience. C6 leaving_reason=needs_to_go. C7 schedule_conflict=true. C8 casual_comment=i'm, spot.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sorry, madam.", "streaming_reasoning": "The content at C1 was skipped (low_information).", "trace": "[SKIP: low_information]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "You have to wait your turn.", "streaming_reasoning": "As more information arrives, the user comments on wait.", "trace": "casual_comment=wait, turn."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The parking lot is full Unbelievable!", "streaming_reasoning": "As more information arrives, the user comments on parking.", "trace": "casual_comment=parking, lot."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Parking in this city is such a nightmare!", "streaming_reasoning": "As more information arrives, the user comments on parking.", "trace": "casual_comment=parking, city."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Madam, patience is a virtue Oh, gosh!", "streaming_reasoning": "As more information arrives, the user comments on madam.", "trace": "casual_comment=madam, patience."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I have to go to the restroom so bad!", "streaming_reasoning": "As more information arrives, leaving reason: needs_to_go..", "trace": "leaving_reason=needs_to_go."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I can't bear it anymore!", "streaming_reasoning": "As more information arrives, schedule conflict: true..", "trace": "schedule_conflict=true."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'm sure a spot will open up soon.", "streaming_reasoning": "Finally, the user comments on i'm.", "trace": "casual_comment=i'm, spot."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002540", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Try something in the center of town Yes please.\nChunk 2: It's for 2 people and 2 nights starting on Thursday.\nChunk 3: How about a place to dine in the expensive price range serving indian food.\nChunk 4: I would like somewhere in the same area as the hotel.\nChunk 5: Then please pick one and give me their phone number band postcode That is everything.\nChunk 6: Thank you for your help.", "streaming_reasoning": "C1 area+=centre; acceptance=selected_option. C2 time+=2; day+=thursday; party_size+=2 people; stay_length+=2 nights. C3 domain=restaurant; goal=recommendation; cuisine+=indian; price+=expensive; destination+=dine in the expensive price range serving. C4 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C5 goal=request_info; requested_info+=phone, postcode. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, hotel; goal=recommendation, modify_constraint, request_info; area=centre; food=indian; price=expensive; party_size=2 people; stay_length=2 nights; destination=dine in the expensive price range serving; requested_info=phone, postcode; when=thursday, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Try something in the center of town Yes please.\nChunk 2: It's for 2 people and 2 nights starting on Thursday.\nChunk 3: How about a place to dine in the expensive price range serving indian food.\nChunk 4: I would like somewhere in the same area as the hotel.\nChunk 5: Then please pick one and give me their phone number band postcode That is everything.\nChunk 6: Thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre; acceptance=selected_option. C2 time+=2; day+=thursday; party_size+=2 people; stay_length+=2 nights. C3 domain=restaurant; goal=recommendation; cuisine+=indian; price+=expensive; destination+=dine in the expensive price range serving. C4 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C5 goal=request_info; requested_info+=phone, postcode. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, hotel; goal=recommendation, modify_constraint, request_info; area=centre; food=indian; price=expensive; party_size=2 people; stay_length=2 nights; destination=dine in the expensive price range serving; requested_info=phone, postcode; when=thursday, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Try something in the center of town Yes please.\nChunk 2: It's for 2 people and 2 nights starting on Thursday.\nChunk 3: How about a place to dine in the expensive price range serving indian food.\nChunk 4: I would like somewhere in the same area as the hotel.\nChunk 5: Then please pick one and give me their phone number band postcode That is everything.\nChunk 6: Thank you for your help.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: centre; acceptance: selected_option. Next, time: 2; day: thursday; party size: 2 people; stay length: 2 nights. Next, the topic is restaurant; the goal is recommendation; cuisine: indian; price: expensive; destination: dine in the expensive price range serving. Next, the topic is hotel; the goal is modify constraint; hotel type: hotel. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is request info. area: centre; acceptance: selected_option.; time: 2; day: thursday; party size: 2 people; stay length: 2 nights.; cuisine: indian; price: expensive; destination: dine in the expensive price range serving.; hotel type: hotel.; requested information: phone.", "trace": "C1 area+=centre; acceptance=selected_option. C2 time+=2; day+=thursday; party_size+=2 people; stay_length+=2 nights. C3 domain=restaurant; goal=recommendation; cuisine+=indian; price+=expensive; destination+=dine in the expensive price range serving. C4 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C5 goal=request_info; requested_info+=phone, postcode. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Try something in the center of town Yes please.", "streaming_reasoning": "Initially, area: centre; acceptance: selected_option..", "trace": "area+=centre; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It's for 2 people and 2 nights starting on Thursday.", "streaming_reasoning": "As more information arrives, time: 2; day: thursday; party size: 2 people; stay length: 2 nights..", "trace": "time+=2; day+=thursday; party_size+=2 people; stay_length+=2 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about a place to dine in the expensive price range serving indian food.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is recommendation; cuisine: indian; price: expensive; destination: dine in the expensive price range serving..", "trace": "domain=restaurant; goal=recommendation; cuisine+=indian; price+=expensive; destination+=dine in the expensive price range serving."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like somewhere in the same area as the hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is modify constraint; hotel type: hotel..", "trace": "domain=hotel; goal=modify_constraint; hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Then please pick one and give me their phone number band postcode That is everything.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: area is centre; cuisine is indian; price is expensive; party size is 2 people; stay length is 2 nights; destination is dine in the expensive price range serving; requested information is phone; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=recommendation, modify_constraint, request_info; area=centre; food=indian; price=expensive; party_size=2 people; stay_length=2 nights; destination=dine in the expensive price range serving; requested_info=phone, postcode; when=thursday, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002541", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I need some information about a restaurant called pizza express.\nChunk 2: I'd like to know if I can book a reservation for 7 people at 18:00 monday.\nChunk 3: Either one will work, I just need to book for 7 people at 18:00 on monday?\nChunk 4: How about 17:00?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:00.\nChunk 7: Great that was all I needed today, thank you!", "streaming_reasoning": "C1 domain=restaurant; goal=search; acceptance=selected_option. C2 goal=booking; time+=7, 18:00; day+=monday; party_size+=7 people. C3 goal=request_info. C4 goal=recommendation; time+=17:00. C5 destination+=find a restaurant. C6 intent=context_update. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, recommendation; party_size=7 people; destination=find a restaurant; when=monday, 7, 18:00, 17:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I need some information about a restaurant called pizza express.\nChunk 2: I'd like to know if I can book a reservation for 7 people at 18:00 monday.\nChunk 3: Either one will work, I just need to book for 7 people at 18:00 on monday?\nChunk 4: How about 17:00?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:00.\nChunk 7: Great that was all I needed today, thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; acceptance=selected_option. C2 goal=booking; time+=7, 18:00; day+=monday; party_size+=7 people. C3 goal=request_info. C4 goal=recommendation; time+=17:00. C5 destination+=find a restaurant. C6 intent=context_update. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, recommendation; party_size=7 people; destination=find a restaurant; when=monday, 7, 18:00, 17:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I need some information about a restaurant called pizza express.\nChunk 2: I'd like to know if I can book a reservation for 7 people at 18:00 monday.\nChunk 3: Either one will work, I just need to book for 7 people at 18:00 on monday?\nChunk 4: How about 17:00?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:00.\nChunk 7: Great that was all I needed today, thank you!", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; acceptance: selected_option. Next, the goal is booking; time: 7; day: monday; party size: 7 people. Next, the goal is request info. Next, the goal is recommendation; time: 17:00. Next, destination: find a restaurant. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is recommendation. acceptance: selected_option.; time: 7, 17:00.; day: monday; party size: 7 people.; destination: find a restaurant.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; acceptance=selected_option. C2 goal=booking; time+=7, 18:00; day+=monday; party_size+=7 people. C3 goal=request_info. C4 goal=recommendation; time+=17:00. C5 destination+=find a restaurant. C6 intent=context_update. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I need some information about a restaurant called pizza express.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; acceptance: selected_option..", "trace": "domain=restaurant; goal=search; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to know if I can book a reservation for 7 people at 18:00 monday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 7; day: monday; party size: 7 people..", "trace": "goal=booking; time+=7, 18:00; day+=monday; party_size+=7 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Either one will work, I just need to book for 7 people at 18:00 on monday?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "How about 17:00?", "streaming_reasoning": "As more information arrives, the goal is recommendation; time: 17:00..", "trace": "goal=recommendation; time+=17:00."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, destination: find a restaurant..", "trace": "destination+=find a restaurant."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 17:00.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Great that was all I needed today, thank you!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 7 people; destination is find a restaurant; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, recommendation; party_size=7 people; destination=find a restaurant; when=monday, 7, 18:00, 17:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002542", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: In the centre please.\nChunk 2: And make it Portuguese.\nChunk 3: I don't care about price.\nChunk 4: I have no idea where I got the idea of cheap Italian from, smh i apologize.\nChunk 5: my husband wants something expensive.\nChunk 6: do you have any portuguese places that are expensive?\nChunk 7: in that case what about french?\nChunk 8: I'd rather the one in the center.\nChunk 9: What is it called That sounds good.\nChunk 10: Can you get me the address, post code and phone number, please?\nChunk 11: No thank you I do not need reservations.", "streaming_reasoning": "C1 area+=centre. C2 goal=modify_constraint. C3 intent=context_update. C4 cuisine+=italian; price+=cheap. C5 price+=expensive. C6 goal=request_info. C7 goal=recommendation; cuisine+=french. C8 intent=context_update. C9 goal=request_info; acceptance=selected_option. C10 goal=search; requested_info+=address, phone, postcode. C11 [SKIP: thanks_only].", "deep_reasoning": "Need goal=modify_constraint, recommendation, request_info, search; area=centre; food=italian, french; price=cheap, expensive; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: In the centre please.\nChunk 2: And make it Portuguese.\nChunk 3: I don't care about price.\nChunk 4: I have no idea where I got the idea of cheap Italian from, smh i apologize.\nChunk 5: my husband wants something expensive.\nChunk 6: do you have any portuguese places that are expensive?\nChunk 7: in that case what about french?\nChunk 8: I'd rather the one in the center.\nChunk 9: What is it called That sounds good.\nChunk 10: Can you get me the address, post code and phone number, please?\nChunk 11: No thank you I do not need reservations."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre. C2 goal=modify_constraint. C3 intent=context_update. C4 cuisine+=italian; price+=cheap. C5 price+=expensive. C6 goal=request_info. C7 goal=recommendation; cuisine+=french. C8 intent=context_update. C9 goal=request_info; acceptance=selected_option. C10 goal=search; requested_info+=address, phone, postcode. C11 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=modify_constraint, recommendation, request_info, search; area=centre; food=italian, french; price=cheap, expensive; requested_info=address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: In the centre please.\nChunk 2: And make it Portuguese.\nChunk 3: I don't care about price.\nChunk 4: I have no idea where I got the idea of cheap Italian from, smh i apologize.\nChunk 5: my husband wants something expensive.\nChunk 6: do you have any portuguese places that are expensive?\nChunk 7: in that case what about french?\nChunk 8: I'd rather the one in the center.\nChunk 9: What is it called That sounds good.\nChunk 10: Can you get me the address, post code and phone number, please?\nChunk 11: No thank you I do not need reservations.", "input_token_count": 105, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, area: centre. Next, the goal is modify constraint. Next, intent: context_update. Next, cuisine: italian; price: cheap. Next, price: expensive. Next, the goal is request info. Next, the goal is recommendation; cuisine: french. Next, intent: context_update. Next, the goal is request info; acceptance: selected_option. Finally, the goal is search; requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, the goal is search. area: centre.; intent: context_update.; cuisine: italian, french.; price: cheap., expensive.; acceptance: selected_option.; requested information: address.", "trace": "C1 area+=centre. C2 goal=modify_constraint. C3 intent=context_update. C4 cuisine+=italian; price+=cheap. C5 price+=expensive. C6 goal=request_info. C7 goal=recommendation; cuisine+=french. C8 intent=context_update. C9 goal=request_info; acceptance=selected_option. C10 goal=search; requested_info+=address, phone, postcode. C11 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "In the centre please.", "streaming_reasoning": "Initially, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "And make it Portuguese.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I don't care about price.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I have no idea where I got the idea of cheap Italian from, smh i apologize.", "streaming_reasoning": "As more information arrives, cuisine: italian; price: cheap..", "trace": "cuisine+=italian; price+=cheap."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "my husband wants something expensive.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "do you have any portuguese places that are expensive?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "in that case what about french?", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: french..", "trace": "goal=recommendation; cuisine+=french."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'd rather the one in the center.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "What is it called That sounds good.", "streaming_reasoning": "As more information arrives, the goal is request info; acceptance: selected_option..", "trace": "goal=request_info; acceptance=selected_option."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Can you get me the address, post code and phone number, please?", "streaming_reasoning": "As more information arrives, the goal is search; requested information: address.", "trace": "goal=search; requested_info+=address, phone, postcode."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "No thank you I do not need reservations.", "streaming_reasoning": "The content at C11 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=modify_constraint, recommendation, request_info, search; area=centre; food=italian, french; price=cheap, expensive; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002543", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I also need a train leaving after 18:30 from kings lynn to cambridge.\nChunk 2: same day as my hotel booking Great!\nChunk 3: I will need 5 tickets Thank you.\nChunk 4: What's the travel time?\nChunk 5: Thank you very much.\nChunk 6: No, that is all I need.\nChunk 7: Thanks!", "streaming_reasoning": "C1 domain=train; goal=search; time+=18:30; destination+=cambridge; departure+=kings lynn; acceptance=selected_option. C2 domain=hotel; goal=booking; hotel_type+=hotel. C3 intent=context_update. C4 goal=request_info; requested_info+=travel_time. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, hotel; goal=search, booking, request_info; destination=cambridge; departure=kings lynn; requested_info=travel_time; when=18:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I also need a train leaving after 18:30 from kings lynn to cambridge.\nChunk 2: same day as my hotel booking Great!\nChunk 3: I will need 5 tickets Thank you.\nChunk 4: What's the travel time?\nChunk 5: Thank you very much.\nChunk 6: No, that is all I need.\nChunk 7: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; time+=18:30; destination+=cambridge; departure+=kings lynn; acceptance=selected_option. C2 domain=hotel; goal=booking; hotel_type+=hotel. C3 intent=context_update. C4 goal=request_info; requested_info+=travel_time. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, hotel; goal=search, booking, request_info; destination=cambridge; departure=kings lynn; requested_info=travel_time; when=18:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I also need a train leaving after 18:30 from kings lynn to cambridge.\nChunk 2: same day as my hotel booking Great!\nChunk 3: I will need 5 tickets Thank you.\nChunk 4: What's the travel time?\nChunk 5: Thank you very much.\nChunk 6: No, that is all I need.\nChunk 7: Thanks!", "input_token_count": 58, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 18:30; destination: cambridge; departure point: kings lynn; acceptance: selected_option. Next, the topic is hotel; the goal is booking; hotel type: hotel. Next, intent: context_update. Finally, the goal is request info; requested information: travel_time.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is request info. time: 18:30; destination: cambridge; departure point: kings lynn; acceptance: selected_option.; hotel type: hotel.; intent: context_update.; requested information: travel_time..", "trace": "C1 domain=train; goal=search; time+=18:30; destination+=cambridge; departure+=kings lynn; acceptance=selected_option. C2 domain=hotel; goal=booking; hotel_type+=hotel. C3 intent=context_update. C4 goal=request_info; requested_info+=travel_time. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I also need a train leaving after 18:30 from kings lynn to cambridge.", "streaming_reasoning": "Initially, the topic is train; the goal is search; time: 18:30; destination: cambridge; departure point: kings lynn; acceptance: selected_option..", "trace": "domain=train; goal=search; time+=18:30; destination+=cambridge; departure+=kings lynn; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "same day as my hotel booking Great!", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is booking; hotel type: hotel..", "trace": "domain=hotel; goal=booking; hotel_type+=hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I will need 5 tickets Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What's the travel time?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, that is all I need.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge; departure point is kings lynn; requested information is travel_time; timing is 18:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, booking, request_info; destination=cambridge; departure=kings lynn; requested_info=travel_time; when=18:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002544", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for places to go in the centre of Cambridge.\nChunk 2: What's the postcode for your favorite one?\nChunk 3: I also need to book a train.\nChunk 4: I need to leave on sunday after 12:30 from cambridge to stevenage.\nChunk 5: Great, can I get two tickets on it, please No, thank you.\nChunk 6: You've been very helpful Goodbye.", "streaming_reasoning": "C1 goal=search; area+=centre; destination+=go in the centre of cambridge. C2 goal=request_info; requested_info+=postcode. C3 domain=train; goal=booking. C4 time+=12:30; day+=sunday; destination+=stevenage; departure+=cambridge. C5 goal=modify_constraint. C6 intent=context_update.", "deep_reasoning": "Need domain=train; goal=search, recommendation, request_info, booking; area=centre; destination=go in the centre of cambridge, stevenage; departure=cambridge; requested_info=postcode; when=sunday, 12:30.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for places to go in the centre of Cambridge.\nChunk 2: What's the postcode for your favorite one?\nChunk 3: I also need to book a train.\nChunk 4: I need to leave on sunday after 12:30 from cambridge to stevenage.\nChunk 5: Great, can I get two tickets on it, please No, thank you.\nChunk 6: You've been very helpful Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre; destination+=go in the centre of cambridge. C2 goal=request_info; requested_info+=postcode. C3 domain=train; goal=booking. C4 time+=12:30; day+=sunday; destination+=stevenage; departure+=cambridge. C5 goal=modify_constraint. C6 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=search, recommendation, request_info, booking; area=centre; destination=go in the centre of cambridge, stevenage; departure=cambridge; requested_info=postcode; when=sunday, 12:30.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for places to go in the centre of Cambridge.\nChunk 2: What's the postcode for your favorite one?\nChunk 3: I also need to book a train.\nChunk 4: I need to leave on sunday after 12:30 from cambridge to stevenage.\nChunk 5: Great, can I get two tickets on it, please No, thank you.\nChunk 6: You've been very helpful Goodbye.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre; destination: go in the centre of cambridge. Next, the goal is request info; requested information: postcode. Next, the topic is train; the goal is booking. Next, time: 12:30; day: sunday; destination: stevenage; departure point: cambridge. Next, the goal is modify constraint. Finally, intent: context_update. In summary, The overall topic is train. the goal is modify constraint.. area: centre; destination: go in the centre of cambridge., stevenage; requested information: postcode.; time: 12:30; day: sunday; departure point: cambridge.; intent: context_update..", "trace": "C1 goal=search; area+=centre; destination+=go in the centre of cambridge. C2 goal=request_info; requested_info+=postcode. C3 domain=train; goal=booking. C4 time+=12:30; day+=sunday; destination+=stevenage; departure+=cambridge. C5 goal=modify_constraint. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for places to go in the centre of Cambridge.", "streaming_reasoning": "Initially, the goal is search; area: centre; destination: go in the centre of cambridge..", "trace": "goal=search; area+=centre; destination+=go in the centre of cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What's the postcode for your favorite one?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need to book a train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is booking..", "trace": "domain=train; goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to leave on sunday after 12:30 from cambridge to stevenage.", "streaming_reasoning": "As more information arrives, time: 12:30; day: sunday; destination: stevenage; departure point: cambridge..", "trace": "time+=12:30; day+=sunday; destination+=stevenage; departure+=cambridge."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Great, can I get two tickets on it, please No, thank you.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "You've been very helpful Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is centre; destination is go in the centre of cambridge; departure point is cambridge; requested information is postcode; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=search, recommendation, request_info, booking; area=centre; destination=go in the centre of cambridge, stevenage; departure=cambridge; requested_info=postcode; when=sunday, 12:30."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002545", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I'm looking for a train, please.\nChunk 3: I need to leave from Cambridge on Sunday.\nChunk 4: Well, I'm thinking I need to leave sometime after 10:45 for Norwich.\nChunk 5: Yes, I'd like one ticket please.\nChunk 6: Thank you very much.\nChunk 7: I am all set.\nChunk 8: Have a nice day.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=search. C3 day+=sunday. C4 time+=10:45; destination+=leave sometime after 10:45 for norwich. C5 goal=confirm_booking; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 intent=context_update. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, confirm_booking; destination=leave sometime after 10:45 for norwich; when=sunday, 10:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I'm looking for a train, please.\nChunk 3: I need to leave from Cambridge on Sunday.\nChunk 4: Well, I'm thinking I need to leave sometime after 10:45 for Norwich.\nChunk 5: Yes, I'd like one ticket please.\nChunk 6: Thank you very much.\nChunk 7: I am all set.\nChunk 8: Have a nice day."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=search. C3 day+=sunday. C4 time+=10:45; destination+=leave sometime after 10:45 for norwich. C5 goal=confirm_booking; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 intent=context_update. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, confirm_booking; destination=leave sometime after 10:45 for norwich; when=sunday, 10:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I'm looking for a train, please.\nChunk 3: I need to leave from Cambridge on Sunday.\nChunk 4: Well, I'm thinking I need to leave sometime after 10:45 for Norwich.\nChunk 5: Yes, I'd like one ticket please.\nChunk 6: Thank you very much.\nChunk 7: I am all set.\nChunk 8: Have a nice day.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, day: sunday. Next, time: 10:45; destination: leave sometime after 10:45 for norwich. Next, the goal is confirm booking; acceptance: selected_option. Finally, intent: context_update.  Some chunks were skipped because they contained acknowledgement_only or closing_only or thanks_only. In summary, The overall topic is train. the goal is confirm booking. day: sunday.; time: 10:45; destination: leave sometime after 10:45 for norwich.; acceptance: selected_option.; intent: context_update..", "trace": "C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=search. C3 day+=sunday. C4 time+=10:45; destination+=leave sometime after 10:45 for norwich. C5 goal=confirm_booking; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 intent=context_update. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm looking for a train, please.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to leave from Cambridge on Sunday.", "streaming_reasoning": "As more information arrives, day: sunday..", "trace": "day+=sunday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Well, I'm thinking I need to leave sometime after 10:45 for Norwich.", "streaming_reasoning": "As more information arrives, time: 10:45; destination: leave sometime after 10:45 for norwich..", "trace": "time+=10:45; destination+=leave sometime after 10:45 for norwich."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, I'd like one ticket please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking; acceptance: selected_option..", "trace": "goal=confirm_booking; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am all set.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Have a nice day.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is leave sometime after 10:45 for norwich; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, confirm_booking; destination=leave sometime after 10:45 for norwich; when=sunday, 10:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002546", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please help me find a train that leaves Norwich after 5:45 PM.\nChunk 2: Thanks.\nChunk 3: I would like to travel on Saturday please.\nChunk 4: yes book for me fo 3 people and provide me with reference number.\nChunk 5: Yes, I'd also like to find some places to go while I'm in town.\nChunk 6: What is there in the way of architectural attractions in the city centre?\nChunk 7: Yes, can you please send that to me No, that's perfect.\nChunk 8: Thank you for you help.", "streaming_reasoning": "C1 domain=train; goal=search; time+=5:45 pm. C2 [SKIP: thanks_only]. C3 day+=saturday; destination+=travel on saturday please. C4 goal=confirm_booking; party_size+=3 people; requested_info+=reference_number; goal=confirm_booking. C5 destination+=find some places to go while i'm in town; goal=confirm_booking. C6 area+=centre. C7 destination+=me no; goal=confirm_booking. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search, booking, request_info, confirm_booking; area=centre; party_size=3 people; destination=travel on saturday please, find some places to go while i'm in town, me no; requested_info=reference_number; when=saturday, 5:45 pm; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Please help me find a train that leaves Norwich after 5:45 PM.\nChunk 2: Thanks.\nChunk 3: I would like to travel on Saturday please.\nChunk 4: yes book for me fo 3 people and provide me with reference number.\nChunk 5: Yes, I'd also like to find some places to go while I'm in town.\nChunk 6: What is there in the way of architectural attractions in the city centre?\nChunk 7: Yes, can you please send that to me No, that's perfect.\nChunk 8: Thank you for you help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; time+=5:45 pm. C2 [SKIP: thanks_only]. C3 day+=saturday; destination+=travel on saturday please. C4 goal=confirm_booking; party_size+=3 people; requested_info+=reference_number; goal=confirm_booking. C5 destination+=find some places to go while i'm in town; goal=confirm_booking. C6 area+=centre. C7 destination+=me no; goal=confirm_booking. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search, booking, request_info, confirm_booking; area=centre; party_size=3 people; destination=travel on saturday please, find some places to go while i'm in town, me no; requested_info=reference_number; when=saturday, 5:45 pm; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please help me find a train that leaves Norwich after 5:45 PM.\nChunk 2: Thanks.\nChunk 3: I would like to travel on Saturday please.\nChunk 4: yes book for me fo 3 people and provide me with reference number.\nChunk 5: Yes, I'd also like to find some places to go while I'm in town.\nChunk 6: What is there in the way of architectural attractions in the city centre?\nChunk 7: Yes, can you please send that to me No, that's perfect.\nChunk 8: Thank you for you help.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 5:45 pm. Next, day: saturday; destination: travel on saturday please. Next, the goal is confirm booking.; party size: 3 people; requested information: reference_number. Next, the goal is confirm booking.; destination: find some places to go while i'm in town. Next, area: centre. Finally, the goal is confirm booking.; destination: me no.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is confirm booking.. time: 5:45 pm.; day: saturday; destination: travel on saturday please., find some places to go while i'm in town, me no; party size: 3 people; requested information: reference_number; area: centre..", "trace": "C1 domain=train; goal=search; time+=5:45 pm. C2 [SKIP: thanks_only]. C3 day+=saturday; destination+=travel on saturday please. C4 goal=confirm_booking; party_size+=3 people; requested_info+=reference_number; goal=confirm_booking. C5 destination+=find some places to go while i'm in town; goal=confirm_booking. C6 area+=centre. C7 destination+=me no; goal=confirm_booking. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Please help me find a train that leaves Norwich after 5:45 PM.", "streaming_reasoning": "Initially, the topic is train; the goal is search; time: 5:45 pm..", "trace": "domain=train; goal=search; time+=5:45 pm."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to travel on Saturday please.", "streaming_reasoning": "As more information arrives, day: saturday; destination: travel on saturday please..", "trace": "day+=saturday; destination+=travel on saturday please."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "yes book for me fo 3 people and provide me with reference number.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; party size: 3 people; requested information: reference_number.", "trace": "goal=confirm_booking; party_size+=3 people; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, I'd also like to find some places to go while I'm in town.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; destination: find some places to go while i'm in town.", "trace": "destination+=find some places to go while i'm in town; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What is there in the way of architectural attractions in the city centre?", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, can you please send that to me No, that's perfect.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; destination: me no.", "trace": "destination+=me no; goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for you help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is centre; party size is 3 people; destination is travel on saturday please; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, booking, request_info, confirm_booking; area=centre; party_size=3 people; destination=travel on saturday please, find some places to go while i'm in town, me no; requested_info=reference_number; when=saturday, 5:45 pm; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002547", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you.I am looking for a guest house.I am also looking for one that is rather cheap.\nChunk 2: The hotel doesn't need to have free parking and should have a star of 3.\nChunk 3: advic me on any other option.\nChunk 4: No, how about a moderate-price guesthouse, please Try that.\nChunk 5: Can I just get the phone number instead please?\nChunk 6: No, that is all good bye.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking; destination+=have free parking and should have a star. C3 intent=context_update. C4 goal=recommendation; price+=moderate; hotel_type+=guesthouse. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, recommendation, compare_alternative, request_info; price=moderate; amenities=parking, free parking; destination=have free parking and should have a star; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you.I am looking for a guest house.I am also looking for one that is rather cheap.\nChunk 2: The hotel doesn't need to have free parking and should have a star of 3.\nChunk 3: advic me on any other option.\nChunk 4: No, how about a moderate-price guesthouse, please Try that.\nChunk 5: Can I just get the phone number instead please?\nChunk 6: No, that is all good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking; destination+=have free parking and should have a star. C3 intent=context_update. C4 goal=recommendation; price+=moderate; hotel_type+=guesthouse. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, recommendation, compare_alternative, request_info; price=moderate; amenities=parking, free parking; destination=have free parking and should have a star; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you.I am looking for a guest house.I am also looking for one that is rather cheap.\nChunk 2: The hotel doesn't need to have free parking and should have a star of 3.\nChunk 3: advic me on any other option.\nChunk 4: No, how about a moderate-price guesthouse, please Try that.\nChunk 5: Can I just get the phone number instead please?\nChunk 6: No, that is all good bye.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; amenities: parking; destination: have free parking and should have a star. Next, intent: context_update. Next, the goal is recommendation; price: moderate; hotel type: guesthouse. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is request info. hotel type: hotel, guesthouse.; amenities: parking; destination: have free parking and should have a star.; intent: context_update.; price: moderate; requested information: phone..", "trace": "C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking; destination+=have free parking and should have a star. C3 intent=context_update. C4 goal=recommendation; price+=moderate; hotel_type+=guesthouse. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you.I am looking for a guest house.I am also looking for one that is rather cheap.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The hotel doesn't need to have free parking and should have a star of 3.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: hotel; amenities: parking; destination: have free parking and should have a star..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking; destination+=have free parking and should have a star."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "advic me on any other option.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, how about a moderate-price guesthouse, please Try that.", "streaming_reasoning": "As more information arrives, the goal is recommendation; price: moderate; hotel type: guesthouse..", "trace": "goal=recommendation; price+=moderate; hotel_type+=guesthouse."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I just get the phone number instead please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, that is all good bye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is moderate; amenities is parking; destination is have free parking and should have a star; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, recommendation, compare_alternative, request_info; price=moderate; amenities=parking, free parking; destination=have free parking and should have a star; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000532", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Check if a Remote Control is Transmitting an Infrared Signal.\nChunk 2: • The remote control you think is not working.\nChunk 3: • Good tested batteries installed properly into remote control.\nChunk 4: • Any digital camera (camera phone and computer cams work too) • A helper to press the remote button (optional) • Try pointing remote control towards the back of a radio (switched on) on an empty channel on the am band and listen for \"clicking\" sounds.", "streaming_reasoning": "C1 task=check_if_a_remote. C2 step=the_remote_control_you. C3 step=good_tested_batteries_installed. C4 step=any_digital_camera_camera.", "deep_reasoning": "Procedure for Check if a Remote Control is Transmitting an: The remote control you think is not working, Good tested batteries installed properly into remote control, Any digital camera A helper to press the remote button.", "answer": "For Check if a Remote Control is Transmitting an, follow the steps in order: The remote control you think is not working, Good tested batteries installed properly into remote control, Any digital camera A helper to press the remote button.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Check if a Remote Control is Transmitting an Infrared Signal.\nChunk 2: • The remote control you think is not working.\nChunk 3: • Good tested batteries installed properly into remote control.\nChunk 4: • Any digital camera (camera phone and computer cams work too) • A helper to press the remote button (optional) • Try pointing remote control towards the back of a radio (switched on) on an empty channel on the am band and listen for \"clicking\" sounds."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=check_if_a_remote. C2 step=the_remote_control_you. C3 step=good_tested_batteries_installed. C4 step=any_digital_camera_camera.\n\nDeep reasoning: Procedure for Check if a Remote Control is Transmitting an: The remote control you think is not working, Good tested batteries installed properly into remote control, Any digital camera A helper to press the remote button.\n\nAnswer: For Check if a Remote Control is Transmitting an, follow the steps in order: The remote control you think is not working, Good tested batteries installed properly into remote control, Any digital camera A helper to press the remote button."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Check if a Remote Control is Transmitting an Infrared Signal.\nChunk 2: • The remote control you think is not working.\nChunk 3: • Good tested batteries installed properly into remote control.\nChunk 4: • Any digital camera (camera phone and computer cams work too) • A helper to press the remote button (optional) • Try pointing remote control towards the back of a radio (switched on) on an empty channel on the am band and listen for \"clicking\" sounds.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, task: check_if_a_remote. Next, step: the_remote_control_you. Next, step: good_tested_batteries_installed. Finally, step: any_digital_camera_camera. In summary, task: check_if_a_remote.; step: the_remote_control_you., good_tested_batteries_installed., any_digital_camera_camera..", "trace": "C1 task=check_if_a_remote. C2 step=the_remote_control_you. C3 step=good_tested_batteries_installed. C4 step=any_digital_camera_camera.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Check if a Remote Control is Transmitting an Infrared Signal.", "streaming_reasoning": "Initially, task: check_if_a_remote..", "trace": "task=check_if_a_remote."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• The remote control you think is not working.", "streaming_reasoning": "As more information arrives, step: the_remote_control_you..", "trace": "step=the_remote_control_you."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "• Good tested batteries installed properly into remote control.", "streaming_reasoning": "As more information arrives, step: good_tested_batteries_installed..", "trace": "step=good_tested_batteries_installed."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "• Any digital camera (camera phone and computer cams work too) • A helper to press the remote button (optional) • Try pointing remote control towards the back of a radio (switched on) on an empty channel on the am band and listen for \"clicking\" sounds.", "streaming_reasoning": "Finally, step: any_digital_camera_camera..", "trace": "step=any_digital_camera_camera."}]}, "output": {"deep_reasoning": "Procedure for Check if a Remote Control is Transmitting an: The remote control you think is not working, Good tested batteries installed properly into remote control, Any digital camera A helper to press the remote button.", "answer": "For Check if a Remote Control is Transmitting an, follow the steps in order: The remote control you think is not working, Good tested batteries installed properly into remote control, Any digital camera A helper to press the remote button."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002548", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I am looking for an upscale restaurant in the Centre.\nChunk 2: I would like on that serves chinese food.\nChunk 3: The Ugly Duckling sounds fine.\nChunk 4: Could you reserve a table for one on Wednesday at 12:00?\nChunk 5: Yes, I want to find a place to visit in the same area.\nChunk 6: Are there any cinemas?\nChunk 7: How much is the entrance fee?\nChunk 8: That's alright, I don't need anything further Goodbye!\nChunk 9: Thanks!", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre. C2 cuisine+=chinese. C3 intent=context_update. C4 goal=booking; time+=12:00; day+=wednesday. C5 goal=modify_constraint; destination+=find a place to visit in the same area; goal=confirm_booking. C6 goal=request_info. C7 goal=request_info; requested_info+=entrance_fee. C8 intent=context_update. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, modify_constraint, request_info; area=centre; food=chinese; destination=find a place to visit in the same area; requested_info=entrance_fee; when=wednesday, 12:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I am looking for an upscale restaurant in the Centre.\nChunk 2: I would like on that serves chinese food.\nChunk 3: The Ugly Duckling sounds fine.\nChunk 4: Could you reserve a table for one on Wednesday at 12:00?\nChunk 5: Yes, I want to find a place to visit in the same area.\nChunk 6: Are there any cinemas?\nChunk 7: How much is the entrance fee?\nChunk 8: That's alright, I don't need anything further Goodbye!\nChunk 9: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre. C2 cuisine+=chinese. C3 intent=context_update. C4 goal=booking; time+=12:00; day+=wednesday. C5 goal=modify_constraint; destination+=find a place to visit in the same area; goal=confirm_booking. C6 goal=request_info. C7 goal=request_info; requested_info+=entrance_fee. C8 intent=context_update. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, modify_constraint, request_info; area=centre; food=chinese; destination=find a place to visit in the same area; requested_info=entrance_fee; when=wednesday, 12:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I am looking for an upscale restaurant in the Centre.\nChunk 2: I would like on that serves chinese food.\nChunk 3: The Ugly Duckling sounds fine.\nChunk 4: Could you reserve a table for one on Wednesday at 12:00?\nChunk 5: Yes, I want to find a place to visit in the same area.\nChunk 6: Are there any cinemas?\nChunk 7: How much is the entrance fee?\nChunk 8: That's alright, I don't need anything further Goodbye!\nChunk 9: Thanks!", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre. Next, cuisine: chinese. Next, intent: context_update. Next, the goal is booking; time: 12:00; day: wednesday. Next, the goal is confirm booking.; destination: find a place to visit in the same area. Next, the goal is request info. Next, the goal is request info; requested information: entrance_fee. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: centre.; cuisine: chinese.; intent: context_update.; time: 12:00; day: wednesday.; destination: find a place to visit in the same area; requested information: entrance_fee..", "trace": "C1 domain=restaurant; goal=search; area+=centre. C2 cuisine+=chinese. C3 intent=context_update. C4 goal=booking; time+=12:00; day+=wednesday. C5 goal=modify_constraint; destination+=find a place to visit in the same area; goal=confirm_booking. C6 goal=request_info. C7 goal=request_info; requested_info+=entrance_fee. C8 intent=context_update. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I am looking for an upscale restaurant in the Centre.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre..", "trace": "domain=restaurant; goal=search; area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like on that serves chinese food.", "streaming_reasoning": "As more information arrives, cuisine: chinese..", "trace": "cuisine+=chinese."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The Ugly Duckling sounds fine.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you reserve a table for one on Wednesday at 12:00?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 12:00; day: wednesday..", "trace": "goal=booking; time+=12:00; day+=wednesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, I want to find a place to visit in the same area.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; destination: find a place to visit in the same area.", "trace": "goal=modify_constraint; destination+=find a place to visit in the same area; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Are there any cinemas?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "How much is the entrance fee?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's alright, I don't need anything further Goodbye!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; destination is find a place to visit in the same area; requested information is entrance_fee; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, modify_constraint, request_info; area=centre; food=chinese; destination=find a place to visit in the same area; requested_info=entrance_fee; when=wednesday, 12:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002549", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with train.\nChunk 2: The time is wednesday, 10:15.\nChunk 3: Yes, please book two seats for me at 10:40.\nChunk 4: What time will it arrive in Cambridge?\nChunk 5: I need the price for the train that leaves at 10:40 for one and the arrival time Thanks so much.\nChunk 6: Could I bother you to help me find an expensive Chinese restaurant No preference.\nChunk 7: But please make sure I get the address That is perfect.\nChunk 8: Thank you that's all I needed today.", "streaming_reasoning": "C1 domain=train; goal=search. C2 time+=10:15; day+=wednesday. C3 goal=confirm_booking; time+=10:40; goal=confirm_booking. C4 goal=request_info. C5 requested_info+=price. C6 domain=restaurant; cuisine+=chinese; price+=expensive. C7 goal=request_info; requested_info+=address; goal=confirm_booking. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, restaurant; goal=search, booking, confirm_booking, request_info; food=chinese; price=expensive; requested_info=price, address; when=wednesday, 10:15, 10:40; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need help with train.\nChunk 2: The time is wednesday, 10:15.\nChunk 3: Yes, please book two seats for me at 10:40.\nChunk 4: What time will it arrive in Cambridge?\nChunk 5: I need the price for the train that leaves at 10:40 for one and the arrival time Thanks so much.\nChunk 6: Could I bother you to help me find an expensive Chinese restaurant No preference.\nChunk 7: But please make sure I get the address That is perfect.\nChunk 8: Thank you that's all I needed today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 time+=10:15; day+=wednesday. C3 goal=confirm_booking; time+=10:40; goal=confirm_booking. C4 goal=request_info. C5 requested_info+=price. C6 domain=restaurant; cuisine+=chinese; price+=expensive. C7 goal=request_info; requested_info+=address; goal=confirm_booking. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=search, booking, confirm_booking, request_info; food=chinese; price=expensive; requested_info=price, address; when=wednesday, 10:15, 10:40; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with train.\nChunk 2: The time is wednesday, 10:15.\nChunk 3: Yes, please book two seats for me at 10:40.\nChunk 4: What time will it arrive in Cambridge?\nChunk 5: I need the price for the train that leaves at 10:40 for one and the arrival time Thanks so much.\nChunk 6: Could I bother you to help me find an expensive Chinese restaurant No preference.\nChunk 7: But please make sure I get the address That is perfect.\nChunk 8: Thank you that's all I needed today.", "input_token_count": 97, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, time: 10:15; day: wednesday. Next, the goal is confirm booking.; time: 10:40. Next, the goal is request info. Next, requested information: price. Next, the topic is restaurant; cuisine: chinese; price: expensive. Finally, the goal is confirm booking.; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is confirm booking.. time: 10:15, 10:40; day: wednesday.; requested information: price., address; cuisine: chinese; price: expensive..", "trace": "C1 domain=train; goal=search. C2 time+=10:15; day+=wednesday. C3 goal=confirm_booking; time+=10:40; goal=confirm_booking. C4 goal=request_info. C5 requested_info+=price. C6 domain=restaurant; cuisine+=chinese; price+=expensive. C7 goal=request_info; requested_info+=address; goal=confirm_booking. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need help with train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is wednesday, 10:15.", "streaming_reasoning": "As more information arrives, time: 10:15; day: wednesday..", "trace": "time+=10:15; day+=wednesday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, please book two seats for me at 10:40.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 10:40.", "trace": "goal=confirm_booking; time+=10:40; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What time will it arrive in Cambridge?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need the price for the train that leaves at 10:40 for one and the arrival time Thanks so much.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could I bother you to help me find an expensive Chinese restaurant No preference.", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: chinese; price: expensive..", "trace": "domain=restaurant; cuisine+=chinese; price+=expensive."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "But please make sure I get the address That is perfect.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: address.", "trace": "goal=request_info; requested_info+=address; goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you that's all I needed today.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: cuisine is chinese; price is expensive; requested information is price; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=search, booking, confirm_booking, request_info; food=chinese; price=expensive; requested_info=price, address; when=wednesday, 10:15, 10:40; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001713", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I was angry about my work today, It's been frustrating.\nChunk 2: I've been unhappy with my work today Why is that?\nChunk 3: My tasks have been frustrating and tedious.", "streaming_reasoning": "C1 emotion=frustrated; cause=my work today, It's been frustrating; need=validation. C2 emotion=happy; event=I've been unhappy with my work today Why is that?; need=clarification. C3 support_signal=received.", "deep_reasoning": "User feels happy because I've been unhappy with my work today Why is that? and needs clarification.", "answer": "That is worth celebrating, especially because I've been unhappy with my work today Why is that?. Take a moment to enjoy it and share the good news with someone who will be happy for you.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I was angry about my work today, It's been frustrating.\nChunk 2: I've been unhappy with my work today Why is that?\nChunk 3: My tasks have been frustrating and tedious."}, {"role": "assistant", "content": "Streaming reasoning: C1 emotion=frustrated; cause=my work today, It's been frustrating; need=validation. C2 emotion=happy; event=I've been unhappy with my work today Why is that?; need=clarification. C3 support_signal=received.\n\nDeep reasoning: User feels happy because I've been unhappy with my work today Why is that? and needs clarification.\n\nAnswer: That is worth celebrating, especially because I've been unhappy with my work today Why is that?. Take a moment to enjoy it and share the good news with someone who will be happy for you."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I was angry about my work today, It's been frustrating.\nChunk 2: I've been unhappy with my work today Why is that?\nChunk 3: My tasks have been frustrating and tedious.", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user expresses frustrated about my work today; the user needs validation. Next, the user expresses happy; the user needs clarification.; event: I've been unhappy with my work today Why is that?. Finally, the user signals support or acknowledgment.", "trace": "C1 emotion=frustrated; cause=my work today, It's been frustrating; need=validation. C2 emotion=happy; event=I've been unhappy with my work today Why is that?; need=clarification. C3 support_signal=received.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I was angry about my work today, It's been frustrating.", "streaming_reasoning": "Initially, the user expresses frustrated about my work today; the user needs validation..", "trace": "emotion=frustrated; cause=my work today, It's been frustrating; need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I've been unhappy with my work today Why is that?", "streaming_reasoning": "As more information arrives, the user expresses happy; the user needs clarification.; event: I've been unhappy with my work today Why is that?.", "trace": "emotion=happy; event=I've been unhappy with my work today Why is that?; need=clarification."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "My tasks have been frustrating and tedious.", "streaming_reasoning": "Finally, the user signals support or acknowledgment.", "trace": "support_signal=received."}]}, "output": {"deep_reasoning": "User feels happy because I've been unhappy with my work today Why is that? and needs clarification.", "answer": "That is worth celebrating, especially because I've been unhappy with my work today Why is that?. Take a moment to enjoy it and share the good news with someone who will be happy for you."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002550", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you locate a train departing from Cambridge on Friday?\nChunk 2: Thanks!\nChunk 3: Yes, I'd like to go to peterborough and should leave afer 20:00.\nChunk 4: That would be great.\nChunk 5: Can you book 5 seats for me please?\nChunk 6: What is the reference number Thank you.\nChunk 7: I am also looking for a cinema in the centre.\nChunk 8: Could you give me the entrance fee and phone number?\nChunk 9: Great that was all I needed thanks for your help today.", "streaming_reasoning": "C1 domain=train; day+=friday; departure+=cambridge on friday. C2 [SKIP: thanks_only]. C3 time+=20:00; destination+=go to peterborough and should leave afer; acceptance=selected_option. C4 intent=context_update. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 goal=search; area+=centre. C8 requested_info+=phone, entrance_fee. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=booking, request_info, search; area=centre; destination=go to peterborough and should leave afer; departure=cambridge on friday; requested_info=reference_number, phone, entrance_fee; when=friday, 20:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you locate a train departing from Cambridge on Friday?\nChunk 2: Thanks!\nChunk 3: Yes, I'd like to go to peterborough and should leave afer 20:00.\nChunk 4: That would be great.\nChunk 5: Can you book 5 seats for me please?\nChunk 6: What is the reference number Thank you.\nChunk 7: I am also looking for a cinema in the centre.\nChunk 8: Could you give me the entrance fee and phone number?\nChunk 9: Great that was all I needed thanks for your help today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; day+=friday; departure+=cambridge on friday. C2 [SKIP: thanks_only]. C3 time+=20:00; destination+=go to peterborough and should leave afer; acceptance=selected_option. C4 intent=context_update. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 goal=search; area+=centre. C8 requested_info+=phone, entrance_fee. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=booking, request_info, search; area=centre; destination=go to peterborough and should leave afer; departure=cambridge on friday; requested_info=reference_number, phone, entrance_fee; when=friday, 20:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you locate a train departing from Cambridge on Friday?\nChunk 2: Thanks!\nChunk 3: Yes, I'd like to go to peterborough and should leave afer 20:00.\nChunk 4: That would be great.\nChunk 5: Can you book 5 seats for me please?\nChunk 6: What is the reference number Thank you.\nChunk 7: I am also looking for a cinema in the centre.\nChunk 8: Could you give me the entrance fee and phone number?\nChunk 9: Great that was all I needed thanks for your help today.", "input_token_count": 92, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; day: friday; departure point: cambridge on friday. Next, time: 20:00; destination: go to peterborough and should leave afer; acceptance: selected_option. Next, intent: context_update. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the goal is search; area: centre. Finally, requested information: phone.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is search. day: friday; departure point: cambridge on friday.; time: 20:00; destination: go to peterborough and should leave afer; acceptance: selected_option.; intent: context_update.; requested information: reference_number., phone; area: centre..", "trace": "C1 domain=train; day+=friday; departure+=cambridge on friday. C2 [SKIP: thanks_only]. C3 time+=20:00; destination+=go to peterborough and should leave afer; acceptance=selected_option. C4 intent=context_update. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 goal=search; area+=centre. C8 requested_info+=phone, entrance_fee. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you locate a train departing from Cambridge on Friday?", "streaming_reasoning": "Initially, the topic is train; day: friday; departure point: cambridge on friday..", "trace": "domain=train; day+=friday; departure+=cambridge on friday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks!", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I'd like to go to peterborough and should leave afer 20:00.", "streaming_reasoning": "As more information arrives, time: 20:00; destination: go to peterborough and should leave afer; acceptance: selected_option..", "trace": "time+=20:00; destination+=go to peterborough and should leave afer; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That would be great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you book 5 seats for me please?", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What is the reference number Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am also looking for a cinema in the centre.", "streaming_reasoning": "As more information arrives, the goal is search; area: centre..", "trace": "goal=search; area+=centre."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Could you give me the entrance fee and phone number?", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, entrance_fee."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Great that was all I needed thanks for your help today.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: area is centre; destination is go to peterborough and should leave afer; departure point is cambridge on friday; requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, request_info, search; area=centre; destination=go to peterborough and should leave afer; departure=cambridge on friday; requested_info=reference_number, phone, entrance_fee; when=friday, 20:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002551", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a taxi today.\nChunk 2: I need to leave from broughton house gallery.\nChunk 3: I really need to get there by 16:30 please.\nChunk 4: My destination is downing college.\nChunk 5: That's all I need, thanks!", "streaming_reasoning": "C1 domain=taxi; goal=search; day+=today. C2 domain=attraction. C3 goal=request_info; time+=16:30. C4 intent=context_update. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi, attraction; goal=search, request_info; when=today, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a taxi today.\nChunk 2: I need to leave from broughton house gallery.\nChunk 3: I really need to get there by 16:30 please.\nChunk 4: My destination is downing college.\nChunk 5: That's all I need, thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search; day+=today. C2 domain=attraction. C3 goal=request_info; time+=16:30. C4 intent=context_update. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi, attraction; goal=search, request_info; when=today, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a taxi today.\nChunk 2: I need to leave from broughton house gallery.\nChunk 3: I really need to get there by 16:30 please.\nChunk 4: My destination is downing college.\nChunk 5: That's all I need, thanks!", "input_token_count": 43, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search; day: today. Next, the topic is attraction. Next, the goal is request info; time: 16:30. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction.. the goal is request info. day: today.; time: 16:30.; intent: context_update..", "trace": "C1 domain=taxi; goal=search; day+=today. C2 domain=attraction. C3 goal=request_info; time+=16:30. C4 intent=context_update. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a taxi today.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search; day: today..", "trace": "domain=taxi; goal=search; day+=today."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to leave from broughton house gallery.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I really need to get there by 16:30 please.", "streaming_reasoning": "As more information arrives, the goal is request info; time: 16:30..", "trace": "goal=request_info; time+=16:30."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "My destination is downing college.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That's all I need, thanks!", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: timing is today. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, attraction; goal=search, request_info; when=today, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002552", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Anything with a 0 star rating?\nChunk 2: I want a super trashy place.\nChunk 3: Does it have free parking?\nChunk 4: Okay, let me book El Shaddai for 5 night starting Sunday for 4 people.\nChunk 5: Yes, could you book a taxi for me too?\nChunk 6: I will need to leave the attraction by 14:00 Great thank you!\nChunk 7: That will be all!", "streaming_reasoning": "C1 stars+=0 stars. C2 goal=search. C3 amenities+=parking, free parking. C4 goal=booking; time+=5, 4; day+=sunday; party_size+=4 people; stay_length+=5 nights. C5 domain=taxi; goal=confirm_booking; goal=confirm_booking. C6 domain=attraction; time+=14:00; destination+=leave the attraction by 14:00 great thank. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi, attraction; goal=search, booking, confirm_booking; party_size=4 people; stay_length=5 nights; stars=0 stars; amenities=parking, free parking; destination=leave the attraction by 14:00 great thank; when=sunday, 5, 4, 14:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Anything with a 0 star rating?\nChunk 2: I want a super trashy place.\nChunk 3: Does it have free parking?\nChunk 4: Okay, let me book El Shaddai for 5 night starting Sunday for 4 people.\nChunk 5: Yes, could you book a taxi for me too?\nChunk 6: I will need to leave the attraction by 14:00 Great thank you!\nChunk 7: That will be all!"}, {"role": "assistant", "content": "Streaming reasoning: C1 stars+=0 stars. C2 goal=search. C3 amenities+=parking, free parking. C4 goal=booking; time+=5, 4; day+=sunday; party_size+=4 people; stay_length+=5 nights. C5 domain=taxi; goal=confirm_booking; goal=confirm_booking. C6 domain=attraction; time+=14:00; destination+=leave the attraction by 14:00 great thank. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi, attraction; goal=search, booking, confirm_booking; party_size=4 people; stay_length=5 nights; stars=0 stars; amenities=parking, free parking; destination=leave the attraction by 14:00 great thank; when=sunday, 5, 4, 14:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Anything with a 0 star rating?\nChunk 2: I want a super trashy place.\nChunk 3: Does it have free parking?\nChunk 4: Okay, let me book El Shaddai for 5 night starting Sunday for 4 people.\nChunk 5: Yes, could you book a taxi for me too?\nChunk 6: I will need to leave the attraction by 14:00 Great thank you!\nChunk 7: That will be all!", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, star rating: 0 stars. Next, the goal is search. Next, amenities: parking. Next, the goal is booking; time: 5; day: sunday; party size: 4 people; stay length: 5 nights. Next, the topic is taxi; the goal is confirm booking. Finally, the topic is attraction; time: 14:00; destination: leave the attraction by 14:00 great thank.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is confirm booking.. star rating: 0 stars.; amenities: parking; time: 5, 14:00; day: sunday; party size: 4 people; stay length: 5 nights.; destination: leave the attraction by 14:00 great thank..", "trace": "C1 stars+=0 stars. C2 goal=search. C3 amenities+=parking, free parking. C4 goal=booking; time+=5, 4; day+=sunday; party_size+=4 people; stay_length+=5 nights. C5 domain=taxi; goal=confirm_booking; goal=confirm_booking. C6 domain=attraction; time+=14:00; destination+=leave the attraction by 14:00 great thank. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Anything with a 0 star rating?", "streaming_reasoning": "Initially, star rating: 0 stars..", "trace": "stars+=0 stars."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want a super trashy place.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Does it have free parking?", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Okay, let me book El Shaddai for 5 night starting Sunday for 4 people.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 5; day: sunday; party size: 4 people; stay length: 5 nights..", "trace": "goal=booking; time+=5, 4; day+=sunday; party_size+=4 people; stay_length+=5 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, could you book a taxi for me too?", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is confirm booking..", "trace": "domain=taxi; goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I will need to leave the attraction by 14:00 Great thank you!", "streaming_reasoning": "As more information arrives, the topic is attraction; time: 14:00; destination: leave the attraction by 14:00 great thank..", "trace": "domain=attraction; time+=14:00; destination+=leave the attraction by 14:00 great thank."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That will be all!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: party size is 4 people; stay length is 5 nights; star rating is 0 stars; amenities is parking; destination is leave the attraction by 14:00 great thank; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, attraction; goal=search, booking, confirm_booking; party_size=4 people; stay_length=5 nights; stars=0 stars; amenities=parking, free parking; destination=leave the attraction by 14:00 great thank; when=sunday, 5, 4, 14:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002553", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm sure Moroccan food will impress my clients.\nChunk 2: Are there any restaurants that serve it?\nChunk 3: Can you search for British food instead?\nChunk 4: It is for 4 people.\nChunk 5: The time is wednesday, 4, 13:30.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number Thank you.\nChunk 8: I also need info on a college to visit in the town centre Anyone will do Whatever you recommend.\nChunk 9: Great thanks, what is their entrance fee and phone number?\nChunk 10: Thank you for all your help Goodbye.", "streaming_reasoning": "C1 domain=restaurant. C2 goal=request_info. C3 goal=compare_alternative; cuisine+=british. C4 party_size+=4 people. C5 time+=4, 13:30; day+=wednesday. C6 goal=booking. C7 goal=request_info; requested_info+=reference_number. C8 domain=attraction; goal=recommendation; area+=centre; destination+=visit in the town centre anyone will do w. C9 requested_info+=phone, entrance_fee. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, attraction; goal=search, compare_alternative, booking, request_info, recommendation; area=centre; food=british; party_size=4 people; destination=visit in the town centre anyone will do w; requested_info=reference_number, phone, entrance_fee; when=wednesday, 4, 13:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm sure Moroccan food will impress my clients.\nChunk 2: Are there any restaurants that serve it?\nChunk 3: Can you search for British food instead?\nChunk 4: It is for 4 people.\nChunk 5: The time is wednesday, 4, 13:30.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number Thank you.\nChunk 8: I also need info on a college to visit in the town centre Anyone will do Whatever you recommend.\nChunk 9: Great thanks, what is their entrance fee and phone number?\nChunk 10: Thank you for all your help Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant. C2 goal=request_info. C3 goal=compare_alternative; cuisine+=british. C4 party_size+=4 people. C5 time+=4, 13:30; day+=wednesday. C6 goal=booking. C7 goal=request_info; requested_info+=reference_number. C8 domain=attraction; goal=recommendation; area+=centre; destination+=visit in the town centre anyone will do w. C9 requested_info+=phone, entrance_fee. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, attraction; goal=search, compare_alternative, booking, request_info, recommendation; area=centre; food=british; party_size=4 people; destination=visit in the town centre anyone will do w; requested_info=reference_number, phone, entrance_fee; when=wednesday, 4, 13:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm sure Moroccan food will impress my clients.\nChunk 2: Are there any restaurants that serve it?\nChunk 3: Can you search for British food instead?\nChunk 4: It is for 4 people.\nChunk 5: The time is wednesday, 4, 13:30.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number Thank you.\nChunk 8: I also need info on a college to visit in the town centre Anyone will do Whatever you recommend.\nChunk 9: Great thanks, what is their entrance fee and phone number?\nChunk 10: Thank you for all your help Goodbye.", "input_token_count": 102, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant. Next, the goal is request info. Next, the goal is compare alternative; cuisine: british. Next, party size: 4 people. Next, time: 4; day: wednesday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the topic is attraction; the goal is recommendation; area: centre; destination: visit in the town centre anyone will do w. Finally, requested information: phone.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction. the goal is recommendation. cuisine: british.; party size: 4 people.; time: 4; day: wednesday.; requested information: reference_number., phone; area: centre; destination: visit in the town centre anyone will do w..", "trace": "C1 domain=restaurant. C2 goal=request_info. C3 goal=compare_alternative; cuisine+=british. C4 party_size+=4 people. C5 time+=4, 13:30; day+=wednesday. C6 goal=booking. C7 goal=request_info; requested_info+=reference_number. C8 domain=attraction; goal=recommendation; area+=centre; destination+=visit in the town centre anyone will do w. C9 requested_info+=phone, entrance_fee. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm sure Moroccan food will impress my clients.", "streaming_reasoning": "Initially, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Are there any restaurants that serve it?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you search for British food instead?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; cuisine: british..", "trace": "goal=compare_alternative; cuisine+=british."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It is for 4 people.", "streaming_reasoning": "As more information arrives, party size: 4 people..", "trace": "party_size+=4 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is wednesday, 4, 13:30.", "streaming_reasoning": "As more information arrives, time: 4; day: wednesday..", "trace": "time+=4, 13:30; day+=wednesday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the reference number Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need info on a college to visit in the town centre Anyone will do Whatever you recommend.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is recommendation; area: centre; destination: visit in the town centre anyone will do w..", "trace": "domain=attraction; goal=recommendation; area+=centre; destination+=visit in the town centre anyone will do w."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Great thanks, what is their entrance fee and phone number?", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, entrance_fee."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you for all your help Goodbye.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is british; party size is 4 people; destination is visit in the town centre anyone will do w; requested information is reference_number; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction; goal=search, compare_alternative, booking, request_info, recommendation; area=centre; food=british; party_size=4 people; destination=visit in the town centre anyone will do w; requested_info=reference_number, phone, entrance_fee; when=wednesday, 4, 13:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002554", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for information on a hotel.\nChunk 2: I am looking for a hotel called the A and B Guest House.\nChunk 3: I would like to book it for 7 people for 4 nights starting on Sunday.\nChunk 4: Hmm, how about a different hotel in the same price range?\nChunk 5: Great thank you that's all I needed today.\nChunk 6: Thank you for all the help.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 hotel_type+=guesthouse. C3 goal=booking; time+=7, 4; day+=sunday; party_size+=7 people; stay_length+=4 nights. C4 goal=modify_constraint; price+=same price. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking, recommendation, compare_alternative, modify_constraint; price=same price; party_size=7 people; stay_length=4 nights; when=sunday, 7, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for information on a hotel.\nChunk 2: I am looking for a hotel called the A and B Guest House.\nChunk 3: I would like to book it for 7 people for 4 nights starting on Sunday.\nChunk 4: Hmm, how about a different hotel in the same price range?\nChunk 5: Great thank you that's all I needed today.\nChunk 6: Thank you for all the help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel. C2 hotel_type+=guesthouse. C3 goal=booking; time+=7, 4; day+=sunday; party_size+=7 people; stay_length+=4 nights. C4 goal=modify_constraint; price+=same price. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking, recommendation, compare_alternative, modify_constraint; price=same price; party_size=7 people; stay_length=4 nights; when=sunday, 7, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for information on a hotel.\nChunk 2: I am looking for a hotel called the A and B Guest House.\nChunk 3: I would like to book it for 7 people for 4 nights starting on Sunday.\nChunk 4: Hmm, how about a different hotel in the same price range?\nChunk 5: Great thank you that's all I needed today.\nChunk 6: Thank you for all the help.", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel. Next, hotel type: guesthouse. Next, the goal is booking; time: 7; day: sunday; party size: 7 people; stay length: 4 nights. Finally, the goal is modify constraint; price: same price.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is modify constraint. hotel type: hotel., guesthouse.; time: 7; day: sunday; party size: 7 people; stay length: 4 nights.; price: same price..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 hotel_type+=guesthouse. C3 goal=booking; time+=7, 4; day+=sunday; party_size+=7 people; stay_length+=4 nights. C4 goal=modify_constraint; price+=same price. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for information on a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am looking for a hotel called the A and B Guest House.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse..", "trace": "hotel_type+=guesthouse."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to book it for 7 people for 4 nights starting on Sunday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 7; day: sunday; party size: 7 people; stay length: 4 nights..", "trace": "goal=booking; time+=7, 4; day+=sunday; party_size+=7 people; stay_length+=4 nights."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Hmm, how about a different hotel in the same price range?", "streaming_reasoning": "As more information arrives, the goal is modify constraint; price: same price..", "trace": "goal=modify_constraint; price+=same price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Great thank you that's all I needed today.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for all the help.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is same price; party size is 7 people; stay length is 4 nights; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, recommendation, compare_alternative, modify_constraint; price=same price; party_size=7 people; stay_length=4 nights; when=sunday, 7, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002555", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: ok, what's their address and postcode?\nChunk 2: I also need a taxi.\nChunk 3: I will want to go between the attraction, and the hotel.\nChunk 4: I want to leave by 15:30.\nChunk 5: Can I get the contact number and the car type please?\nChunk 6: Thank you very much.\nChunk 7: That is all that I need.", "streaming_reasoning": "C1 goal=request_info; requested_info+=address, postcode. C2 domain=taxi; goal=search. C3 domain=attraction; hotel_type+=hotel; destination+=go between the attraction. C4 time+=15:30; destination+=leave by 15:30. C5 goal=request_info. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi, hotel, attraction; goal=request_info, search; destination=go between the attraction, leave by 15:30; requested_info=address, postcode; when=15:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: ok, what's their address and postcode?\nChunk 2: I also need a taxi.\nChunk 3: I will want to go between the attraction, and the hotel.\nChunk 4: I want to leave by 15:30.\nChunk 5: Can I get the contact number and the car type please?\nChunk 6: Thank you very much.\nChunk 7: That is all that I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address, postcode. C2 domain=taxi; goal=search. C3 domain=attraction; hotel_type+=hotel; destination+=go between the attraction. C4 time+=15:30; destination+=leave by 15:30. C5 goal=request_info. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi, hotel, attraction; goal=request_info, search; destination=go between the attraction, leave by 15:30; requested_info=address, postcode; when=15:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: ok, what's their address and postcode?\nChunk 2: I also need a taxi.\nChunk 3: I will want to go between the attraction, and the hotel.\nChunk 4: I want to leave by 15:30.\nChunk 5: Can I get the contact number and the car type please?\nChunk 6: Thank you very much.\nChunk 7: That is all that I need.", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the topic is taxi; the goal is search. Next, the topic is attraction; hotel type: hotel; destination: go between the attraction. Next, time: 15:30; destination: leave by 15:30. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction. the goal is request info.. requested information: address; hotel type: hotel; destination: go between the attraction., leave by 15:30.; time: 15:30.", "trace": "C1 goal=request_info; requested_info+=address, postcode. C2 domain=taxi; goal=search. C3 domain=attraction; hotel_type+=hotel; destination+=go between the attraction. C4 time+=15:30; destination+=leave by 15:30. C5 goal=request_info. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "ok, what's their address and postcode?", "streaming_reasoning": "Initially, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need a taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is search..", "trace": "domain=taxi; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I will want to go between the attraction, and the hotel.", "streaming_reasoning": "As more information arrives, the topic is attraction; hotel type: hotel; destination: go between the attraction..", "trace": "domain=attraction; hotel_type+=hotel; destination+=go between the attraction."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want to leave by 15:30.", "streaming_reasoning": "As more information arrives, time: 15:30; destination: leave by 15:30..", "trace": "time+=15:30; destination+=leave by 15:30."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get the contact number and the car type please?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all that I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of request info. Key information: destination is go between the attraction; requested information is address; timing is 15:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, hotel, attraction; goal=request_info, search; destination=go between the attraction, leave by 15:30; requested_info=address, postcode; when=15:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002556", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to make reservations for 5 people.\nChunk 2: Thanks!\nChunk 3: I'm also looking for a Chinese restaurant in the centre.\nChunk 4: Um no, not really.\nChunk 5: Yes!\nChunk 6: What place would you recommend?\nChunk 7: It is for 5 people.\nChunk 8: The time is thursday, 5, 21:00.\nChunk 9: Please make a booking.\nChunk 10: I also need the reference number.\nChunk 11: Thank you for all your help.", "streaming_reasoning": "C1 party_size+=5 people; destination+=make reservations for 5 people. C2 [SKIP: thanks_only]. C3 domain=restaurant; goal=search; area+=centre; cuisine+=chinese. C4 goal=modify_constraint. C5 [SKIP: acknowledgement_only]. C6 goal=recommendation. C7 [SKIP: repeated_information]. C8 time+=5, 21:00; day+=thursday. C9 goal=booking. C10 goal=request_info; requested_info+=reference_number. C11 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, booking, request_info; area=centre; food=chinese; party_size=5 people; destination=make reservations for 5 people; requested_info=reference_number; when=thursday, 5, 21:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to make reservations for 5 people.\nChunk 2: Thanks!\nChunk 3: I'm also looking for a Chinese restaurant in the centre.\nChunk 4: Um no, not really.\nChunk 5: Yes!\nChunk 6: What place would you recommend?\nChunk 7: It is for 5 people.\nChunk 8: The time is thursday, 5, 21:00.\nChunk 9: Please make a booking.\nChunk 10: I also need the reference number.\nChunk 11: Thank you for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 party_size+=5 people; destination+=make reservations for 5 people. C2 [SKIP: thanks_only]. C3 domain=restaurant; goal=search; area+=centre; cuisine+=chinese. C4 goal=modify_constraint. C5 [SKIP: acknowledgement_only]. C6 goal=recommendation. C7 [SKIP: repeated_information]. C8 time+=5, 21:00; day+=thursday. C9 goal=booking. C10 goal=request_info; requested_info+=reference_number. C11 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, booking, request_info; area=centre; food=chinese; party_size=5 people; destination=make reservations for 5 people; requested_info=reference_number; when=thursday, 5, 21:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to make reservations for 5 people.\nChunk 2: Thanks!\nChunk 3: I'm also looking for a Chinese restaurant in the centre.\nChunk 4: Um no, not really.\nChunk 5: Yes!\nChunk 6: What place would you recommend?\nChunk 7: It is for 5 people.\nChunk 8: The time is thursday, 5, 21:00.\nChunk 9: Please make a booking.\nChunk 10: I also need the reference number.\nChunk 11: Thank you for all your help.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, party size: 5 people; destination: make reservations for 5 people. Next, the topic is restaurant; the goal is search; area: centre; cuisine: chinese. Next, the goal is modify constraint. Next, the goal is recommendation. Next, time: 5; day: thursday. Next, the goal is booking. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained acknowledgement_only or repeated_information or thanks_only. In summary, The overall topic is restaurant. the goal is request info. party size: 5 people; destination: make reservations for 5 people.; area: centre; cuisine: chinese.; time: 5; day: thursday.; requested information: reference_number..", "trace": "C1 party_size+=5 people; destination+=make reservations for 5 people. C2 [SKIP: thanks_only]. C3 domain=restaurant; goal=search; area+=centre; cuisine+=chinese. C4 goal=modify_constraint. C5 [SKIP: acknowledgement_only]. C6 goal=recommendation. C7 [SKIP: repeated_information]. C8 time+=5, 21:00; day+=thursday. C9 goal=booking. C10 goal=request_info; requested_info+=reference_number. C11 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to make reservations for 5 people.", "streaming_reasoning": "Initially, party size: 5 people; destination: make reservations for 5 people..", "trace": "party_size+=5 people; destination+=make reservations for 5 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks!", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm also looking for a Chinese restaurant in the centre.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; area: centre; cuisine: chinese..", "trace": "domain=restaurant; goal=search; area+=centre; cuisine+=chinese."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Um no, not really.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes!", "streaming_reasoning": "The content at C5 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What place would you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "It is for 5 people.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "The time is thursday, 5, 21:00.", "streaming_reasoning": "As more information arrives, time: 5; day: thursday..", "trace": "time+=5, 21:00; day+=thursday."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C11 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; party size is 5 people; destination is make reservations for 5 people; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, booking, request_info; area=centre; food=chinese; party_size=5 people; destination=make reservations for 5 people; requested_info=reference_number; when=thursday, 5, 21:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002557", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I have heard a lot of good things about the Arbury Lodge Guesthouse.\nChunk 2: Would you be able to provide any information on them No thank you.\nChunk 3: How many stars does it have?\nChunk 4: What is the postcode?\nChunk 5: Okay thank you that is all I need to know.", "streaming_reasoning": "C1 domain=hotel; hotel_type+=guesthouse. C2 destination+=provide any information on them no thank. C3 goal=request_info. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=request_info; destination=provide any information on them no thank; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I have heard a lot of good things about the Arbury Lodge Guesthouse.\nChunk 2: Would you be able to provide any information on them No thank you.\nChunk 3: How many stars does it have?\nChunk 4: What is the postcode?\nChunk 5: Okay thank you that is all I need to know."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=guesthouse. C2 destination+=provide any information on them no thank. C3 goal=request_info. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info; destination=provide any information on them no thank; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I have heard a lot of good things about the Arbury Lodge Guesthouse.\nChunk 2: Would you be able to provide any information on them No thank you.\nChunk 3: How many stars does it have?\nChunk 4: What is the postcode?\nChunk 5: Okay thank you that is all I need to know.", "input_token_count": 56, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse. Next, destination: provide any information on them no thank. Next, the goal is request info. Finally, the goal is request info; requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. hotel type: guesthouse.; destination: provide any information on them no thank.; requested information: postcode..", "trace": "C1 domain=hotel; hotel_type+=guesthouse. C2 destination+=provide any information on them no thank. C3 goal=request_info. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I have heard a lot of good things about the Arbury Lodge Guesthouse.", "streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Would you be able to provide any information on them No thank you.", "streaming_reasoning": "As more information arrives, destination: provide any information on them no thank..", "trace": "destination+=provide any information on them no thank."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How many stars does it have?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is the postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Okay thank you that is all I need to know.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: destination is provide any information on them no thank; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info; destination=provide any information on them no thank; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002558", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to book a train.\nChunk 2: I would like to depart from cambridge and arrive by 16:45.\nChunk 3: The train should depart from cambridge and should arrive by 16:45 Going to Ely.\nChunk 4: I would like to go on Saturday.\nChunk 5: Sure, I would like to book that train for 4 passengers That's wonderful.\nChunk 6: I am all set Thank you Goodbye.", "streaming_reasoning": "C1 domain=train; goal=booking. C2 time+=16:45; departure+=cambridge and arrive by 16:45. C3 destination+=ely; departure+=cambridge and should arrive by 16:45, cambridge and should arrive by 16:45 going to ely. C4 day+=saturday; destination+=go on saturday. C5 intent=context_update. C6 intent=context_update.", "deep_reasoning": "Need domain=train; goal=search, booking; destination=ely, go on saturday; departure=cambridge and arrive by 16:45, cambridge and should arrive by 16:45, cambridge and should arrive by 16:45 going to ely; when=saturday, 16:45.", "answer": "Got it. I will use train, saturday, 16:45 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to book a train.\nChunk 2: I would like to depart from cambridge and arrive by 16:45.\nChunk 3: The train should depart from cambridge and should arrive by 16:45 Going to Ely.\nChunk 4: I would like to go on Saturday.\nChunk 5: Sure, I would like to book that train for 4 passengers That's wonderful.\nChunk 6: I am all set Thank you Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=booking. C2 time+=16:45; departure+=cambridge and arrive by 16:45. C3 destination+=ely; departure+=cambridge and should arrive by 16:45, cambridge and should arrive by 16:45 going to ely. C4 day+=saturday; destination+=go on saturday. C5 intent=context_update. C6 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=search, booking; destination=ely, go on saturday; departure=cambridge and arrive by 16:45, cambridge and should arrive by 16:45, cambridge and should arrive by 16:45 going to ely; when=saturday, 16:45.\n\nAnswer: Got it. I will use train, saturday, 16:45 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to book a train.\nChunk 2: I would like to depart from cambridge and arrive by 16:45.\nChunk 3: The train should depart from cambridge and should arrive by 16:45 Going to Ely.\nChunk 4: I would like to go on Saturday.\nChunk 5: Sure, I would like to book that train for 4 passengers That's wonderful.\nChunk 6: I am all set Thank you Goodbye.", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is booking. Next, time: 16:45; departure point: cambridge and arrive by 16:45. Next, destination: ely; departure point: cambridge and should arrive by 16:45. Next, day: saturday; destination: go on saturday. Next, intent: context_update. Finally, intent: context_update. In summary, The overall topic is train. the goal is booking.. time: 16:45; departure point: cambridge and arrive by 16:45., cambridge and should arrive by 16:45; destination: ely, go on saturday.; day: saturday; intent: context_update..", "trace": "C1 domain=train; goal=booking. C2 time+=16:45; departure+=cambridge and arrive by 16:45. C3 destination+=ely; departure+=cambridge and should arrive by 16:45, cambridge and should arrive by 16:45 going to ely. C4 day+=saturday; destination+=go on saturday. C5 intent=context_update. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to book a train.", "streaming_reasoning": "Initially, the topic is train; the goal is booking..", "trace": "domain=train; goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to depart from cambridge and arrive by 16:45.", "streaming_reasoning": "As more information arrives, time: 16:45; departure point: cambridge and arrive by 16:45..", "trace": "time+=16:45; departure+=cambridge and arrive by 16:45."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The train should depart from cambridge and should arrive by 16:45 Going to Ely.", "streaming_reasoning": "As more information arrives, destination: ely; departure point: cambridge and should arrive by 16:45.", "trace": "destination+=ely; departure+=cambridge and should arrive by 16:45, cambridge and should arrive by 16:45 going to ely."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like to go on Saturday.", "streaming_reasoning": "As more information arrives, day: saturday; destination: go on saturday..", "trace": "day+=saturday; destination+=go on saturday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Sure, I would like to book that train for 4 passengers That's wonderful.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I am all set Thank you Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is ely; departure point is cambridge and arrive by 16:45; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use train, saturday, 16:45 and move the task forward.", "deep_reasoning_trace": "Need domain=train; goal=search, booking; destination=ely, go on saturday; departure=cambridge and arrive by 16:45, cambridge and should arrive by 16:45, cambridge and should arrive by 16:45 going to ely; when=saturday, 16:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002559", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you please help me find a cheap hotel to stay in that includes free wifi?\nChunk 2: I would like a little more information about the Belfry hotel.\nChunk 3: does it have a 4 star rating?\nChunk 4: No but what is the address?\nChunk 5: No thank you that will be all.", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel; amenities+=wifi; destination+=stay in that includes free wifi. C2 intent=context_update. C3 stars+=4 stars. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info; price=cheap; stars=4 stars; amenities=wifi; destination=stay in that includes free wifi; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you please help me find a cheap hotel to stay in that includes free wifi?\nChunk 2: I would like a little more information about the Belfry hotel.\nChunk 3: does it have a 4 star rating?\nChunk 4: No but what is the address?\nChunk 5: No thank you that will be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel; amenities+=wifi; destination+=stay in that includes free wifi. C2 intent=context_update. C3 stars+=4 stars. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info; price=cheap; stars=4 stars; amenities=wifi; destination=stay in that includes free wifi; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you please help me find a cheap hotel to stay in that includes free wifi?\nChunk 2: I would like a little more information about the Belfry hotel.\nChunk 3: does it have a 4 star rating?\nChunk 4: No but what is the address?\nChunk 5: No thank you that will be all.", "input_token_count": 57, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: cheap; hotel type: hotel; amenities: wifi; destination: stay in that includes free wifi. Next, intent: context_update. Next, star rating: 4 stars. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. price: cheap; hotel type: hotel; amenities: wifi; destination: stay in that includes free wifi.; intent: context_update.; star rating: 4 stars.; requested information: address..", "trace": "C1 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel; amenities+=wifi; destination+=stay in that includes free wifi. C2 intent=context_update. C3 stars+=4 stars. C4 goal=request_info; requested_info+=address. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you please help me find a cheap hotel to stay in that includes free wifi?", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: cheap; hotel type: hotel; amenities: wifi; destination: stay in that includes free wifi..", "trace": "domain=hotel; goal=search; price+=cheap; hotel_type+=hotel; amenities+=wifi; destination+=stay in that includes free wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like a little more information about the Belfry hotel.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "does it have a 4 star rating?", "streaming_reasoning": "As more information arrives, star rating: 4 stars..", "trace": "stars+=4 stars."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No but what is the address?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No thank you that will be all.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is cheap; star rating is 4 stars; amenities is wifi; destination is stay in that includes free wifi; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info; price=cheap; stars=4 stars; amenities=wifi; destination=stay in that includes free wifi; requested_info=address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003222", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you for your compliments.It ' s just that you are a good leader.\nChunk 2: Do you like the fox-trot and tango?\nChunk 3: Yes.\nChunk 4: And what dances do you do best?\nChunk 5: Disco is my favorite.\nChunk 6: I like it better than any other dances because it can release one's pent-up feelings, and is a healthy exercise.\nChunk 7: But I don't do the rock and roll and the break dance.\nChunk 8: Oh, well, the music has stopped.\nChunk 9: Thank you for the dance My pleasure.\nChunk 10: Let's go and have a drink.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 question=true. C3 [SKIP: acknowledgement_only]. C4 question=true. C5 preference=true. C6 preference=true. C7 casual_comment=don't, rock. C8 casual_comment=music, stopped. C9 [SKIP: thanks_only]. C10 casual_comment=let's, drink.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you for your compliments.It ' s just that you are a good leader.\nChunk 2: Do you like the fox-trot and tango?\nChunk 3: Yes.\nChunk 4: And what dances do you do best?\nChunk 5: Disco is my favorite.\nChunk 6: I like it better than any other dances because it can release one's pent-up feelings, and is a healthy exercise.\nChunk 7: But I don't do the rock and roll and the break dance.\nChunk 8: Oh, well, the music has stopped.\nChunk 9: Thank you for the dance My pleasure.\nChunk 10: Let's go and have a drink."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 question=true. C3 [SKIP: acknowledgement_only]. C4 question=true. C5 preference=true. C6 preference=true. C7 casual_comment=don't, rock. C8 casual_comment=music, stopped. C9 [SKIP: thanks_only]. C10 casual_comment=let's, drink.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you for your compliments.It ' s just that you are a good leader.\nChunk 2: Do you like the fox-trot and tango?\nChunk 3: Yes.\nChunk 4: And what dances do you do best?\nChunk 5: Disco is my favorite.\nChunk 6: I like it better than any other dances because it can release one's pent-up feelings, and is a healthy exercise.\nChunk 7: But I don't do the rock and roll and the break dance.\nChunk 8: Oh, well, the music has stopped.\nChunk 9: Thank you for the dance My pleasure.\nChunk 10: Let's go and have a drink.", "input_token_count": 104, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the input provides additional context about question=true. Next, preference: true. Next, preference: true. Next, the user comments on don't. Next, the user comments on music. Finally, the user comments on let's.  Some chunks were skipped because they contained acknowledgement_only or thanks_only. In summary, preference: true..", "trace": "C1 [SKIP: thanks_only]. C2 question=true. C3 [SKIP: acknowledgement_only]. C4 question=true. C5 preference=true. C6 preference=true. C7 casual_comment=don't, rock. C8 casual_comment=music, stopped. C9 [SKIP: thanks_only]. C10 casual_comment=let's, drink.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you for your compliments.It ' s just that you are a good leader.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do you like the fox-trot and tango?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes.", "streaming_reasoning": "The content at C3 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "And what dances do you do best?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Disco is my favorite.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I like it better than any other dances because it can release one's pent-up feelings, and is a healthy exercise.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "But I don't do the rock and roll and the break dance.", "streaming_reasoning": "As more information arrives, the user comments on don't.", "trace": "casual_comment=don't, rock."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Oh, well, the music has stopped.", "streaming_reasoning": "As more information arrives, the user comments on music.", "trace": "casual_comment=music, stopped."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you for the dance My pleasure.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Let's go and have a drink.", "streaming_reasoning": "Finally, the user comments on let's.", "trace": "casual_comment=let's, drink."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003223", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm glad you are getting better.\nChunk 2: And I was glad to receive your letter.\nChunk 3: Then when will you be back again?\nChunk 4: I will be back again next Wednesday.\nChunk 5: I hope to see you at that time again.\nChunk 6: Bye.", "streaming_reasoning": "C1 casual_comment=i'm, glad. C2 casual_comment=glad, receive. C3 question=true. C4 casual_comment=will, back. C5 casual_comment=hope, see. C6 [SKIP: closing_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm glad you are getting better.\nChunk 2: And I was glad to receive your letter.\nChunk 3: Then when will you be back again?\nChunk 4: I will be back again next Wednesday.\nChunk 5: I hope to see you at that time again.\nChunk 6: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=i'm, glad. C2 casual_comment=glad, receive. C3 question=true. C4 casual_comment=will, back. C5 casual_comment=hope, see. C6 [SKIP: closing_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm glad you are getting better.\nChunk 2: And I was glad to receive your letter.\nChunk 3: Then when will you be back again?\nChunk 4: I will be back again next Wednesday.\nChunk 5: I hope to see you at that time again.\nChunk 6: Bye.", "input_token_count": 50, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on i'm. Next, the user comments on glad. Next, the input provides additional context about question=true. Next, the user comments on will. Finally, the user comments on hope.  Some chunks were skipped because they contained closing_only.", "trace": "C1 casual_comment=i'm, glad. C2 casual_comment=glad, receive. C3 question=true. C4 casual_comment=will, back. C5 casual_comment=hope, see. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm glad you are getting better.", "streaming_reasoning": "Initially, the user comments on i'm.", "trace": "casual_comment=i'm, glad."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "And I was glad to receive your letter.", "streaming_reasoning": "As more information arrives, the user comments on glad.", "trace": "casual_comment=glad, receive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Then when will you be back again?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I will be back again next Wednesday.", "streaming_reasoning": "As more information arrives, the user comments on will.", "trace": "casual_comment=will, back."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I hope to see you at that time again.", "streaming_reasoning": "As more information arrives, the user comments on hope.", "trace": "casual_comment=hope, see."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Bye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002560", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for something moderately priced with a 4 star rating.\nChunk 2: No, but I would like to have free wifi.\nChunk 3: That does not matter.\nChunk 4: Which one would you recommend?\nChunk 5: Actually, I would like something that has 4 stars.\nChunk 6: Does A and B have 4 stars?\nChunk 7: Yes, and can I get the phone number for the guesthouse, please.\nChunk 8: No, you have been very helpful, thanks.\nChunk 9: I don't need anything else at the moment.\nChunk 10: Bye.", "streaming_reasoning": "C1 goal=search; price+=moderate; stars+=4 stars. C2 amenities+=wifi; destination+=have free wifi. C3 goal=modify_constraint. C4 goal=recommendation. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 domain=hotel; goal=request_info; hotel_type+=guesthouse; requested_info+=phone; acceptance=selected_option. C8 goal=modify_constraint. C9 goal=compare_alternative. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, recommendation, request_info, compare_alternative; price=moderate; stars=4 stars; amenities=wifi; destination=have free wifi; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for something moderately priced with a 4 star rating.\nChunk 2: No, but I would like to have free wifi.\nChunk 3: That does not matter.\nChunk 4: Which one would you recommend?\nChunk 5: Actually, I would like something that has 4 stars.\nChunk 6: Does A and B have 4 stars?\nChunk 7: Yes, and can I get the phone number for the guesthouse, please.\nChunk 8: No, you have been very helpful, thanks.\nChunk 9: I don't need anything else at the moment.\nChunk 10: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; price+=moderate; stars+=4 stars. C2 amenities+=wifi; destination+=have free wifi. C3 goal=modify_constraint. C4 goal=recommendation. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 domain=hotel; goal=request_info; hotel_type+=guesthouse; requested_info+=phone; acceptance=selected_option. C8 goal=modify_constraint. C9 goal=compare_alternative. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, recommendation, request_info, compare_alternative; price=moderate; stars=4 stars; amenities=wifi; destination=have free wifi; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for something moderately priced with a 4 star rating.\nChunk 2: No, but I would like to have free wifi.\nChunk 3: That does not matter.\nChunk 4: Which one would you recommend?\nChunk 5: Actually, I would like something that has 4 stars.\nChunk 6: Does A and B have 4 stars?\nChunk 7: Yes, and can I get the phone number for the guesthouse, please.\nChunk 8: No, you have been very helpful, thanks.\nChunk 9: I don't need anything else at the moment.\nChunk 10: Bye.", "input_token_count": 93, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; price: moderate; star rating: 4 stars. Next, amenities: wifi; destination: have free wifi. Next, the goal is modify constraint. Next, the goal is recommendation. Next, intent: context_update. Next, the topic is hotel; the goal is request info; hotel type: guesthouse; requested information: phone; acceptance: selected_option. Next, the goal is modify constraint. Finally, the goal is compare alternative.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is hotel. the goal is compare alternative.. price: moderate; star rating: 4 stars.; amenities: wifi; destination: have free wifi.; intent: context_update.; hotel type: guesthouse; requested information: phone; acceptance: selected_option..", "trace": "C1 goal=search; price+=moderate; stars+=4 stars. C2 amenities+=wifi; destination+=have free wifi. C3 goal=modify_constraint. C4 goal=recommendation. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 domain=hotel; goal=request_info; hotel_type+=guesthouse; requested_info+=phone; acceptance=selected_option. C8 goal=modify_constraint. C9 goal=compare_alternative. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for something moderately priced with a 4 star rating.", "streaming_reasoning": "Initially, the goal is search; price: moderate; star rating: 4 stars..", "trace": "goal=search; price+=moderate; stars+=4 stars."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, but I would like to have free wifi.", "streaming_reasoning": "As more information arrives, amenities: wifi; destination: have free wifi..", "trace": "amenities+=wifi; destination+=have free wifi."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That does not matter.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Which one would you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Actually, I would like something that has 4 stars.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Does A and B have 4 stars?", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, and can I get the phone number for the guesthouse, please.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is request info; hotel type: guesthouse; requested information: phone; acceptance: selected_option..", "trace": "domain=hotel; goal=request_info; hotel_type+=guesthouse; requested_info+=phone; acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, you have been very helpful, thanks.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I don't need anything else at the moment.", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Bye.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is moderate; star rating is 4 stars; amenities is wifi; destination is have free wifi; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, recommendation, request_info, compare_alternative; price=moderate; stars=4 stars; amenities=wifi; destination=have free wifi; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002561", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm going to Ely from Cambridge on Sunday Thank you.\nChunk 2: I would like to arrive by 20:15.\nChunk 3: Do you have something that leaves later but still makes the arrival time?\nChunk 4: I want to find a cheap indian restaurant.\nChunk 5: It should be in the north part of town.\nChunk 6: Yes, any you choose will be fine.\nChunk 7: I'll need to book a table for the same day, at 15:30, and it will just be me.\nChunk 8: Great, that's all I need, thanks so much for your help!\nChunk 9: Have a great day!", "streaming_reasoning": "C1 day+=sunday. C2 time+=20:15; destination+=arrive by 20:15. C3 goal=request_info. C4 domain=restaurant; goal=search; cuisine+=indian; price+=cheap; destination+=find a cheap indian restaurant. C5 area+=north. C6 acceptance=selected_option. C7 goal=booking; time+=15:30. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking; area=north; food=indian; price=cheap; destination=arrive by 20:15, find a cheap indian restaurant; when=sunday, 20:15, 15:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm going to Ely from Cambridge on Sunday Thank you.\nChunk 2: I would like to arrive by 20:15.\nChunk 3: Do you have something that leaves later but still makes the arrival time?\nChunk 4: I want to find a cheap indian restaurant.\nChunk 5: It should be in the north part of town.\nChunk 6: Yes, any you choose will be fine.\nChunk 7: I'll need to book a table for the same day, at 15:30, and it will just be me.\nChunk 8: Great, that's all I need, thanks so much for your help!\nChunk 9: Have a great day!"}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=sunday. C2 time+=20:15; destination+=arrive by 20:15. C3 goal=request_info. C4 domain=restaurant; goal=search; cuisine+=indian; price+=cheap; destination+=find a cheap indian restaurant. C5 area+=north. C6 acceptance=selected_option. C7 goal=booking; time+=15:30. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking; area=north; food=indian; price=cheap; destination=arrive by 20:15, find a cheap indian restaurant; when=sunday, 20:15, 15:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm going to Ely from Cambridge on Sunday Thank you.\nChunk 2: I would like to arrive by 20:15.\nChunk 3: Do you have something that leaves later but still makes the arrival time?\nChunk 4: I want to find a cheap indian restaurant.\nChunk 5: It should be in the north part of town.\nChunk 6: Yes, any you choose will be fine.\nChunk 7: I'll need to book a table for the same day, at 15:30, and it will just be me.\nChunk 8: Great, that's all I need, thanks so much for your help!\nChunk 9: Have a great day!", "input_token_count": 107, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, day: sunday. Next, time: 20:15; destination: arrive by 20:15. Next, the goal is request info. Next, the topic is restaurant; the goal is search; cuisine: indian; price: cheap; destination: find a cheap indian restaurant. Next, area: north. Next, acceptance: selected_option. Finally, the goal is booking; time: 15:30.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. day: sunday.; time: 20:15, 15:30.; destination: arrive by 20:15., find a cheap indian restaurant.; cuisine: indian; price: cheap; area: north.; acceptance: selected_option..", "trace": "C1 day+=sunday. C2 time+=20:15; destination+=arrive by 20:15. C3 goal=request_info. C4 domain=restaurant; goal=search; cuisine+=indian; price+=cheap; destination+=find a cheap indian restaurant. C5 area+=north. C6 acceptance=selected_option. C7 goal=booking; time+=15:30. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm going to Ely from Cambridge on Sunday Thank you.", "streaming_reasoning": "Initially, day: sunday..", "trace": "day+=sunday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to arrive by 20:15.", "streaming_reasoning": "As more information arrives, time: 20:15; destination: arrive by 20:15..", "trace": "time+=20:15; destination+=arrive by 20:15."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Do you have something that leaves later but still makes the arrival time?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want to find a cheap indian restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; cuisine: indian; price: cheap; destination: find a cheap indian restaurant..", "trace": "domain=restaurant; goal=search; cuisine+=indian; price+=cheap; destination+=find a cheap indian restaurant."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, any you choose will be fine.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'll need to book a table for the same day, at 15:30, and it will just be me.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 15:30..", "trace": "goal=booking; time+=15:30."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Great, that's all I need, thanks so much for your help!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Have a great day!", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; cuisine is indian; price is cheap; destination is arrive by 20:15; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking; area=north; food=indian; price=cheap; destination=arrive by 20:15, find a cheap indian restaurant; when=sunday, 20:15, 15:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002562", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me book a train on Sunday?\nChunk 2: I want to go to Ely.\nChunk 3: I need it to leave after 08:15 please.\nChunk 4: Yes please book just one ticket for me.\nChunk 5: Yes, what is the reference number for the reservation?\nChunk 6: No that is all for now.\nChunk 7: Thank you for all your help.", "streaming_reasoning": "C1 domain=train; goal=booking; day+=sunday. C2 destination+=go to ely. C3 time+=08:15; destination+=leave after 08:15 please. C4 goal=confirm_booking; goal=confirm_booking. C5 goal=request_info; requested_info+=reference_number; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search, booking, confirm_booking, request_info; destination=go to ely, leave after 08:15 please; requested_info=reference_number; when=sunday, 08:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you help me book a train on Sunday?\nChunk 2: I want to go to Ely.\nChunk 3: I need it to leave after 08:15 please.\nChunk 4: Yes please book just one ticket for me.\nChunk 5: Yes, what is the reference number for the reservation?\nChunk 6: No that is all for now.\nChunk 7: Thank you for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=booking; day+=sunday. C2 destination+=go to ely. C3 time+=08:15; destination+=leave after 08:15 please. C4 goal=confirm_booking; goal=confirm_booking. C5 goal=request_info; requested_info+=reference_number; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search, booking, confirm_booking, request_info; destination=go to ely, leave after 08:15 please; requested_info=reference_number; when=sunday, 08:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me book a train on Sunday?\nChunk 2: I want to go to Ely.\nChunk 3: I need it to leave after 08:15 please.\nChunk 4: Yes please book just one ticket for me.\nChunk 5: Yes, what is the reference number for the reservation?\nChunk 6: No that is all for now.\nChunk 7: Thank you for all your help.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is booking; day: sunday. Next, destination: go to ely. Next, time: 08:15; destination: leave after 08:15 please. Next, the goal is confirm booking. Finally, the goal is confirm booking.; requested information: reference_number.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is confirm booking.. day: sunday.; destination: go to ely., leave after 08:15 please.; time: 08:15; requested information: reference_number.", "trace": "C1 domain=train; goal=booking; day+=sunday. C2 destination+=go to ely. C3 time+=08:15; destination+=leave after 08:15 please. C4 goal=confirm_booking; goal=confirm_booking. C5 goal=request_info; requested_info+=reference_number; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you help me book a train on Sunday?", "streaming_reasoning": "Initially, the topic is train; the goal is booking; day: sunday..", "trace": "domain=train; goal=booking; day+=sunday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to go to Ely.", "streaming_reasoning": "As more information arrives, destination: go to ely..", "trace": "destination+=go to ely."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need it to leave after 08:15 please.", "streaming_reasoning": "As more information arrives, time: 08:15; destination: leave after 08:15 please..", "trace": "time+=08:15; destination+=leave after 08:15 please."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes please book just one ticket for me.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, what is the reference number for the reservation?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "goal=request_info; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No that is all for now.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is go to ely; requested information is reference_number; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, booking, confirm_booking, request_info; destination=go to ely, leave after 08:15 please; requested_info=reference_number; when=sunday, 08:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002563", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want a restaurant that is moderately priced and located in the south.\nChunk 2: Are there any other restaurants I can choose from?\nChunk 3: Can I have the address, phone number, and type of food served by Restaurant Alimentum Thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=south; price+=moderate. C2 goal=request_info. C3 goal=request_info; requested_info+=address, phone.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=south; price=moderate; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want a restaurant that is moderately priced and located in the south.\nChunk 2: Are there any other restaurants I can choose from?\nChunk 3: Can I have the address, phone number, and type of food served by Restaurant Alimentum Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=south; price+=moderate. C2 goal=request_info. C3 goal=request_info; requested_info+=address, phone.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=south; price=moderate; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want a restaurant that is moderately priced and located in the south.\nChunk 2: Are there any other restaurants I can choose from?\nChunk 3: Can I have the address, phone number, and type of food served by Restaurant Alimentum Thank you.", "input_token_count": 45, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: south; price: moderate. Next, the goal is request info. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. area: south; price: moderate.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; area+=south; price+=moderate. C2 goal=request_info. C3 goal=request_info; requested_info+=address, phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want a restaurant that is moderately priced and located in the south.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: south; price: moderate..", "trace": "domain=restaurant; goal=search; area+=south; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Are there any other restaurants I can choose from?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I have the address, phone number, and type of food served by Restaurant Alimentum Thank you.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; price is moderate; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=south; price=moderate; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000538", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Make \"Georgia Ice Cream\".\nChunk 2: • Grits (not the instant kind) • Water • Sugar or sweetener • Salt • Butter • This recipe allows for a lot of personalization.\nChunk 3: Check the grits label for ingredient quantities (grits & water) and cooking times per the distributor's guidelines.", "streaming_reasoning": "C1 task=make_georgia_ice_cream. C2 step=grits_not_the_instant. C3 step=check_the_grits_label.", "deep_reasoning": "Procedure for Make \"Georgia Ice Cream\": Grits Water Sugar or sweetener Salt Butter This recipe allows, Check the grits label for ingredient quantities and cooking times.", "answer": "For Make \"Georgia Ice Cream\", follow the steps in order: Grits Water Sugar or sweetener Salt Butter This recipe allows, Check the grits label for ingredient quantities and cooking times.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Make \"Georgia Ice Cream\".\nChunk 2: • Grits (not the instant kind) • Water • Sugar or sweetener • Salt • Butter • This recipe allows for a lot of personalization.\nChunk 3: Check the grits label for ingredient quantities (grits & water) and cooking times per the distributor's guidelines."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=make_georgia_ice_cream. C2 step=grits_not_the_instant. C3 step=check_the_grits_label.\n\nDeep reasoning: Procedure for Make \"Georgia Ice Cream\": Grits Water Sugar or sweetener Salt Butter This recipe allows, Check the grits label for ingredient quantities and cooking times.\n\nAnswer: For Make \"Georgia Ice Cream\", follow the steps in order: Grits Water Sugar or sweetener Salt Butter This recipe allows, Check the grits label for ingredient quantities and cooking times."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Make \"Georgia Ice Cream\".\nChunk 2: • Grits (not the instant kind) • Water • Sugar or sweetener • Salt • Butter • This recipe allows for a lot of personalization.\nChunk 3: Check the grits label for ingredient quantities (grits & water) and cooking times per the distributor's guidelines.", "input_token_count": 46, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, task: make_georgia_ice_cream. Next, step: grits_not_the_instant. Finally, step: check_the_grits_label. In summary, task: make_georgia_ice_cream.; step: grits_not_the_instant., check_the_grits_label..", "trace": "C1 task=make_georgia_ice_cream. C2 step=grits_not_the_instant. C3 step=check_the_grits_label.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Make \"Georgia Ice Cream\".", "streaming_reasoning": "Initially, task: make_georgia_ice_cream..", "trace": "task=make_georgia_ice_cream."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• Grits (not the instant kind) • Water • Sugar or sweetener • Salt • Butter • This recipe allows for a lot of personalization.", "streaming_reasoning": "As more information arrives, step: grits_not_the_instant..", "trace": "step=grits_not_the_instant."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Check the grits label for ingredient quantities (grits & water) and cooking times per the distributor's guidelines.", "streaming_reasoning": "Finally, step: check_the_grits_label..", "trace": "step=check_the_grits_label."}]}, "output": {"deep_reasoning": "Procedure for Make \"Georgia Ice Cream\": Grits Water Sugar or sweetener Salt Butter This recipe allows, Check the grits label for ingredient quantities and cooking times.", "answer": "For Make \"Georgia Ice Cream\", follow the steps in order: Grits Water Sugar or sweetener Salt Butter This recipe allows, Check the grits label for ingredient quantities and cooking times."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002564", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like for it to be 3 stars, please.\nChunk 2: Can you book that for 5 people for 2 nights starting on wednesday?\nChunk 3: Can you also find the address for Club Salsa?\nChunk 4: I actually need the postcode and phone number for Club Salsa.\nChunk 5: I want to find a hotel.\nChunk 6: The time is 5:45.\nChunk 7: Please make a booking.\nChunk 8: Nope, that'll do it!\nChunk 9: Thank you for all your help!", "streaming_reasoning": "C1 stars+=3 stars; destination+=be 3 stars. C2 goal=booking; time+=5, 2; day+=wednesday; party_size+=5 people; stay_length+=2 nights. C3 goal=request_info; requested_info+=address. C4 requested_info+=phone, postcode. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 time+=5:45. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=booking, search, request_info; party_size=5 people; stay_length=2 nights; stars=3 stars; destination=be 3 stars, find a hotel; requested_info=address, phone, postcode; when=wednesday, 5, 2, 5:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like for it to be 3 stars, please.\nChunk 2: Can you book that for 5 people for 2 nights starting on wednesday?\nChunk 3: Can you also find the address for Club Salsa?\nChunk 4: I actually need the postcode and phone number for Club Salsa.\nChunk 5: I want to find a hotel.\nChunk 6: The time is 5:45.\nChunk 7: Please make a booking.\nChunk 8: Nope, that'll do it!\nChunk 9: Thank you for all your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 stars+=3 stars; destination+=be 3 stars. C2 goal=booking; time+=5, 2; day+=wednesday; party_size+=5 people; stay_length+=2 nights. C3 goal=request_info; requested_info+=address. C4 requested_info+=phone, postcode. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 time+=5:45. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=booking, search, request_info; party_size=5 people; stay_length=2 nights; stars=3 stars; destination=be 3 stars, find a hotel; requested_info=address, phone, postcode; when=wednesday, 5, 2, 5:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like for it to be 3 stars, please.\nChunk 2: Can you book that for 5 people for 2 nights starting on wednesday?\nChunk 3: Can you also find the address for Club Salsa?\nChunk 4: I actually need the postcode and phone number for Club Salsa.\nChunk 5: I want to find a hotel.\nChunk 6: The time is 5:45.\nChunk 7: Please make a booking.\nChunk 8: Nope, that'll do it!\nChunk 9: Thank you for all your help!", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, star rating: 3 stars; destination: be 3 stars. Next, the goal is booking; time: 5; day: wednesday; party size: 5 people; stay length: 2 nights. Next, the goal is request info; requested information: address. Next, requested information: phone. Next, the topic is hotel; hotel type: hotel; destination: find a hotel. Next, time: 5:45. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is request info. star rating: 3 stars; destination: be 3 stars., find a hotel.; time: 5, 5:45.; day: wednesday; party size: 5 people; stay length: 2 nights.; requested information: address., phone; hotel type: hotel; intent: context_update..", "trace": "C1 stars+=3 stars; destination+=be 3 stars. C2 goal=booking; time+=5, 2; day+=wednesday; party_size+=5 people; stay_length+=2 nights. C3 goal=request_info; requested_info+=address. C4 requested_info+=phone, postcode. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 time+=5:45. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like for it to be 3 stars, please.", "streaming_reasoning": "Initially, star rating: 3 stars; destination: be 3 stars..", "trace": "stars+=3 stars; destination+=be 3 stars."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you book that for 5 people for 2 nights starting on wednesday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 5; day: wednesday; party size: 5 people; stay length: 2 nights..", "trace": "goal=booking; time+=5, 2; day+=wednesday; party_size+=5 people; stay_length+=2 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you also find the address for Club Salsa?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I actually need the postcode and phone number for Club Salsa.", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 5:45.", "streaming_reasoning": "As more information arrives, time: 5:45..", "trace": "time+=5:45."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Nope, that'll do it!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you for all your help!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: party size is 5 people; stay length is 2 nights; star rating is 3 stars; destination is be 3 stars; requested information is address; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, search, request_info; party_size=5 people; stay_length=2 nights; stars=3 stars; destination=be 3 stars, find a hotel; requested_info=address, phone, postcode; when=wednesday, 5, 2, 5:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002565", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want a place to stay.\nChunk 2: Is there an expensive hotel?\nChunk 3: It doesn't need to include internet.\nChunk 4: If you have anything in the south that would be perfect.\nChunk 5: not now but will come back laiter.\nChunk 6: That is all I need, thank you.", "streaming_reasoning": "C1 domain=hotel; goal=search; destination+=stay. C2 price+=expensive; hotel_type+=hotel. C3 amenities+=internet; destination+=include internet. C4 area+=south; acceptance=selected_option. C5 goal=modify_constraint. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search; area=south; price=expensive; amenities=internet; destination=stay, include internet; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want a place to stay.\nChunk 2: Is there an expensive hotel?\nChunk 3: It doesn't need to include internet.\nChunk 4: If you have anything in the south that would be perfect.\nChunk 5: not now but will come back laiter.\nChunk 6: That is all I need, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; destination+=stay. C2 price+=expensive; hotel_type+=hotel. C3 amenities+=internet; destination+=include internet. C4 area+=south; acceptance=selected_option. C5 goal=modify_constraint. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search; area=south; price=expensive; amenities=internet; destination=stay, include internet; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want a place to stay.\nChunk 2: Is there an expensive hotel?\nChunk 3: It doesn't need to include internet.\nChunk 4: If you have anything in the south that would be perfect.\nChunk 5: not now but will come back laiter.\nChunk 6: That is all I need, thank you.", "input_token_count": 54, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay. Next, price: expensive; hotel type: hotel. Next, amenities: internet; destination: include internet. Next, area: south; acceptance: selected_option. Finally, the goal is modify constraint.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is modify constraint.. destination: stay., include internet.; price: expensive; hotel type: hotel.; amenities: internet; area: south; acceptance: selected_option..", "trace": "C1 domain=hotel; goal=search; destination+=stay. C2 price+=expensive; hotel_type+=hotel. C3 amenities+=internet; destination+=include internet. C4 area+=south; acceptance=selected_option. C5 goal=modify_constraint. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want a place to stay.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there an expensive hotel?", "streaming_reasoning": "As more information arrives, price: expensive; hotel type: hotel..", "trace": "price+=expensive; hotel_type+=hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It doesn't need to include internet.", "streaming_reasoning": "As more information arrives, amenities: internet; destination: include internet..", "trace": "amenities+=internet; destination+=include internet."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "If you have anything in the south that would be perfect.", "streaming_reasoning": "As more information arrives, area: south; acceptance: selected_option..", "trace": "area+=south; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "not now but will come back laiter.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all I need, thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is south; price is expensive; amenities is internet; destination is stay. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search; area=south; price=expensive; amenities=internet; destination=stay, include internet; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002566", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a particular hotel.\nChunk 2: Its name is called city centre north b and b Yes please.\nChunk 3: I need reservations for eight people starting this Wednesday and we need it for three nights.\nChunk 4: Could you start the booking on Saturday?\nChunk 5: That's all I need, thank you!", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=north, centre; acceptance=selected_option. C3 day+=wednesday; party_size+=8 people. C4 goal=booking; day+=saturday. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking; area=north, centre; party_size=8 people; when=wednesday, saturday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a particular hotel.\nChunk 2: Its name is called city centre north b and b Yes please.\nChunk 3: I need reservations for eight people starting this Wednesday and we need it for three nights.\nChunk 4: Could you start the booking on Saturday?\nChunk 5: That's all I need, thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=north, centre; acceptance=selected_option. C3 day+=wednesday; party_size+=8 people. C4 goal=booking; day+=saturday. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking; area=north, centre; party_size=8 people; when=wednesday, saturday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a particular hotel.\nChunk 2: Its name is called city centre north b and b Yes please.\nChunk 3: I need reservations for eight people starting this Wednesday and we need it for three nights.\nChunk 4: Could you start the booking on Saturday?\nChunk 5: That's all I need, thank you!", "input_token_count": 58, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel. Next, area: north; acceptance: selected_option. Next, day: wednesday; party size: 8 people. Finally, the goal is booking; day: saturday.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking. hotel type: hotel.; area: north; acceptance: selected_option.; day: wednesday, saturday.; party size: 8 people..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=north, centre; acceptance=selected_option. C3 day+=wednesday; party_size+=8 people. C4 goal=booking; day+=saturday. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a particular hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Its name is called city centre north b and b Yes please.", "streaming_reasoning": "As more information arrives, area: north; acceptance: selected_option..", "trace": "area+=north, centre; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need reservations for eight people starting this Wednesday and we need it for three nights.", "streaming_reasoning": "As more information arrives, day: wednesday; party size: 8 people..", "trace": "day+=wednesday; party_size+=8 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you start the booking on Saturday?", "streaming_reasoning": "As more information arrives, the goal is booking; day: saturday..", "trace": "goal=booking; day+=saturday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That's all I need, thank you!", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; party size is 8 people; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking; area=north, centre; party_size=8 people; when=wednesday, saturday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002567", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for an expensive restaurant that serves italian food I don't care.\nChunk 2: May I have the address and phone number please Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=italian; price+=expensive. C2 goal=request_info; requested_info+=address, phone.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; food=italian; price=expensive; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for an expensive restaurant that serves italian food I don't care.\nChunk 2: May I have the address and phone number please Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=italian; price+=expensive. C2 goal=request_info; requested_info+=address, phone.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; food=italian; price=expensive; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for an expensive restaurant that serves italian food I don't care.\nChunk 2: May I have the address and phone number please Thank you, goodbye.", "input_token_count": 29, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: italian; price: expensive. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. cuisine: italian; price: expensive.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; cuisine+=italian; price+=expensive. C2 goal=request_info; requested_info+=address, phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for an expensive restaurant that serves italian food I don't care.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: italian; price: expensive..", "trace": "domain=restaurant; goal=search; cuisine+=italian; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "May I have the address and phone number please Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is italian; price is expensive; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; food=italian; price=expensive; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002568", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Not yet, but I would like the postcode.\nChunk 2: I am also looking for places to go in town, preferably in the centre.\nChunk 3: How about a concert hall Thank you.\nChunk 4: Can I also get the address and postcode?\nChunk 5: Thank you for your help.\nChunk 6: That's all for today.\nChunk 7: Thank you, take care!", "streaming_reasoning": "C1 goal=request_info; requested_info+=postcode. C2 goal=search; area+=centre; destination+=go in town. C3 goal=recommendation. C4 requested_info+=address. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "deep_reasoning": "Need goal=request_info, search, recommendation; area=centre; destination=go in town; requested_info=postcode, address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Not yet, but I would like the postcode.\nChunk 2: I am also looking for places to go in town, preferably in the centre.\nChunk 3: How about a concert hall Thank you.\nChunk 4: Can I also get the address and postcode?\nChunk 5: Thank you for your help.\nChunk 6: That's all for today.\nChunk 7: Thank you, take care!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=postcode. C2 goal=search; area+=centre; destination+=go in town. C3 goal=recommendation. C4 requested_info+=address. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=request_info, search, recommendation; area=centre; destination=go in town; requested_info=postcode, address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Not yet, but I would like the postcode.\nChunk 2: I am also looking for places to go in town, preferably in the centre.\nChunk 3: How about a concert hall Thank you.\nChunk 4: Can I also get the address and postcode?\nChunk 5: Thank you for your help.\nChunk 6: That's all for today.\nChunk 7: Thank you, take care!", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: postcode. Next, the goal is search; area: centre; destination: go in town. Next, the goal is recommendation. Finally, requested information: address.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is recommendation.. requested information: postcode., address.; area: centre; destination: go in town..", "trace": "C1 goal=request_info; requested_info+=postcode. C2 goal=search; area+=centre; destination+=go in town. C3 goal=recommendation. C4 requested_info+=address. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Not yet, but I would like the postcode.", "streaming_reasoning": "Initially, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also looking for places to go in town, preferably in the centre.", "streaming_reasoning": "As more information arrives, the goal is search; area: centre; destination: go in town..", "trace": "goal=search; area+=centre; destination+=go in town."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about a concert hall Thank you.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I also get the address and postcode?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all for today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you, take care!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=request_info, search, recommendation; area=centre; destination=go in town; requested_info=postcode, address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002569", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: It should be in the south part of town.\nChunk 3: What is the star of that hotel?\nChunk 4: The address, including area of town too Great, thanks.\nChunk 5: Can you also help me get a taxi from the restaurant?\nChunk 6: Thanks!\nChunk 7: I don't care, I just want to leave at 06:45, please.\nChunk 8: Thanks that's all I need Thanks again, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 area+=south. C3 domain=hotel; goal=request_info; hotel_type+=hotel. C4 requested_info+=address. C5 domain=taxi. C6 [SKIP: thanks_only]. C7 time+=06:45; destination+=leave at 06:45. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel, taxi; goal=search, request_info; area=south; destination=find a restaurant, leave at 06:45; requested_info=address; when=06:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a restaurant.\nChunk 2: It should be in the south part of town.\nChunk 3: What is the star of that hotel?\nChunk 4: The address, including area of town too Great, thanks.\nChunk 5: Can you also help me get a taxi from the restaurant?\nChunk 6: Thanks!\nChunk 7: I don't care, I just want to leave at 06:45, please.\nChunk 8: Thanks that's all I need Thanks again, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 area+=south. C3 domain=hotel; goal=request_info; hotel_type+=hotel. C4 requested_info+=address. C5 domain=taxi. C6 [SKIP: thanks_only]. C7 time+=06:45; destination+=leave at 06:45. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel, taxi; goal=search, request_info; area=south; destination=find a restaurant, leave at 06:45; requested_info=address; when=06:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: It should be in the south part of town.\nChunk 3: What is the star of that hotel?\nChunk 4: The address, including area of town too Great, thanks.\nChunk 5: Can you also help me get a taxi from the restaurant?\nChunk 6: Thanks!\nChunk 7: I don't care, I just want to leave at 06:45, please.\nChunk 8: Thanks that's all I need Thanks again, goodbye.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant. Next, area: south. Next, the topic is hotel; the goal is request info; hotel type: hotel. Next, requested information: address. Next, the topic is taxi. Finally, time: 06:45; destination: leave at 06:45.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi.. the goal is request info. destination: find a restaurant., leave at 06:45.; area: south.; hotel type: hotel.; requested information: address.; time: 06:45.", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 area+=south. C3 domain=hotel; goal=request_info; hotel_type+=hotel. C4 requested_info+=address. C5 domain=taxi. C6 [SKIP: thanks_only]. C7 time+=06:45; destination+=leave at 06:45. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the south part of town.", "streaming_reasoning": "As more information arrives, area: south..", "trace": "area+=south."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the star of that hotel?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is request info; hotel type: hotel..", "trace": "domain=hotel; goal=request_info; hotel_type+=hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The address, including area of town too Great, thanks.", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you also help me get a taxi from the restaurant?", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I don't care, I just want to leave at 06:45, please.", "streaming_reasoning": "As more information arrives, time: 06:45; destination: leave at 06:45..", "trace": "time+=06:45; destination+=leave at 06:45."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks that's all I need Thanks again, goodbye.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; destination is find a restaurant; requested information is address; timing is 06:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel, taxi; goal=search, request_info; area=south; destination=find a restaurant, leave at 06:45; requested_info=address; when=06:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003237", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, thank you.\nChunk 2: I've given up, you know.\nChunk 3: You don't mind if I have one Well, all tight.\nChunk 4: But you know, smoking does do harm to your health.\nChunk 5: Yes, you are right.\nChunk 6: Why don't you try and give it up?", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 casual_comment=i've, given. C3 casual_comment=don't, mind. C4 casual_comment=smoking, harm. C5 casual_comment=right. C6 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, thank you.\nChunk 2: I've given up, you know.\nChunk 3: You don't mind if I have one Well, all tight.\nChunk 4: But you know, smoking does do harm to your health.\nChunk 5: Yes, you are right.\nChunk 6: Why don't you try and give it up?"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 casual_comment=i've, given. C3 casual_comment=don't, mind. C4 casual_comment=smoking, harm. C5 casual_comment=right. C6 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, thank you.\nChunk 2: I've given up, you know.\nChunk 3: You don't mind if I have one Well, all tight.\nChunk 4: But you know, smoking does do harm to your health.\nChunk 5: Yes, you are right.\nChunk 6: Why don't you try and give it up?", "input_token_count": 52, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on i've. Next, the user comments on don't. Next, the user comments on smoking. Next, the user comments on right. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 [SKIP: thanks_only]. C2 casual_comment=i've, given. C3 casual_comment=don't, mind. C4 casual_comment=smoking, harm. C5 casual_comment=right. C6 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, thank you.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I've given up, you know.", "streaming_reasoning": "As more information arrives, the user comments on i've.", "trace": "casual_comment=i've, given."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "You don't mind if I have one Well, all tight.", "streaming_reasoning": "As more information arrives, the user comments on don't.", "trace": "casual_comment=don't, mind."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "But you know, smoking does do harm to your health.", "streaming_reasoning": "As more information arrives, the user comments on smoking.", "trace": "casual_comment=smoking, harm."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, you are right.", "streaming_reasoning": "As more information arrives, the user comments on right..", "trace": "casual_comment=right."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Why don't you try and give it up?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002570", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd really like to stay in a guesthouse.\nChunk 2: What do you have available?\nChunk 3: It is for 5 people.\nChunk 4: The time is saturday, 5, 2.\nChunk 5: Please make a booking.\nChunk 6: I also need the reference number Thank you.\nChunk 7: I am also looking for a train that departs from cambridge after 19:30.\nChunk 8: Going to broxbourne on Monday Yes, it will.\nChunk 9: Can you book 5 tickets for me please?\nChunk 10: No thank you that is all I need today.", "streaming_reasoning": "C1 domain=hotel; hotel_type+=guesthouse; destination+=stay in a guesthouse. C2 goal=request_info. C3 party_size+=5 people. C4 time+=5, 2; day+=saturday. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 domain=train; time+=19:30. C8 day+=monday; destination+=broxbourne on monday yes; goal=confirm_booking. C9 goal=request_info. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, train; goal=booking, search, request_info; party_size=5 people; destination=stay in a guesthouse, broxbourne on monday yes; requested_info=reference_number; when=saturday, monday, 5, 2, 19:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd really like to stay in a guesthouse.\nChunk 2: What do you have available?\nChunk 3: It is for 5 people.\nChunk 4: The time is saturday, 5, 2.\nChunk 5: Please make a booking.\nChunk 6: I also need the reference number Thank you.\nChunk 7: I am also looking for a train that departs from cambridge after 19:30.\nChunk 8: Going to broxbourne on Monday Yes, it will.\nChunk 9: Can you book 5 tickets for me please?\nChunk 10: No thank you that is all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=guesthouse; destination+=stay in a guesthouse. C2 goal=request_info. C3 party_size+=5 people. C4 time+=5, 2; day+=saturday. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 domain=train; time+=19:30. C8 day+=monday; destination+=broxbourne on monday yes; goal=confirm_booking. C9 goal=request_info. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, train; goal=booking, search, request_info; party_size=5 people; destination=stay in a guesthouse, broxbourne on monday yes; requested_info=reference_number; when=saturday, monday, 5, 2, 19:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd really like to stay in a guesthouse.\nChunk 2: What do you have available?\nChunk 3: It is for 5 people.\nChunk 4: The time is saturday, 5, 2.\nChunk 5: Please make a booking.\nChunk 6: I also need the reference number Thank you.\nChunk 7: I am also looking for a train that departs from cambridge after 19:30.\nChunk 8: Going to broxbourne on Monday Yes, it will.\nChunk 9: Can you book 5 tickets for me please?\nChunk 10: No thank you that is all I need today.", "input_token_count": 95, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse; destination: stay in a guesthouse. Next, the goal is request info. Next, party size: 5 people. Next, time: 5; day: saturday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the topic is train; time: 19:30. Next, the goal is confirm booking.; day: monday; destination: broxbourne on monday yes. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info.. hotel type: guesthouse; destination: stay in a guesthouse., broxbourne on monday yes; party size: 5 people.; time: 5, 19:30.; day: saturday., monday; requested information: reference_number..", "trace": "C1 domain=hotel; hotel_type+=guesthouse; destination+=stay in a guesthouse. C2 goal=request_info. C3 party_size+=5 people. C4 time+=5, 2; day+=saturday. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 domain=train; time+=19:30. C8 day+=monday; destination+=broxbourne on monday yes; goal=confirm_booking. C9 goal=request_info. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd really like to stay in a guesthouse.", "streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse; destination: stay in a guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse; destination+=stay in a guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What do you have available?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 5 people.", "streaming_reasoning": "As more information arrives, party size: 5 people..", "trace": "party_size+=5 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is saturday, 5, 2.", "streaming_reasoning": "As more information arrives, time: 5; day: saturday..", "trace": "time+=5, 2; day+=saturday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need the reference number Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am also looking for a train that departs from cambridge after 19:30.", "streaming_reasoning": "As more information arrives, the topic is train; time: 19:30..", "trace": "domain=train; time+=19:30."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Going to broxbourne on Monday Yes, it will.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; day: monday; destination: broxbourne on monday yes.", "trace": "day+=monday; destination+=broxbourne on monday yes; goal=confirm_booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Can you book 5 tickets for me please?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "No thank you that is all I need today.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: party size is 5 people; destination is stay in a guesthouse; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, train; goal=booking, search, request_info; party_size=5 people; destination=stay in a guesthouse, broxbourne on monday yes; requested_info=reference_number; when=saturday, monday, 5, 2, 19:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002571", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for something serving christmas food.\nChunk 2: How about a moderately priced chinese restaurant?\nChunk 3: Ok, what's the phone number?\nChunk 4: Is there anything else Thanks You too!", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 goal=recommendation; cuisine+=chinese; price+=moderate. C3 goal=request_info; requested_info+=phone. C4 goal=compare_alternative.", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, request_info, compare_alternative; food=chinese; price=moderate; requested_info=phone.", "answer": "I can help with that and include the phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for something serving christmas food.\nChunk 2: How about a moderately priced chinese restaurant?\nChunk 3: Ok, what's the phone number?\nChunk 4: Is there anything else Thanks You too!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 goal=recommendation; cuisine+=chinese; price+=moderate. C3 goal=request_info; requested_info+=phone. C4 goal=compare_alternative.\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, request_info, compare_alternative; food=chinese; price=moderate; requested_info=phone.\n\nAnswer: I can help with that and include the phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for something serving christmas food.\nChunk 2: How about a moderately priced chinese restaurant?\nChunk 3: Ok, what's the phone number?\nChunk 4: Is there anything else Thanks You too!", "input_token_count": 34, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, the goal is recommendation; cuisine: chinese; price: moderate. Next, the goal is request info; requested information: phone. Finally, the goal is compare alternative. In summary, The overall topic is restaurant. the goal is compare alternative.. cuisine: chinese; price: moderate.; requested information: phone..", "trace": "C1 domain=restaurant; goal=search. C2 goal=recommendation; cuisine+=chinese; price+=moderate. C3 goal=request_info; requested_info+=phone. C4 goal=compare_alternative.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for something serving christmas food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How about a moderately priced chinese restaurant?", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: chinese; price: moderate..", "trace": "goal=recommendation; cuisine+=chinese; price+=moderate."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Ok, what's the phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is there anything else Thanks You too!", "streaming_reasoning": "Finally, the goal is compare alternative..", "trace": "goal=compare_alternative."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is chinese; price is moderate; requested information is phone.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, request_info, compare_alternative; food=chinese; price=moderate; requested_info=phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002572", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with taxi.\nChunk 2: Please make a booking.\nChunk 3: I would like to arrive by 17:15.\nChunk 4: No, that is all I need today.\nChunk 5: Thanks!", "streaming_reasoning": "C1 domain=taxi; goal=search. C2 goal=booking. C3 time+=17:15; destination+=arrive by 17:15. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi; goal=search, booking; destination=arrive by 17:15; when=17:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need help with taxi.\nChunk 2: Please make a booking.\nChunk 3: I would like to arrive by 17:15.\nChunk 4: No, that is all I need today.\nChunk 5: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search. C2 goal=booking. C3 time+=17:15; destination+=arrive by 17:15. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi; goal=search, booking; destination=arrive by 17:15; when=17:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with taxi.\nChunk 2: Please make a booking.\nChunk 3: I would like to arrive by 17:15.\nChunk 4: No, that is all I need today.\nChunk 5: Thanks!", "input_token_count": 35, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search. Next, the goal is booking. Finally, time: 17:15; destination: arrive by 17:15.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is booking.. time: 17:15; destination: arrive by 17:15..", "trace": "C1 domain=taxi; goal=search. C2 goal=booking. C3 time+=17:15; destination+=arrive by 17:15. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need help with taxi.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search..", "trace": "domain=taxi; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to arrive by 17:15.", "streaming_reasoning": "As more information arrives, time: 17:15; destination: arrive by 17:15..", "trace": "time+=17:15; destination+=arrive by 17:15."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, that is all I need today.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks!", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is arrive by 17:15; timing is 17:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search, booking; destination=arrive by 17:15; when=17:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002573", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm curious about attractions located in the center of town.\nChunk 2: I don't care about entrance fees.\nChunk 3: Yes I would like the center.\nChunk 4: Sounds good, could I get the address please?\nChunk 5: no that takes crare of it.", "streaming_reasoning": "C1 area+=centre. C2 intent=context_update. C3 [SKIP: repeated_information]. C4 goal=request_info; requested_info+=address; acceptance=selected_option. C5 goal=modify_constraint.", "deep_reasoning": "Need goal=request_info; area=centre; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I'm curious about attractions located in the center of town.\nChunk 2: I don't care about entrance fees.\nChunk 3: Yes I would like the center.\nChunk 4: Sounds good, could I get the address please?\nChunk 5: no that takes crare of it."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre. C2 intent=context_update. C3 [SKIP: repeated_information]. C4 goal=request_info; requested_info+=address; acceptance=selected_option. C5 goal=modify_constraint.\n\nDeep reasoning: Need goal=request_info; area=centre; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm curious about attractions located in the center of town.\nChunk 2: I don't care about entrance fees.\nChunk 3: Yes I would like the center.\nChunk 4: Sounds good, could I get the address please?\nChunk 5: no that takes crare of it.", "input_token_count": 47, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, area: centre. Next, intent: context_update. Next, the goal is request info; requested information: address; acceptance: selected_option. Finally, the goal is modify constraint.  Some chunks were skipped because they contained repeated_information. In summary, the goal is modify constraint.. area: centre.; intent: context_update.; requested information: address; acceptance: selected_option..", "trace": "C1 area+=centre. C2 intent=context_update. C3 [SKIP: repeated_information]. C4 goal=request_info; requested_info+=address; acceptance=selected_option. C5 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I'm curious about attractions located in the center of town.", "streaming_reasoning": "Initially, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I don't care about entrance fees.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes I would like the center.", "streaming_reasoning": "The content at C3 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Sounds good, could I get the address please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=address; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "no that takes crare of it.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "Need goal=request_info; area=centre; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002574", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need the reservation for 1 person for Friday at 10:15.\nChunk 2: Yes, I need a train on Friday also, going into Cambridge.\nChunk 3: I am leaving peterborough and want to get to cambridge by 08:15 Just one.\nChunk 4: Can I get the reference number for that?\nChunk 5: Yes, could you please email or fax me the fare amount, as well as the reference number Thank you.\nChunk 6: That is all that I need.", "streaming_reasoning": "C1 goal=booking; time+=1, 10:15; day+=friday. C2 domain=train; goal=confirm_booking. C3 goal=request_info; time+=08:15. C4 requested_info+=reference_number. C5 goal=confirm_booking. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, booking, request_info; requested_info=reference_number; when=friday, 1, 10:15, 08:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need the reservation for 1 person for Friday at 10:15.\nChunk 2: Yes, I need a train on Friday also, going into Cambridge.\nChunk 3: I am leaving peterborough and want to get to cambridge by 08:15 Just one.\nChunk 4: Can I get the reference number for that?\nChunk 5: Yes, could you please email or fax me the fare amount, as well as the reference number Thank you.\nChunk 6: That is all that I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=1, 10:15; day+=friday. C2 domain=train; goal=confirm_booking. C3 goal=request_info; time+=08:15. C4 requested_info+=reference_number. C5 goal=confirm_booking. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, booking, request_info; requested_info=reference_number; when=friday, 1, 10:15, 08:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need the reservation for 1 person for Friday at 10:15.\nChunk 2: Yes, I need a train on Friday also, going into Cambridge.\nChunk 3: I am leaving peterborough and want to get to cambridge by 08:15 Just one.\nChunk 4: Can I get the reference number for that?\nChunk 5: Yes, could you please email or fax me the fare amount, as well as the reference number Thank you.\nChunk 6: That is all that I need.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 1; day: friday. Next, the topic is train; the goal is confirm booking. Next, the goal is request info; time: 08:15. Next, requested information: reference_number. Finally, the goal is confirm booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is confirm booking.. time: 1, 08:15.; day: friday.; requested information: reference_number..", "trace": "C1 goal=booking; time+=1, 10:15; day+=friday. C2 domain=train; goal=confirm_booking. C3 goal=request_info; time+=08:15. C4 requested_info+=reference_number. C5 goal=confirm_booking. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need the reservation for 1 person for Friday at 10:15.", "streaming_reasoning": "Initially, the goal is booking; time: 1; day: friday..", "trace": "goal=booking; time+=1, 10:15; day+=friday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I need a train on Friday also, going into Cambridge.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is confirm booking..", "trace": "domain=train; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am leaving peterborough and want to get to cambridge by 08:15 Just one.", "streaming_reasoning": "As more information arrives, the goal is request info; time: 08:15..", "trace": "goal=request_info; time+=08:15."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I get the reference number for that?", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, could you please email or fax me the fare amount, as well as the reference number Thank you.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all that I need.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, booking, request_info; requested_info=reference_number; when=friday, 1, 10:15, 08:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002575", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure that sounds good.\nChunk 2: Would like that address please.\nChunk 3: Yes, I need a train out of Cambridge on Thursday, please.\nChunk 4: I need to leave after 8:15 and go to London Kings Cross, please.\nChunk 5: No, but what is the travel time for that train ID?\nChunk 6: Nah that won't be necessary.\nChunk 7: I think that's everything I need right now.\nChunk 8: Thank you very much!", "streaming_reasoning": "C1 acceptance=selected_option. C2 goal=request_info; requested_info+=address. C3 domain=train; goal=search; day+=thursday; acceptance=selected_option. C4 time+=8:15; destination+=leave after 8:15 and go to london kings c. C5 requested_info+=travel_time. C6 intent=context_update. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=request_info, search; destination=leave after 8:15 and go to london kings c; requested_info=address, travel_time; when=thursday, 8:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sure that sounds good.\nChunk 2: Would like that address please.\nChunk 3: Yes, I need a train out of Cambridge on Thursday, please.\nChunk 4: I need to leave after 8:15 and go to London Kings Cross, please.\nChunk 5: No, but what is the travel time for that train ID?\nChunk 6: Nah that won't be necessary.\nChunk 7: I think that's everything I need right now.\nChunk 8: Thank you very much!"}, {"role": "assistant", "content": "Streaming reasoning: C1 acceptance=selected_option. C2 goal=request_info; requested_info+=address. C3 domain=train; goal=search; day+=thursday; acceptance=selected_option. C4 time+=8:15; destination+=leave after 8:15 and go to london kings c. C5 requested_info+=travel_time. C6 intent=context_update. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search; destination=leave after 8:15 and go to london kings c; requested_info=address, travel_time; when=thursday, 8:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure that sounds good.\nChunk 2: Would like that address please.\nChunk 3: Yes, I need a train out of Cambridge on Thursday, please.\nChunk 4: I need to leave after 8:15 and go to London Kings Cross, please.\nChunk 5: No, but what is the travel time for that train ID?\nChunk 6: Nah that won't be necessary.\nChunk 7: I think that's everything I need right now.\nChunk 8: Thank you very much!", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, acceptance: selected_option. Next, the goal is request info; requested information: address. Next, the topic is train; the goal is search; day: thursday; acceptance: selected_option. Next, time: 8:15; destination: leave after 8:15 and go to london kings c. Next, requested information: travel_time. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is search. acceptance: selected_option.; requested information: address., travel_time.; day: thursday; time: 8:15; destination: leave after 8:15 and go to london kings c.; intent: context_update..", "trace": "C1 acceptance=selected_option. C2 goal=request_info; requested_info+=address. C3 domain=train; goal=search; day+=thursday; acceptance=selected_option. C4 time+=8:15; destination+=leave after 8:15 and go to london kings c. C5 requested_info+=travel_time. C6 intent=context_update. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sure that sounds good.", "streaming_reasoning": "Initially, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Would like that address please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I need a train out of Cambridge on Thursday, please.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: thursday; acceptance: selected_option..", "trace": "domain=train; goal=search; day+=thursday; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to leave after 8:15 and go to London Kings Cross, please.", "streaming_reasoning": "As more information arrives, time: 8:15; destination: leave after 8:15 and go to london kings c..", "trace": "time+=8:15; destination+=leave after 8:15 and go to london kings c."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, but what is the travel time for that train ID?", "streaming_reasoning": "As more information arrives, requested information: travel_time..", "trace": "requested_info+=travel_time."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Nah that won't be necessary.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I think that's everything I need right now.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you very much!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: destination is leave after 8:15 and go to london kings c; requested information is address; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search; destination=leave after 8:15 and go to london kings c; requested_info=address, travel_time; when=thursday, 8:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001744", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Looking back on my childhood and how happy it was.\nChunk 2: How was life when you were growing up?\nChunk 3: It was pretty great but it was rough at times You?\nChunk 4: Looking back it seems to have been very happy.\nChunk 5: That's great to hear!\nChunk 6: Mine was mostly happy but of course there was some issues.", "streaming_reasoning": "C1 emotion=happy; event=Looking back on my childhood and how it was; need=celebration. C2 need=clarification. C3 support_signal=received. C4 emotion=happy; need=celebration. C5 support_signal=received. C6 emotion=happy.", "deep_reasoning": "User feels happy because Looking back on my childhood and how it was and needs celebration.", "answer": "That is worth celebrating, especially because Looking back on my childhood and how it was. Take a moment to enjoy it and share the good news with someone who will be happy for you.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Looking back on my childhood and how happy it was.\nChunk 2: How was life when you were growing up?\nChunk 3: It was pretty great but it was rough at times You?\nChunk 4: Looking back it seems to have been very happy.\nChunk 5: That's great to hear!\nChunk 6: Mine was mostly happy but of course there was some issues."}, {"role": "assistant", "content": "Streaming reasoning: C1 emotion=happy; event=Looking back on my childhood and how it was; need=celebration. C2 need=clarification. C3 support_signal=received. C4 emotion=happy; need=celebration. C5 support_signal=received. C6 emotion=happy.\n\nDeep reasoning: User feels happy because Looking back on my childhood and how it was and needs celebration.\n\nAnswer: That is worth celebrating, especially because Looking back on my childhood and how it was. Take a moment to enjoy it and share the good news with someone who will be happy for you."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Looking back on my childhood and how happy it was.\nChunk 2: How was life when you were growing up?\nChunk 3: It was pretty great but it was rough at times You?\nChunk 4: Looking back it seems to have been very happy.\nChunk 5: That's great to hear!\nChunk 6: Mine was mostly happy but of course there was some issues.", "input_token_count": 65, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user expresses happy; the user needs celebration.; event: Looking back on my childhood and how it was. Next, the user needs clarification. Next, the user signals support or acknowledgment. Next, the user expresses happy; the user needs celebration. Next, the user signals support or acknowledgment. Finally, the user expresses happy.", "trace": "C1 emotion=happy; event=Looking back on my childhood and how it was; need=celebration. C2 need=clarification. C3 support_signal=received. C4 emotion=happy; need=celebration. C5 support_signal=received. C6 emotion=happy.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Looking back on my childhood and how happy it was.", "streaming_reasoning": "Initially, the user expresses happy; the user needs celebration.; event: Looking back on my childhood and how it was.", "trace": "emotion=happy; event=Looking back on my childhood and how it was; need=celebration."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How was life when you were growing up?", "streaming_reasoning": "As more information arrives, the user needs clarification..", "trace": "need=clarification."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It was pretty great but it was rough at times You?", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Looking back it seems to have been very happy.", "streaming_reasoning": "As more information arrives, the user expresses happy; the user needs celebration..", "trace": "emotion=happy; need=celebration."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That's great to hear!", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Mine was mostly happy but of course there was some issues.", "streaming_reasoning": "Finally, the user expresses happy..", "trace": "emotion=happy."}]}, "output": {"deep_reasoning": "User feels happy because Looking back on my childhood and how it was and needs celebration.", "answer": "That is worth celebrating, especially because Looking back on my childhood and how it was. Take a moment to enjoy it and share the good news with someone who will be happy for you."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002577", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is there a hospital close by?\nChunk 2: I need the address, postcode and phone number for Addenbrookes Hospital Thank you.\nChunk 3: That is all I need.", "streaming_reasoning": "C1 domain=hospital. C2 goal=request_info; requested_info+=address, phone, postcode. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search, request_info; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Is there a hospital close by?\nChunk 2: I need the address, postcode and phone number for Addenbrookes Hospital Thank you.\nChunk 3: That is all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital. C2 goal=request_info; requested_info+=address, phone, postcode. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; requested_info=address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is there a hospital close by?\nChunk 2: I need the address, postcode and phone number for Addenbrookes Hospital Thank you.\nChunk 3: That is all I need.", "input_token_count": 30, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital.. the goal is request info. requested information: address.", "trace": "C1 domain=hospital. C2 goal=request_info; requested_info+=address, phone, postcode. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Is there a hospital close by?", "streaming_reasoning": "Initially, the topic is hospital..", "trace": "domain=hospital."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need the address, postcode and phone number for Addenbrookes Hospital Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That is all I need.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; requested_info=address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002579", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with taxi.\nChunk 2: The time is 17:15.\nChunk 3: Please make a booking Thank you!\nChunk 4: That will be all!", "streaming_reasoning": "C1 domain=taxi; goal=search. C2 time+=17:15. C3 goal=booking. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi; goal=search, booking; when=17:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need help with taxi.\nChunk 2: The time is 17:15.\nChunk 3: Please make a booking Thank you!\nChunk 4: That will be all!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search. C2 time+=17:15. C3 goal=booking. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi; goal=search, booking; when=17:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with taxi.\nChunk 2: The time is 17:15.\nChunk 3: Please make a booking Thank you!\nChunk 4: That will be all!", "input_token_count": 28, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search. Next, time: 17:15. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is booking.. time: 17:15..", "trace": "C1 domain=taxi; goal=search. C2 time+=17:15. C3 goal=booking. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need help with taxi.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search..", "trace": "domain=taxi; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is 17:15.", "streaming_reasoning": "As more information arrives, time: 17:15..", "trace": "time+=17:15."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Please make a booking Thank you!", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That will be all!", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: timing is 17:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search, booking; when=17:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002580", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a cheap option please.\nChunk 2: Possibly, do they have free wifi?\nChunk 3: The time is wednesday, friday, 1, 3.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number Thank you!\nChunk 6: Have a great day Thank for calling.\nChunk 7: No.\nChunk 8: The restaurant and lodging are all Thank you, again Goodbye.", "streaming_reasoning": "C1 price+=cheap. C2 amenities+=wifi. C3 time+=1; day+=wednesday, friday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 intent=context_update. C7 goal=modify_constraint. C8 domain=hotel.", "deep_reasoning": "Need domain=restaurant, hotel; goal=booking, search, request_info; price=cheap; amenities=wifi; requested_info=reference_number; when=wednesday, friday, 1.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a cheap option please.\nChunk 2: Possibly, do they have free wifi?\nChunk 3: The time is wednesday, friday, 1, 3.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number Thank you!\nChunk 6: Have a great day Thank for calling.\nChunk 7: No.\nChunk 8: The restaurant and lodging are all Thank you, again Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 price+=cheap. C2 amenities+=wifi. C3 time+=1; day+=wednesday, friday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 intent=context_update. C7 goal=modify_constraint. C8 domain=hotel.\n\nDeep reasoning: Need domain=restaurant, hotel; goal=booking, search, request_info; price=cheap; amenities=wifi; requested_info=reference_number; when=wednesday, friday, 1.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a cheap option please.\nChunk 2: Possibly, do they have free wifi?\nChunk 3: The time is wednesday, friday, 1, 3.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number Thank you!\nChunk 6: Have a great day Thank for calling.\nChunk 7: No.\nChunk 8: The restaurant and lodging are all Thank you, again Goodbye.", "input_token_count": 66, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, price: cheap. Next, amenities: wifi. Next, time: 1; day: wednesday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, intent: context_update. Next, the goal is modify constraint. Finally, the topic is hotel. In summary, The overall topic is hotel.. the goal is modify constraint.. price: cheap.; amenities: wifi.; time: 1; day: wednesday; requested information: reference_number.; intent: context_update..", "trace": "C1 price+=cheap. C2 amenities+=wifi. C3 time+=1; day+=wednesday, friday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 intent=context_update. C7 goal=modify_constraint. C8 domain=hotel.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a cheap option please.", "streaming_reasoning": "Initially, price: cheap..", "trace": "price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Possibly, do they have free wifi?", "streaming_reasoning": "As more information arrives, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is wednesday, friday, 1, 3.", "streaming_reasoning": "As more information arrives, time: 1; day: wednesday.", "trace": "time+=1; day+=wednesday, friday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the reference number Thank you!", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Have a great day Thank for calling.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "The restaurant and lodging are all Thank you, again Goodbye.", "streaming_reasoning": "Finally, the topic is hotel..", "trace": "domain=hotel."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: price is cheap; amenities is wifi; requested information is reference_number; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=booking, search, request_info; price=cheap; amenities=wifi; requested_info=reference_number; when=wednesday, friday, 1."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002581", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for information on the Kings college attraction.\nChunk 2: What is the postcode?\nChunk 3: That is all I needed today, thanks!", "streaming_reasoning": "C1 domain=attraction; goal=search. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction; goal=search, request_info; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for information on the Kings college attraction.\nChunk 2: What is the postcode?\nChunk 3: That is all I needed today, thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for information on the Kings college attraction.\nChunk 2: What is the postcode?\nChunk 3: That is all I needed today, thanks!", "input_token_count": 27, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search. Finally, the goal is request info; requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is request info. requested information: postcode..", "trace": "C1 domain=attraction; goal=search. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for information on the Kings college attraction.", "streaming_reasoning": "Initially, the topic is attraction; the goal is search..", "trace": "domain=attraction; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That is all I needed today, thanks!", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000541", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Master Dance Dance Revolution.\nChunk 2: • Comfortable Shoes • Money • Water (Or some other hydrating liquid) • Comfortable clothing that is easy to move in • Sweat Towels (Optional) • Windex for the pad (only if playing on arcade machine.\nChunk 3: it helps with the traction on your shoes).", "streaming_reasoning": "C1 task=master_dance_dance_revolution. C2 step=comfortable_shoes_money_water. C3 step=it_helps_with_the.", "deep_reasoning": "Procedure for Master Dance Dance Revolution: Comfortable Shoes Money Water Comfortable clothing that is easy to, it helps with the traction on your shoes).", "answer": "For Master Dance Dance Revolution, follow the steps in order: Comfortable Shoes Money Water Comfortable clothing that is easy to, it helps with the traction on your shoes).", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Master Dance Dance Revolution.\nChunk 2: • Comfortable Shoes • Money • Water (Or some other hydrating liquid) • Comfortable clothing that is easy to move in • Sweat Towels (Optional) • Windex for the pad (only if playing on arcade machine.\nChunk 3: it helps with the traction on your shoes)."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=master_dance_dance_revolution. C2 step=comfortable_shoes_money_water. C3 step=it_helps_with_the.\n\nDeep reasoning: Procedure for Master Dance Dance Revolution: Comfortable Shoes Money Water Comfortable clothing that is easy to, it helps with the traction on your shoes).\n\nAnswer: For Master Dance Dance Revolution, follow the steps in order: Comfortable Shoes Money Water Comfortable clothing that is easy to, it helps with the traction on your shoes)."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Master Dance Dance Revolution.\nChunk 2: • Comfortable Shoes • Money • Water (Or some other hydrating liquid) • Comfortable clothing that is easy to move in • Sweat Towels (Optional) • Windex for the pad (only if playing on arcade machine.\nChunk 3: it helps with the traction on your shoes).", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, task: master_dance_dance_revolution. Next, step: comfortable_shoes_money_water. Finally, step: it_helps_with_the. In summary, task: master_dance_dance_revolution.; step: comfortable_shoes_money_water., it_helps_with_the..", "trace": "C1 task=master_dance_dance_revolution. C2 step=comfortable_shoes_money_water. C3 step=it_helps_with_the.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Master Dance Dance Revolution.", "streaming_reasoning": "Initially, task: master_dance_dance_revolution..", "trace": "task=master_dance_dance_revolution."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• Comfortable Shoes • Money • Water (Or some other hydrating liquid) • Comfortable clothing that is easy to move in • Sweat Towels (Optional) • Windex for the pad (only if playing on arcade machine.", "streaming_reasoning": "As more information arrives, step: comfortable_shoes_money_water..", "trace": "step=comfortable_shoes_money_water."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "it helps with the traction on your shoes).", "streaming_reasoning": "Finally, step: it_helps_with_the..", "trace": "step=it_helps_with_the."}]}, "output": {"deep_reasoning": "Procedure for Master Dance Dance Revolution: Comfortable Shoes Money Water Comfortable clothing that is easy to, it helps with the traction on your shoes).", "answer": "For Master Dance Dance Revolution, follow the steps in order: Comfortable Shoes Money Water Comfortable clothing that is easy to, it helps with the traction on your shoes)."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001746", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: When my friend got a scholarship that I didnt I felt jealous.\nChunk 2: i felt bad that I was jealous and not as happy for him.\nChunk 3: My friend got a scholarship last year that he was barely able to get, it was quite a large amount of money Nice What scholarship?\nChunk 4: It was the national merit, I felt bad because i felt jealous before i felt happy for him That's natural.\nChunk 5: Just don't tell him lol.\nChunk 6: You'll be alright buddy.", "streaming_reasoning": "C1 cause=my friend got a scholarship that I didnt I felt jealous; need=encouragement. C2 emotion=happy; event=bad that I was jealous and not as for him; need=celebration. C3 need=clarification. C4 emotion=happy; event=jealous before i felt for him That's natural; need=celebration. C5 support_signal=received. C6 support_signal=received.", "deep_reasoning": "User feels happy because jealous before i felt for him That's natural and needs celebration.", "answer": "That is worth celebrating, especially because jealous before i felt for him That's natural. Take a moment to enjoy it and share the good news with someone who will be happy for you.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: When my friend got a scholarship that I didnt I felt jealous.\nChunk 2: i felt bad that I was jealous and not as happy for him.\nChunk 3: My friend got a scholarship last year that he was barely able to get, it was quite a large amount of money Nice What scholarship?\nChunk 4: It was the national merit, I felt bad because i felt jealous before i felt happy for him That's natural.\nChunk 5: Just don't tell him lol.\nChunk 6: You'll be alright buddy."}, {"role": "assistant", "content": "Streaming reasoning: C1 cause=my friend got a scholarship that I didnt I felt jealous; need=encouragement. C2 emotion=happy; event=bad that I was jealous and not as for him; need=celebration. C3 need=clarification. C4 emotion=happy; event=jealous before i felt for him That's natural; need=celebration. C5 support_signal=received. C6 support_signal=received.\n\nDeep reasoning: User feels happy because jealous before i felt for him That's natural and needs celebration.\n\nAnswer: That is worth celebrating, especially because jealous before i felt for him That's natural. Take a moment to enjoy it and share the good news with someone who will be happy for you."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: When my friend got a scholarship that I didnt I felt jealous.\nChunk 2: i felt bad that I was jealous and not as happy for him.\nChunk 3: My friend got a scholarship last year that he was barely able to get, it was quite a large amount of money Nice What scholarship?\nChunk 4: It was the national merit, I felt bad because i felt jealous before i felt happy for him That's natural.\nChunk 5: Just don't tell him lol.\nChunk 6: You'll be alright buddy.", "input_token_count": 91, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user mentions my friend got a scholarship that I didnt I felt jealous; the user needs encouragement. Next, the user expresses happy; the user needs celebration.; event: bad that I was jealous and not as for him. Next, the user needs clarification. Next, the user expresses happy; the user needs celebration.; event: jealous before i felt for him That's natural. Next, the user signals support or acknowledgment. Finally, the user signals support or acknowledgment.", "trace": "C1 cause=my friend got a scholarship that I didnt I felt jealous; need=encouragement. C2 emotion=happy; event=bad that I was jealous and not as for him; need=celebration. C3 need=clarification. C4 emotion=happy; event=jealous before i felt for him That's natural; need=celebration. C5 support_signal=received. C6 support_signal=received.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "When my friend got a scholarship that I didnt I felt jealous.", "streaming_reasoning": "Initially, the user mentions my friend got a scholarship that I didnt I felt jealous; the user needs encouragement..", "trace": "cause=my friend got a scholarship that I didnt I felt jealous; need=encouragement."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "i felt bad that I was jealous and not as happy for him.", "streaming_reasoning": "As more information arrives, the user expresses happy; the user needs celebration.; event: bad that I was jealous and not as for him.", "trace": "emotion=happy; event=bad that I was jealous and not as for him; need=celebration."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "My friend got a scholarship last year that he was barely able to get, it was quite a large amount of money Nice What scholarship?", "streaming_reasoning": "As more information arrives, the user needs clarification..", "trace": "need=clarification."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It was the national merit, I felt bad because i felt jealous before i felt happy for him That's natural.", "streaming_reasoning": "As more information arrives, the user expresses happy; the user needs celebration.; event: jealous before i felt for him That's natural.", "trace": "emotion=happy; event=jealous before i felt for him That's natural; need=celebration."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Just don't tell him lol.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "You'll be alright buddy.", "streaming_reasoning": "Finally, the user signals support or acknowledgment.", "trace": "support_signal=received."}]}, "output": {"deep_reasoning": "User feels happy because jealous before i felt for him That's natural and needs celebration.", "answer": "That is worth celebrating, especially because jealous before i felt for him That's natural. Take a moment to enjoy it and share the good news with someone who will be happy for you."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002583", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I am also looking for a place to stay, that has moderate pricing.\nChunk 2: I need something in the north, with free wifi and free parking.\nChunk 3: I would love if you could suggest one.\nChunk 4: It can be so overwhelming.\nChunk 5: What is the address and how many stars is it rated?\nChunk 6: Thank you for the address and star rating of Acorn Guest House.\nChunk 7: No that will be all thank you.", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=moderate; destination+=stay; acceptance=selected_option. C2 area+=north; amenities+=parking, wifi, free parking. C3 goal=recommendation. C4 intent=context_update. C5 goal=request_info; requested_info+=address. C6 hotel_type+=guesthouse. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, recommendation, request_info; area=north; price=moderate; amenities=parking, wifi, free parking; destination=stay; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I am also looking for a place to stay, that has moderate pricing.\nChunk 2: I need something in the north, with free wifi and free parking.\nChunk 3: I would love if you could suggest one.\nChunk 4: It can be so overwhelming.\nChunk 5: What is the address and how many stars is it rated?\nChunk 6: Thank you for the address and star rating of Acorn Guest House.\nChunk 7: No that will be all thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=moderate; destination+=stay; acceptance=selected_option. C2 area+=north; amenities+=parking, wifi, free parking. C3 goal=recommendation. C4 intent=context_update. C5 goal=request_info; requested_info+=address. C6 hotel_type+=guesthouse. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, recommendation, request_info; area=north; price=moderate; amenities=parking, wifi, free parking; destination=stay; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I am also looking for a place to stay, that has moderate pricing.\nChunk 2: I need something in the north, with free wifi and free parking.\nChunk 3: I would love if you could suggest one.\nChunk 4: It can be so overwhelming.\nChunk 5: What is the address and how many stars is it rated?\nChunk 6: Thank you for the address and star rating of Acorn Guest House.\nChunk 7: No that will be all thank you.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: moderate; destination: stay; acceptance: selected_option. Next, area: north; amenities: parking. Next, the goal is recommendation. Next, intent: context_update. Next, the goal is request info; requested information: address. Finally, hotel type: guesthouse.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. price: moderate; destination: stay; acceptance: selected_option.; area: north; amenities: parking; intent: context_update.; requested information: address.; hotel type: guesthouse..", "trace": "C1 domain=hotel; goal=search; price+=moderate; destination+=stay; acceptance=selected_option. C2 area+=north; amenities+=parking, wifi, free parking. C3 goal=recommendation. C4 intent=context_update. C5 goal=request_info; requested_info+=address. C6 hotel_type+=guesthouse. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I am also looking for a place to stay, that has moderate pricing.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: moderate; destination: stay; acceptance: selected_option..", "trace": "domain=hotel; goal=search; price+=moderate; destination+=stay; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need something in the north, with free wifi and free parking.", "streaming_reasoning": "As more information arrives, area: north; amenities: parking.", "trace": "area+=north; amenities+=parking, wifi, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would love if you could suggest one.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It can be so overwhelming.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What is the address and how many stars is it rated?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for the address and star rating of Acorn Guest House.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse..", "trace": "hotel_type+=guesthouse."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No that will be all thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; price is moderate; amenities is parking; destination is stay; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, recommendation, request_info; area=north; price=moderate; amenities=parking, wifi, free parking; destination=stay; requested_info=address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002584", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes the north please Yes, please.\nChunk 2: We'd like a table for 3 at 15:30 on Tuesday.\nChunk 3: I want to find a restaurant.\nChunk 4: Please make a booking.\nChunk 5: Moderate price range please.\nChunk 6: Sure, please book it for 3 people.\nChunk 7: We'll arrive tuesday and stay for 2 nights.\nChunk 8: That's all for now Thank you.", "streaming_reasoning": "C1 area+=north; acceptance=selected_option. C2 time+=3, 15:30; day+=tuesday. C3 domain=restaurant; goal=search; destination+=find a restaurant. C4 goal=booking. C5 price+=moderate. C6 party_size+=3 people. C7 domain=hotel; time+=2; stay_length+=2 nights. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel; goal=search, booking; area=north; price=moderate; party_size=3 people; stay_length=2 nights; destination=find a restaurant; when=tuesday, 3, 15:30, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes the north please Yes, please.\nChunk 2: We'd like a table for 3 at 15:30 on Tuesday.\nChunk 3: I want to find a restaurant.\nChunk 4: Please make a booking.\nChunk 5: Moderate price range please.\nChunk 6: Sure, please book it for 3 people.\nChunk 7: We'll arrive tuesday and stay for 2 nights.\nChunk 8: That's all for now Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=north; acceptance=selected_option. C2 time+=3, 15:30; day+=tuesday. C3 domain=restaurant; goal=search; destination+=find a restaurant. C4 goal=booking. C5 price+=moderate. C6 party_size+=3 people. C7 domain=hotel; time+=2; stay_length+=2 nights. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel; goal=search, booking; area=north; price=moderate; party_size=3 people; stay_length=2 nights; destination=find a restaurant; when=tuesday, 3, 15:30, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes the north please Yes, please.\nChunk 2: We'd like a table for 3 at 15:30 on Tuesday.\nChunk 3: I want to find a restaurant.\nChunk 4: Please make a booking.\nChunk 5: Moderate price range please.\nChunk 6: Sure, please book it for 3 people.\nChunk 7: We'll arrive tuesday and stay for 2 nights.\nChunk 8: That's all for now Thank you.", "input_token_count": 68, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: north; acceptance: selected_option. Next, time: 3; day: tuesday. Next, the topic is restaurant; the goal is search; destination: find a restaurant. Next, the goal is booking. Next, price: moderate. Next, party size: 3 people. Finally, the topic is hotel; time: 2; stay length: 2 nights.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking.. area: north; acceptance: selected_option.; time: 3, 2; day: tuesday.; destination: find a restaurant.; price: moderate.; party size: 3 people.; stay length: 2 nights..", "trace": "C1 area+=north; acceptance=selected_option. C2 time+=3, 15:30; day+=tuesday. C3 domain=restaurant; goal=search; destination+=find a restaurant. C4 goal=booking. C5 price+=moderate. C6 party_size+=3 people. C7 domain=hotel; time+=2; stay_length+=2 nights. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes the north please Yes, please.", "streaming_reasoning": "Initially, area: north; acceptance: selected_option..", "trace": "area+=north; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "We'd like a table for 3 at 15:30 on Tuesday.", "streaming_reasoning": "As more information arrives, time: 3; day: tuesday..", "trace": "time+=3, 15:30; day+=tuesday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; destination: find a restaurant..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Moderate price range please.", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Sure, please book it for 3 people.", "streaming_reasoning": "As more information arrives, party size: 3 people..", "trace": "party_size+=3 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "We'll arrive tuesday and stay for 2 nights.", "streaming_reasoning": "As more information arrives, the topic is hotel; time: 2; stay length: 2 nights..", "trace": "domain=hotel; time+=2; stay_length+=2 nights."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's all for now Thank you.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; price is moderate; party size is 3 people; stay length is 2 nights; destination is find a restaurant; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=search, booking; area=north; price=moderate; party_size=3 people; stay_length=2 nights; destination=find a restaurant; when=tuesday, 3, 15:30, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002585", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you tell me the address and phone number for the one in the center of town?\nChunk 2: Thanks.\nChunk 3: I also need to check on trains.\nChunk 4: I need to travel on Wednesday.\nChunk 5: I need to leave london liverpool street and be in cambridge by 21:00.\nChunk 6: I don't care about the departure time so please give me the ID and price of any one of those trains.\nChunk 7: I would like to book that train Thank You.\nChunk 8: No, that will be everything Goodbye.", "streaming_reasoning": "C1 goal=request_info; area+=centre; requested_info+=address, phone. C2 [SKIP: thanks_only]. C3 goal=search; destination+=check on trains. C4 day+=wednesday; destination+=travel on wednesday. C5 time+=21:00; amenities+=pool; destination+=leave london liverpool street and be in c. C6 requested_info+=price. C7 domain=train; goal=booking. C8 goal=modify_constraint.", "deep_reasoning": "Need domain=train; goal=request_info, search, booking; area=centre; amenities=pool; destination=check on trains, travel on wednesday, leave london liverpool street and be in c; requested_info=address, phone, price; when=wednesday, 21:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you tell me the address and phone number for the one in the center of town?\nChunk 2: Thanks.\nChunk 3: I also need to check on trains.\nChunk 4: I need to travel on Wednesday.\nChunk 5: I need to leave london liverpool street and be in cambridge by 21:00.\nChunk 6: I don't care about the departure time so please give me the ID and price of any one of those trains.\nChunk 7: I would like to book that train Thank You.\nChunk 8: No, that will be everything Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; area+=centre; requested_info+=address, phone. C2 [SKIP: thanks_only]. C3 goal=search; destination+=check on trains. C4 day+=wednesday; destination+=travel on wednesday. C5 time+=21:00; amenities+=pool; destination+=leave london liverpool street and be in c. C6 requested_info+=price. C7 domain=train; goal=booking. C8 goal=modify_constraint.\n\nDeep reasoning: Need domain=train; goal=request_info, search, booking; area=centre; amenities=pool; destination=check on trains, travel on wednesday, leave london liverpool street and be in c; requested_info=address, phone, price; when=wednesday, 21:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you tell me the address and phone number for the one in the center of town?\nChunk 2: Thanks.\nChunk 3: I also need to check on trains.\nChunk 4: I need to travel on Wednesday.\nChunk 5: I need to leave london liverpool street and be in cambridge by 21:00.\nChunk 6: I don't care about the departure time so please give me the ID and price of any one of those trains.\nChunk 7: I would like to book that train Thank You.\nChunk 8: No, that will be everything Goodbye.", "input_token_count": 97, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; area: centre; requested information: address. Next, the goal is search; destination: check on trains. Next, day: wednesday; destination: travel on wednesday. Next, time: 21:00; amenities: pool; destination: leave london liverpool street and be in c. Next, requested information: price. Next, the topic is train; the goal is booking. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is modify constraint.. area: centre; requested information: address, price.; destination: check on trains., travel on wednesday., leave london liverpool street and be in c.; day: wednesday; time: 21:00; amenities: pool.", "trace": "C1 goal=request_info; area+=centre; requested_info+=address, phone. C2 [SKIP: thanks_only]. C3 goal=search; destination+=check on trains. C4 day+=wednesday; destination+=travel on wednesday. C5 time+=21:00; amenities+=pool; destination+=leave london liverpool street and be in c. C6 requested_info+=price. C7 domain=train; goal=booking. C8 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you tell me the address and phone number for the one in the center of town?", "streaming_reasoning": "Initially, the goal is request info; area: centre; requested information: address.", "trace": "goal=request_info; area+=centre; requested_info+=address, phone."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need to check on trains.", "streaming_reasoning": "As more information arrives, the goal is search; destination: check on trains..", "trace": "goal=search; destination+=check on trains."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to travel on Wednesday.", "streaming_reasoning": "As more information arrives, day: wednesday; destination: travel on wednesday..", "trace": "day+=wednesday; destination+=travel on wednesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need to leave london liverpool street and be in cambridge by 21:00.", "streaming_reasoning": "As more information arrives, time: 21:00; amenities: pool; destination: leave london liverpool street and be in c..", "trace": "time+=21:00; amenities+=pool; destination+=leave london liverpool street and be in c."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I don't care about the departure time so please give me the ID and price of any one of those trains.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I would like to book that train Thank You.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is booking..", "trace": "domain=train; goal=booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, that will be everything Goodbye.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: area is centre; amenities is pool; destination is check on trains; requested information is address; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search, booking; area=centre; amenities=pool; destination=check on trains, travel on wednesday, leave london liverpool street and be in c; requested_info=address, phone, price; when=wednesday, 21:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002586", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to leave the hotel by 05:00.\nChunk 2: Going to the attraction.\nChunk 3: somewhere in the south, sorry need the phone # and admission fee.\nChunk 4: Can you make a recommendation?\nChunk 5: Great, can I have the phone number and reference fee.\nChunk 6: Please send info on tenpin.\nChunk 7: Thanks for the help.\nChunk 8: Thank you for the help.\nChunk 9: That's all for now.", "streaming_reasoning": "C1 domain=hotel; goal=search; time+=05:00; hotel_type+=hotel; destination+=leave the hotel by 05:00. C2 domain=attraction; destination+=the attraction. C3 goal=request_info; area+=south; requested_info+=phone, entrance_fee. C4 requested_info+=recommendation. C5 requested_info+=reference_number. C6 intent=context_update. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, attraction; goal=search, request_info; area=south; destination=leave the hotel by 05:00, the attraction; requested_info=phone, entrance_fee, recommendation, reference_number; when=05:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to leave the hotel by 05:00.\nChunk 2: Going to the attraction.\nChunk 3: somewhere in the south, sorry need the phone # and admission fee.\nChunk 4: Can you make a recommendation?\nChunk 5: Great, can I have the phone number and reference fee.\nChunk 6: Please send info on tenpin.\nChunk 7: Thanks for the help.\nChunk 8: Thank you for the help.\nChunk 9: That's all for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; time+=05:00; hotel_type+=hotel; destination+=leave the hotel by 05:00. C2 domain=attraction; destination+=the attraction. C3 goal=request_info; area+=south; requested_info+=phone, entrance_fee. C4 requested_info+=recommendation. C5 requested_info+=reference_number. C6 intent=context_update. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, attraction; goal=search, request_info; area=south; destination=leave the hotel by 05:00, the attraction; requested_info=phone, entrance_fee, recommendation, reference_number; when=05:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to leave the hotel by 05:00.\nChunk 2: Going to the attraction.\nChunk 3: somewhere in the south, sorry need the phone # and admission fee.\nChunk 4: Can you make a recommendation?\nChunk 5: Great, can I have the phone number and reference fee.\nChunk 6: Please send info on tenpin.\nChunk 7: Thanks for the help.\nChunk 8: Thank you for the help.\nChunk 9: That's all for now.", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; time: 05:00; hotel type: hotel; destination: leave the hotel by 05:00. Next, the topic is attraction; destination: the attraction. Next, the goal is request info; area: south; requested information: phone. Next, requested information: recommendation. Next, requested information: reference_number. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction. the goal is request info. time: 05:00; hotel type: hotel; destination: leave the hotel by 05:00., the attraction.; area: south; requested information: phone, recommendation., reference_number.; intent: context_update..", "trace": "C1 domain=hotel; goal=search; time+=05:00; hotel_type+=hotel; destination+=leave the hotel by 05:00. C2 domain=attraction; destination+=the attraction. C3 goal=request_info; area+=south; requested_info+=phone, entrance_fee. C4 requested_info+=recommendation. C5 requested_info+=reference_number. C6 intent=context_update. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to leave the hotel by 05:00.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; time: 05:00; hotel type: hotel; destination: leave the hotel by 05:00..", "trace": "domain=hotel; goal=search; time+=05:00; hotel_type+=hotel; destination+=leave the hotel by 05:00."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Going to the attraction.", "streaming_reasoning": "As more information arrives, the topic is attraction; destination: the attraction..", "trace": "domain=attraction; destination+=the attraction."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "somewhere in the south, sorry need the phone # and admission fee.", "streaming_reasoning": "As more information arrives, the goal is request info; area: south; requested information: phone.", "trace": "goal=request_info; area+=south; requested_info+=phone, entrance_fee."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you make a recommendation?", "streaming_reasoning": "As more information arrives, requested information: recommendation..", "trace": "requested_info+=recommendation."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Great, can I have the phone number and reference fee.", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please send info on tenpin.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks for the help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for the help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That's all for now.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is south; destination is leave the hotel by 05:00; requested information is phone; timing is 05:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, attraction; goal=search, request_info; area=south; destination=leave the hotel by 05:00, the attraction; requested_info=phone, entrance_fee, recommendation, reference_number; when=05:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002587", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I see, can you tell me about museums in the west then.\nChunk 2: And what is the postcode?\nChunk 3: What is the postcode of the county folk museum?\nChunk 4: Thanks I also need a train leaving monday arriving by 1900.\nChunk 5: I am going from stevenage to cambridge.\nChunk 6: I need the price, travel, and depart times please.\nChunk 7: Thank you so much!\nChunk 8: I think that covers all the information I need today.\nChunk 9: That is all Thank you!", "streaming_reasoning": "C1 goal=request_info; area+=west. C2 requested_info+=postcode. C3 domain=attraction. C4 domain=train; goal=search; day+=monday. C5 destination+=cambridge; departure+=stevenage. C6 requested_info+=price. C7 [SKIP: thanks_only]. C8 day+=today. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, train; goal=request_info, search; area=west; destination=cambridge; departure=stevenage; requested_info=postcode, price; when=monday, today; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I see, can you tell me about museums in the west then.\nChunk 2: And what is the postcode?\nChunk 3: What is the postcode of the county folk museum?\nChunk 4: Thanks I also need a train leaving monday arriving by 1900.\nChunk 5: I am going from stevenage to cambridge.\nChunk 6: I need the price, travel, and depart times please.\nChunk 7: Thank you so much!\nChunk 8: I think that covers all the information I need today.\nChunk 9: That is all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; area+=west. C2 requested_info+=postcode. C3 domain=attraction. C4 domain=train; goal=search; day+=monday. C5 destination+=cambridge; departure+=stevenage. C6 requested_info+=price. C7 [SKIP: thanks_only]. C8 day+=today. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, train; goal=request_info, search; area=west; destination=cambridge; departure=stevenage; requested_info=postcode, price; when=monday, today; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I see, can you tell me about museums in the west then.\nChunk 2: And what is the postcode?\nChunk 3: What is the postcode of the county folk museum?\nChunk 4: Thanks I also need a train leaving monday arriving by 1900.\nChunk 5: I am going from stevenage to cambridge.\nChunk 6: I need the price, travel, and depart times please.\nChunk 7: Thank you so much!\nChunk 8: I think that covers all the information I need today.\nChunk 9: That is all Thank you!", "input_token_count": 90, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; area: west. Next, requested information: postcode. Next, the topic is attraction. Next, the topic is train; the goal is search; day: monday. Next, destination: cambridge; departure point: stevenage. Next, requested information: price. Finally, day: today.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is search. area: west.; requested information: postcode., price.; day: monday., today.; destination: cambridge; departure point: stevenage..", "trace": "C1 goal=request_info; area+=west. C2 requested_info+=postcode. C3 domain=attraction. C4 domain=train; goal=search; day+=monday. C5 destination+=cambridge; departure+=stevenage. C6 requested_info+=price. C7 [SKIP: thanks_only]. C8 day+=today. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I see, can you tell me about museums in the west then.", "streaming_reasoning": "Initially, the goal is request info; area: west..", "trace": "goal=request_info; area+=west."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "And what is the postcode?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the postcode of the county folk museum?", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks I also need a train leaving monday arriving by 1900.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: monday..", "trace": "domain=train; goal=search; day+=monday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I am going from stevenage to cambridge.", "streaming_reasoning": "As more information arrives, destination: cambridge; departure point: stevenage..", "trace": "destination+=cambridge; departure+=stevenage."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need the price, travel, and depart times please.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you so much!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I think that covers all the information I need today.", "streaming_reasoning": "As more information arrives, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That is all Thank you!", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: area is west; destination is cambridge; departure point is stevenage; requested information is postcode; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, train; goal=request_info, search; area=west; destination=cambridge; departure=stevenage; requested_info=postcode, price; when=monday, today; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002588", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking to get some eritrean food in the west part of town.\nChunk 2: Can you see if there are any that serve indian food?\nChunk 3: It is for 8 people.\nChunk 4: The time is sunday, 8, 12:15.\nChunk 5: Please make a booking.\nChunk 6: Sure as long as it's in the same area and price range.\nChunk 7: I need the reference number too please.\nChunk 8: Thank you, that's all I needed today!", "streaming_reasoning": "C1 domain=restaurant; goal=request_info; area+=west. C2 cuisine+=indian. C3 party_size+=8 people. C4 time+=8, 12:15; day+=sunday. C5 goal=booking. C6 goal=modify_constraint. C7 goal=search; requested_info+=reference_number. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=request_info, booking, modify_constraint, search; area=west; food=indian; party_size=8 people; requested_info=reference_number; when=sunday, 8, 12:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking to get some eritrean food in the west part of town.\nChunk 2: Can you see if there are any that serve indian food?\nChunk 3: It is for 8 people.\nChunk 4: The time is sunday, 8, 12:15.\nChunk 5: Please make a booking.\nChunk 6: Sure as long as it's in the same area and price range.\nChunk 7: I need the reference number too please.\nChunk 8: Thank you, that's all I needed today!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=request_info; area+=west. C2 cuisine+=indian. C3 party_size+=8 people. C4 time+=8, 12:15; day+=sunday. C5 goal=booking. C6 goal=modify_constraint. C7 goal=search; requested_info+=reference_number. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=request_info, booking, modify_constraint, search; area=west; food=indian; party_size=8 people; requested_info=reference_number; when=sunday, 8, 12:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking to get some eritrean food in the west part of town.\nChunk 2: Can you see if there are any that serve indian food?\nChunk 3: It is for 8 people.\nChunk 4: The time is sunday, 8, 12:15.\nChunk 5: Please make a booking.\nChunk 6: Sure as long as it's in the same area and price range.\nChunk 7: I need the reference number too please.\nChunk 8: Thank you, that's all I needed today!", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is request info; area: west. Next, cuisine: indian. Next, party size: 8 people. Next, time: 8; day: sunday. Next, the goal is booking. Next, the goal is modify constraint. Finally, the goal is search; requested information: reference_number.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is search. area: west.; cuisine: indian.; party size: 8 people.; time: 8; day: sunday.; requested information: reference_number..", "trace": "C1 domain=restaurant; goal=request_info; area+=west. C2 cuisine+=indian. C3 party_size+=8 people. C4 time+=8, 12:15; day+=sunday. C5 goal=booking. C6 goal=modify_constraint. C7 goal=search; requested_info+=reference_number. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking to get some eritrean food in the west part of town.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is request info; area: west..", "trace": "domain=restaurant; goal=request_info; area+=west."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you see if there are any that serve indian food?", "streaming_reasoning": "As more information arrives, cuisine: indian..", "trace": "cuisine+=indian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 8 people.", "streaming_reasoning": "As more information arrives, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is sunday, 8, 12:15.", "streaming_reasoning": "As more information arrives, time: 8; day: sunday..", "trace": "time+=8, 12:15; day+=sunday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Sure as long as it's in the same area and price range.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need the reference number too please.", "streaming_reasoning": "As more information arrives, the goal is search; requested information: reference_number..", "trace": "goal=search; requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you, that's all I needed today!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is west; cuisine is indian; party size is 8 people; requested information is reference_number; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info, booking, modify_constraint, search; area=west; food=indian; party_size=8 people; requested_info=reference_number; when=sunday, 8, 12:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002589", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could I get the phone number, postcode, and the area that The Cost of Clare Hall is located in, please Okay great.\nChunk 2: I'd also like to find a guesthouse that has a 4 star rating.\nChunk 3: I need a hotel that's cheap with free parking.\nChunk 4: That would work, can you please book it for 1 person for 5 nights starting from Monday?\nChunk 5: Four nights would work Great Thank you.\nChunk 6: That's all I need.", "streaming_reasoning": "C1 goal=request_info; requested_info+=phone, postcode, price. C2 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars; destination+=find a guesthouse that has a 4 star ratin. C3 price+=cheap; hotel_type+=hotel; amenities+=parking, free parking. C4 goal=booking; time+=1, 5; day+=monday; stay_length+=5 nights. C5 intent=context_update. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=request_info, search, booking; price=cheap; stay_length=5 nights; stars=4 stars; amenities=parking, free parking; destination=find a guesthouse that has a 4 star ratin; requested_info=phone, postcode, price; when=monday, 1, 5; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Could I get the phone number, postcode, and the area that The Cost of Clare Hall is located in, please Okay great.\nChunk 2: I'd also like to find a guesthouse that has a 4 star rating.\nChunk 3: I need a hotel that's cheap with free parking.\nChunk 4: That would work, can you please book it for 1 person for 5 nights starting from Monday?\nChunk 5: Four nights would work Great Thank you.\nChunk 6: That's all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=phone, postcode, price. C2 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars; destination+=find a guesthouse that has a 4 star ratin. C3 price+=cheap; hotel_type+=hotel; amenities+=parking, free parking. C4 goal=booking; time+=1, 5; day+=monday; stay_length+=5 nights. C5 intent=context_update. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info, search, booking; price=cheap; stay_length=5 nights; stars=4 stars; amenities=parking, free parking; destination=find a guesthouse that has a 4 star ratin; requested_info=phone, postcode, price; when=monday, 1, 5; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could I get the phone number, postcode, and the area that The Cost of Clare Hall is located in, please Okay great.\nChunk 2: I'd also like to find a guesthouse that has a 4 star rating.\nChunk 3: I need a hotel that's cheap with free parking.\nChunk 4: That would work, can you please book it for 1 person for 5 nights starting from Monday?\nChunk 5: Four nights would work Great Thank you.\nChunk 6: That's all I need.", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: phone. Next, the topic is hotel; the goal is search; hotel type: guesthouse; star rating: 4 stars; destination: find a guesthouse that has a 4 star ratin. Next, price: cheap; hotel type: hotel; amenities: parking. Next, the goal is booking; time: 1; day: monday; stay length: 5 nights. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking. requested information: phone; hotel type: guesthouse, hotel; star rating: 4 stars; destination: find a guesthouse that has a 4 star ratin.; price: cheap; amenities: parking; time: 1; day: monday; stay length: 5 nights.; intent: context_update..", "trace": "C1 goal=request_info; requested_info+=phone, postcode, price. C2 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars; destination+=find a guesthouse that has a 4 star ratin. C3 price+=cheap; hotel_type+=hotel; amenities+=parking, free parking. C4 goal=booking; time+=1, 5; day+=monday; stay_length+=5 nights. C5 intent=context_update. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Could I get the phone number, postcode, and the area that The Cost of Clare Hall is located in, please Okay great.", "streaming_reasoning": "Initially, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode, price."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd also like to find a guesthouse that has a 4 star rating.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: guesthouse; star rating: 4 stars; destination: find a guesthouse that has a 4 star ratin..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars; destination+=find a guesthouse that has a 4 star ratin."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need a hotel that's cheap with free parking.", "streaming_reasoning": "As more information arrives, price: cheap; hotel type: hotel; amenities: parking.", "trace": "price+=cheap; hotel_type+=hotel; amenities+=parking, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That would work, can you please book it for 1 person for 5 nights starting from Monday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 1; day: monday; stay length: 5 nights..", "trace": "goal=booking; time+=1, 5; day+=monday; stay_length+=5 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Four nights would work Great Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all I need.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: price is cheap; stay length is 5 nights; star rating is 4 stars; amenities is parking; destination is find a guesthouse that has a 4 star ratin; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search, booking; price=cheap; stay_length=5 nights; stars=4 stars; amenities=parking, free parking; destination=find a guesthouse that has a 4 star ratin; requested_info=phone, postcode, price; when=monday, 1, 5; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002590", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a train from broxbourne on Tuesday.\nChunk 2: Travelling to Cambridge, I need to arrive by 14:45.\nChunk 3: No, but I need two tickets Great.\nChunk 4: That's all I need.\nChunk 5: Thanks.", "streaming_reasoning": "C1 domain=train; goal=search; day+=tuesday. C2 time+=14:45; destination+=cambridge. C3 goal=modify_constraint. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search; destination=cambridge; when=tuesday, 14:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a train from broxbourne on Tuesday.\nChunk 2: Travelling to Cambridge, I need to arrive by 14:45.\nChunk 3: No, but I need two tickets Great.\nChunk 4: That's all I need.\nChunk 5: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=tuesday. C2 time+=14:45; destination+=cambridge. C3 goal=modify_constraint. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search; destination=cambridge; when=tuesday, 14:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a train from broxbourne on Tuesday.\nChunk 2: Travelling to Cambridge, I need to arrive by 14:45.\nChunk 3: No, but I need two tickets Great.\nChunk 4: That's all I need.\nChunk 5: Thanks.", "input_token_count": 40, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: tuesday. Next, time: 14:45; destination: cambridge. Finally, the goal is modify constraint.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is modify constraint.. day: tuesday.; time: 14:45; destination: cambridge..", "trace": "C1 domain=train; goal=search; day+=tuesday. C2 time+=14:45; destination+=cambridge. C3 goal=modify_constraint. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a train from broxbourne on Tuesday.", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: tuesday..", "trace": "domain=train; goal=search; day+=tuesday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Travelling to Cambridge, I need to arrive by 14:45.", "streaming_reasoning": "As more information arrives, time: 14:45; destination: cambridge..", "trace": "time+=14:45; destination+=cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, but I need two tickets Great.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That's all I need.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search; destination=cambridge; when=tuesday, 14:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002591", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a guesthouse.\nChunk 2: It should be in the south part of town.\nChunk 3: How about a moderate price range and a star rating of three Yes please.\nChunk 4: Can I get that for 2 nights for 6 people starting on Friday?\nChunk 5: I also need a taxi to commute.\nChunk 6: I need to leave the hotel by 15:30.\nChunk 7: Thank you, That will be all Thank you goodbye.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 area+=south. C3 goal=recommendation; price+=moderate; acceptance=selected_option. C4 goal=request_info; time+=2, 6; day+=friday; party_size+=6 people; stay_length+=2 nights. C5 domain=taxi; destination+=commute. C6 time+=15:30; hotel_type+=hotel; destination+=leave the hotel by 15:30. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, taxi; goal=search, recommendation, request_info; area=south; price=moderate; party_size=6 people; stay_length=2 nights; destination=find a guesthouse, commute, leave the hotel by 15:30; when=friday, 2, 6, 15:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a guesthouse.\nChunk 2: It should be in the south part of town.\nChunk 3: How about a moderate price range and a star rating of three Yes please.\nChunk 4: Can I get that for 2 nights for 6 people starting on Friday?\nChunk 5: I also need a taxi to commute.\nChunk 6: I need to leave the hotel by 15:30.\nChunk 7: Thank you, That will be all Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 area+=south. C3 goal=recommendation; price+=moderate; acceptance=selected_option. C4 goal=request_info; time+=2, 6; day+=friday; party_size+=6 people; stay_length+=2 nights. C5 domain=taxi; destination+=commute. C6 time+=15:30; hotel_type+=hotel; destination+=leave the hotel by 15:30. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, taxi; goal=search, recommendation, request_info; area=south; price=moderate; party_size=6 people; stay_length=2 nights; destination=find a guesthouse, commute, leave the hotel by 15:30; when=friday, 2, 6, 15:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a guesthouse.\nChunk 2: It should be in the south part of town.\nChunk 3: How about a moderate price range and a star rating of three Yes please.\nChunk 4: Can I get that for 2 nights for 6 people starting on Friday?\nChunk 5: I also need a taxi to commute.\nChunk 6: I need to leave the hotel by 15:30.\nChunk 7: Thank you, That will be all Thank you goodbye.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; destination: find a guesthouse. Next, area: south. Next, the goal is recommendation; price: moderate; acceptance: selected_option. Next, the goal is request info; time: 2; day: friday; party size: 6 people; stay length: 2 nights. Next, the topic is taxi; destination: commute. Finally, time: 15:30; hotel type: hotel; destination: leave the hotel by 15:30.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is request info. hotel type: guesthouse, hotel; destination: find a guesthouse., commute., leave the hotel by 15:30.; area: south.; price: moderate; acceptance: selected_option.; time: 2, 15:30; day: friday; party size: 6 people; stay length: 2 nights..", "trace": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 area+=south. C3 goal=recommendation; price+=moderate; acceptance=selected_option. C4 goal=request_info; time+=2, 6; day+=friday; party_size+=6 people; stay_length+=2 nights. C5 domain=taxi; destination+=commute. C6 time+=15:30; hotel_type+=hotel; destination+=leave the hotel by 15:30. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a guesthouse.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; destination: find a guesthouse..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the south part of town.", "streaming_reasoning": "As more information arrives, area: south..", "trace": "area+=south."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about a moderate price range and a star rating of three Yes please.", "streaming_reasoning": "As more information arrives, the goal is recommendation; price: moderate; acceptance: selected_option..", "trace": "goal=recommendation; price+=moderate; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I get that for 2 nights for 6 people starting on Friday?", "streaming_reasoning": "As more information arrives, the goal is request info; time: 2; day: friday; party size: 6 people; stay length: 2 nights..", "trace": "goal=request_info; time+=2, 6; day+=friday; party_size+=6 people; stay_length+=2 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need a taxi to commute.", "streaming_reasoning": "As more information arrives, the topic is taxi; destination: commute..", "trace": "domain=taxi; destination+=commute."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need to leave the hotel by 15:30.", "streaming_reasoning": "As more information arrives, time: 15:30; hotel type: hotel; destination: leave the hotel by 15:30..", "trace": "time+=15:30; hotel_type+=hotel; destination+=leave the hotel by 15:30."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you, That will be all Thank you goodbye.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is south; price is moderate; party size is 6 people; stay length is 2 nights; destination is find a guesthouse; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, taxi; goal=search, recommendation, request_info; area=south; price=moderate; party_size=6 people; stay_length=2 nights; destination=find a guesthouse, commute, leave the hotel by 15:30; when=friday, 2, 6, 15:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002592", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please book it for 4 people at 11:15 on Monday.\nChunk 2: Yes, can you tell me some tourist places in town that are in the same area?\nChunk 3: As long as it is in the same area it doesn't matter, please recommend one.\nChunk 4: I want its postcode and entrance fee as well.\nChunk 5: Thank you very much.\nChunk 6: Actually, can you also reserve a taxi for me?\nChunk 7: I need to leave the church for lunch at the restaurant before the booked time.\nChunk 8: It has been a pleasure talking to you.\nChunk 9: You have helped me get all I need.\nChunk 10: Thank you and goodbye.", "streaming_reasoning": "C1 goal=confirm_booking; time+=4, 11:15; day+=monday; party_size+=4 people; goal=confirm_booking. C2 goal=request_info; goal=confirm_booking. C3 goal=recommendation. C4 goal=search; requested_info+=postcode, entrance_fee. C5 [SKIP: thanks_only]. C6 domain=taxi. C7 domain=restaurant; destination+=leave the church for lunch at the restaur. C8 destination+=you. C9 intent=context_update. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi, restaurant; goal=booking, confirm_booking, modify_constraint, request_info, recommendation, search; party_size=4 people; destination=leave the church for lunch at the restaur, you; requested_info=postcode, entrance_fee; when=monday, 4, 11:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please book it for 4 people at 11:15 on Monday.\nChunk 2: Yes, can you tell me some tourist places in town that are in the same area?\nChunk 3: As long as it is in the same area it doesn't matter, please recommend one.\nChunk 4: I want its postcode and entrance fee as well.\nChunk 5: Thank you very much.\nChunk 6: Actually, can you also reserve a taxi for me?\nChunk 7: I need to leave the church for lunch at the restaurant before the booked time.\nChunk 8: It has been a pleasure talking to you.\nChunk 9: You have helped me get all I need.\nChunk 10: Thank you and goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=confirm_booking; time+=4, 11:15; day+=monday; party_size+=4 people; goal=confirm_booking. C2 goal=request_info; goal=confirm_booking. C3 goal=recommendation. C4 goal=search; requested_info+=postcode, entrance_fee. C5 [SKIP: thanks_only]. C6 domain=taxi. C7 domain=restaurant; destination+=leave the church for lunch at the restaur. C8 destination+=you. C9 intent=context_update. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi, restaurant; goal=booking, confirm_booking, modify_constraint, request_info, recommendation, search; party_size=4 people; destination=leave the church for lunch at the restaur, you; requested_info=postcode, entrance_fee; when=monday, 4, 11:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please book it for 4 people at 11:15 on Monday.\nChunk 2: Yes, can you tell me some tourist places in town that are in the same area?\nChunk 3: As long as it is in the same area it doesn't matter, please recommend one.\nChunk 4: I want its postcode and entrance fee as well.\nChunk 5: Thank you very much.\nChunk 6: Actually, can you also reserve a taxi for me?\nChunk 7: I need to leave the church for lunch at the restaurant before the booked time.\nChunk 8: It has been a pleasure talking to you.\nChunk 9: You have helped me get all I need.\nChunk 10: Thank you and goodbye.", "input_token_count": 120, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is confirm booking.; time: 4; day: monday; party size: 4 people. Next, the goal is confirm booking. Next, the goal is recommendation. Next, the goal is search; requested information: postcode. Next, the topic is taxi. Next, the topic is restaurant; destination: leave the church for lunch at the restaur. Next, destination: you. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is search. time: 4; day: monday; party size: 4 people; requested information: postcode; destination: leave the church for lunch at the restaur., you.; intent: context_update..", "trace": "C1 goal=confirm_booking; time+=4, 11:15; day+=monday; party_size+=4 people; goal=confirm_booking. C2 goal=request_info; goal=confirm_booking. C3 goal=recommendation. C4 goal=search; requested_info+=postcode, entrance_fee. C5 [SKIP: thanks_only]. C6 domain=taxi. C7 domain=restaurant; destination+=leave the church for lunch at the restaur. C8 destination+=you. C9 intent=context_update. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please book it for 4 people at 11:15 on Monday.", "streaming_reasoning": "Initially, the goal is confirm booking.; time: 4; day: monday; party size: 4 people.", "trace": "goal=confirm_booking; time+=4, 11:15; day+=monday; party_size+=4 people; goal=confirm_booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, can you tell me some tourist places in town that are in the same area?", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=request_info; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "As long as it is in the same area it doesn't matter, please recommend one.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want its postcode and entrance fee as well.", "streaming_reasoning": "As more information arrives, the goal is search; requested information: postcode.", "trace": "goal=search; requested_info+=postcode, entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Actually, can you also reserve a taxi for me?", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need to leave the church for lunch at the restaurant before the booked time.", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: leave the church for lunch at the restaur..", "trace": "domain=restaurant; destination+=leave the church for lunch at the restaur."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "It has been a pleasure talking to you.", "streaming_reasoning": "As more information arrives, destination: you..", "trace": "destination+=you."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "You have helped me get all I need.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you and goodbye.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of booking. Key information: party size is 4 people; destination is leave the church for lunch at the restaur; requested information is postcode; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, restaurant; goal=booking, confirm_booking, modify_constraint, request_info, recommendation, search; party_size=4 people; destination=leave the church for lunch at the restaur, you; requested_info=postcode, entrance_fee; when=monday, 4, 11:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002593", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm flexible on the area but I really want a hotel instead of a guesthouse.\nChunk 2: And I would like something with 4 stars.\nChunk 3: Do either of them have free parking?\nChunk 4: I would like to book one of those for 2 nights please.\nChunk 5: 7 people on the same night.\nChunk 6: Sure, try just 1 night.\nChunk 7: Yeah that works for me.\nChunk 8: It's also all I needed for today.\nChunk 9: Thanks!", "streaming_reasoning": "C1 domain=hotel; goal=compare_alternative; hotel_type+=guesthouse, hotel. C2 stars+=4 stars. C3 amenities+=parking, free parking. C4 goal=booking; stay_length+=2 nights. C5 party_size+=7 people. C6 stay_length+=1 nights. C7 goal=confirm_booking. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, compare_alternative, booking; party_size=7 people; stay_length=2 nights, 1 nights; stars=4 stars; amenities=parking, free parking; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm flexible on the area but I really want a hotel instead of a guesthouse.\nChunk 2: And I would like something with 4 stars.\nChunk 3: Do either of them have free parking?\nChunk 4: I would like to book one of those for 2 nights please.\nChunk 5: 7 people on the same night.\nChunk 6: Sure, try just 1 night.\nChunk 7: Yeah that works for me.\nChunk 8: It's also all I needed for today.\nChunk 9: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=compare_alternative; hotel_type+=guesthouse, hotel. C2 stars+=4 stars. C3 amenities+=parking, free parking. C4 goal=booking; stay_length+=2 nights. C5 party_size+=7 people. C6 stay_length+=1 nights. C7 goal=confirm_booking. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, compare_alternative, booking; party_size=7 people; stay_length=2 nights, 1 nights; stars=4 stars; amenities=parking, free parking; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm flexible on the area but I really want a hotel instead of a guesthouse.\nChunk 2: And I would like something with 4 stars.\nChunk 3: Do either of them have free parking?\nChunk 4: I would like to book one of those for 2 nights please.\nChunk 5: 7 people on the same night.\nChunk 6: Sure, try just 1 night.\nChunk 7: Yeah that works for me.\nChunk 8: It's also all I needed for today.\nChunk 9: Thanks!", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is compare alternative; hotel type: guesthouse. Next, star rating: 4 stars. Next, amenities: parking. Next, the goal is booking; stay length: 2 nights. Next, party size: 7 people. Next, stay length: 1 nights. Finally, the goal is confirm booking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is confirm booking.. hotel type: guesthouse; star rating: 4 stars.; amenities: parking; stay length: 2 nights., 1 nights.; party size: 7 people..", "trace": "C1 domain=hotel; goal=compare_alternative; hotel_type+=guesthouse, hotel. C2 stars+=4 stars. C3 amenities+=parking, free parking. C4 goal=booking; stay_length+=2 nights. C5 party_size+=7 people. C6 stay_length+=1 nights. C7 goal=confirm_booking. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm flexible on the area but I really want a hotel instead of a guesthouse.", "streaming_reasoning": "Initially, the topic is hotel; the goal is compare alternative; hotel type: guesthouse.", "trace": "domain=hotel; goal=compare_alternative; hotel_type+=guesthouse, hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "And I would like something with 4 stars.", "streaming_reasoning": "As more information arrives, star rating: 4 stars..", "trace": "stars+=4 stars."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Do either of them have free parking?", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like to book one of those for 2 nights please.", "streaming_reasoning": "As more information arrives, the goal is booking; stay length: 2 nights..", "trace": "goal=booking; stay_length+=2 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "7 people on the same night.", "streaming_reasoning": "As more information arrives, party size: 7 people..", "trace": "party_size+=7 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Sure, try just 1 night.", "streaming_reasoning": "As more information arrives, stay length: 1 nights..", "trace": "stay_length+=1 nights."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yeah that works for me.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "It's also all I needed for today.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 7 people; stay length is 2 nights; star rating is 4 stars; amenities is parking. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, compare_alternative, booking; party_size=7 people; stay_length=2 nights, 1 nights; stars=4 stars; amenities=parking, free parking; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002594", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant serving mediterranean food.\nChunk 2: Is there another venue?\nChunk 3: What is the address and phone number Thank you, goodbye.\nChunk 4: I don't care about the price Thank you goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 goal=compare_alternative. C3 goal=request_info; requested_info+=address, phone. C4 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, compare_alternative, request_info; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant serving mediterranean food.\nChunk 2: Is there another venue?\nChunk 3: What is the address and phone number Thank you, goodbye.\nChunk 4: I don't care about the price Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 goal=compare_alternative. C3 goal=request_info; requested_info+=address, phone. C4 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, compare_alternative, request_info; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant serving mediterranean food.\nChunk 2: Is there another venue?\nChunk 3: What is the address and phone number Thank you, goodbye.\nChunk 4: I don't care about the price Thank you goodbye.", "input_token_count": 40, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, the goal is compare alternative. Next, the goal is request info; requested information: address. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is request info. requested information: address; intent: context_update..", "trace": "C1 domain=restaurant; goal=search. C2 goal=compare_alternative. C3 goal=request_info; requested_info+=address, phone. C4 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant serving mediterranean food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there another venue?", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the address and phone number Thank you, goodbye.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't care about the price Thank you goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, compare_alternative, request_info; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002595", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a restaurant in anatolia.\nChunk 2: Yes.\nChunk 3: I need a reservation for 8 people please.\nChunk 4: It is for 8 people.\nChunk 5: The time is tuesday, friday, 8, 13:00.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: No that was it, thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant in anatolia. C2 [SKIP: acknowledgement_only]. C3 goal=booking; party_size+=8 people. C4 [SKIP: repeated_information]. C5 time+=8, 13:00; day+=tuesday, friday. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 goal=modify_constraint.", "deep_reasoning": "Need domain=restaurant; goal=search, booking, request_info; party_size=8 people; destination=find a restaurant in anatolia; requested_info=reference_number; when=tuesday, friday, 8, 13:00.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to find a restaurant in anatolia.\nChunk 2: Yes.\nChunk 3: I need a reservation for 8 people please.\nChunk 4: It is for 8 people.\nChunk 5: The time is tuesday, friday, 8, 13:00.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: No that was it, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant in anatolia. C2 [SKIP: acknowledgement_only]. C3 goal=booking; party_size+=8 people. C4 [SKIP: repeated_information]. C5 time+=8, 13:00; day+=tuesday, friday. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 goal=modify_constraint.\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, request_info; party_size=8 people; destination=find a restaurant in anatolia; requested_info=reference_number; when=tuesday, friday, 8, 13:00.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a restaurant in anatolia.\nChunk 2: Yes.\nChunk 3: I need a reservation for 8 people please.\nChunk 4: It is for 8 people.\nChunk 5: The time is tuesday, friday, 8, 13:00.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: No that was it, thank you.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant in anatolia. Next, the goal is booking; party size: 8 people. Next, time: 8; day: tuesday. Next, intent: context_update. Next, the goal is request info; requested information: reference_number. Finally, the goal is modify constraint.  Some chunks were skipped because they contained acknowledgement_only or repeated_information. In summary, The overall topic is restaurant. the goal is modify constraint.. destination: find a restaurant in anatolia.; party size: 8 people.; time: 8; day: tuesday; intent: context_update.; requested information: reference_number..", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant in anatolia. C2 [SKIP: acknowledgement_only]. C3 goal=booking; party_size+=8 people. C4 [SKIP: repeated_information]. C5 time+=8, 13:00; day+=tuesday, friday. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to find a restaurant in anatolia.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant in anatolia..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant in anatolia."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes.", "streaming_reasoning": "The content at C2 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need a reservation for 8 people please.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 8 people..", "trace": "goal=booking; party_size+=8 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It is for 8 people.", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is tuesday, friday, 8, 13:00.", "streaming_reasoning": "As more information arrives, time: 8; day: tuesday.", "trace": "time+=8, 13:00; day+=tuesday, friday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No that was it, thank you.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 8 people; destination is find a restaurant in anatolia; requested information is reference_number; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, request_info; party_size=8 people; destination=find a restaurant in anatolia; requested_info=reference_number; when=tuesday, friday, 8, 13:00."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002597", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I do not want to stay in a guesthouse.\nChunk 2: I want to stay in a hotel please.\nChunk 3: I want to find a guesthouse.\nChunk 4: It should be in the centre part of town.\nChunk 5: Is there a possibly a hotel instead then?\nChunk 6: Do they have free parking?\nChunk 7: No, but can you give me the post code, please?\nChunk 8: Nope, that's it, thanks for your help!", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=stay in a guesthouse. C2 hotel_type+=hotel; destination+=stay in a hotel please. C3 destination+=find a guesthouse. C4 area+=centre. C5 goal=compare_alternative. C6 amenities+=parking, free parking. C7 goal=request_info; requested_info+=postcode. C8 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=search, compare_alternative, request_info; area=centre; amenities=parking, free parking; destination=stay in a guesthouse, stay in a hotel please, find a guesthouse; requested_info=postcode.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I do not want to stay in a guesthouse.\nChunk 2: I want to stay in a hotel please.\nChunk 3: I want to find a guesthouse.\nChunk 4: It should be in the centre part of town.\nChunk 5: Is there a possibly a hotel instead then?\nChunk 6: Do they have free parking?\nChunk 7: No, but can you give me the post code, please?\nChunk 8: Nope, that's it, thanks for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=stay in a guesthouse. C2 hotel_type+=hotel; destination+=stay in a hotel please. C3 destination+=find a guesthouse. C4 area+=centre. C5 goal=compare_alternative. C6 amenities+=parking, free parking. C7 goal=request_info; requested_info+=postcode. C8 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=search, compare_alternative, request_info; area=centre; amenities=parking, free parking; destination=stay in a guesthouse, stay in a hotel please, find a guesthouse; requested_info=postcode.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I do not want to stay in a guesthouse.\nChunk 2: I want to stay in a hotel please.\nChunk 3: I want to find a guesthouse.\nChunk 4: It should be in the centre part of town.\nChunk 5: Is there a possibly a hotel instead then?\nChunk 6: Do they have free parking?\nChunk 7: No, but can you give me the post code, please?\nChunk 8: Nope, that's it, thanks for your help!", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; destination: stay in a guesthouse. Next, hotel type: hotel; destination: stay in a hotel please. Next, destination: find a guesthouse. Next, area: centre. Next, the goal is compare alternative. Next, amenities: parking. Next, the goal is request info; requested information: postcode. Finally, intent: context_update. In summary, The overall topic is hotel. the goal is request info. hotel type: guesthouse, hotel; destination: stay in a guesthouse., stay in a hotel please., find a guesthouse.; area: centre.; amenities: parking; requested information: postcode.; intent: context_update..", "trace": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=stay in a guesthouse. C2 hotel_type+=hotel; destination+=stay in a hotel please. C3 destination+=find a guesthouse. C4 area+=centre. C5 goal=compare_alternative. C6 amenities+=parking, free parking. C7 goal=request_info; requested_info+=postcode. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I do not want to stay in a guesthouse.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; destination: stay in a guesthouse..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; destination+=stay in a guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to stay in a hotel please.", "streaming_reasoning": "As more information arrives, hotel type: hotel; destination: stay in a hotel please..", "trace": "hotel_type+=hotel; destination+=stay in a hotel please."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a guesthouse.", "streaming_reasoning": "As more information arrives, destination: find a guesthouse..", "trace": "destination+=find a guesthouse."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Is there a possibly a hotel instead then?", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Do they have free parking?", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, but can you give me the post code, please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Nope, that's it, thanks for your help!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; amenities is parking; destination is stay in a guesthouse; requested information is postcode.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=search, compare_alternative, request_info; area=centre; amenities=parking, free parking; destination=stay in a guesthouse, stay in a hotel please, find a guesthouse; requested_info=postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002598", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there no international places to dine in the area?\nChunk 2: Anything other than British food in the area?\nChunk 3: It is for 5 people.\nChunk 4: The time is tuesday, 13:45, 5.\nChunk 5: Please make a booking.\nChunk 6: I also need a taxi to take me between the two places please Thank you!\nChunk 7: From the hotel to the restaurant, please.\nChunk 8: by the restaurant booked time Awesome.\nChunk 9: Thanks for all of your help.\nChunk 10: I have everything I need now.", "streaming_reasoning": "C1 destination+=dine in the area. C2 domain=restaurant; cuisine+=british. C3 party_size+=5 people. C4 time+=13:45, 5; day+=tuesday. C5 goal=booking. C6 domain=taxi; goal=search; destination+=take me between the two places please tha. C7 domain=hotel; hotel_type+=hotel; destination+=the restaurant; departure+=the hotel. C8 intent=context_update. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi, hotel; goal=booking, search; food=british; party_size=5 people; destination=dine in the area, take me between the two places please tha, the restaurant; departure=the hotel; when=tuesday, 13:45, 5; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Are there no international places to dine in the area?\nChunk 2: Anything other than British food in the area?\nChunk 3: It is for 5 people.\nChunk 4: The time is tuesday, 13:45, 5.\nChunk 5: Please make a booking.\nChunk 6: I also need a taxi to take me between the two places please Thank you!\nChunk 7: From the hotel to the restaurant, please.\nChunk 8: by the restaurant booked time Awesome.\nChunk 9: Thanks for all of your help.\nChunk 10: I have everything I need now."}, {"role": "assistant", "content": "Streaming reasoning: C1 destination+=dine in the area. C2 domain=restaurant; cuisine+=british. C3 party_size+=5 people. C4 time+=13:45, 5; day+=tuesday. C5 goal=booking. C6 domain=taxi; goal=search; destination+=take me between the two places please tha. C7 domain=hotel; hotel_type+=hotel; destination+=the restaurant; departure+=the hotel. C8 intent=context_update. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi, hotel; goal=booking, search; food=british; party_size=5 people; destination=dine in the area, take me between the two places please tha, the restaurant; departure=the hotel; when=tuesday, 13:45, 5; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there no international places to dine in the area?\nChunk 2: Anything other than British food in the area?\nChunk 3: It is for 5 people.\nChunk 4: The time is tuesday, 13:45, 5.\nChunk 5: Please make a booking.\nChunk 6: I also need a taxi to take me between the two places please Thank you!\nChunk 7: From the hotel to the restaurant, please.\nChunk 8: by the restaurant booked time Awesome.\nChunk 9: Thanks for all of your help.\nChunk 10: I have everything I need now.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, destination: dine in the area. Next, the topic is restaurant; cuisine: british. Next, party size: 5 people. Next, time: 13:45; day: tuesday. Next, the goal is booking. Next, the topic is taxi; the goal is search; destination: take me between the two places please tha. Next, the topic is hotel; hotel type: hotel; destination: the restaurant; departure point: the hotel. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is search. destination: dine in the area., take me between the two places please tha., the restaurant; cuisine: british.; party size: 5 people.; time: 13:45; day: tuesday.; hotel type: hotel; departure point: the hotel.; intent: context_update..", "trace": "C1 destination+=dine in the area. C2 domain=restaurant; cuisine+=british. C3 party_size+=5 people. C4 time+=13:45, 5; day+=tuesday. C5 goal=booking. C6 domain=taxi; goal=search; destination+=take me between the two places please tha. C7 domain=hotel; hotel_type+=hotel; destination+=the restaurant; departure+=the hotel. C8 intent=context_update. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Are there no international places to dine in the area?", "streaming_reasoning": "Initially, destination: dine in the area..", "trace": "destination+=dine in the area."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Anything other than British food in the area?", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: british..", "trace": "domain=restaurant; cuisine+=british."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 5 people.", "streaming_reasoning": "As more information arrives, party size: 5 people..", "trace": "party_size+=5 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is tuesday, 13:45, 5.", "streaming_reasoning": "As more information arrives, time: 13:45; day: tuesday..", "trace": "time+=13:45, 5; day+=tuesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need a taxi to take me between the two places please Thank you!", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is search; destination: take me between the two places please tha..", "trace": "domain=taxi; goal=search; destination+=take me between the two places please tha."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "From the hotel to the restaurant, please.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: the restaurant; departure point: the hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=the restaurant; departure+=the hotel."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "by the restaurant booked time Awesome.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks for all of your help.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "I have everything I need now.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: cuisine is british; party size is 5 people; destination is dine in the area; departure point is the hotel; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi, hotel; goal=booking, search; food=british; party_size=5 people; destination=dine in the area, take me between the two places please tha, the restaurant; departure=the hotel; when=tuesday, 13:45, 5; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002599", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That sounds fantastic Thank you!\nChunk 2: I want to find a moderate restaurant.\nChunk 3: It should be in the centre part of town.\nChunk 4: I also need the entrance fee.\nChunk 5: I also need the price.\nChunk 6: Do they serve Christmas food?\nChunk 7: Not in British food.\nChunk 8: Are there any that serve Italian food?\nChunk 9: Could you just give me the number for pizza express That is all.\nChunk 10: Thanks for your help.", "streaming_reasoning": "C1 intent=context_update. C2 domain=restaurant; goal=search; price+=moderate; destination+=find a moderate restaurant. C3 area+=centre. C4 goal=request_info; requested_info+=entrance_fee. C5 requested_info+=price. C6 goal=request_info. C7 cuisine+=british. C8 cuisine+=italian. C9 intent=context_update. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=centre; food=british, italian; price=moderate; destination=find a moderate restaurant; requested_info=entrance_fee, price; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: That sounds fantastic Thank you!\nChunk 2: I want to find a moderate restaurant.\nChunk 3: It should be in the centre part of town.\nChunk 4: I also need the entrance fee.\nChunk 5: I also need the price.\nChunk 6: Do they serve Christmas food?\nChunk 7: Not in British food.\nChunk 8: Are there any that serve Italian food?\nChunk 9: Could you just give me the number for pizza express That is all.\nChunk 10: Thanks for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 domain=restaurant; goal=search; price+=moderate; destination+=find a moderate restaurant. C3 area+=centre. C4 goal=request_info; requested_info+=entrance_fee. C5 requested_info+=price. C6 goal=request_info. C7 cuisine+=british. C8 cuisine+=italian. C9 intent=context_update. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=centre; food=british, italian; price=moderate; destination=find a moderate restaurant; requested_info=entrance_fee, price; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That sounds fantastic Thank you!\nChunk 2: I want to find a moderate restaurant.\nChunk 3: It should be in the centre part of town.\nChunk 4: I also need the entrance fee.\nChunk 5: I also need the price.\nChunk 6: Do they serve Christmas food?\nChunk 7: Not in British food.\nChunk 8: Are there any that serve Italian food?\nChunk 9: Could you just give me the number for pizza express That is all.\nChunk 10: Thanks for your help.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the topic is restaurant; the goal is search; price: moderate; destination: find a moderate restaurant. Next, area: centre. Next, the goal is request info; requested information: entrance_fee. Next, requested information: price. Next, the goal is request info. Next, cuisine: british. Next, cuisine: italian. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info.. intent: context_update.; price: moderate; destination: find a moderate restaurant.; area: centre.; requested information: entrance_fee., price.; cuisine: british., italian..", "trace": "C1 intent=context_update. C2 domain=restaurant; goal=search; price+=moderate; destination+=find a moderate restaurant. C3 area+=centre. C4 goal=request_info; requested_info+=entrance_fee. C5 requested_info+=price. C6 goal=request_info. C7 cuisine+=british. C8 cuisine+=italian. C9 intent=context_update. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "That sounds fantastic Thank you!", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to find a moderate restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; price: moderate; destination: find a moderate restaurant..", "trace": "domain=restaurant; goal=search; price+=moderate; destination+=find a moderate restaurant."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the entrance fee.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Do they serve Christmas food?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Not in British food.", "streaming_reasoning": "As more information arrives, cuisine: british..", "trace": "cuisine+=british."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Are there any that serve Italian food?", "streaming_reasoning": "As more information arrives, cuisine: italian..", "trace": "cuisine+=italian."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Could you just give me the number for pizza express That is all.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thanks for your help.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is british; price is moderate; destination is find a moderate restaurant; requested information is entrance_fee. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=centre; food=british, italian; price=moderate; destination=find a moderate restaurant; requested_info=entrance_fee, price; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003266", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you for telling me about this.\nChunk 2: What should I do here?\nChunk 3: First, change your shoes to slippers.\nChunk 4: Then walk up to the changing room to get prepared for a shower.\nChunk 5: OK.\nChunk 6: How about after the shower?\nChunk 7: After the shower, step into the washroom with birch switches, dip them in the warm water and briskly whisk them over your skin That sounds comfortable.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=first, change. C4 casual_comment=then, walk. C5 [SKIP: backchannel_only]. C6 question=true. C7 casual_comment=shower, step.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you for telling me about this.\nChunk 2: What should I do here?\nChunk 3: First, change your shoes to slippers.\nChunk 4: Then walk up to the changing room to get prepared for a shower.\nChunk 5: OK.\nChunk 6: How about after the shower?\nChunk 7: After the shower, step into the washroom with birch switches, dip them in the warm water and briskly whisk them over your skin That sounds comfortable."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=first, change. C4 casual_comment=then, walk. C5 [SKIP: backchannel_only]. C6 question=true. C7 casual_comment=shower, step.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you for telling me about this.\nChunk 2: What should I do here?\nChunk 3: First, change your shoes to slippers.\nChunk 4: Then walk up to the changing room to get prepared for a shower.\nChunk 5: OK.\nChunk 6: How about after the shower?\nChunk 7: After the shower, step into the washroom with birch switches, dip them in the warm water and briskly whisk them over your skin That sounds comfortable.", "input_token_count": 77, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on first. Next, the user comments on then. Next, the input provides additional context about question=true. Finally, the user comments on shower.  Some chunks were skipped because they contained backchannel_only or thanks_only.", "trace": "C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=first, change. C4 casual_comment=then, walk. C5 [SKIP: backchannel_only]. C6 question=true. C7 casual_comment=shower, step.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you for telling me about this.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What should I do here?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "First, change your shoes to slippers.", "streaming_reasoning": "As more information arrives, the user comments on first.", "trace": "casual_comment=first, change."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Then walk up to the changing room to get prepared for a shower.", "streaming_reasoning": "As more information arrives, the user comments on then.", "trace": "casual_comment=then, walk."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "OK.", "streaming_reasoning": "The content at C5 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "How about after the shower?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "After the shower, step into the washroom with birch switches, dip them in the warm water and briskly whisk them over your skin That sounds comfortable.", "streaming_reasoning": "Finally, the user comments on shower.", "trace": "casual_comment=shower, step."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002600", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I really like the north.\nChunk 2: It seems much more peaceful.\nChunk 3: Is it a 4 star?\nChunk 4: If so, can you give me the phone number?\nChunk 5: Either way is fine with me.\nChunk 6: What's the phone number?\nChunk 7: I also would like to find Chinese food in the north.\nChunk 8: no, could you just reserve a table for 4 at 11:45 thurs and I'll need the ref # too please.\nChunk 9: No, that will be all Thank you!", "streaming_reasoning": "C1 area+=north. C2 intent=context_update. C3 stars+=4 stars. C4 goal=request_info; requested_info+=phone. C5 intent=context_update. C6 goal=request_info. C7 domain=restaurant; goal=search; cuisine+=chinese; destination+=find chinese food in the north. C8 goal=booking; time+=4, 11:45. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=request_info, search, booking; area=north; food=chinese; stars=4 stars; destination=find chinese food in the north; requested_info=phone; when=4, 11:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I really like the north.\nChunk 2: It seems much more peaceful.\nChunk 3: Is it a 4 star?\nChunk 4: If so, can you give me the phone number?\nChunk 5: Either way is fine with me.\nChunk 6: What's the phone number?\nChunk 7: I also would like to find Chinese food in the north.\nChunk 8: no, could you just reserve a table for 4 at 11:45 thurs and I'll need the ref # too please.\nChunk 9: No, that will be all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=north. C2 intent=context_update. C3 stars+=4 stars. C4 goal=request_info; requested_info+=phone. C5 intent=context_update. C6 goal=request_info. C7 domain=restaurant; goal=search; cuisine+=chinese; destination+=find chinese food in the north. C8 goal=booking; time+=4, 11:45. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=request_info, search, booking; area=north; food=chinese; stars=4 stars; destination=find chinese food in the north; requested_info=phone; when=4, 11:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I really like the north.\nChunk 2: It seems much more peaceful.\nChunk 3: Is it a 4 star?\nChunk 4: If so, can you give me the phone number?\nChunk 5: Either way is fine with me.\nChunk 6: What's the phone number?\nChunk 7: I also would like to find Chinese food in the north.\nChunk 8: no, could you just reserve a table for 4 at 11:45 thurs and I'll need the ref # too please.\nChunk 9: No, that will be all Thank you!", "input_token_count": 90, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: north. Next, intent: context_update. Next, star rating: 4 stars. Next, the goal is request info; requested information: phone. Next, intent: context_update. Next, the goal is request info. Next, the topic is restaurant; the goal is search; cuisine: chinese; destination: find chinese food in the north. Finally, the goal is booking; time: 4.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. area: north.; intent: context_update.; star rating: 4 stars.; requested information: phone.; cuisine: chinese; destination: find chinese food in the north.; time: 4.", "trace": "C1 area+=north. C2 intent=context_update. C3 stars+=4 stars. C4 goal=request_info; requested_info+=phone. C5 intent=context_update. C6 goal=request_info. C7 domain=restaurant; goal=search; cuisine+=chinese; destination+=find chinese food in the north. C8 goal=booking; time+=4, 11:45. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I really like the north.", "streaming_reasoning": "Initially, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It seems much more peaceful.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Is it a 4 star?", "streaming_reasoning": "As more information arrives, star rating: 4 stars..", "trace": "stars+=4 stars."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "If so, can you give me the phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Either way is fine with me.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What's the phone number?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also would like to find Chinese food in the north.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; cuisine: chinese; destination: find chinese food in the north..", "trace": "domain=restaurant; goal=search; cuisine+=chinese; destination+=find chinese food in the north."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "no, could you just reserve a table for 4 at 11:45 thurs and I'll need the ref # too please.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 4.", "trace": "goal=booking; time+=4, 11:45."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No, that will be all Thank you!", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is north; cuisine is chinese; star rating is 4 stars; destination is find chinese food in the north; requested information is phone; timing is 4. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info, search, booking; area=north; food=chinese; stars=4 stars; destination=find chinese food in the north; requested_info=phone; when=4, 11:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002602", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, but I need to book a table for 4 people at 14:30 on monday.\nChunk 2: Where are some places to go on the east side of town?\nChunk 3: Actually, I would like you to make a recommendation for me.\nChunk 4: What's the attraction type?\nChunk 5: I need a taxi to commute to the restaurant by my reserved time from the attraction, and will need the contact number and car type.\nChunk 6: Okay, I think I'd like to do the Caamboats.\nChunk 7: Okay, I think that's all I need.\nChunk 8: Thanks for the help!", "streaming_reasoning": "C1 goal=booking; time+=4, 14:30; day+=monday; party_size+=4 people. C2 area+=east; destination+=go on the east side of town. C3 destination+=make a recommendation for me. C4 domain=attraction; goal=request_info. C5 domain=taxi. C6 destination+=do the caamboats. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, restaurant, taxi; goal=search, booking, request_info; area=east; party_size=4 people; destination=go on the east side of town, make a recommendation for me, do the caamboats; when=monday, 4, 14:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, but I need to book a table for 4 people at 14:30 on monday.\nChunk 2: Where are some places to go on the east side of town?\nChunk 3: Actually, I would like you to make a recommendation for me.\nChunk 4: What's the attraction type?\nChunk 5: I need a taxi to commute to the restaurant by my reserved time from the attraction, and will need the contact number and car type.\nChunk 6: Okay, I think I'd like to do the Caamboats.\nChunk 7: Okay, I think that's all I need.\nChunk 8: Thanks for the help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=4, 14:30; day+=monday; party_size+=4 people. C2 area+=east; destination+=go on the east side of town. C3 destination+=make a recommendation for me. C4 domain=attraction; goal=request_info. C5 domain=taxi. C6 destination+=do the caamboats. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, restaurant, taxi; goal=search, booking, request_info; area=east; party_size=4 people; destination=go on the east side of town, make a recommendation for me, do the caamboats; when=monday, 4, 14:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, but I need to book a table for 4 people at 14:30 on monday.\nChunk 2: Where are some places to go on the east side of town?\nChunk 3: Actually, I would like you to make a recommendation for me.\nChunk 4: What's the attraction type?\nChunk 5: I need a taxi to commute to the restaurant by my reserved time from the attraction, and will need the contact number and car type.\nChunk 6: Okay, I think I'd like to do the Caamboats.\nChunk 7: Okay, I think that's all I need.\nChunk 8: Thanks for the help!", "input_token_count": 104, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 4; day: monday; party size: 4 people. Next, area: east; destination: go on the east side of town. Next, destination: make a recommendation for me. Next, the topic is attraction; the goal is request info. Next, the topic is taxi. Finally, destination: do the caamboats.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi.. the goal is request info.. time: 4; day: monday; party size: 4 people.; area: east; destination: go on the east side of town., make a recommendation for me., do the caamboats..", "trace": "C1 goal=booking; time+=4, 14:30; day+=monday; party_size+=4 people. C2 area+=east; destination+=go on the east side of town. C3 destination+=make a recommendation for me. C4 domain=attraction; goal=request_info. C5 domain=taxi. C6 destination+=do the caamboats. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, but I need to book a table for 4 people at 14:30 on monday.", "streaming_reasoning": "Initially, the goal is booking; time: 4; day: monday; party size: 4 people..", "trace": "goal=booking; time+=4, 14:30; day+=monday; party_size+=4 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Where are some places to go on the east side of town?", "streaming_reasoning": "As more information arrives, area: east; destination: go on the east side of town..", "trace": "area+=east; destination+=go on the east side of town."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Actually, I would like you to make a recommendation for me.", "streaming_reasoning": "As more information arrives, destination: make a recommendation for me..", "trace": "destination+=make a recommendation for me."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What's the attraction type?", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is request info..", "trace": "domain=attraction; goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need a taxi to commute to the restaurant by my reserved time from the attraction, and will need the contact number and car type.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Okay, I think I'd like to do the Caamboats.", "streaming_reasoning": "As more information arrives, destination: do the caamboats..", "trace": "destination+=do the caamboats."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Okay, I think that's all I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks for the help!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is east; party size is 4 people; destination is go on the east side of town; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant, taxi; goal=search, booking, request_info; area=east; party_size=4 people; destination=go on the east side of town, make a recommendation for me, do the caamboats; when=monday, 4, 14:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002603", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I'm looking for a train.\nChunk 2: I need to leave on Wednesday from Norwich.\nChunk 3: I am looking to go to Cambridge.\nChunk 4: i'm leaving after 09:00.\nChunk 5: What is the Price and travel time?\nChunk 6: Ok great, can you book it for me please?\nChunk 7: That will be all, thank you for your help.", "streaming_reasoning": "C1 domain=train; goal=search. C2 day+=wednesday. C3 destination+=go to cambridge. C4 time+=09:00. C5 goal=request_info; requested_info+=travel_time, price. C6 goal=booking. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info, booking; destination=go to cambridge; requested_info=travel_time, price; when=wednesday, 09:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, I'm looking for a train.\nChunk 2: I need to leave on Wednesday from Norwich.\nChunk 3: I am looking to go to Cambridge.\nChunk 4: i'm leaving after 09:00.\nChunk 5: What is the Price and travel time?\nChunk 6: Ok great, can you book it for me please?\nChunk 7: That will be all, thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 day+=wednesday. C3 destination+=go to cambridge. C4 time+=09:00. C5 goal=request_info; requested_info+=travel_time, price. C6 goal=booking. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking; destination=go to cambridge; requested_info=travel_time, price; when=wednesday, 09:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I'm looking for a train.\nChunk 2: I need to leave on Wednesday from Norwich.\nChunk 3: I am looking to go to Cambridge.\nChunk 4: i'm leaving after 09:00.\nChunk 5: What is the Price and travel time?\nChunk 6: Ok great, can you book it for me please?\nChunk 7: That will be all, thank you for your help.", "input_token_count": 65, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, day: wednesday. Next, destination: go to cambridge. Next, time: 09:00. Next, the goal is request info; requested information: travel_time. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is booking.. day: wednesday.; destination: go to cambridge.; time: 09:00.; requested information: travel_time.", "trace": "C1 domain=train; goal=search. C2 day+=wednesday. C3 destination+=go to cambridge. C4 time+=09:00. C5 goal=request_info; requested_info+=travel_time, price. C6 goal=booking. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, I'm looking for a train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to leave on Wednesday from Norwich.", "streaming_reasoning": "As more information arrives, day: wednesday..", "trace": "day+=wednesday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am looking to go to Cambridge.", "streaming_reasoning": "As more information arrives, destination: go to cambridge..", "trace": "destination+=go to cambridge."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "i'm leaving after 09:00.", "streaming_reasoning": "As more information arrives, time: 09:00..", "trace": "time+=09:00."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What is the Price and travel time?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time.", "trace": "goal=request_info; requested_info+=travel_time, price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Ok great, can you book it for me please?", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That will be all, thank you for your help.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is go to cambridge; requested information is travel_time; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking; destination=go to cambridge; requested_info=travel_time, price; when=wednesday, 09:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002604", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi.\nChunk 2: I a looking for a cheap place to stay.\nChunk 3: What can you recommend for me?\nChunk 4: I would like something in the east of the city, I don't care about internet.\nChunk 5: That sounds good, Thank you.\nChunk 6: Yes.\nChunk 7: I need a reservation for 2 people for 4 nights starting on Saturday.\nChunk 8: Sure, can you try just 2 nights, please?\nChunk 9: No that would be all.", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 domain=hotel; goal=search; price+=cheap; destination+=stay. C3 goal=recommendation. C4 area+=east; amenities+=internet. C5 acceptance=selected_option. C6 [SKIP: acknowledgement_only]. C7 goal=booking; time+=2, 4; day+=saturday; party_size+=2 people; stay_length+=4 nights. C8 stay_length+=2 nights. C9 goal=modify_constraint.", "deep_reasoning": "Need domain=hotel; goal=search, recommendation, booking; area=east; price=cheap; party_size=2 people; stay_length=4 nights, 2 nights; amenities=internet; destination=stay; when=saturday, 2, 4.", "answer": "Got it. I will use hotel, east, cheap, 2 people, saturday, 2, 4 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi.\nChunk 2: I a looking for a cheap place to stay.\nChunk 3: What can you recommend for me?\nChunk 4: I would like something in the east of the city, I don't care about internet.\nChunk 5: That sounds good, Thank you.\nChunk 6: Yes.\nChunk 7: I need a reservation for 2 people for 4 nights starting on Saturday.\nChunk 8: Sure, can you try just 2 nights, please?\nChunk 9: No that would be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 domain=hotel; goal=search; price+=cheap; destination+=stay. C3 goal=recommendation. C4 area+=east; amenities+=internet. C5 acceptance=selected_option. C6 [SKIP: acknowledgement_only]. C7 goal=booking; time+=2, 4; day+=saturday; party_size+=2 people; stay_length+=4 nights. C8 stay_length+=2 nights. C9 goal=modify_constraint.\n\nDeep reasoning: Need domain=hotel; goal=search, recommendation, booking; area=east; price=cheap; party_size=2 people; stay_length=4 nights, 2 nights; amenities=internet; destination=stay; when=saturday, 2, 4.\n\nAnswer: Got it. I will use hotel, east, cheap, 2 people, saturday, 2, 4 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi.\nChunk 2: I a looking for a cheap place to stay.\nChunk 3: What can you recommend for me?\nChunk 4: I would like something in the east of the city, I don't care about internet.\nChunk 5: That sounds good, Thank you.\nChunk 6: Yes.\nChunk 7: I need a reservation for 2 people for 4 nights starting on Saturday.\nChunk 8: Sure, can you try just 2 nights, please?\nChunk 9: No that would be all.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: cheap; destination: stay. Next, the goal is recommendation. Next, area: east; amenities: internet. Next, acceptance: selected_option. Next, the goal is booking; time: 2; day: saturday; party size: 2 people; stay length: 4 nights. Next, stay length: 2 nights. Finally, the goal is modify constraint.  Some chunks were skipped because they contained acknowledgement_only or greeting_only. In summary, The overall topic is hotel. the goal is modify constraint.. price: cheap; destination: stay.; area: east; amenities: internet.; acceptance: selected_option.; time: 2; day: saturday; party size: 2 people; stay length: 4 nights., 2 nights..", "trace": "C1 [SKIP: greeting_only]. C2 domain=hotel; goal=search; price+=cheap; destination+=stay. C3 goal=recommendation. C4 area+=east; amenities+=internet. C5 acceptance=selected_option. C6 [SKIP: acknowledgement_only]. C7 goal=booking; time+=2, 4; day+=saturday; party_size+=2 people; stay_length+=4 nights. C8 stay_length+=2 nights. C9 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi.", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I a looking for a cheap place to stay.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; price: cheap; destination: stay..", "trace": "domain=hotel; goal=search; price+=cheap; destination+=stay."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What can you recommend for me?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like something in the east of the city, I don't care about internet.", "streaming_reasoning": "As more information arrives, area: east; amenities: internet..", "trace": "area+=east; amenities+=internet."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That sounds good, Thank you.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes.", "streaming_reasoning": "The content at C6 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need a reservation for 2 people for 4 nights starting on Saturday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 2; day: saturday; party size: 2 people; stay length: 4 nights..", "trace": "goal=booking; time+=2, 4; day+=saturday; party_size+=2 people; stay_length+=4 nights."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Sure, can you try just 2 nights, please?", "streaming_reasoning": "As more information arrives, stay length: 2 nights..", "trace": "stay_length+=2 nights."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No that would be all.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is east; price is cheap; party size is 2 people; stay length is 4 nights; amenities is internet; destination is stay; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use hotel, east, cheap, 2 people, saturday, 2, 4 and move the task forward.", "deep_reasoning_trace": "Need domain=hotel; goal=search, recommendation, booking; area=east; price=cheap; party_size=2 people; stay_length=4 nights, 2 nights; amenities=internet; destination=stay; when=saturday, 2, 4."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003272", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I receive this as a birthday present, but the price tag is still on the skirt though.\nChunk 2: Will that be OK?\nChunk 3: Oh, yes, that will help me a lot.\nChunk 4: Do you have any more skirts in this style?\nChunk 5: I would like to find a size larger I'm sorry.\nChunk 6: I think we're out of this skirt in this color.\nChunk 7: Do you want me to call another one of our store to see if it's available there?\nChunk 8: No, that's all right.\nChunk 9: I'll just look for something else.", "streaming_reasoning": "C1 casual_comment=receive, birthday. C2 question=true. C3 casual_comment=will, help. C4 question=true. C5 preference=true. C6 casual_comment=think, we're. C7 question=true. C8 [SKIP: closing_only]. C9 casual_comment=i'll, look.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, I receive this as a birthday present, but the price tag is still on the skirt though.\nChunk 2: Will that be OK?\nChunk 3: Oh, yes, that will help me a lot.\nChunk 4: Do you have any more skirts in this style?\nChunk 5: I would like to find a size larger I'm sorry.\nChunk 6: I think we're out of this skirt in this color.\nChunk 7: Do you want me to call another one of our store to see if it's available there?\nChunk 8: No, that's all right.\nChunk 9: I'll just look for something else."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=receive, birthday. C2 question=true. C3 casual_comment=will, help. C4 question=true. C5 preference=true. C6 casual_comment=think, we're. C7 question=true. C8 [SKIP: closing_only]. C9 casual_comment=i'll, look.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I receive this as a birthday present, but the price tag is still on the skirt though.\nChunk 2: Will that be OK?\nChunk 3: Oh, yes, that will help me a lot.\nChunk 4: Do you have any more skirts in this style?\nChunk 5: I would like to find a size larger I'm sorry.\nChunk 6: I think we're out of this skirt in this color.\nChunk 7: Do you want me to call another one of our store to see if it's available there?\nChunk 8: No, that's all right.\nChunk 9: I'll just look for something else.", "input_token_count": 104, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the user comments on receive. Next, the input provides additional context about question=true. Next, the user comments on will. Next, the input provides additional context about question=true. Next, preference: true. Next, the user comments on think. Next, the input provides additional context about question=true. Finally, the user comments on i'll.  Some chunks were skipped because they contained closing_only. In summary, preference: true..", "trace": "C1 casual_comment=receive, birthday. C2 question=true. C3 casual_comment=will, help. C4 question=true. C5 preference=true. C6 casual_comment=think, we're. C7 question=true. C8 [SKIP: closing_only]. C9 casual_comment=i'll, look.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, I receive this as a birthday present, but the price tag is still on the skirt though.", "streaming_reasoning": "Initially, the user comments on receive.", "trace": "casual_comment=receive, birthday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Will that be OK?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Oh, yes, that will help me a lot.", "streaming_reasoning": "As more information arrives, the user comments on will.", "trace": "casual_comment=will, help."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Do you have any more skirts in this style?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like to find a size larger I'm sorry.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I think we're out of this skirt in this color.", "streaming_reasoning": "As more information arrives, the user comments on think.", "trace": "casual_comment=think, we're."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Do you want me to call another one of our store to see if it's available there?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, that's all right.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I'll just look for something else.", "streaming_reasoning": "Finally, the user comments on i'll.", "trace": "casual_comment=i'll, look."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002605", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a hospital here in the area.\nChunk 2: can i get thhe phone number and postcode.\nChunk 3: I need the paediatric clinic please.\nChunk 4: Yes, may I please have the post code?\nChunk 5: No, thank you that's all I need for now.", "streaming_reasoning": "C1 domain=hospital; goal=search; destination+=find a hospital here in the area. C2 goal=request_info; requested_info+=phone, postcode. C3 intent=context_update. C4 acceptance=selected_option. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search, request_info; destination=find a hospital here in the area; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to find a hospital here in the area.\nChunk 2: can i get thhe phone number and postcode.\nChunk 3: I need the paediatric clinic please.\nChunk 4: Yes, may I please have the post code?\nChunk 5: No, thank you that's all I need for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search; destination+=find a hospital here in the area. C2 goal=request_info; requested_info+=phone, postcode. C3 intent=context_update. C4 acceptance=selected_option. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; destination=find a hospital here in the area; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a hospital here in the area.\nChunk 2: can i get thhe phone number and postcode.\nChunk 3: I need the paediatric clinic please.\nChunk 4: Yes, may I please have the post code?\nChunk 5: No, thank you that's all I need for now.", "input_token_count": 51, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital here in the area. Next, the goal is request info; requested information: phone. Next, intent: context_update. Finally, acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital. the goal is request info. destination: find a hospital here in the area.; requested information: phone; intent: context_update.; acceptance: selected_option..", "trace": "C1 domain=hospital; goal=search; destination+=find a hospital here in the area. C2 goal=request_info; requested_info+=phone, postcode. C3 intent=context_update. C4 acceptance=selected_option. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to find a hospital here in the area.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital here in the area..", "trace": "domain=hospital; goal=search; destination+=find a hospital here in the area."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "can i get thhe phone number and postcode.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need the paediatric clinic please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, may I please have the post code?", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, thank you that's all I need for now.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: destination is find a hospital here in the area; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; destination=find a hospital here in the area; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002607", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find somewhere in town to go to for entertainment?\nChunk 2: Preferably the town centre.\nChunk 3: No, that's ok How about colleges?\nChunk 4: Can you recommend a good one in the centre of town Yes, please.\nChunk 5: I;m also looking for an expensive place to dine in the same area as the college.\nChunk 6: Can you help me with that?\nChunk 7: If there is a restaurant which serves Indian food, that would be perfect.\nChunk 8: I want to find a restaurant.\nChunk 9: Please make a booking.\nChunk 10: I also need the address.\nChunk 11: I also need the phone.\nChunk 12: I also need the postcode.", "streaming_reasoning": "C1 goal=search; destination+=go to for entertainment. C2 area+=centre. C3 goal=recommendation. C4 goal=confirm_booking; acceptance=selected_option. C5 domain=attraction; goal=modify_constraint; price+=expensive; destination+=dine in the same area as the college. C6 [SKIP: repeated_information]. C7 domain=restaurant; cuisine+=indian; acceptance=selected_option. C8 [SKIP: repeated_information]. C9 goal=booking. C10 goal=request_info; requested_info+=address. C11 requested_info+=phone. C12 requested_info+=postcode.", "deep_reasoning": "Need domain=attraction, restaurant; goal=search, recommendation, confirm_booking, modify_constraint, booking, request_info; area=centre; food=indian; price=expensive; destination=go to for entertainment, dine in the same area as the college; requested_info=address, phone, postcode.", "answer": "I can help with that and include the address, phone, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you help me find somewhere in town to go to for entertainment?\nChunk 2: Preferably the town centre.\nChunk 3: No, that's ok How about colleges?\nChunk 4: Can you recommend a good one in the centre of town Yes, please.\nChunk 5: I;m also looking for an expensive place to dine in the same area as the college.\nChunk 6: Can you help me with that?\nChunk 7: If there is a restaurant which serves Indian food, that would be perfect.\nChunk 8: I want to find a restaurant.\nChunk 9: Please make a booking.\nChunk 10: I also need the address.\nChunk 11: I also need the phone.\nChunk 12: I also need the postcode."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; destination+=go to for entertainment. C2 area+=centre. C3 goal=recommendation. C4 goal=confirm_booking; acceptance=selected_option. C5 domain=attraction; goal=modify_constraint; price+=expensive; destination+=dine in the same area as the college. C6 [SKIP: repeated_information]. C7 domain=restaurant; cuisine+=indian; acceptance=selected_option. C8 [SKIP: repeated_information]. C9 goal=booking. C10 goal=request_info; requested_info+=address. C11 requested_info+=phone. C12 requested_info+=postcode.\n\nDeep reasoning: Need domain=attraction, restaurant; goal=search, recommendation, confirm_booking, modify_constraint, booking, request_info; area=centre; food=indian; price=expensive; destination=go to for entertainment, dine in the same area as the college; requested_info=address, phone, postcode.\n\nAnswer: I can help with that and include the address, phone, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find somewhere in town to go to for entertainment?\nChunk 2: Preferably the town centre.\nChunk 3: No, that's ok How about colleges?\nChunk 4: Can you recommend a good one in the centre of town Yes, please.\nChunk 5: I;m also looking for an expensive place to dine in the same area as the college.\nChunk 6: Can you help me with that?\nChunk 7: If there is a restaurant which serves Indian food, that would be perfect.\nChunk 8: I want to find a restaurant.\nChunk 9: Please make a booking.\nChunk 10: I also need the address.\nChunk 11: I also need the phone.\nChunk 12: I also need the postcode.", "input_token_count": 121, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; destination: go to for entertainment. Next, area: centre. Next, the goal is recommendation. Next, the goal is confirm booking; acceptance: selected_option. Next, the topic is attraction; the goal is modify constraint; price: expensive; destination: dine in the same area as the college. Next, the topic is restaurant; cuisine: indian; acceptance: selected_option. Next, the goal is booking. Next, the goal is request info; requested information: address. Next, requested information: phone. Finally, requested information: postcode.  Some chunks were skipped because they contained repeated_information. In summary, The overall topic is restaurant. the goal is request info. destination: go to for entertainment., dine in the same area as the college.; area: centre.; acceptance: selected_option.; price: expensive; cuisine: indian; requested information: address., phone., postcode..", "trace": "C1 goal=search; destination+=go to for entertainment. C2 area+=centre. C3 goal=recommendation. C4 goal=confirm_booking; acceptance=selected_option. C5 domain=attraction; goal=modify_constraint; price+=expensive; destination+=dine in the same area as the college. C6 [SKIP: repeated_information]. C7 domain=restaurant; cuisine+=indian; acceptance=selected_option. C8 [SKIP: repeated_information]. C9 goal=booking. C10 goal=request_info; requested_info+=address. C11 requested_info+=phone. C12 requested_info+=postcode.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you help me find somewhere in town to go to for entertainment?", "streaming_reasoning": "Initially, the goal is search; destination: go to for entertainment..", "trace": "goal=search; destination+=go to for entertainment."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Preferably the town centre.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, that's ok How about colleges?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you recommend a good one in the centre of town Yes, please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking; acceptance: selected_option..", "trace": "goal=confirm_booking; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I;m also looking for an expensive place to dine in the same area as the college.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is modify constraint; price: expensive; destination: dine in the same area as the college..", "trace": "domain=attraction; goal=modify_constraint; price+=expensive; destination+=dine in the same area as the college."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you help me with that?", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "If there is a restaurant which serves Indian food, that would be perfect.", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: indian; acceptance: selected_option..", "trace": "domain=restaurant; cuisine+=indian; acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "The content at C8 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "I also need the address.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C12", "chunk_index": 11, "observed_text": "I also need the postcode.", "streaming_reasoning": "Finally, requested information: postcode..", "trace": "requested_info+=postcode."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; cuisine is indian; price is expensive; destination is go to for entertainment; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=search, recommendation, confirm_booking, modify_constraint, booking, request_info; area=centre; food=indian; price=expensive; destination=go to for entertainment, dine in the same area as the college; requested_info=address, phone, postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002608", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like something in the centre of town for a moderate price.\nChunk 2: Let's go with Shanghai Family.\nChunk 3: What is the address, phone number and postcode?\nChunk 4: Yes, I'm also looking for a train to London Kings Cross on Thursday.\nChunk 5: I can depart anytime, but need to arrive by 08:15 please.\nChunk 6: What is the arrival time and the train id for a train arriving closest to 08:15 in london kings cross from cambridge on thursday?\nChunk 7: yes, that will work.\nChunk 8: thats all the information i need thanks goodbye.", "streaming_reasoning": "C1 area+=centre; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address, phone, postcode. C4 domain=train; goal=search; day+=thursday; destination+=london kings cross on thursday; acceptance=selected_option. C5 time+=08:15; destination+=arrive by 08:15 please. C6 goal=request_info. C7 acceptance=selected_option. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=request_info, search; area=centre; price=moderate; destination=london kings cross on thursday, arrive by 08:15 please; requested_info=address, phone, postcode; when=thursday, 08:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like something in the centre of town for a moderate price.\nChunk 2: Let's go with Shanghai Family.\nChunk 3: What is the address, phone number and postcode?\nChunk 4: Yes, I'm also looking for a train to London Kings Cross on Thursday.\nChunk 5: I can depart anytime, but need to arrive by 08:15 please.\nChunk 6: What is the arrival time and the train id for a train arriving closest to 08:15 in london kings cross from cambridge on thursday?\nChunk 7: yes, that will work.\nChunk 8: thats all the information i need thanks goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address, phone, postcode. C4 domain=train; goal=search; day+=thursday; destination+=london kings cross on thursday; acceptance=selected_option. C5 time+=08:15; destination+=arrive by 08:15 please. C6 goal=request_info. C7 acceptance=selected_option. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search; area=centre; price=moderate; destination=london kings cross on thursday, arrive by 08:15 please; requested_info=address, phone, postcode; when=thursday, 08:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like something in the centre of town for a moderate price.\nChunk 2: Let's go with Shanghai Family.\nChunk 3: What is the address, phone number and postcode?\nChunk 4: Yes, I'm also looking for a train to London Kings Cross on Thursday.\nChunk 5: I can depart anytime, but need to arrive by 08:15 please.\nChunk 6: What is the arrival time and the train id for a train arriving closest to 08:15 in london kings cross from cambridge on thursday?\nChunk 7: yes, that will work.\nChunk 8: thats all the information i need thanks goodbye.", "input_token_count": 103, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, area: centre; price: moderate. Next, intent: context_update. Next, the goal is request info; requested information: address. Next, the topic is train; the goal is search; day: thursday; destination: london kings cross on thursday; acceptance: selected_option. Next, time: 08:15; destination: arrive by 08:15 please. Next, the goal is request info. Finally, acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info.. area: centre; price: moderate.; intent: context_update.; requested information: address; day: thursday; destination: london kings cross on thursday, arrive by 08:15 please.; acceptance: selected_option.; time: 08:15.", "trace": "C1 area+=centre; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address, phone, postcode. C4 domain=train; goal=search; day+=thursday; destination+=london kings cross on thursday; acceptance=selected_option. C5 time+=08:15; destination+=arrive by 08:15 please. C6 goal=request_info. C7 acceptance=selected_option. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like something in the centre of town for a moderate price.", "streaming_reasoning": "Initially, area: centre; price: moderate..", "trace": "area+=centre; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Let's go with Shanghai Family.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the address, phone number and postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I'm also looking for a train to London Kings Cross on Thursday.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: thursday; destination: london kings cross on thursday; acceptance: selected_option..", "trace": "domain=train; goal=search; day+=thursday; destination+=london kings cross on thursday; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I can depart anytime, but need to arrive by 08:15 please.", "streaming_reasoning": "As more information arrives, time: 08:15; destination: arrive by 08:15 please..", "trace": "time+=08:15; destination+=arrive by 08:15 please."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What is the arrival time and the train id for a train arriving closest to 08:15 in london kings cross from cambridge on thursday?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "yes, that will work.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "thats all the information i need thanks goodbye.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: area is centre; price is moderate; destination is london kings cross on thursday; requested information is address; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search; area=centre; price=moderate; destination=london kings cross on thursday, arrive by 08:15 please; requested_info=address, phone, postcode; when=thursday, 08:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002609", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I think I like it, please book me room for two people for three nights and get me confirmation number.\nChunk 2: Oppss sorry, I thought I had given it to you.\nChunk 3: We'll be checking in on Monday.\nChunk 4: I also need a restaurant reservation.\nChunk 5: I need something moderately priced in the centre.\nChunk 6: What would you recommend?\nChunk 7: The time is monday, 1, 12:30.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number.\nChunk 10: that is it for today.\nChunk 11: have a nice day.", "streaming_reasoning": "C1 domain=hotel; goal=request_info; party_size+=2 people. C2 destination+=you. C3 day+=monday. C4 domain=restaurant. C5 area+=centre; price+=moderate. C6 goal=recommendation. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 requested_info+=reference_number. C10 day+=today. C11 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, booking, request_info, recommendation; area=centre; price=moderate; party_size=2 people; destination=you; requested_info=reference_number; when=monday, today; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I think I like it, please book me room for two people for three nights and get me confirmation number.\nChunk 2: Oppss sorry, I thought I had given it to you.\nChunk 3: We'll be checking in on Monday.\nChunk 4: I also need a restaurant reservation.\nChunk 5: I need something moderately priced in the centre.\nChunk 6: What would you recommend?\nChunk 7: The time is monday, 1, 12:30.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number.\nChunk 10: that is it for today.\nChunk 11: have a nice day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=request_info; party_size+=2 people. C2 destination+=you. C3 day+=monday. C4 domain=restaurant. C5 area+=centre; price+=moderate. C6 goal=recommendation. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 requested_info+=reference_number. C10 day+=today. C11 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, booking, request_info, recommendation; area=centre; price=moderate; party_size=2 people; destination=you; requested_info=reference_number; when=monday, today; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I think I like it, please book me room for two people for three nights and get me confirmation number.\nChunk 2: Oppss sorry, I thought I had given it to you.\nChunk 3: We'll be checking in on Monday.\nChunk 4: I also need a restaurant reservation.\nChunk 5: I need something moderately priced in the centre.\nChunk 6: What would you recommend?\nChunk 7: The time is monday, 1, 12:30.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number.\nChunk 10: that is it for today.\nChunk 11: have a nice day.", "input_token_count": 102, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is request info; party size: 2 people. Next, destination: you. Next, day: monday. Next, the topic is restaurant. Next, area: centre; price: moderate. Next, the goal is recommendation. Next, intent: context_update. Next, requested information: reference_number. Finally, day: today.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is restaurant.. the goal is recommendation.. party size: 2 people.; destination: you.; day: monday., today.; area: centre; price: moderate.; intent: context_update.; requested information: reference_number..", "trace": "C1 domain=hotel; goal=request_info; party_size+=2 people. C2 destination+=you. C3 day+=monday. C4 domain=restaurant. C5 area+=centre; price+=moderate. C6 goal=recommendation. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 requested_info+=reference_number. C10 day+=today. C11 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I think I like it, please book me room for two people for three nights and get me confirmation number.", "streaming_reasoning": "Initially, the topic is hotel; the goal is request info; party size: 2 people..", "trace": "domain=hotel; goal=request_info; party_size+=2 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Oppss sorry, I thought I had given it to you.", "streaming_reasoning": "As more information arrives, destination: you..", "trace": "destination+=you."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "We'll be checking in on Monday.", "streaming_reasoning": "As more information arrives, day: monday..", "trace": "day+=monday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need a restaurant reservation.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need something moderately priced in the centre.", "streaming_reasoning": "As more information arrives, area: centre; price: moderate..", "trace": "area+=centre; price+=moderate."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What would you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is monday, 1, 12:30.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "that is it for today.", "streaming_reasoning": "As more information arrives, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "have a nice day.", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; price is moderate; party size is 2 people; destination is you; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, booking, request_info, recommendation; area=centre; price=moderate; party_size=2 people; destination=you; requested_info=reference_number; when=monday, today; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002610", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please.\nChunk 2: I would like it for 8 people for 5 nights starting from Monday Great!\nChunk 3: I am also looking for a Tuscan restaurant, are there any in the same price range as the bed and breakfast No Tuscan restaurants?\nChunk 4: I also like Italian food.\nChunk 5: Anything in the cheap price range?\nChunk 6: It is for 8 people.\nChunk 7: The time is monday, 8, 18:00.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number.\nChunk 10: Can I please have the reference number?\nChunk 11: No that will be all Thank you.", "streaming_reasoning": "C1 acceptance=selected_option. C2 time+=8, 5; day+=monday; party_size+=8 people; stay_length+=5 nights. C3 domain=restaurant; goal=modify_constraint; price+=same price; amenities+=breakfast. C4 cuisine+=italian. C5 price+=cheap. C6 [SKIP: repeated_information]. C7 [SKIP: repeated_information]. C8 goal=booking. C9 goal=request_info; requested_info+=reference_number. C10 [SKIP: repeated_information]. C11 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, modify_constraint, booking, request_info; food=italian; price=same price, cheap; party_size=8 people; stay_length=5 nights; amenities=breakfast; requested_info=reference_number; when=monday, 8, 5; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please.\nChunk 2: I would like it for 8 people for 5 nights starting from Monday Great!\nChunk 3: I am also looking for a Tuscan restaurant, are there any in the same price range as the bed and breakfast No Tuscan restaurants?\nChunk 4: I also like Italian food.\nChunk 5: Anything in the cheap price range?\nChunk 6: It is for 8 people.\nChunk 7: The time is monday, 8, 18:00.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number.\nChunk 10: Can I please have the reference number?\nChunk 11: No that will be all Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 acceptance=selected_option. C2 time+=8, 5; day+=monday; party_size+=8 people; stay_length+=5 nights. C3 domain=restaurant; goal=modify_constraint; price+=same price; amenities+=breakfast. C4 cuisine+=italian. C5 price+=cheap. C6 [SKIP: repeated_information]. C7 [SKIP: repeated_information]. C8 goal=booking. C9 goal=request_info; requested_info+=reference_number. C10 [SKIP: repeated_information]. C11 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, modify_constraint, booking, request_info; food=italian; price=same price, cheap; party_size=8 people; stay_length=5 nights; amenities=breakfast; requested_info=reference_number; when=monday, 8, 5; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please.\nChunk 2: I would like it for 8 people for 5 nights starting from Monday Great!\nChunk 3: I am also looking for a Tuscan restaurant, are there any in the same price range as the bed and breakfast No Tuscan restaurants?\nChunk 4: I also like Italian food.\nChunk 5: Anything in the cheap price range?\nChunk 6: It is for 8 people.\nChunk 7: The time is monday, 8, 18:00.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number.\nChunk 10: Can I please have the reference number?\nChunk 11: No that will be all Thank you.", "input_token_count": 109, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, acceptance: selected_option. Next, time: 8; day: monday; party size: 8 people; stay length: 5 nights. Next, the topic is restaurant; the goal is modify constraint; price: same price; amenities: breakfast. Next, cuisine: italian. Next, price: cheap. Next, the goal is booking. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is restaurant. the goal is request info. acceptance: selected_option.; time: 8; day: monday; party size: 8 people; stay length: 5 nights.; price: same price, cheap.; amenities: breakfast.; cuisine: italian.; requested information: reference_number..", "trace": "C1 acceptance=selected_option. C2 time+=8, 5; day+=monday; party_size+=8 people; stay_length+=5 nights. C3 domain=restaurant; goal=modify_constraint; price+=same price; amenities+=breakfast. C4 cuisine+=italian. C5 price+=cheap. C6 [SKIP: repeated_information]. C7 [SKIP: repeated_information]. C8 goal=booking. C9 goal=request_info; requested_info+=reference_number. C10 [SKIP: repeated_information]. C11 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please.", "streaming_reasoning": "Initially, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like it for 8 people for 5 nights starting from Monday Great!", "streaming_reasoning": "As more information arrives, time: 8; day: monday; party size: 8 people; stay length: 5 nights..", "trace": "time+=8, 5; day+=monday; party_size+=8 people; stay_length+=5 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am also looking for a Tuscan restaurant, are there any in the same price range as the bed and breakfast No Tuscan restaurants?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint; price: same price; amenities: breakfast..", "trace": "domain=restaurant; goal=modify_constraint; price+=same price; amenities+=breakfast."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also like Italian food.", "streaming_reasoning": "As more information arrives, cuisine: italian..", "trace": "cuisine+=italian."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Anything in the cheap price range?", "streaming_reasoning": "As more information arrives, price: cheap..", "trace": "price+=cheap."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It is for 8 people.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is monday, 8, 18:00.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Can I please have the reference number?", "streaming_reasoning": "The content at C10 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "No that will be all Thank you.", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is italian; price is same price; party size is 8 people; stay length is 5 nights; amenities is breakfast; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, modify_constraint, booking, request_info; food=italian; price=same price, cheap; party_size=8 people; stay_length=5 nights; amenities=breakfast; requested_info=reference_number; when=monday, 8, 5; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002611", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please, including the postcode.\nChunk 2: Is there an entrance fee?\nChunk 3: Thanks!\nChunk 4: I also need a 4-star place to stay that has free parking.\nChunk 5: Sounds great,and I will take it!\nChunk 6: On second thought, I'm actually looking for a hotel.\nChunk 7: Same criteria, but it needs to be in the moderate price range.\nChunk 8: What area is it in?\nChunk 9: Do you know the area the hotel is located in?", "streaming_reasoning": "C1 goal=request_info; requested_info+=postcode; acceptance=selected_option. C2 requested_info+=entrance_fee. C3 [SKIP: thanks_only]. C4 domain=hotel; goal=search; amenities+=parking, free parking; destination+=stay that has free parking. C5 intent=context_update. C6 hotel_type+=hotel. C7 price+=moderate; destination+=be in the moderate price range. C8 goal=request_info. C9 goal=request_info.", "deep_reasoning": "Need domain=hotel; goal=request_info, search; price=moderate; amenities=parking, free parking; destination=stay that has free parking, be in the moderate price range; requested_info=postcode, entrance_fee; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please, including the postcode.\nChunk 2: Is there an entrance fee?\nChunk 3: Thanks!\nChunk 4: I also need a 4-star place to stay that has free parking.\nChunk 5: Sounds great,and I will take it!\nChunk 6: On second thought, I'm actually looking for a hotel.\nChunk 7: Same criteria, but it needs to be in the moderate price range.\nChunk 8: What area is it in?\nChunk 9: Do you know the area the hotel is located in?"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=postcode; acceptance=selected_option. C2 requested_info+=entrance_fee. C3 [SKIP: thanks_only]. C4 domain=hotel; goal=search; amenities+=parking, free parking; destination+=stay that has free parking. C5 intent=context_update. C6 hotel_type+=hotel. C7 price+=moderate; destination+=be in the moderate price range. C8 goal=request_info. C9 goal=request_info.\n\nDeep reasoning: Need domain=hotel; goal=request_info, search; price=moderate; amenities=parking, free parking; destination=stay that has free parking, be in the moderate price range; requested_info=postcode, entrance_fee; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please, including the postcode.\nChunk 2: Is there an entrance fee?\nChunk 3: Thanks!\nChunk 4: I also need a 4-star place to stay that has free parking.\nChunk 5: Sounds great,and I will take it!\nChunk 6: On second thought, I'm actually looking for a hotel.\nChunk 7: Same criteria, but it needs to be in the moderate price range.\nChunk 8: What area is it in?\nChunk 9: Do you know the area the hotel is located in?", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: postcode; acceptance: selected_option. Next, requested information: entrance_fee. Next, the topic is hotel; the goal is search; amenities: parking; destination: stay that has free parking. Next, intent: context_update. Next, hotel type: hotel. Next, price: moderate; destination: be in the moderate price range. Next, the goal is request info. Finally, the goal is request info.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is request info.. requested information: postcode, entrance_fee.; acceptance: selected_option.; amenities: parking; destination: stay that has free parking., be in the moderate price range.; intent: context_update.; hotel type: hotel.; price: moderate.", "trace": "C1 goal=request_info; requested_info+=postcode; acceptance=selected_option. C2 requested_info+=entrance_fee. C3 [SKIP: thanks_only]. C4 domain=hotel; goal=search; amenities+=parking, free parking; destination+=stay that has free parking. C5 intent=context_update. C6 hotel_type+=hotel. C7 price+=moderate; destination+=be in the moderate price range. C8 goal=request_info. C9 goal=request_info.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please, including the postcode.", "streaming_reasoning": "Initially, the goal is request info; requested information: postcode; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=postcode; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there an entrance fee?", "streaming_reasoning": "As more information arrives, requested information: entrance_fee..", "trace": "requested_info+=entrance_fee."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks!", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need a 4-star place to stay that has free parking.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; amenities: parking; destination: stay that has free parking..", "trace": "domain=hotel; goal=search; amenities+=parking, free parking; destination+=stay that has free parking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Sounds great,and I will take it!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "On second thought, I'm actually looking for a hotel.", "streaming_reasoning": "As more information arrives, hotel type: hotel..", "trace": "hotel_type+=hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Same criteria, but it needs to be in the moderate price range.", "streaming_reasoning": "As more information arrives, price: moderate; destination: be in the moderate price range..", "trace": "price+=moderate; destination+=be in the moderate price range."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "What area is it in?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Do you know the area the hotel is located in?", "streaming_reasoning": "Finally, the goal is request info..", "trace": "goal=request_info."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: price is moderate; amenities is parking; destination is stay that has free parking; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search; price=moderate; amenities=parking, free parking; destination=stay that has free parking, be in the moderate price range; requested_info=postcode, entrance_fee; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002612", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a moderate priced restaurant please.\nChunk 2: I would like an Italian restaurant in the south.\nChunk 3: Yes can you book for 6 people at 19:15 on Wednesday That's disappointing.\nChunk 4: Is there anything else moderately priced in that area?\nChunk 5: Sure, as long as it's in the south.\nChunk 6: Can you give me the reference number once booked?\nChunk 7: No, that will take care of it.\nChunk 8: Thank you very much for your help!", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=moderate. C2 area+=south; cuisine+=italian. C3 goal=confirm_booking; time+=6, 19:15; day+=wednesday; party_size+=6 people; goal=confirm_booking. C4 goal=compare_alternative. C5 intent=context_update. C6 goal=request_info; requested_info+=reference_number. C7 goal=modify_constraint. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, confirm_booking, compare_alternative, request_info; area=south; food=italian; price=moderate; party_size=6 people; requested_info=reference_number; when=wednesday, 6, 19:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a moderate priced restaurant please.\nChunk 2: I would like an Italian restaurant in the south.\nChunk 3: Yes can you book for 6 people at 19:15 on Wednesday That's disappointing.\nChunk 4: Is there anything else moderately priced in that area?\nChunk 5: Sure, as long as it's in the south.\nChunk 6: Can you give me the reference number once booked?\nChunk 7: No, that will take care of it.\nChunk 8: Thank you very much for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=moderate. C2 area+=south; cuisine+=italian. C3 goal=confirm_booking; time+=6, 19:15; day+=wednesday; party_size+=6 people; goal=confirm_booking. C4 goal=compare_alternative. C5 intent=context_update. C6 goal=request_info; requested_info+=reference_number. C7 goal=modify_constraint. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, confirm_booking, compare_alternative, request_info; area=south; food=italian; price=moderate; party_size=6 people; requested_info=reference_number; when=wednesday, 6, 19:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a moderate priced restaurant please.\nChunk 2: I would like an Italian restaurant in the south.\nChunk 3: Yes can you book for 6 people at 19:15 on Wednesday That's disappointing.\nChunk 4: Is there anything else moderately priced in that area?\nChunk 5: Sure, as long as it's in the south.\nChunk 6: Can you give me the reference number once booked?\nChunk 7: No, that will take care of it.\nChunk 8: Thank you very much for your help!", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate. Next, area: south; cuisine: italian. Next, the goal is confirm booking.; time: 6; day: wednesday; party size: 6 people. Next, the goal is compare alternative. Next, intent: context_update. Next, the goal is request info; requested information: reference_number. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is modify constraint.. price: moderate.; area: south; cuisine: italian.; time: 6; day: wednesday; party size: 6 people; intent: context_update.; requested information: reference_number..", "trace": "C1 domain=restaurant; goal=search; price+=moderate. C2 area+=south; cuisine+=italian. C3 goal=confirm_booking; time+=6, 19:15; day+=wednesday; party_size+=6 people; goal=confirm_booking. C4 goal=compare_alternative. C5 intent=context_update. C6 goal=request_info; requested_info+=reference_number. C7 goal=modify_constraint. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a moderate priced restaurant please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate..", "trace": "domain=restaurant; goal=search; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like an Italian restaurant in the south.", "streaming_reasoning": "As more information arrives, area: south; cuisine: italian..", "trace": "area+=south; cuisine+=italian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes can you book for 6 people at 19:15 on Wednesday That's disappointing.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 6; day: wednesday; party size: 6 people.", "trace": "goal=confirm_booking; time+=6, 19:15; day+=wednesday; party_size+=6 people; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is there anything else moderately priced in that area?", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Sure, as long as it's in the south.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you give me the reference number once booked?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that will take care of it.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you very much for your help!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; cuisine is italian; price is moderate; party size is 6 people; requested information is reference_number; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, confirm_booking, compare_alternative, request_info; area=south; food=italian; price=moderate; party_size=6 people; requested_info=reference_number; when=wednesday, 6, 19:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002613", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I wanted to visit the restaurant named La Raza, could you tell me the hours it is open, and if I should try to book a reservation?\nChunk 2: What type of food does La Raza serve?\nChunk 3: And what area is it in Thanks a lot.\nChunk 4: I am also looking for places to go to in the centre of town.\nChunk 5: I don't really have a preference, what would you suggest?\nChunk 6: I'm kind of new to town That sounds great.\nChunk 7: Can I get their phone number and postcode please?\nChunk 8: Thank you very much, you've been very helpful.", "streaming_reasoning": "C1 domain=restaurant; goal=request_info; destination+=visit the restaurant named la raza. C2 goal=request_info. C3 intent=context_update. C4 goal=search; area+=centre; destination+=go to in the centre of town. C5 goal=recommendation. C6 destination+=town that sounds great. C7 requested_info+=phone, postcode. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=booking, request_info, search, recommendation; area=centre; destination=visit the restaurant named la raza, go to in the centre of town, town that sounds great; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I wanted to visit the restaurant named La Raza, could you tell me the hours it is open, and if I should try to book a reservation?\nChunk 2: What type of food does La Raza serve?\nChunk 3: And what area is it in Thanks a lot.\nChunk 4: I am also looking for places to go to in the centre of town.\nChunk 5: I don't really have a preference, what would you suggest?\nChunk 6: I'm kind of new to town That sounds great.\nChunk 7: Can I get their phone number and postcode please?\nChunk 8: Thank you very much, you've been very helpful."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=request_info; destination+=visit the restaurant named la raza. C2 goal=request_info. C3 intent=context_update. C4 goal=search; area+=centre; destination+=go to in the centre of town. C5 goal=recommendation. C6 destination+=town that sounds great. C7 requested_info+=phone, postcode. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=booking, request_info, search, recommendation; area=centre; destination=visit the restaurant named la raza, go to in the centre of town, town that sounds great; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I wanted to visit the restaurant named La Raza, could you tell me the hours it is open, and if I should try to book a reservation?\nChunk 2: What type of food does La Raza serve?\nChunk 3: And what area is it in Thanks a lot.\nChunk 4: I am also looking for places to go to in the centre of town.\nChunk 5: I don't really have a preference, what would you suggest?\nChunk 6: I'm kind of new to town That sounds great.\nChunk 7: Can I get their phone number and postcode please?\nChunk 8: Thank you very much, you've been very helpful.", "input_token_count": 110, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is request info; destination: visit the restaurant named la raza. Next, the goal is request info. Next, intent: context_update. Next, the goal is search; area: centre; destination: go to in the centre of town. Next, the goal is recommendation. Next, destination: town that sounds great. Finally, requested information: phone.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is recommendation.. destination: visit the restaurant named la raza., go to in the centre of town., town that sounds great.; intent: context_update.; area: centre; requested information: phone.", "trace": "C1 domain=restaurant; goal=request_info; destination+=visit the restaurant named la raza. C2 goal=request_info. C3 intent=context_update. C4 goal=search; area+=centre; destination+=go to in the centre of town. C5 goal=recommendation. C6 destination+=town that sounds great. C7 requested_info+=phone, postcode. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I wanted to visit the restaurant named La Raza, could you tell me the hours it is open, and if I should try to book a reservation?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is request info; destination: visit the restaurant named la raza..", "trace": "domain=restaurant; goal=request_info; destination+=visit the restaurant named la raza."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What type of food does La Raza serve?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "And what area is it in Thanks a lot.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am also looking for places to go to in the centre of town.", "streaming_reasoning": "As more information arrives, the goal is search; area: centre; destination: go to in the centre of town..", "trace": "goal=search; area+=centre; destination+=go to in the centre of town."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I don't really have a preference, what would you suggest?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'm kind of new to town That sounds great.", "streaming_reasoning": "As more information arrives, destination: town that sounds great..", "trace": "destination+=town that sounds great."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can I get their phone number and postcode please?", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, postcode."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you very much, you've been very helpful.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: area is centre; destination is visit the restaurant named la raza; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=booking, request_info, search, recommendation; area=centre; destination=visit the restaurant named la raza, go to in the centre of town, town that sounds great; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002614", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: It should be in the east part of town.\nChunk 3: Can you help me find some Chinese food then?\nChunk 4: What is the address, phone number, and postcode Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 area+=east. C3 cuisine+=chinese. C4 goal=request_info; requested_info+=address, phone, postcode.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=east; food=chinese; destination=find a restaurant; requested_info=address, phone, postcode.", "answer": "I can help with that and include the address, phone, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a restaurant.\nChunk 2: It should be in the east part of town.\nChunk 3: Can you help me find some Chinese food then?\nChunk 4: What is the address, phone number, and postcode Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 area+=east. C3 cuisine+=chinese. C4 goal=request_info; requested_info+=address, phone, postcode.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=east; food=chinese; destination=find a restaurant; requested_info=address, phone, postcode.\n\nAnswer: I can help with that and include the address, phone, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: It should be in the east part of town.\nChunk 3: Can you help me find some Chinese food then?\nChunk 4: What is the address, phone number, and postcode Thank you, goodbye.", "input_token_count": 43, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant. Next, area: east. Next, cuisine: chinese. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. destination: find a restaurant.; area: east.; cuisine: chinese.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 area+=east. C3 cuisine+=chinese. C4 goal=request_info; requested_info+=address, phone, postcode.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the east part of town.", "streaming_reasoning": "As more information arrives, area: east..", "trace": "area+=east."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you help me find some Chinese food then?", "streaming_reasoning": "As more information arrives, cuisine: chinese..", "trace": "cuisine+=chinese."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is the address, phone number, and postcode Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, postcode."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is east; cuisine is chinese; destination is find a restaurant; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=east; food=chinese; destination=find a restaurant; requested_info=address, phone, postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002615", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to leave after 15:15 please.\nChunk 2: Yes, can you please book that for me and send me a reference number Thank you.\nChunk 3: i also want to check out some museums while i'm in town.\nChunk 4: In the centre, please.\nChunk 5: If you can go ahead and recommend one and provide me with the phone number and address please Thanks so much.\nChunk 6: That's all for today.\nChunk 7: Thank you for your help!", "streaming_reasoning": "C1 time+=15:15; destination+=leave after 15:15 please. C2 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C3 goal=search; destination+=check out some museums while i'm in town. C4 area+=centre. C5 goal=recommendation; requested_info+=address, phone. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "deep_reasoning": "Need goal=booking, request_info, confirm_booking, search, recommendation; area=centre; destination=leave after 15:15 please, check out some museums while i'm in town; requested_info=reference_number, address, phone; when=15:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like to leave after 15:15 please.\nChunk 2: Yes, can you please book that for me and send me a reference number Thank you.\nChunk 3: i also want to check out some museums while i'm in town.\nChunk 4: In the centre, please.\nChunk 5: If you can go ahead and recommend one and provide me with the phone number and address please Thanks so much.\nChunk 6: That's all for today.\nChunk 7: Thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=15:15; destination+=leave after 15:15 please. C2 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C3 goal=search; destination+=check out some museums while i'm in town. C4 area+=centre. C5 goal=recommendation; requested_info+=address, phone. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=booking, request_info, confirm_booking, search, recommendation; area=centre; destination=leave after 15:15 please, check out some museums while i'm in town; requested_info=reference_number, address, phone; when=15:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to leave after 15:15 please.\nChunk 2: Yes, can you please book that for me and send me a reference number Thank you.\nChunk 3: i also want to check out some museums while i'm in town.\nChunk 4: In the centre, please.\nChunk 5: If you can go ahead and recommend one and provide me with the phone number and address please Thanks so much.\nChunk 6: That's all for today.\nChunk 7: Thank you for your help!", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 15:15; destination: leave after 15:15 please. Next, the goal is confirm booking.; requested information: reference_number. Next, the goal is search; destination: check out some museums while i'm in town. Next, area: centre. Finally, the goal is recommendation; requested information: address.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is recommendation. time: 15:15; destination: leave after 15:15 please., check out some museums while i'm in town.; requested information: reference_number, address; area: centre..", "trace": "C1 time+=15:15; destination+=leave after 15:15 please. C2 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C3 goal=search; destination+=check out some museums while i'm in town. C4 area+=centre. C5 goal=recommendation; requested_info+=address, phone. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like to leave after 15:15 please.", "streaming_reasoning": "Initially, time: 15:15; destination: leave after 15:15 please..", "trace": "time+=15:15; destination+=leave after 15:15 please."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, can you please book that for me and send me a reference number Thank you.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "i also want to check out some museums while i'm in town.", "streaming_reasoning": "As more information arrives, the goal is search; destination: check out some museums while i'm in town..", "trace": "goal=search; destination+=check out some museums while i'm in town."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "In the centre, please.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "If you can go ahead and recommend one and provide me with the phone number and address please Thanks so much.", "streaming_reasoning": "As more information arrives, the goal is recommendation; requested information: address.", "trace": "goal=recommendation; requested_info+=address, phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all for today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your help!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=booking, request_info, confirm_booking, search, recommendation; area=centre; destination=leave after 15:15 please, check out some museums while i'm in town; requested_info=reference_number, address, phone; when=15:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002616", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: TR2534 arrives at what time?\nChunk 2: Yes I would like this train booked.\nChunk 3: I need ticket for 4 people.\nChunk 4: I also need the reference number please.\nChunk 5: I want to find a guesthouse.\nChunk 6: It should be in the north part of town.\nChunk 7: The one with wifi will work.\nChunk 8: I need to book it for Friday, 5 nights, 4 people.\nChunk 9: Reference number please, come on, this is taking too long.\nChunk 10: And I didn't even get the hotel name from you, is there a manager?\nChunk 11: That was all I needed.", "streaming_reasoning": "C1 goal=request_info. C2 domain=train; acceptance=selected_option. C3 goal=search; party_size+=4 people. C4 goal=request_info; requested_info+=reference_number. C5 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C6 area+=north. C7 amenities+=wifi. C8 goal=booking; day+=friday; stay_length+=5 nights. C9 intent=context_update. C10 hotel_type+=hotel. C11 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, hotel; goal=search, request_info, booking; area=north; party_size=4 people; stay_length=5 nights; amenities=wifi; destination=find a guesthouse; requested_info=reference_number; when=friday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: TR2534 arrives at what time?\nChunk 2: Yes I would like this train booked.\nChunk 3: I need ticket for 4 people.\nChunk 4: I also need the reference number please.\nChunk 5: I want to find a guesthouse.\nChunk 6: It should be in the north part of town.\nChunk 7: The one with wifi will work.\nChunk 8: I need to book it for Friday, 5 nights, 4 people.\nChunk 9: Reference number please, come on, this is taking too long.\nChunk 10: And I didn't even get the hotel name from you, is there a manager?\nChunk 11: That was all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 domain=train; acceptance=selected_option. C3 goal=search; party_size+=4 people. C4 goal=request_info; requested_info+=reference_number. C5 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C6 area+=north. C7 amenities+=wifi. C8 goal=booking; day+=friday; stay_length+=5 nights. C9 intent=context_update. C10 hotel_type+=hotel. C11 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, hotel; goal=search, request_info, booking; area=north; party_size=4 people; stay_length=5 nights; amenities=wifi; destination=find a guesthouse; requested_info=reference_number; when=friday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: TR2534 arrives at what time?\nChunk 2: Yes I would like this train booked.\nChunk 3: I need ticket for 4 people.\nChunk 4: I also need the reference number please.\nChunk 5: I want to find a guesthouse.\nChunk 6: It should be in the north part of town.\nChunk 7: The one with wifi will work.\nChunk 8: I need to book it for Friday, 5 nights, 4 people.\nChunk 9: Reference number please, come on, this is taking too long.\nChunk 10: And I didn't even get the hotel name from you, is there a manager?\nChunk 11: That was all I needed.", "input_token_count": 108, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, the topic is train; acceptance: selected_option. Next, the goal is search; party size: 4 people. Next, the goal is request info; requested information: reference_number. Next, the topic is hotel; hotel type: guesthouse; destination: find a guesthouse. Next, area: north. Next, amenities: wifi. Next, the goal is booking; day: friday; stay length: 5 nights. Next, intent: context_update. Finally, hotel type: hotel.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking. acceptance: selected_option.; party size: 4 people.; requested information: reference_number.; hotel type: guesthouse, hotel.; destination: find a guesthouse.; area: north.; amenities: wifi.; day: friday; stay length: 5 nights.; intent: context_update..", "trace": "C1 goal=request_info. C2 domain=train; acceptance=selected_option. C3 goal=search; party_size+=4 people. C4 goal=request_info; requested_info+=reference_number. C5 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C6 area+=north. C7 amenities+=wifi. C8 goal=booking; day+=friday; stay_length+=5 nights. C9 intent=context_update. C10 hotel_type+=hotel. C11 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "TR2534 arrives at what time?", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes I would like this train booked.", "streaming_reasoning": "As more information arrives, the topic is train; acceptance: selected_option..", "trace": "domain=train; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need ticket for 4 people.", "streaming_reasoning": "As more information arrives, the goal is search; party size: 4 people..", "trace": "goal=search; party_size+=4 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the reference number please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a guesthouse.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse; destination: find a guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The one with wifi will work.", "streaming_reasoning": "As more information arrives, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I need to book it for Friday, 5 nights, 4 people.", "streaming_reasoning": "As more information arrives, the goal is booking; day: friday; stay length: 5 nights..", "trace": "goal=booking; day+=friday; stay_length+=5 nights."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Reference number please, come on, this is taking too long.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "And I didn't even get the hotel name from you, is there a manager?", "streaming_reasoning": "As more information arrives, hotel type: hotel..", "trace": "hotel_type+=hotel."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "That was all I needed.", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is north; party size is 4 people; stay length is 5 nights; amenities is wifi; destination is find a guesthouse; requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, request_info, booking; area=north; party_size=4 people; stay_length=5 nights; amenities=wifi; destination=find a guesthouse; requested_info=reference_number; when=friday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002617", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please, for 5 people and 2 nights starting Sunday.\nChunk 2: Thank you, I will also need a taxi.\nChunk 3: I would like to leave the hotel by 24:45.\nChunk 4: I need help with attraction.\nChunk 5: It should be in the centre part of town.\nChunk 6: I also need the address That sounds perfect.\nChunk 7: I will need the taxi for going between the two places.\nChunk 8: As well as the car type and contact number.\nChunk 9: That's all for now.\nChunk 10: Thank you for all your help.", "streaming_reasoning": "C1 time+=5, 2; day+=sunday; party_size+=5 people; stay_length+=2 nights; acceptance=selected_option. C2 domain=taxi; goal=search. C3 domain=hotel; time+=24:45; hotel_type+=hotel; destination+=leave the hotel by 24:45. C4 domain=attraction. C5 area+=centre. C6 goal=request_info; requested_info+=address; acceptance=selected_option. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi, hotel, attraction; goal=search, request_info; area=centre; party_size=5 people; stay_length=2 nights; destination=leave the hotel by 24:45; requested_info=address; when=sunday, 5, 2, 24:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please, for 5 people and 2 nights starting Sunday.\nChunk 2: Thank you, I will also need a taxi.\nChunk 3: I would like to leave the hotel by 24:45.\nChunk 4: I need help with attraction.\nChunk 5: It should be in the centre part of town.\nChunk 6: I also need the address That sounds perfect.\nChunk 7: I will need the taxi for going between the two places.\nChunk 8: As well as the car type and contact number.\nChunk 9: That's all for now.\nChunk 10: Thank you for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=5, 2; day+=sunday; party_size+=5 people; stay_length+=2 nights; acceptance=selected_option. C2 domain=taxi; goal=search. C3 domain=hotel; time+=24:45; hotel_type+=hotel; destination+=leave the hotel by 24:45. C4 domain=attraction. C5 area+=centre. C6 goal=request_info; requested_info+=address; acceptance=selected_option. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi, hotel, attraction; goal=search, request_info; area=centre; party_size=5 people; stay_length=2 nights; destination=leave the hotel by 24:45; requested_info=address; when=sunday, 5, 2, 24:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please, for 5 people and 2 nights starting Sunday.\nChunk 2: Thank you, I will also need a taxi.\nChunk 3: I would like to leave the hotel by 24:45.\nChunk 4: I need help with attraction.\nChunk 5: It should be in the centre part of town.\nChunk 6: I also need the address That sounds perfect.\nChunk 7: I will need the taxi for going between the two places.\nChunk 8: As well as the car type and contact number.\nChunk 9: That's all for now.\nChunk 10: Thank you for all your help.", "input_token_count": 100, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, time: 5; day: sunday; party size: 5 people; stay length: 2 nights; acceptance: selected_option. Next, the topic is taxi; the goal is search. Next, the topic is hotel; time: 24:45; hotel type: hotel; destination: leave the hotel by 24:45. Next, the topic is attraction. Next, area: centre. Next, the goal is request info; requested information: address; acceptance: selected_option. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction.. the goal is request info. time: 5, 24:45; day: sunday; party size: 5 people; stay length: 2 nights; acceptance: selected_option.; hotel type: hotel; destination: leave the hotel by 24:45.; area: centre.; requested information: address; intent: context_update..", "trace": "C1 time+=5, 2; day+=sunday; party_size+=5 people; stay_length+=2 nights; acceptance=selected_option. C2 domain=taxi; goal=search. C3 domain=hotel; time+=24:45; hotel_type+=hotel; destination+=leave the hotel by 24:45. C4 domain=attraction. C5 area+=centre. C6 goal=request_info; requested_info+=address; acceptance=selected_option. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please, for 5 people and 2 nights starting Sunday.", "streaming_reasoning": "Initially, time: 5; day: sunday; party size: 5 people; stay length: 2 nights; acceptance: selected_option..", "trace": "time+=5, 2; day+=sunday; party_size+=5 people; stay_length+=2 nights; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thank you, I will also need a taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is search..", "trace": "domain=taxi; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to leave the hotel by 24:45.", "streaming_reasoning": "As more information arrives, the topic is hotel; time: 24:45; hotel type: hotel; destination: leave the hotel by 24:45..", "trace": "domain=hotel; time+=24:45; hotel_type+=hotel; destination+=leave the hotel by 24:45."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need help with attraction.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need the address That sounds perfect.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=address; acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I will need the taxi for going between the two places.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "As well as the car type and contact number.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That's all for now.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: area is centre; party size is 5 people; stay length is 2 nights; destination is leave the hotel by 24:45; requested information is address; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, hotel, attraction; goal=search, request_info; area=centre; party_size=5 people; stay_length=2 nights; destination=leave the hotel by 24:45; requested_info=address; when=sunday, 5, 2, 24:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002618", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to leave after 9:00.\nChunk 2: Yes, could you please help me find a expensive danish restaurant?\nChunk 3: British food would be a suitable replacement I suppose No preference.\nChunk 4: Can you recommend one and book the same group of people on the same day please.\nChunk 5: i would like the reservation to be for sunday for 7 people at 20:15.\nChunk 6: Thanks That's all Goodbye.", "streaming_reasoning": "C1 time+=9:00; destination+=leave after 9:00. C2 domain=restaurant; goal=search; cuisine+=danish; price+=expensive; acceptance=selected_option. C3 cuisine+=british. C4 goal=recommendation. C5 time+=7, 20:15; day+=sunday; party_size+=7 people; destination+=be for sunday for 7 people at 20:15. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, recommendation; food=danish, british; price=expensive; party_size=7 people; destination=leave after 9:00, be for sunday for 7 people at 20:15; when=sunday, 9:00, 7, 20:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to leave after 9:00.\nChunk 2: Yes, could you please help me find a expensive danish restaurant?\nChunk 3: British food would be a suitable replacement I suppose No preference.\nChunk 4: Can you recommend one and book the same group of people on the same day please.\nChunk 5: i would like the reservation to be for sunday for 7 people at 20:15.\nChunk 6: Thanks That's all Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=9:00; destination+=leave after 9:00. C2 domain=restaurant; goal=search; cuisine+=danish; price+=expensive; acceptance=selected_option. C3 cuisine+=british. C4 goal=recommendation. C5 time+=7, 20:15; day+=sunday; party_size+=7 people; destination+=be for sunday for 7 people at 20:15. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, recommendation; food=danish, british; price=expensive; party_size=7 people; destination=leave after 9:00, be for sunday for 7 people at 20:15; when=sunday, 9:00, 7, 20:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to leave after 9:00.\nChunk 2: Yes, could you please help me find a expensive danish restaurant?\nChunk 3: British food would be a suitable replacement I suppose No preference.\nChunk 4: Can you recommend one and book the same group of people on the same day please.\nChunk 5: i would like the reservation to be for sunday for 7 people at 20:15.\nChunk 6: Thanks That's all Goodbye.", "input_token_count": 77, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 9:00; destination: leave after 9:00. Next, the topic is restaurant; the goal is search; cuisine: danish; price: expensive; acceptance: selected_option. Next, cuisine: british. Next, the goal is recommendation. Finally, time: 7; day: sunday; party size: 7 people; destination: be for sunday for 7 people at 20:15.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is recommendation.. time: 9:00, 7; destination: leave after 9:00., be for sunday for 7 people at 20:15.; cuisine: danish, british.; price: expensive; acceptance: selected_option.; day: sunday; party size: 7 people.", "trace": "C1 time+=9:00; destination+=leave after 9:00. C2 domain=restaurant; goal=search; cuisine+=danish; price+=expensive; acceptance=selected_option. C3 cuisine+=british. C4 goal=recommendation. C5 time+=7, 20:15; day+=sunday; party_size+=7 people; destination+=be for sunday for 7 people at 20:15. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to leave after 9:00.", "streaming_reasoning": "Initially, time: 9:00; destination: leave after 9:00..", "trace": "time+=9:00; destination+=leave after 9:00."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, could you please help me find a expensive danish restaurant?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; cuisine: danish; price: expensive; acceptance: selected_option..", "trace": "domain=restaurant; goal=search; cuisine+=danish; price+=expensive; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "British food would be a suitable replacement I suppose No preference.", "streaming_reasoning": "As more information arrives, cuisine: british..", "trace": "cuisine+=british."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you recommend one and book the same group of people on the same day please.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "i would like the reservation to be for sunday for 7 people at 20:15.", "streaming_reasoning": "As more information arrives, time: 7; day: sunday; party size: 7 people; destination: be for sunday for 7 people at 20:15..", "trace": "time+=7, 20:15; day+=sunday; party_size+=7 people; destination+=be for sunday for 7 people at 20:15."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks That's all Goodbye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is danish; price is expensive; party size is 7 people; destination is leave after 9:00; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, recommendation; food=danish, british; price=expensive; party_size=7 people; destination=leave after 9:00, be for sunday for 7 people at 20:15; when=sunday, 9:00, 7, 20:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002619", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Do any of them include free parking?\nChunk 2: Price range does not matter.\nChunk 3: North part of town.Cheap would be better.\nChunk 4: Yes, can you book it for 7 people for 4 nights on Thursday?\nChunk 5: Yes let's try another hotel in the same price range.\nChunk 6: No that will be all.\nChunk 7: Thanks.", "streaming_reasoning": "C1 amenities+=parking, free parking. C2 goal=modify_constraint. C3 area+=north; price+=cheap. C4 goal=confirm_booking; day+=thursday; party_size+=7 people; stay_length+=4 nights; goal=confirm_booking. C5 domain=hotel; goal=modify_constraint; price+=same price; hotel_type+=hotel; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=booking, confirm_booking, compare_alternative, modify_constraint; area=north; price=cheap, same price; party_size=7 people; stay_length=4 nights; amenities=parking, free parking; when=thursday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Do any of them include free parking?\nChunk 2: Price range does not matter.\nChunk 3: North part of town.Cheap would be better.\nChunk 4: Yes, can you book it for 7 people for 4 nights on Thursday?\nChunk 5: Yes let's try another hotel in the same price range.\nChunk 6: No that will be all.\nChunk 7: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 amenities+=parking, free parking. C2 goal=modify_constraint. C3 area+=north; price+=cheap. C4 goal=confirm_booking; day+=thursday; party_size+=7 people; stay_length+=4 nights; goal=confirm_booking. C5 domain=hotel; goal=modify_constraint; price+=same price; hotel_type+=hotel; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=booking, confirm_booking, compare_alternative, modify_constraint; area=north; price=cheap, same price; party_size=7 people; stay_length=4 nights; amenities=parking, free parking; when=thursday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Do any of them include free parking?\nChunk 2: Price range does not matter.\nChunk 3: North part of town.Cheap would be better.\nChunk 4: Yes, can you book it for 7 people for 4 nights on Thursday?\nChunk 5: Yes let's try another hotel in the same price range.\nChunk 6: No that will be all.\nChunk 7: Thanks.", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, amenities: parking. Next, the goal is modify constraint. Next, area: north; price: cheap. Next, the goal is confirm booking.; day: thursday; party size: 7 people; stay length: 4 nights. Finally, the topic is hotel; the goal is confirm booking.; price: same price; hotel type: hotel.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is confirm booking.. amenities: parking; area: north; price: cheap., same price; day: thursday; party size: 7 people; stay length: 4 nights; hotel type: hotel.", "trace": "C1 amenities+=parking, free parking. C2 goal=modify_constraint. C3 area+=north; price+=cheap. C4 goal=confirm_booking; day+=thursday; party_size+=7 people; stay_length+=4 nights; goal=confirm_booking. C5 domain=hotel; goal=modify_constraint; price+=same price; hotel_type+=hotel; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Do any of them include free parking?", "streaming_reasoning": "Initially, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Price range does not matter.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "North part of town.Cheap would be better.", "streaming_reasoning": "As more information arrives, area: north; price: cheap..", "trace": "area+=north; price+=cheap."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, can you book it for 7 people for 4 nights on Thursday?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; day: thursday; party size: 7 people; stay length: 4 nights.", "trace": "goal=confirm_booking; day+=thursday; party_size+=7 people; stay_length+=4 nights; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes let's try another hotel in the same price range.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is confirm booking.; price: same price; hotel type: hotel.", "trace": "domain=hotel; goal=modify_constraint; price+=same price; hotel_type+=hotel; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No that will be all.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: area is north; price is cheap; party size is 7 people; stay length is 4 nights; amenities is parking; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, confirm_booking, compare_alternative, modify_constraint; area=north; price=cheap, same price; party_size=7 people; stay_length=4 nights; amenities=parking, free parking; when=thursday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002620", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you I also need to find a college to go to.\nChunk 2: Whichever you recommend is great.\nChunk 3: What part of town is it in Thank you!\nChunk 4: Can you please tell me the postcode?\nChunk 5: That is everything thank you so much.\nChunk 6: Yes, you have Thank you.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 goal=recommendation. C3 intent=context_update. C4 goal=request_info; requested_info+=postcode. C5 intent=context_update. C6 [SKIP: repeated_information].", "deep_reasoning": "Need goal=recommendation, request_info; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you I also need to find a college to go to.\nChunk 2: Whichever you recommend is great.\nChunk 3: What part of town is it in Thank you!\nChunk 4: Can you please tell me the postcode?\nChunk 5: That is everything thank you so much.\nChunk 6: Yes, you have Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 goal=recommendation. C3 intent=context_update. C4 goal=request_info; requested_info+=postcode. C5 intent=context_update. C6 [SKIP: repeated_information].\n\nDeep reasoning: Need goal=recommendation, request_info; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you I also need to find a college to go to.\nChunk 2: Whichever you recommend is great.\nChunk 3: What part of town is it in Thank you!\nChunk 4: Can you please tell me the postcode?\nChunk 5: That is everything thank you so much.\nChunk 6: Yes, you have Thank you.", "input_token_count": 57, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is recommendation. Next, intent: context_update. Next, the goal is request info; requested information: postcode. Finally, intent: context_update.  Some chunks were skipped because they contained repeated_information or thanks_only. In summary, the goal is request info. intent: context_update.; requested information: postcode..", "trace": "C1 [SKIP: thanks_only]. C2 goal=recommendation. C3 intent=context_update. C4 goal=request_info; requested_info+=postcode. C5 intent=context_update. C6 [SKIP: repeated_information].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you I also need to find a college to go to.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Whichever you recommend is great.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What part of town is it in Thank you!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you please tell me the postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That is everything thank you so much.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, you have Thank you.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}]}, "output": {"deep_reasoning": "Need goal=recommendation, request_info; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002621", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What about a college Thank you!\nChunk 2: Just give me the postcode and I should be good to go Awesome.\nChunk 3: Can I get a taxi from the College by 12:15?\nChunk 4: I'm headed to Tandoori Palace from the College.\nChunk 5: Thank you for booking that taxi and giving the contact number and car type No thank you!\nChunk 6: That will be all!", "streaming_reasoning": "C1 domain=attraction; goal=recommendation. C2 goal=request_info; destination+=go awesome; requested_info+=postcode. C3 domain=taxi; time+=12:15. C4 intent=context_update. C5 goal=booking. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, taxi; goal=recommendation, request_info, booking; destination=go awesome; requested_info=postcode; when=12:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What about a college Thank you!\nChunk 2: Just give me the postcode and I should be good to go Awesome.\nChunk 3: Can I get a taxi from the College by 12:15?\nChunk 4: I'm headed to Tandoori Palace from the College.\nChunk 5: Thank you for booking that taxi and giving the contact number and car type No thank you!\nChunk 6: That will be all!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=recommendation. C2 goal=request_info; destination+=go awesome; requested_info+=postcode. C3 domain=taxi; time+=12:15. C4 intent=context_update. C5 goal=booking. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, taxi; goal=recommendation, request_info, booking; destination=go awesome; requested_info=postcode; when=12:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What about a college Thank you!\nChunk 2: Just give me the postcode and I should be good to go Awesome.\nChunk 3: Can I get a taxi from the College by 12:15?\nChunk 4: I'm headed to Tandoori Palace from the College.\nChunk 5: Thank you for booking that taxi and giving the contact number and car type No thank you!\nChunk 6: That will be all!", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is recommendation. Next, the goal is request info; destination: go awesome; requested information: postcode. Next, the topic is taxi; time: 12:15. Next, intent: context_update. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is booking.. destination: go awesome; requested information: postcode.; time: 12:15.; intent: context_update..", "trace": "C1 domain=attraction; goal=recommendation. C2 goal=request_info; destination+=go awesome; requested_info+=postcode. C3 domain=taxi; time+=12:15. C4 intent=context_update. C5 goal=booking. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What about a college Thank you!", "streaming_reasoning": "Initially, the topic is attraction; the goal is recommendation..", "trace": "domain=attraction; goal=recommendation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Just give me the postcode and I should be good to go Awesome.", "streaming_reasoning": "As more information arrives, the goal is request info; destination: go awesome; requested information: postcode..", "trace": "goal=request_info; destination+=go awesome; requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I get a taxi from the College by 12:15?", "streaming_reasoning": "As more information arrives, the topic is taxi; time: 12:15..", "trace": "domain=taxi; time+=12:15."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm headed to Tandoori Palace from the College.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you for booking that taxi and giving the contact number and car type No thank you!", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That will be all!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of recommendation. Key information: destination is go awesome; requested information is postcode; timing is 12:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, taxi; goal=recommendation, request_info, booking; destination=go awesome; requested_info=postcode; when=12:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002622", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: depart from birmingham new street,I want to leave on Friday and arrive by 14:30.\nChunk 2: Book it for myself I'm sorry.\nChunk 3: Yes.\nChunk 4: Please book the train on Friday arriving by 14:30 for one person.\nChunk 5: I'm looking for a hotel to stay in the north, specifically, a guesthouse.\nChunk 6: The time is friday, 1, 3.\nChunk 7: Please make a booking.\nChunk 8: That is all I need, thank you.\nChunk 9: Bye.", "streaming_reasoning": "C1 goal=search; time+=14:30; day+=friday; destination+=leave; departure+=birmingham new street,i want, birmingham new street. C2 goal=booking. C3 goal=confirm_booking. C4 domain=train. C5 domain=hotel; area+=north; hotel_type+=guesthouse, hotel; destination+=stay in the north. C6 [SKIP: repeated_information]. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, hotel; goal=search, booking; area=north; destination=leave, stay in the north; departure=birmingham new street,i want, birmingham new street; when=friday, 14:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: depart from birmingham new street,I want to leave on Friday and arrive by 14:30.\nChunk 2: Book it for myself I'm sorry.\nChunk 3: Yes.\nChunk 4: Please book the train on Friday arriving by 14:30 for one person.\nChunk 5: I'm looking for a hotel to stay in the north, specifically, a guesthouse.\nChunk 6: The time is friday, 1, 3.\nChunk 7: Please make a booking.\nChunk 8: That is all I need, thank you.\nChunk 9: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; time+=14:30; day+=friday; destination+=leave; departure+=birmingham new street,i want, birmingham new street. C2 goal=booking. C3 goal=confirm_booking. C4 domain=train. C5 domain=hotel; area+=north; hotel_type+=guesthouse, hotel; destination+=stay in the north. C6 [SKIP: repeated_information]. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, hotel; goal=search, booking; area=north; destination=leave, stay in the north; departure=birmingham new street,i want, birmingham new street; when=friday, 14:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: depart from birmingham new street,I want to leave on Friday and arrive by 14:30.\nChunk 2: Book it for myself I'm sorry.\nChunk 3: Yes.\nChunk 4: Please book the train on Friday arriving by 14:30 for one person.\nChunk 5: I'm looking for a hotel to stay in the north, specifically, a guesthouse.\nChunk 6: The time is friday, 1, 3.\nChunk 7: Please make a booking.\nChunk 8: That is all I need, thank you.\nChunk 9: Bye.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; time: 14:30; day: friday; destination: leave; departure point: birmingham new street. Next, the goal is booking. Next, the goal is confirm booking. Next, the topic is train. Next, the topic is hotel; area: north; hotel type: guesthouse; destination: stay in the north. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is hotel. the goal is confirm booking.. time: 14:30; day: friday; destination: leave, stay in the north.; departure point: birmingham new street; area: north; hotel type: guesthouse; intent: context_update..", "trace": "C1 goal=search; time+=14:30; day+=friday; destination+=leave; departure+=birmingham new street,i want, birmingham new street. C2 goal=booking. C3 goal=confirm_booking. C4 domain=train. C5 domain=hotel; area+=north; hotel_type+=guesthouse, hotel; destination+=stay in the north. C6 [SKIP: repeated_information]. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "depart from birmingham new street,I want to leave on Friday and arrive by 14:30.", "streaming_reasoning": "Initially, the goal is search; time: 14:30; day: friday; destination: leave; departure point: birmingham new street.", "trace": "goal=search; time+=14:30; day+=friday; destination+=leave; departure+=birmingham new street,i want, birmingham new street."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Book it for myself I'm sorry.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please book the train on Friday arriving by 14:30 for one person.", "streaming_reasoning": "As more information arrives, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm looking for a hotel to stay in the north, specifically, a guesthouse.", "streaming_reasoning": "As more information arrives, the topic is hotel; area: north; hotel type: guesthouse; destination: stay in the north..", "trace": "domain=hotel; area+=north; hotel_type+=guesthouse, hotel; destination+=stay in the north."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is friday, 1, 3.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all I need, thank you.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Bye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is north; destination is leave; departure point is birmingham new street; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, booking; area=north; destination=leave, stay in the north; departure=birmingham new street,i want, birmingham new street; when=friday, 14:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002623", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm trying to find out where the Parkside Police Station is.\nChunk 2: Can you help me?\nChunk 3: That's all I needed.\nChunk 4: Thanks so much for your help!", "streaming_reasoning": "C1 domain=train; goal=search; destination+=find out where the parkside police statio. C2 goal=request_info. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search; destination=find out where the parkside police statio; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm trying to find out where the Parkside Police Station is.\nChunk 2: Can you help me?\nChunk 3: That's all I needed.\nChunk 4: Thanks so much for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=find out where the parkside police statio. C2 goal=request_info. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search; destination=find out where the parkside police statio; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm trying to find out where the Parkside Police Station is.\nChunk 2: Can you help me?\nChunk 3: That's all I needed.\nChunk 4: Thanks so much for your help!", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: find out where the parkside police statio. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is request info.. destination: find out where the parkside police statio..", "trace": "C1 domain=train; goal=search; destination+=find out where the parkside police statio. C2 goal=request_info. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm trying to find out where the Parkside Police Station is.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: find out where the parkside police statio..", "trace": "domain=train; goal=search; destination+=find out where the parkside police statio."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you help me?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That's all I needed.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks so much for your help!", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is find out where the parkside police statio. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search; destination=find out where the parkside police statio; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002624", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: It should be in the east part of town.\nChunk 3: Is that because there are no options without internet?\nChunk 4: I can stay in a place with internet if there are no other options, but I do need free parking It doesn't matter.\nChunk 5: I'd like 4 stars though Sure.\nChunk 6: What is the hotel type and address please No thank you.\nChunk 7: I also need a train that arrives by 19:45 and departs from Cambridge.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=east. C3 amenities+=internet. C4 amenities+=parking, free parking. C5 stars+=4 stars. C6 goal=request_info; requested_info+=address. C7 domain=train; time+=19:45.", "deep_reasoning": "Need domain=hotel, train; goal=search, request_info; area=east; stars=4 stars; amenities=internet, parking, free parking; destination=find a hotel; requested_info=address; when=19:45.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a hotel.\nChunk 2: It should be in the east part of town.\nChunk 3: Is that because there are no options without internet?\nChunk 4: I can stay in a place with internet if there are no other options, but I do need free parking It doesn't matter.\nChunk 5: I'd like 4 stars though Sure.\nChunk 6: What is the hotel type and address please No thank you.\nChunk 7: I also need a train that arrives by 19:45 and departs from Cambridge."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=east. C3 amenities+=internet. C4 amenities+=parking, free parking. C5 stars+=4 stars. C6 goal=request_info; requested_info+=address. C7 domain=train; time+=19:45.\n\nDeep reasoning: Need domain=hotel, train; goal=search, request_info; area=east; stars=4 stars; amenities=internet, parking, free parking; destination=find a hotel; requested_info=address; when=19:45.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: It should be in the east part of town.\nChunk 3: Is that because there are no options without internet?\nChunk 4: I can stay in a place with internet if there are no other options, but I do need free parking It doesn't matter.\nChunk 5: I'd like 4 stars though Sure.\nChunk 6: What is the hotel type and address please No thank you.\nChunk 7: I also need a train that arrives by 19:45 and departs from Cambridge.", "input_token_count": 92, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, area: east. Next, amenities: internet. Next, amenities: parking. Next, star rating: 4 stars. Next, the goal is request info; requested information: address. Finally, the topic is train; time: 19:45. In summary, The overall topic is train. the goal is request info. hotel type: hotel; destination: find a hotel.; area: east.; amenities: internet., parking; star rating: 4 stars.; requested information: address.; time: 19:45..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=east. C3 amenities+=internet. C4 amenities+=parking, free parking. C5 stars+=4 stars. C6 goal=request_info; requested_info+=address. C7 domain=train; time+=19:45.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the east part of town.", "streaming_reasoning": "As more information arrives, area: east..", "trace": "area+=east."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Is that because there are no options without internet?", "streaming_reasoning": "As more information arrives, amenities: internet..", "trace": "amenities+=internet."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I can stay in a place with internet if there are no other options, but I do need free parking It doesn't matter.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'd like 4 stars though Sure.", "streaming_reasoning": "As more information arrives, star rating: 4 stars..", "trace": "stars+=4 stars."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What is the hotel type and address please No thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need a train that arrives by 19:45 and departs from Cambridge.", "streaming_reasoning": "Finally, the topic is train; time: 19:45..", "trace": "domain=train; time+=19:45."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is east; star rating is 4 stars; amenities is internet; destination is find a hotel; requested information is address; timing is 19:45.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel, train; goal=search, request_info; area=east; stars=4 stars; amenities=internet, parking, free parking; destination=find a hotel; requested_info=address; when=19:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002625", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: book it for 7 people and 5 nights starting from saturday.\nChunk 2: Can you find a restaurant called riverside brasserie for me, please?\nChunk 3: Yes, 11:15 7 people on Saturday.\nChunk 4: That will be all thank you for your help.\nChunk 5: I want to find a restaurant.\nChunk 6: Please make a booking.\nChunk 7: No thank you that will be all.", "streaming_reasoning": "C1 goal=booking; time+=7, 5; day+=saturday; party_size+=7 people; stay_length+=5 nights. C2 domain=restaurant; goal=search. C3 [SKIP: repeated_information]. C4 [SKIP: closing_only]. C5 [SKIP: repeated_information]. C6 intent=context_update. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=booking, search; party_size=7 people; stay_length=5 nights; when=saturday, 7, 5; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: book it for 7 people and 5 nights starting from saturday.\nChunk 2: Can you find a restaurant called riverside brasserie for me, please?\nChunk 3: Yes, 11:15 7 people on Saturday.\nChunk 4: That will be all thank you for your help.\nChunk 5: I want to find a restaurant.\nChunk 6: Please make a booking.\nChunk 7: No thank you that will be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=7, 5; day+=saturday; party_size+=7 people; stay_length+=5 nights. C2 domain=restaurant; goal=search. C3 [SKIP: repeated_information]. C4 [SKIP: closing_only]. C5 [SKIP: repeated_information]. C6 intent=context_update. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=booking, search; party_size=7 people; stay_length=5 nights; when=saturday, 7, 5; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: book it for 7 people and 5 nights starting from saturday.\nChunk 2: Can you find a restaurant called riverside brasserie for me, please?\nChunk 3: Yes, 11:15 7 people on Saturday.\nChunk 4: That will be all thank you for your help.\nChunk 5: I want to find a restaurant.\nChunk 6: Please make a booking.\nChunk 7: No thank you that will be all.", "input_token_count": 69, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 7; day: saturday; party size: 7 people; stay length: 5 nights. Next, the topic is restaurant; the goal is search. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is restaurant. the goal is search.. time: 7; day: saturday; party size: 7 people; stay length: 5 nights.; intent: context_update..", "trace": "C1 goal=booking; time+=7, 5; day+=saturday; party_size+=7 people; stay_length+=5 nights. C2 domain=restaurant; goal=search. C3 [SKIP: repeated_information]. C4 [SKIP: closing_only]. C5 [SKIP: repeated_information]. C6 intent=context_update. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "book it for 7 people and 5 nights starting from saturday.", "streaming_reasoning": "Initially, the goal is booking; time: 7; day: saturday; party size: 7 people; stay length: 5 nights..", "trace": "goal=booking; time+=7, 5; day+=saturday; party_size+=7 people; stay_length+=5 nights."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you find a restaurant called riverside brasserie for me, please?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, 11:15 7 people on Saturday.", "streaming_reasoning": "The content at C3 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That will be all thank you for your help.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "The content at C5 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No thank you that will be all.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: party size is 7 people; stay length is 5 nights; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=booking, search; party_size=7 people; stay_length=5 nights; when=saturday, 7, 5; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002626", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: Can you please help me?\nChunk 3: I'm looking for information on Great Saint Mary's Church.\nChunk 4: Thanks very much, that's all I need for now Goodbye.", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 goal=search. C3 intent=context_update. C4 [SKIP: closing_only].", "deep_reasoning": "Need goal=search; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi!\nChunk 2: Can you please help me?\nChunk 3: I'm looking for information on Great Saint Mary's Church.\nChunk 4: Thanks very much, that's all I need for now Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 goal=search. C3 intent=context_update. C4 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: Can you please help me?\nChunk 3: I'm looking for information on Great Saint Mary's Church.\nChunk 4: Thanks very much, that's all I need for now Goodbye.", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or greeting_only. In summary, the goal is search.. intent: context_update..", "trace": "C1 [SKIP: greeting_only]. C2 goal=search. C3 intent=context_update. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi!", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you please help me?", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm looking for information on Great Saint Mary's Church.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks very much, that's all I need for now Goodbye.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002627", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi I was just robbed...\nChunk 2: Can I get some help?\nChunk 3: Thank you, could you also give me the postcode?\nChunk 4: No, that's it, thanks.", "streaming_reasoning": "C1 intent=context_update. C2 goal=request_info. C3 requested_info+=postcode. C4 goal=modify_constraint.", "deep_reasoning": "Need goal=search, request_info; requested_info=postcode.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi I was just robbed...\nChunk 2: Can I get some help?\nChunk 3: Thank you, could you also give me the postcode?\nChunk 4: No, that's it, thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=request_info. C3 requested_info+=postcode. C4 goal=modify_constraint.\n\nDeep reasoning: Need goal=search, request_info; requested_info=postcode.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi I was just robbed...\nChunk 2: Can I get some help?\nChunk 3: Thank you, could you also give me the postcode?\nChunk 4: No, that's it, thanks.", "input_token_count": 31, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is request info. Next, requested information: postcode. Finally, the goal is modify constraint. In summary, the goal is modify constraint.. intent: context_update.; requested information: postcode..", "trace": "C1 intent=context_update. C2 goal=request_info. C3 requested_info+=postcode. C4 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi I was just robbed...", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I get some help?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you, could you also give me the postcode?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, that's it, thanks.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "Need goal=search, request_info; requested_info=postcode.", "answer": "I can help with that and include the postcode once I find the matching option."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002628", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you help me find a moderate priced restaurant in the centre?\nChunk 2: Is there anything cheap in the town centre?\nChunk 3: I want to find a moderate restaurant.\nChunk 4: It should be in the centre part of town.\nChunk 5: I also need the price Please surprise me.\nChunk 6: Can I have their phone number and address please?\nChunk 7: No, I think I have everything I need.\nChunk 8: Thanks.\nChunk 9: Bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 price+=cheap. C3 [SKIP: repeated_information]. C4 intent=context_update. C5 requested_info+=price. C6 goal=request_info; requested_info+=address, phone. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=centre; price=moderate, cheap; requested_info=price, address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Could you help me find a moderate priced restaurant in the centre?\nChunk 2: Is there anything cheap in the town centre?\nChunk 3: I want to find a moderate restaurant.\nChunk 4: It should be in the centre part of town.\nChunk 5: I also need the price Please surprise me.\nChunk 6: Can I have their phone number and address please?\nChunk 7: No, I think I have everything I need.\nChunk 8: Thanks.\nChunk 9: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 price+=cheap. C3 [SKIP: repeated_information]. C4 intent=context_update. C5 requested_info+=price. C6 goal=request_info; requested_info+=address, phone. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=centre; price=moderate, cheap; requested_info=price, address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you help me find a moderate priced restaurant in the centre?\nChunk 2: Is there anything cheap in the town centre?\nChunk 3: I want to find a moderate restaurant.\nChunk 4: It should be in the centre part of town.\nChunk 5: I also need the price Please surprise me.\nChunk 6: Can I have their phone number and address please?\nChunk 7: No, I think I have everything I need.\nChunk 8: Thanks.\nChunk 9: Bye.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: moderate. Next, price: cheap. Next, intent: context_update. Next, requested information: price. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only or repeated_information or thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: centre; price: moderate., cheap.; intent: context_update.; requested information: price., address.", "trace": "C1 domain=restaurant; goal=search; area+=centre; price+=moderate. C2 price+=cheap. C3 [SKIP: repeated_information]. C4 intent=context_update. C5 requested_info+=price. C6 goal=request_info; requested_info+=address, phone. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Could you help me find a moderate priced restaurant in the centre?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: moderate..", "trace": "domain=restaurant; goal=search; area+=centre; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there anything cheap in the town centre?", "streaming_reasoning": "As more information arrives, price: cheap..", "trace": "price+=cheap."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a moderate restaurant.", "streaming_reasoning": "The content at C3 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the price Please surprise me.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I have their phone number and address please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, I think I have everything I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Bye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is moderate; requested information is price. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=centre; price=moderate, cheap; requested_info=price, address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002629", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a train from Cambridge going to stansted airport on wednesday.\nChunk 2: I would like to arrive by 08:00 Yes please.\nChunk 3: Can you also please confirm the train ID, price, and departure time for me Thank you Awesome.\nChunk 4: Could you also suggest a museum for me to visit?\nChunk 5: I'm thinking in the east?\nChunk 6: Can I get the address and and postal code for the Cambridge Artworks please Great, thank you.\nChunk 7: I don't need anything else.\nChunk 8: Bye!", "streaming_reasoning": "C1 domain=train; goal=search; day+=wednesday; destination+=stansted airport; departure+=cambridge. C2 time+=08:00; destination+=arrive by 08:00 yes please; acceptance=selected_option. C3 requested_info+=price. C4 domain=attraction; goal=recommendation; destination+=visit. C5 area+=east. C6 goal=request_info; requested_info+=address, postcode. C7 goal=compare_alternative. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, attraction; goal=search, recommendation, request_info, compare_alternative; area=east; destination=stansted airport, arrive by 08:00 yes please, visit; departure=cambridge; requested_info=price, address, postcode; when=wednesday, 08:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a train from Cambridge going to stansted airport on wednesday.\nChunk 2: I would like to arrive by 08:00 Yes please.\nChunk 3: Can you also please confirm the train ID, price, and departure time for me Thank you Awesome.\nChunk 4: Could you also suggest a museum for me to visit?\nChunk 5: I'm thinking in the east?\nChunk 6: Can I get the address and and postal code for the Cambridge Artworks please Great, thank you.\nChunk 7: I don't need anything else.\nChunk 8: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=wednesday; destination+=stansted airport; departure+=cambridge. C2 time+=08:00; destination+=arrive by 08:00 yes please; acceptance=selected_option. C3 requested_info+=price. C4 domain=attraction; goal=recommendation; destination+=visit. C5 area+=east. C6 goal=request_info; requested_info+=address, postcode. C7 goal=compare_alternative. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, attraction; goal=search, recommendation, request_info, compare_alternative; area=east; destination=stansted airport, arrive by 08:00 yes please, visit; departure=cambridge; requested_info=price, address, postcode; when=wednesday, 08:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a train from Cambridge going to stansted airport on wednesday.\nChunk 2: I would like to arrive by 08:00 Yes please.\nChunk 3: Can you also please confirm the train ID, price, and departure time for me Thank you Awesome.\nChunk 4: Could you also suggest a museum for me to visit?\nChunk 5: I'm thinking in the east?\nChunk 6: Can I get the address and and postal code for the Cambridge Artworks please Great, thank you.\nChunk 7: I don't need anything else.\nChunk 8: Bye!", "input_token_count": 93, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: wednesday; destination: stansted airport; departure point: cambridge. Next, time: 08:00; destination: arrive by 08:00 yes please; acceptance: selected_option. Next, requested information: price. Next, the topic is attraction; the goal is recommendation; destination: visit. Next, area: east. Next, the goal is request info; requested information: address. Finally, the goal is compare alternative.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is compare alternative.. day: wednesday; destination: stansted airport, arrive by 08:00 yes please, visit.; departure point: cambridge.; time: 08:00; acceptance: selected_option.; requested information: price., address; area: east..", "trace": "C1 domain=train; goal=search; day+=wednesday; destination+=stansted airport; departure+=cambridge. C2 time+=08:00; destination+=arrive by 08:00 yes please; acceptance=selected_option. C3 requested_info+=price. C4 domain=attraction; goal=recommendation; destination+=visit. C5 area+=east. C6 goal=request_info; requested_info+=address, postcode. C7 goal=compare_alternative. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a train from Cambridge going to stansted airport on wednesday.", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: wednesday; destination: stansted airport; departure point: cambridge..", "trace": "domain=train; goal=search; day+=wednesday; destination+=stansted airport; departure+=cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to arrive by 08:00 Yes please.", "streaming_reasoning": "As more information arrives, time: 08:00; destination: arrive by 08:00 yes please; acceptance: selected_option..", "trace": "time+=08:00; destination+=arrive by 08:00 yes please; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you also please confirm the train ID, price, and departure time for me Thank you Awesome.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you also suggest a museum for me to visit?", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is recommendation; destination: visit..", "trace": "domain=attraction; goal=recommendation; destination+=visit."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm thinking in the east?", "streaming_reasoning": "As more information arrives, area: east..", "trace": "area+=east."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I get the address and and postal code for the Cambridge Artworks please Great, thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I don't need anything else.", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Bye!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is east; destination is stansted airport; departure point is cambridge; requested information is price; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=search, recommendation, request_info, compare_alternative; area=east; destination=stansted airport, arrive by 08:00 yes please, visit; departure=cambridge; requested_info=price, address, postcode; when=wednesday, 08:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001773", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I feel surprise when new gifts are offer me anyone.\nChunk 2: My experience is too much happier when i am surprise.\nChunk 3: You like being surprised?\nChunk 4: yes.", "streaming_reasoning": "C1 cause=new gifts are offer me anyone; need=encouragement. C2 emotion=stressed; cause=My experience is too much happier when i am surprise; need=validation. C3 support_signal=received. C4 [SKIP: acknowledgement_only].", "deep_reasoning": "User feels stressed after My experience is too much happier when i am surprise and needs validation.", "answer": "It makes sense to feel stressed after My experience is too much happier when i am surprise. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I feel surprise when new gifts are offer me anyone.\nChunk 2: My experience is too much happier when i am surprise.\nChunk 3: You like being surprised?\nChunk 4: yes."}, {"role": "assistant", "content": "Streaming reasoning: C1 cause=new gifts are offer me anyone; need=encouragement. C2 emotion=stressed; cause=My experience is too much happier when i am surprise; need=validation. C3 support_signal=received. C4 [SKIP: acknowledgement_only].\n\nDeep reasoning: User feels stressed after My experience is too much happier when i am surprise and needs validation.\n\nAnswer: It makes sense to feel stressed after My experience is too much happier when i am surprise. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I feel surprise when new gifts are offer me anyone.\nChunk 2: My experience is too much happier when i am surprise.\nChunk 3: You like being surprised?\nChunk 4: yes.", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user mentions new gifts are offer me anyone; the user needs encouragement. Next, the user expresses stressed about My experience is too much happier when i am surprise; the user needs validation. Finally, the user signals support or acknowledgment.  Some chunks were skipped because they contained acknowledgement_only.", "trace": "C1 cause=new gifts are offer me anyone; need=encouragement. C2 emotion=stressed; cause=My experience is too much happier when i am surprise; need=validation. C3 support_signal=received. C4 [SKIP: acknowledgement_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I feel surprise when new gifts are offer me anyone.", "streaming_reasoning": "Initially, the user mentions new gifts are offer me anyone; the user needs encouragement..", "trace": "cause=new gifts are offer me anyone; need=encouragement."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "My experience is too much happier when i am surprise.", "streaming_reasoning": "As more information arrives, the user expresses stressed about My experience is too much happier when i am surprise; the user needs validation..", "trace": "emotion=stressed; cause=My experience is too much happier when i am surprise; need=validation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "You like being surprised?", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "yes.", "streaming_reasoning": "The content at C4 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}]}, "output": {"deep_reasoning": "User feels stressed after My experience is too much happier when i am surprise and needs validation.", "answer": "It makes sense to feel stressed after My experience is too much happier when i am surprise. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002631", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to make a booking for 2 people and 2 nights starting from friday Thank you.\nChunk 2: Do you have information on the Pipasha restaurant?\nChunk 3: What is the postcode to that place?\nChunk 4: I'd also like to book a taxi between my hotel and the restaurant.\nChunk 5: I would like to leave the hotel by 01:00.\nChunk 6: Thank you, that's all I need today.", "streaming_reasoning": "C1 goal=booking; time+=2; day+=friday; party_size+=2 people; stay_length+=2 nights. C2 domain=restaurant. C3 goal=request_info; destination+=that place; requested_info+=postcode. C4 domain=taxi; hotel_type+=hotel. C5 time+=01:00; destination+=leave the hotel by 01:00. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel, taxi; goal=booking, request_info; party_size=2 people; stay_length=2 nights; destination=that place, leave the hotel by 01:00; requested_info=postcode; when=friday, 2, 01:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to make a booking for 2 people and 2 nights starting from friday Thank you.\nChunk 2: Do you have information on the Pipasha restaurant?\nChunk 3: What is the postcode to that place?\nChunk 4: I'd also like to book a taxi between my hotel and the restaurant.\nChunk 5: I would like to leave the hotel by 01:00.\nChunk 6: Thank you, that's all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=2; day+=friday; party_size+=2 people; stay_length+=2 nights. C2 domain=restaurant. C3 goal=request_info; destination+=that place; requested_info+=postcode. C4 domain=taxi; hotel_type+=hotel. C5 time+=01:00; destination+=leave the hotel by 01:00. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel, taxi; goal=booking, request_info; party_size=2 people; stay_length=2 nights; destination=that place, leave the hotel by 01:00; requested_info=postcode; when=friday, 2, 01:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to make a booking for 2 people and 2 nights starting from friday Thank you.\nChunk 2: Do you have information on the Pipasha restaurant?\nChunk 3: What is the postcode to that place?\nChunk 4: I'd also like to book a taxi between my hotel and the restaurant.\nChunk 5: I would like to leave the hotel by 01:00.\nChunk 6: Thank you, that's all I need today.", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 2; day: friday; party size: 2 people; stay length: 2 nights. Next, the topic is restaurant. Next, the goal is request info; destination: that place; requested information: postcode. Next, the topic is taxi; hotel type: hotel. Finally, time: 01:00; destination: leave the hotel by 01:00.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is request info. time: 2, 01:00; day: friday; party size: 2 people; stay length: 2 nights.; destination: that place, leave the hotel by 01:00.; requested information: postcode.; hotel type: hotel..", "trace": "C1 goal=booking; time+=2; day+=friday; party_size+=2 people; stay_length+=2 nights. C2 domain=restaurant. C3 goal=request_info; destination+=that place; requested_info+=postcode. C4 domain=taxi; hotel_type+=hotel. C5 time+=01:00; destination+=leave the hotel by 01:00. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to make a booking for 2 people and 2 nights starting from friday Thank you.", "streaming_reasoning": "Initially, the goal is booking; time: 2; day: friday; party size: 2 people; stay length: 2 nights..", "trace": "goal=booking; time+=2; day+=friday; party_size+=2 people; stay_length+=2 nights."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do you have information on the Pipasha restaurant?", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the postcode to that place?", "streaming_reasoning": "As more information arrives, the goal is request info; destination: that place; requested information: postcode..", "trace": "goal=request_info; destination+=that place; requested_info+=postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd also like to book a taxi between my hotel and the restaurant.", "streaming_reasoning": "As more information arrives, the topic is taxi; hotel type: hotel..", "trace": "domain=taxi; hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like to leave the hotel by 01:00.", "streaming_reasoning": "As more information arrives, time: 01:00; destination: leave the hotel by 01:00..", "trace": "time+=01:00; destination+=leave the hotel by 01:00."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you, that's all I need today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: party size is 2 people; stay length is 2 nights; destination is that place; requested information is postcode; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel, taxi; goal=booking, request_info; party_size=2 people; stay_length=2 nights; destination=that place, leave the hotel by 01:00; requested_info=postcode; when=friday, 2, 01:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002632", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would prefer you to check another area, please.\nChunk 2: Can you search for one that is cheap in price then?\nChunk 3: I need something in the cheap price range with other restrictions retained.\nChunk 4: Are there any cheap 0 star hotels in the north?\nChunk 5: Can you book that for 8 people for 1 night since 5 nights did not work earlier?\nChunk 6: That would be it Thank you.", "streaming_reasoning": "C1 goal=compare_alternative; destination+=check another area. C2 goal=search; price+=cheap; requested_info+=price. C3 intent=context_update. C4 area+=north; hotel_type+=hotel; stars+=0 stars. C5 goal=booking; party_size+=8 people; stay_length+=1 nights. C6 intent=context_update.", "deep_reasoning": "Need goal=compare_alternative, search, booking; area=north; price=cheap; party_size=8 people; stay_length=1 nights; stars=0 stars; destination=check another area; requested_info=price.", "answer": "I can help with that and include the price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would prefer you to check another area, please.\nChunk 2: Can you search for one that is cheap in price then?\nChunk 3: I need something in the cheap price range with other restrictions retained.\nChunk 4: Are there any cheap 0 star hotels in the north?\nChunk 5: Can you book that for 8 people for 1 night since 5 nights did not work earlier?\nChunk 6: That would be it Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=compare_alternative; destination+=check another area. C2 goal=search; price+=cheap; requested_info+=price. C3 intent=context_update. C4 area+=north; hotel_type+=hotel; stars+=0 stars. C5 goal=booking; party_size+=8 people; stay_length+=1 nights. C6 intent=context_update.\n\nDeep reasoning: Need goal=compare_alternative, search, booking; area=north; price=cheap; party_size=8 people; stay_length=1 nights; stars=0 stars; destination=check another area; requested_info=price.\n\nAnswer: I can help with that and include the price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would prefer you to check another area, please.\nChunk 2: Can you search for one that is cheap in price then?\nChunk 3: I need something in the cheap price range with other restrictions retained.\nChunk 4: Are there any cheap 0 star hotels in the north?\nChunk 5: Can you book that for 8 people for 1 night since 5 nights did not work earlier?\nChunk 6: That would be it Thank you.", "input_token_count": 77, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is compare alternative; destination: check another area. Next, the goal is search; price: cheap; requested information: price. Next, intent: context_update. Next, area: north; hotel type: hotel; star rating: 0 stars. Next, the goal is booking; party size: 8 people; stay length: 1 nights. Finally, intent: context_update. In summary, the goal is booking. destination: check another area.; price: cheap; requested information: price.; intent: context_update.; area: north; hotel type: hotel; star rating: 0 stars.; party size: 8 people; stay length: 1 nights..", "trace": "C1 goal=compare_alternative; destination+=check another area. C2 goal=search; price+=cheap; requested_info+=price. C3 intent=context_update. C4 area+=north; hotel_type+=hotel; stars+=0 stars. C5 goal=booking; party_size+=8 people; stay_length+=1 nights. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would prefer you to check another area, please.", "streaming_reasoning": "Initially, the goal is compare alternative; destination: check another area..", "trace": "goal=compare_alternative; destination+=check another area."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you search for one that is cheap in price then?", "streaming_reasoning": "As more information arrives, the goal is search; price: cheap; requested information: price..", "trace": "goal=search; price+=cheap; requested_info+=price."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need something in the cheap price range with other restrictions retained.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Are there any cheap 0 star hotels in the north?", "streaming_reasoning": "As more information arrives, area: north; hotel type: hotel; star rating: 0 stars..", "trace": "area+=north; hotel_type+=hotel; stars+=0 stars."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you book that for 8 people for 1 night since 5 nights did not work earlier?", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 8 people; stay length: 1 nights..", "trace": "goal=booking; party_size+=8 people; stay_length+=1 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That would be it Thank you.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "Need goal=compare_alternative, search, booking; area=north; price=cheap; party_size=8 people; stay_length=1 nights; stars=0 stars; destination=check another area; requested_info=price.", "answer": "I can help with that and include the price once I find the matching option."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002633", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a moderately priced restaurant Turkish food.\nChunk 2: Yes, please give me the one Turkish food restaurant's phone number and address please thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=turkish; price+=moderate. C2 goal=confirm_booking; requested_info+=address, phone; acceptance=selected_option.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, confirm_booking; food=turkish; price=moderate; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a moderately priced restaurant Turkish food.\nChunk 2: Yes, please give me the one Turkish food restaurant's phone number and address please thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=turkish; price+=moderate. C2 goal=confirm_booking; requested_info+=address, phone; acceptance=selected_option.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, confirm_booking; food=turkish; price=moderate; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a moderately priced restaurant Turkish food.\nChunk 2: Yes, please give me the one Turkish food restaurant's phone number and address please thank you.", "input_token_count": 30, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: turkish; price: moderate. Finally, the goal is confirm booking; requested information: address; acceptance: selected_option. In summary, The overall topic is restaurant. the goal is confirm booking. cuisine: turkish; price: moderate.; requested information: address; acceptance: selected_option..", "trace": "C1 domain=restaurant; goal=search; cuisine+=turkish; price+=moderate. C2 goal=confirm_booking; requested_info+=address, phone; acceptance=selected_option.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a moderately priced restaurant Turkish food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: turkish; price: moderate..", "trace": "domain=restaurant; goal=search; cuisine+=turkish; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, please give me the one Turkish food restaurant's phone number and address please thank you.", "streaming_reasoning": "Finally, the goal is confirm booking; requested information: address; acceptance: selected_option..", "trace": "goal=confirm_booking; requested_info+=address, phone; acceptance=selected_option."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is turkish; price is moderate; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, confirm_booking; food=turkish; price=moderate; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002634", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I'd like to reserve it for 6 people for 4 nights starting Sunday, please.\nChunk 2: I am also looking for a train into cambridge the same day please.\nChunk 3: Sunday as well, please.\nChunk 4: Yes, I need to leave Leicester after 11:00.\nChunk 5: Heading to Cambridge for the day.\nChunk 6: Okay.\nChunk 7: Can you purchase tickets for me.\nChunk 8: There will 6 of us.\nChunk 9: Yes.\nChunk 10: Thank you for your help.", "streaming_reasoning": "C1 goal=booking; time+=6, 4; day+=sunday; party_size+=6 people; stay_length+=4 nights; destination+=reserve it for 6 people for 4 nights star; goal=confirm_booking. C2 domain=train; goal=search. C3 intent=context_update. C4 time+=11:00; destination+=leave leicester after 11:00; goal=confirm_booking. C5 destination+=cambridge for the day. C6 [SKIP: backchannel_only]. C7 intent=context_update. C8 intent=context_update. C9 goal=confirm_booking. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=booking, search; party_size=6 people; stay_length=4 nights; destination=reserve it for 6 people for 4 nights star, leave leicester after 11:00, cambridge for the day; when=sunday, 6, 4, 11:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I'd like to reserve it for 6 people for 4 nights starting Sunday, please.\nChunk 2: I am also looking for a train into cambridge the same day please.\nChunk 3: Sunday as well, please.\nChunk 4: Yes, I need to leave Leicester after 11:00.\nChunk 5: Heading to Cambridge for the day.\nChunk 6: Okay.\nChunk 7: Can you purchase tickets for me.\nChunk 8: There will 6 of us.\nChunk 9: Yes.\nChunk 10: Thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=6, 4; day+=sunday; party_size+=6 people; stay_length+=4 nights; destination+=reserve it for 6 people for 4 nights star; goal=confirm_booking. C2 domain=train; goal=search. C3 intent=context_update. C4 time+=11:00; destination+=leave leicester after 11:00; goal=confirm_booking. C5 destination+=cambridge for the day. C6 [SKIP: backchannel_only]. C7 intent=context_update. C8 intent=context_update. C9 goal=confirm_booking. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=booking, search; party_size=6 people; stay_length=4 nights; destination=reserve it for 6 people for 4 nights star, leave leicester after 11:00, cambridge for the day; when=sunday, 6, 4, 11:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I'd like to reserve it for 6 people for 4 nights starting Sunday, please.\nChunk 2: I am also looking for a train into cambridge the same day please.\nChunk 3: Sunday as well, please.\nChunk 4: Yes, I need to leave Leicester after 11:00.\nChunk 5: Heading to Cambridge for the day.\nChunk 6: Okay.\nChunk 7: Can you purchase tickets for me.\nChunk 8: There will 6 of us.\nChunk 9: Yes.\nChunk 10: Thank you for your help.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is confirm booking.; time: 6; day: sunday; party size: 6 people; stay length: 4 nights; destination: reserve it for 6 people for 4 nights star. Next, the topic is train; the goal is search. Next, intent: context_update. Next, the goal is confirm booking.; time: 11:00; destination: leave leicester after 11:00. Next, destination: cambridge for the day. Next, intent: context_update. Next, intent: context_update. Finally, the goal is confirm booking.  Some chunks were skipped because they contained backchannel_only or thanks_only. In summary, The overall topic is train. the goal is confirm booking.. time: 6, 11:00; day: sunday; party size: 6 people; stay length: 4 nights; destination: reserve it for 6 people for 4 nights star, leave leicester after 11:00, cambridge for the day.; intent: context_update..", "trace": "C1 goal=booking; time+=6, 4; day+=sunday; party_size+=6 people; stay_length+=4 nights; destination+=reserve it for 6 people for 4 nights star; goal=confirm_booking. C2 domain=train; goal=search. C3 intent=context_update. C4 time+=11:00; destination+=leave leicester after 11:00; goal=confirm_booking. C5 destination+=cambridge for the day. C6 [SKIP: backchannel_only]. C7 intent=context_update. C8 intent=context_update. C9 goal=confirm_booking. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I'd like to reserve it for 6 people for 4 nights starting Sunday, please.", "streaming_reasoning": "Initially, the goal is confirm booking.; time: 6; day: sunday; party size: 6 people; stay length: 4 nights; destination: reserve it for 6 people for 4 nights star.", "trace": "goal=booking; time+=6, 4; day+=sunday; party_size+=6 people; stay_length+=4 nights; destination+=reserve it for 6 people for 4 nights star; goal=confirm_booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also looking for a train into cambridge the same day please.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Sunday as well, please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I need to leave Leicester after 11:00.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 11:00; destination: leave leicester after 11:00.", "trace": "time+=11:00; destination+=leave leicester after 11:00; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Heading to Cambridge for the day.", "streaming_reasoning": "As more information arrives, destination: cambridge for the day..", "trace": "destination+=cambridge for the day."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Okay.", "streaming_reasoning": "The content at C6 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can you purchase tickets for me.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "There will 6 of us.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Yes.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: party size is 6 people; stay length is 4 nights; destination is reserve it for 6 people for 4 nights star; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, search; party_size=6 people; stay_length=4 nights; destination=reserve it for 6 people for 4 nights star, leave leicester after 11:00, cambridge for the day; when=sunday, 6, 4, 11:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002635", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sorry, I was just kidding about the hating internet part.\nChunk 2: I do need a place that has free wifi.\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 2.\nChunk 5: Please make a booking.\nChunk 6: Thank you so much for all your help.\nChunk 7: I am looking for a particular attraction.\nChunk 8: regency gallery, do you have their phone number?\nChunk 9: OK, thank you so much, that is all that I need.", "streaming_reasoning": "C1 amenities+=internet. C2 goal=search; amenities+=wifi. C3 party_size+=6 people. C4 time+=6, 2; day+=monday. C5 goal=booking. C6 [SKIP: thanks_only]. C7 domain=attraction. C8 goal=request_info; requested_info+=phone. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction; goal=search, booking, request_info; party_size=6 people; amenities=internet, wifi; requested_info=phone; when=monday, 6, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sorry, I was just kidding about the hating internet part.\nChunk 2: I do need a place that has free wifi.\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 2.\nChunk 5: Please make a booking.\nChunk 6: Thank you so much for all your help.\nChunk 7: I am looking for a particular attraction.\nChunk 8: regency gallery, do you have their phone number?\nChunk 9: OK, thank you so much, that is all that I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 amenities+=internet. C2 goal=search; amenities+=wifi. C3 party_size+=6 people. C4 time+=6, 2; day+=monday. C5 goal=booking. C6 [SKIP: thanks_only]. C7 domain=attraction. C8 goal=request_info; requested_info+=phone. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction; goal=search, booking, request_info; party_size=6 people; amenities=internet, wifi; requested_info=phone; when=monday, 6, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sorry, I was just kidding about the hating internet part.\nChunk 2: I do need a place that has free wifi.\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 2.\nChunk 5: Please make a booking.\nChunk 6: Thank you so much for all your help.\nChunk 7: I am looking for a particular attraction.\nChunk 8: regency gallery, do you have their phone number?\nChunk 9: OK, thank you so much, that is all that I need.", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, amenities: internet. Next, the goal is search; amenities: wifi. Next, party size: 6 people. Next, time: 6; day: monday. Next, the goal is booking. Next, the topic is attraction. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction.. the goal is request info. amenities: internet., wifi.; party size: 6 people.; time: 6; day: monday.; requested information: phone..", "trace": "C1 amenities+=internet. C2 goal=search; amenities+=wifi. C3 party_size+=6 people. C4 time+=6, 2; day+=monday. C5 goal=booking. C6 [SKIP: thanks_only]. C7 domain=attraction. C8 goal=request_info; requested_info+=phone. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sorry, I was just kidding about the hating internet part.", "streaming_reasoning": "Initially, amenities: internet..", "trace": "amenities+=internet."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I do need a place that has free wifi.", "streaming_reasoning": "As more information arrives, the goal is search; amenities: wifi..", "trace": "goal=search; amenities+=wifi."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 6 people.", "streaming_reasoning": "As more information arrives, party size: 6 people..", "trace": "party_size+=6 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is monday, 6, 2.", "streaming_reasoning": "As more information arrives, time: 6; day: monday..", "trace": "time+=6, 2; day+=monday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you so much for all your help.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am looking for a particular attraction.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "regency gallery, do you have their phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "OK, thank you so much, that is all that I need.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: party size is 6 people; amenities is internet; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, booking, request_info; party_size=6 people; amenities=internet, wifi; requested_info=phone; when=monday, 6, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002636", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for cheap eats in the centre.\nChunk 2: I am interested in Chinese food Yes, please!\nChunk 3: Can I have a table for 1 at Charlie Chan on Sunday at 14:15?\nChunk 4: No, you've been very helpful.\nChunk 5: Have a good day.", "streaming_reasoning": "C1 goal=search; area+=centre; price+=cheap. C2 domain=restaurant; cuisine+=chinese; acceptance=selected_option. C3 goal=request_info; time+=1, 14:15; day+=sunday. C4 goal=modify_constraint. C5 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=centre; food=chinese; price=cheap; when=sunday, 1, 14:15.", "answer": "Got it. I will use restaurant, centre, chinese, cheap, sunday, 1, 14:15 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for cheap eats in the centre.\nChunk 2: I am interested in Chinese food Yes, please!\nChunk 3: Can I have a table for 1 at Charlie Chan on Sunday at 14:15?\nChunk 4: No, you've been very helpful.\nChunk 5: Have a good day."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre; price+=cheap. C2 domain=restaurant; cuisine+=chinese; acceptance=selected_option. C3 goal=request_info; time+=1, 14:15; day+=sunday. C4 goal=modify_constraint. C5 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=centre; food=chinese; price=cheap; when=sunday, 1, 14:15.\n\nAnswer: Got it. I will use restaurant, centre, chinese, cheap, sunday, 1, 14:15 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for cheap eats in the centre.\nChunk 2: I am interested in Chinese food Yes, please!\nChunk 3: Can I have a table for 1 at Charlie Chan on Sunday at 14:15?\nChunk 4: No, you've been very helpful.\nChunk 5: Have a good day.", "input_token_count": 50, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre; price: cheap. Next, the topic is restaurant; cuisine: chinese; acceptance: selected_option. Next, the goal is request info; time: 1; day: sunday. Next, the goal is modify constraint. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is modify constraint.. area: centre; price: cheap.; cuisine: chinese; acceptance: selected_option.; time: 1; day: sunday.; intent: context_update..", "trace": "C1 goal=search; area+=centre; price+=cheap. C2 domain=restaurant; cuisine+=chinese; acceptance=selected_option. C3 goal=request_info; time+=1, 14:15; day+=sunday. C4 goal=modify_constraint. C5 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for cheap eats in the centre.", "streaming_reasoning": "Initially, the goal is search; area: centre; price: cheap..", "trace": "goal=search; area+=centre; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am interested in Chinese food Yes, please!", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: chinese; acceptance: selected_option..", "trace": "domain=restaurant; cuisine+=chinese; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I have a table for 1 at Charlie Chan on Sunday at 14:15?", "streaming_reasoning": "As more information arrives, the goal is request info; time: 1; day: sunday..", "trace": "goal=request_info; time+=1, 14:15; day+=sunday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, you've been very helpful.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Have a good day.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; price is cheap; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use restaurant, centre, chinese, cheap, sunday, 1, 14:15 and move the task forward.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=centre; food=chinese; price=cheap; when=sunday, 1, 14:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002637", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to go to Peterborough.\nChunk 2: I am departing from Cambridge.\nChunk 3: ill travel on wednesday.\nChunk 4: get me the train ID and price.\nChunk 5: I would like to leave Cambridge after 09:45, please thanks for helping.\nChunk 6: No, I only needed the train info Thanks, again Goodbye.", "streaming_reasoning": "C1 goal=search; destination+=go to peterborough. C2 departure+=cambridge. C3 day+=wednesday. C4 domain=train; goal=request_info. C5 time+=09:45; destination+=leave cambridge after 09:45. C6 goal=modify_constraint.", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=go to peterborough, leave cambridge after 09:45; departure=cambridge; when=wednesday, 09:45.", "answer": "Got it. I will use train, wednesday, 09:45 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to go to Peterborough.\nChunk 2: I am departing from Cambridge.\nChunk 3: ill travel on wednesday.\nChunk 4: get me the train ID and price.\nChunk 5: I would like to leave Cambridge after 09:45, please thanks for helping.\nChunk 6: No, I only needed the train info Thanks, again Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; destination+=go to peterborough. C2 departure+=cambridge. C3 day+=wednesday. C4 domain=train; goal=request_info. C5 time+=09:45; destination+=leave cambridge after 09:45. C6 goal=modify_constraint.\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=go to peterborough, leave cambridge after 09:45; departure=cambridge; when=wednesday, 09:45.\n\nAnswer: Got it. I will use train, wednesday, 09:45 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to go to Peterborough.\nChunk 2: I am departing from Cambridge.\nChunk 3: ill travel on wednesday.\nChunk 4: get me the train ID and price.\nChunk 5: I would like to leave Cambridge after 09:45, please thanks for helping.\nChunk 6: No, I only needed the train info Thanks, again Goodbye.", "input_token_count": 57, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; destination: go to peterborough. Next, departure point: cambridge. Next, day: wednesday. Next, the topic is train; the goal is request info. Next, time: 09:45; destination: leave cambridge after 09:45. Finally, the goal is modify constraint. In summary, The overall topic is train. the goal is modify constraint.. destination: go to peterborough., leave cambridge after 09:45.; departure point: cambridge.; day: wednesday.; time: 09:45.", "trace": "C1 goal=search; destination+=go to peterborough. C2 departure+=cambridge. C3 day+=wednesday. C4 domain=train; goal=request_info. C5 time+=09:45; destination+=leave cambridge after 09:45. C6 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to go to Peterborough.", "streaming_reasoning": "Initially, the goal is search; destination: go to peterborough..", "trace": "goal=search; destination+=go to peterborough."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am departing from Cambridge.", "streaming_reasoning": "As more information arrives, departure point: cambridge..", "trace": "departure+=cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "ill travel on wednesday.", "streaming_reasoning": "As more information arrives, day: wednesday..", "trace": "day+=wednesday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "get me the train ID and price.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is request info..", "trace": "domain=train; goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like to leave Cambridge after 09:45, please thanks for helping.", "streaming_reasoning": "As more information arrives, time: 09:45; destination: leave cambridge after 09:45..", "trace": "time+=09:45; destination+=leave cambridge after 09:45."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, I only needed the train info Thanks, again Goodbye.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is go to peterborough; departure point is cambridge; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use train, wednesday, 09:45 and move the task forward.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=go to peterborough, leave cambridge after 09:45; departure=cambridge; when=wednesday, 09:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002639", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am from out of the area and would love some help finding a room somewhere in the city.\nChunk 2: I'd like it to include free parking and be in the north please.\nChunk 3: Is that a guesthouse?\nChunk 4: I would really like that.\nChunk 5: You certainly can, thank you.\nChunk 6: I will be the only guest and I'd like to check in for 2 nights starting Wednesday.\nChunk 7: Yes, 1 night would be fine.\nChunk 8: Great That's all, thanks!", "streaming_reasoning": "C1 domain=hotel; goal=search. C2 area+=north; amenities+=parking, free parking; destination+=include free parking and be in the north. C3 hotel_type+=guesthouse. C4 intent=context_update. C5 intent=context_update. C6 time+=2; day+=wednesday; stay_length+=2 nights; destination+=check in for 2 nights starting wednesday. C7 stay_length+=1 nights; acceptance=selected_option. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search; area=north; stay_length=2 nights, 1 nights; amenities=parking, free parking; destination=include free parking and be in the north, check in for 2 nights starting wednesday; when=wednesday, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am from out of the area and would love some help finding a room somewhere in the city.\nChunk 2: I'd like it to include free parking and be in the north please.\nChunk 3: Is that a guesthouse?\nChunk 4: I would really like that.\nChunk 5: You certainly can, thank you.\nChunk 6: I will be the only guest and I'd like to check in for 2 nights starting Wednesday.\nChunk 7: Yes, 1 night would be fine.\nChunk 8: Great That's all, thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search. C2 area+=north; amenities+=parking, free parking; destination+=include free parking and be in the north. C3 hotel_type+=guesthouse. C4 intent=context_update. C5 intent=context_update. C6 time+=2; day+=wednesday; stay_length+=2 nights; destination+=check in for 2 nights starting wednesday. C7 stay_length+=1 nights; acceptance=selected_option. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search; area=north; stay_length=2 nights, 1 nights; amenities=parking, free parking; destination=include free parking and be in the north, check in for 2 nights starting wednesday; when=wednesday, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am from out of the area and would love some help finding a room somewhere in the city.\nChunk 2: I'd like it to include free parking and be in the north please.\nChunk 3: Is that a guesthouse?\nChunk 4: I would really like that.\nChunk 5: You certainly can, thank you.\nChunk 6: I will be the only guest and I'd like to check in for 2 nights starting Wednesday.\nChunk 7: Yes, 1 night would be fine.\nChunk 8: Great That's all, thanks!", "input_token_count": 89, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search. Next, area: north; amenities: parking; destination: include free parking and be in the north. Next, hotel type: guesthouse. Next, intent: context_update. Next, intent: context_update. Next, time: 2; day: wednesday; stay length: 2 nights; destination: check in for 2 nights starting wednesday. Finally, stay length: 1 nights; acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is search.. area: north; amenities: parking; destination: include free parking and be in the north., check in for 2 nights starting wednesday.; hotel type: guesthouse.; intent: context_update.; time: 2; day: wednesday; stay length: 2 nights, 1 nights; acceptance: selected_option..", "trace": "C1 domain=hotel; goal=search. C2 area+=north; amenities+=parking, free parking; destination+=include free parking and be in the north. C3 hotel_type+=guesthouse. C4 intent=context_update. C5 intent=context_update. C6 time+=2; day+=wednesday; stay_length+=2 nights; destination+=check in for 2 nights starting wednesday. C7 stay_length+=1 nights; acceptance=selected_option. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am from out of the area and would love some help finding a room somewhere in the city.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search..", "trace": "domain=hotel; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like it to include free parking and be in the north please.", "streaming_reasoning": "As more information arrives, area: north; amenities: parking; destination: include free parking and be in the north..", "trace": "area+=north; amenities+=parking, free parking; destination+=include free parking and be in the north."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Is that a guesthouse?", "streaming_reasoning": "As more information arrives, hotel type: guesthouse..", "trace": "hotel_type+=guesthouse."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would really like that.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "You certainly can, thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I will be the only guest and I'd like to check in for 2 nights starting Wednesday.", "streaming_reasoning": "As more information arrives, time: 2; day: wednesday; stay length: 2 nights; destination: check in for 2 nights starting wednesday..", "trace": "time+=2; day+=wednesday; stay_length+=2 nights; destination+=check in for 2 nights starting wednesday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, 1 night would be fine.", "streaming_reasoning": "As more information arrives, stay length: 1 nights; acceptance: selected_option..", "trace": "stay_length+=1 nights; acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Great That's all, thanks!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; stay length is 2 nights; amenities is parking; destination is include free parking and be in the north; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search; area=north; stay_length=2 nights, 1 nights; amenities=parking, free parking; destination=include free parking and be in the north, check in for 2 nights starting wednesday; when=wednesday, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002640", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i need 15 tickets.\nChunk 2: I need to get the train ID.please.\nChunk 3: I also need an expensive place to eat in the centre of town.\nChunk 4: I'm not too picky.\nChunk 5: Can you recommend anything?\nChunk 6: Can I have the food type, postcode, and address, please?\nChunk 7: No thank you, that will be all for today.", "streaming_reasoning": "C1 goal=search. C2 domain=train; goal=request_info. C3 domain=restaurant; area+=centre; price+=expensive; destination+=eat in the centre of town. C4 goal=modify_constraint. C5 goal=recommendation. C6 requested_info+=address, postcode. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, restaurant; goal=search, request_info, recommendation; area=centre; price=expensive; destination=eat in the centre of town; requested_info=address, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i need 15 tickets.\nChunk 2: I need to get the train ID.please.\nChunk 3: I also need an expensive place to eat in the centre of town.\nChunk 4: I'm not too picky.\nChunk 5: Can you recommend anything?\nChunk 6: Can I have the food type, postcode, and address, please?\nChunk 7: No thank you, that will be all for today."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 domain=train; goal=request_info. C3 domain=restaurant; area+=centre; price+=expensive; destination+=eat in the centre of town. C4 goal=modify_constraint. C5 goal=recommendation. C6 requested_info+=address, postcode. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=search, request_info, recommendation; area=centre; price=expensive; destination=eat in the centre of town; requested_info=address, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i need 15 tickets.\nChunk 2: I need to get the train ID.please.\nChunk 3: I also need an expensive place to eat in the centre of town.\nChunk 4: I'm not too picky.\nChunk 5: Can you recommend anything?\nChunk 6: Can I have the food type, postcode, and address, please?\nChunk 7: No thank you, that will be all for today.", "input_token_count": 66, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, the topic is train; the goal is request info. Next, the topic is restaurant; area: centre; price: expensive; destination: eat in the centre of town. Next, the goal is modify constraint. Next, the goal is recommendation. Finally, requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is recommendation.. area: centre; price: expensive; destination: eat in the centre of town.; requested information: address.", "trace": "C1 goal=search. C2 domain=train; goal=request_info. C3 domain=restaurant; area+=centre; price+=expensive; destination+=eat in the centre of town. C4 goal=modify_constraint. C5 goal=recommendation. C6 requested_info+=address, postcode. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i need 15 tickets.", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to get the train ID.please.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is request info..", "trace": "domain=train; goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need an expensive place to eat in the centre of town.", "streaming_reasoning": "As more information arrives, the topic is restaurant; area: centre; price: expensive; destination: eat in the centre of town..", "trace": "domain=restaurant; area+=centre; price+=expensive; destination+=eat in the centre of town."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm not too picky.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you recommend anything?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I have the food type, postcode, and address, please?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No thank you, that will be all for today.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is centre; price is expensive; destination is eat in the centre of town; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=search, request_info, recommendation; area=centre; price=expensive; destination=eat in the centre of town; requested_info=address, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002641", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes that will be fine.\nChunk 2: Sorry, I'm looking for a 5 star hotel.\nChunk 3: Can you check for 4 stars instead please Thanks very much!\nChunk 4: What is their postcode and phone number?\nChunk 5: Did they have free parking?\nChunk 6: Okay, that's great to know.\nChunk 7: Thanks!\nChunk 8: I won't be needing anything else today.", "streaming_reasoning": "C1 acceptance=selected_option. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=5 stars. C3 goal=compare_alternative; stars+=4 stars. C4 goal=request_info; requested_info+=phone, postcode. C5 amenities+=parking, free parking. C6 destination+=know. C7 [SKIP: thanks_only]. C8 day+=today.", "deep_reasoning": "Need domain=hotel; goal=search, compare_alternative, request_info; stars=5 stars, 4 stars; amenities=parking, free parking; destination=know; requested_info=phone, postcode; when=today; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes that will be fine.\nChunk 2: Sorry, I'm looking for a 5 star hotel.\nChunk 3: Can you check for 4 stars instead please Thanks very much!\nChunk 4: What is their postcode and phone number?\nChunk 5: Did they have free parking?\nChunk 6: Okay, that's great to know.\nChunk 7: Thanks!\nChunk 8: I won't be needing anything else today."}, {"role": "assistant", "content": "Streaming reasoning: C1 acceptance=selected_option. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=5 stars. C3 goal=compare_alternative; stars+=4 stars. C4 goal=request_info; requested_info+=phone, postcode. C5 amenities+=parking, free parking. C6 destination+=know. C7 [SKIP: thanks_only]. C8 day+=today.\n\nDeep reasoning: Need domain=hotel; goal=search, compare_alternative, request_info; stars=5 stars, 4 stars; amenities=parking, free parking; destination=know; requested_info=phone, postcode; when=today; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes that will be fine.\nChunk 2: Sorry, I'm looking for a 5 star hotel.\nChunk 3: Can you check for 4 stars instead please Thanks very much!\nChunk 4: What is their postcode and phone number?\nChunk 5: Did they have free parking?\nChunk 6: Okay, that's great to know.\nChunk 7: Thanks!\nChunk 8: I won't be needing anything else today.", "input_token_count": 65, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, acceptance: selected_option. Next, the topic is hotel; the goal is search; hotel type: hotel; star rating: 5 stars. Next, the goal is compare alternative; star rating: 4 stars. Next, the goal is request info; requested information: phone. Next, amenities: parking. Next, destination: know. Finally, day: today.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is request info. acceptance: selected_option.; hotel type: hotel; star rating: 5 stars., 4 stars.; requested information: phone; amenities: parking; destination: know.; day: today..", "trace": "C1 acceptance=selected_option. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=5 stars. C3 goal=compare_alternative; stars+=4 stars. C4 goal=request_info; requested_info+=phone, postcode. C5 amenities+=parking, free parking. C6 destination+=know. C7 [SKIP: thanks_only]. C8 day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes that will be fine.", "streaming_reasoning": "Initially, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Sorry, I'm looking for a 5 star hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: hotel; star rating: 5 stars..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; stars+=5 stars."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you check for 4 stars instead please Thanks very much!", "streaming_reasoning": "As more information arrives, the goal is compare alternative; star rating: 4 stars..", "trace": "goal=compare_alternative; stars+=4 stars."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is their postcode and phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Did they have free parking?", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Okay, that's great to know.", "streaming_reasoning": "As more information arrives, destination: know..", "trace": "destination+=know."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I won't be needing anything else today.", "streaming_reasoning": "Finally, day: today..", "trace": "day+=today."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: star rating is 5 stars; amenities is parking; destination is know; requested information is phone; timing is today. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, compare_alternative, request_info; stars=5 stars, 4 stars; amenities=parking, free parking; destination=know; requested_info=phone, postcode; when=today; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002642", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like it to be in the west.\nChunk 2: That sounds like it will work.\nChunk 3: Can I book that for 3 nights starting Wednesday?\nChunk 4: I also am looking for somewhere to get afternoon tea.\nChunk 5: Let's try a Chinese restaurant instead.\nChunk 6: It is for 8 people.\nChunk 7: The time is wednesday, 8, 15:45.\nChunk 8: Please make a booking.\nChunk 9: That's all for today Thanks a ton.\nChunk 10: Bye!", "streaming_reasoning": "C1 area+=west; destination+=be in the west. C2 intent=context_update. C3 goal=request_info; time+=3; day+=wednesday; stay_length+=3 nights. C4 goal=search. C5 domain=restaurant; goal=compare_alternative; cuisine+=chinese. C6 party_size+=8 people. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=booking, request_info, search, compare_alternative; area=west; food=chinese; party_size=8 people; stay_length=3 nights; destination=be in the west; when=wednesday, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like it to be in the west.\nChunk 2: That sounds like it will work.\nChunk 3: Can I book that for 3 nights starting Wednesday?\nChunk 4: I also am looking for somewhere to get afternoon tea.\nChunk 5: Let's try a Chinese restaurant instead.\nChunk 6: It is for 8 people.\nChunk 7: The time is wednesday, 8, 15:45.\nChunk 8: Please make a booking.\nChunk 9: That's all for today Thanks a ton.\nChunk 10: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=west; destination+=be in the west. C2 intent=context_update. C3 goal=request_info; time+=3; day+=wednesday; stay_length+=3 nights. C4 goal=search. C5 domain=restaurant; goal=compare_alternative; cuisine+=chinese. C6 party_size+=8 people. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=booking, request_info, search, compare_alternative; area=west; food=chinese; party_size=8 people; stay_length=3 nights; destination=be in the west; when=wednesday, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like it to be in the west.\nChunk 2: That sounds like it will work.\nChunk 3: Can I book that for 3 nights starting Wednesday?\nChunk 4: I also am looking for somewhere to get afternoon tea.\nChunk 5: Let's try a Chinese restaurant instead.\nChunk 6: It is for 8 people.\nChunk 7: The time is wednesday, 8, 15:45.\nChunk 8: Please make a booking.\nChunk 9: That's all for today Thanks a ton.\nChunk 10: Bye!", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: west; destination: be in the west. Next, intent: context_update. Next, the goal is request info; time: 3; day: wednesday; stay length: 3 nights. Next, the goal is search. Next, the topic is restaurant; the goal is compare alternative; cuisine: chinese. Next, party size: 8 people. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is restaurant. the goal is compare alternative. area: west; destination: be in the west.; intent: context_update.; time: 3; day: wednesday; stay length: 3 nights.; cuisine: chinese.; party size: 8 people..", "trace": "C1 area+=west; destination+=be in the west. C2 intent=context_update. C3 goal=request_info; time+=3; day+=wednesday; stay_length+=3 nights. C4 goal=search. C5 domain=restaurant; goal=compare_alternative; cuisine+=chinese. C6 party_size+=8 people. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like it to be in the west.", "streaming_reasoning": "Initially, area: west; destination: be in the west..", "trace": "area+=west; destination+=be in the west."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "That sounds like it will work.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I book that for 3 nights starting Wednesday?", "streaming_reasoning": "As more information arrives, the goal is request info; time: 3; day: wednesday; stay length: 3 nights..", "trace": "goal=request_info; time+=3; day+=wednesday; stay_length+=3 nights."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also am looking for somewhere to get afternoon tea.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Let's try a Chinese restaurant instead.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is compare alternative; cuisine: chinese..", "trace": "domain=restaurant; goal=compare_alternative; cuisine+=chinese."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It is for 8 people.", "streaming_reasoning": "As more information arrives, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is wednesday, 8, 15:45.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That's all for today Thanks a ton.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Bye!", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: area is west; cuisine is chinese; party size is 8 people; stay length is 3 nights; destination is be in the west; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=booking, request_info, search, compare_alternative; area=west; food=chinese; party_size=8 people; stay_length=3 nights; destination=be in the west; when=wednesday, 3; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002643", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: please book me on the 15:39 train.\nChunk 2: No, just one ticket please Great.\nChunk 3: Can you also help me find out about a restaurant called charlie chan?\nChunk 4: It is for 7 people.\nChunk 5: The time is sunday, 7, 21:00.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: How about 20:00?\nChunk 9: I think that is it.\nChunk 10: Thanks so much for your help.", "streaming_reasoning": "C1 domain=train; goal=booking; time+=15:39. C2 goal=modify_constraint. C3 domain=restaurant; goal=search. C4 party_size+=7 people. C5 time+=7, 21:00; day+=sunday. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 goal=recommendation; time+=20:00. C9 intent=context_update. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, restaurant; goal=booking, search, request_info, recommendation; party_size=7 people; requested_info=reference_number; when=sunday, 15:39, 7, 21:00, 20:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: please book me on the 15:39 train.\nChunk 2: No, just one ticket please Great.\nChunk 3: Can you also help me find out about a restaurant called charlie chan?\nChunk 4: It is for 7 people.\nChunk 5: The time is sunday, 7, 21:00.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: How about 20:00?\nChunk 9: I think that is it.\nChunk 10: Thanks so much for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=booking; time+=15:39. C2 goal=modify_constraint. C3 domain=restaurant; goal=search. C4 party_size+=7 people. C5 time+=7, 21:00; day+=sunday. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 goal=recommendation; time+=20:00. C9 intent=context_update. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=booking, search, request_info, recommendation; party_size=7 people; requested_info=reference_number; when=sunday, 15:39, 7, 21:00, 20:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: please book me on the 15:39 train.\nChunk 2: No, just one ticket please Great.\nChunk 3: Can you also help me find out about a restaurant called charlie chan?\nChunk 4: It is for 7 people.\nChunk 5: The time is sunday, 7, 21:00.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: How about 20:00?\nChunk 9: I think that is it.\nChunk 10: Thanks so much for your help.", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is booking; time: 15:39. Next, the goal is modify constraint. Next, the topic is restaurant; the goal is search. Next, party size: 7 people. Next, time: 7; day: sunday. Next, intent: context_update. Next, the goal is request info; requested information: reference_number. Next, the goal is recommendation; time: 20:00. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is recommendation. time: 15:39., 7, 20:00.; party size: 7 people.; day: sunday.; intent: context_update.; requested information: reference_number..", "trace": "C1 domain=train; goal=booking; time+=15:39. C2 goal=modify_constraint. C3 domain=restaurant; goal=search. C4 party_size+=7 people. C5 time+=7, 21:00; day+=sunday. C6 intent=context_update. C7 goal=request_info; requested_info+=reference_number. C8 goal=recommendation; time+=20:00. C9 intent=context_update. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "please book me on the 15:39 train.", "streaming_reasoning": "Initially, the topic is train; the goal is booking; time: 15:39..", "trace": "domain=train; goal=booking; time+=15:39."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, just one ticket please Great.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you also help me find out about a restaurant called charlie chan?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It is for 7 people.", "streaming_reasoning": "As more information arrives, party size: 7 people..", "trace": "party_size+=7 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is sunday, 7, 21:00.", "streaming_reasoning": "As more information arrives, time: 7; day: sunday..", "trace": "time+=7, 21:00; day+=sunday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "How about 20:00?", "streaming_reasoning": "As more information arrives, the goal is recommendation; time: 20:00..", "trace": "goal=recommendation; time+=20:00."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I think that is it.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thanks so much for your help.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: party size is 7 people; requested information is reference_number; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=booking, search, request_info, recommendation; party_size=7 people; requested_info=reference_number; when=sunday, 15:39, 7, 21:00, 20:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002644", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No.\nChunk 2: Can you help me find a very cheap, not shabby hotel that has free parking?\nChunk 3: itshould be in the centre.\nChunk 4: Which one of them has free wifi?\nChunk 5: book for 2 people for 2 nights from wednesday.\nChunk 6: Sorry, can you actually book it for 3 people for 2 nights, please?\nChunk 7: Thank you that is all I needed.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel; amenities+=parking, free parking. C3 area+=centre. C4 amenities+=wifi. C5 goal=booking; day+=wednesday; party_size+=2 people; stay_length+=2 nights. C6 party_size+=3 people. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking; area=centre; price=cheap; party_size=2 people, 3 people; stay_length=2 nights; amenities=parking, free parking, wifi; when=wednesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No.\nChunk 2: Can you help me find a very cheap, not shabby hotel that has free parking?\nChunk 3: itshould be in the centre.\nChunk 4: Which one of them has free wifi?\nChunk 5: book for 2 people for 2 nights from wednesday.\nChunk 6: Sorry, can you actually book it for 3 people for 2 nights, please?\nChunk 7: Thank you that is all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel; amenities+=parking, free parking. C3 area+=centre. C4 amenities+=wifi. C5 goal=booking; day+=wednesday; party_size+=2 people; stay_length+=2 nights. C6 party_size+=3 people. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking; area=centre; price=cheap; party_size=2 people, 3 people; stay_length=2 nights; amenities=parking, free parking, wifi; when=wednesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No.\nChunk 2: Can you help me find a very cheap, not shabby hotel that has free parking?\nChunk 3: itshould be in the centre.\nChunk 4: Which one of them has free wifi?\nChunk 5: book for 2 people for 2 nights from wednesday.\nChunk 6: Sorry, can you actually book it for 3 people for 2 nights, please?\nChunk 7: Thank you that is all I needed.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: cheap; hotel type: hotel; amenities: parking. Next, area: centre. Next, amenities: wifi. Next, the goal is booking; day: wednesday; party size: 2 people; stay length: 2 nights. Finally, party size: 3 people.  Some chunks were skipped because they contained acknowledgement_only or closing_only. In summary, The overall topic is hotel. the goal is booking. price: cheap; hotel type: hotel; amenities: parking, wifi.; area: centre.; day: wednesday; party size: 2 people, 3 people.; stay length: 2 nights..", "trace": "C1 [SKIP: acknowledgement_only]. C2 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel; amenities+=parking, free parking. C3 area+=centre. C4 amenities+=wifi. C5 goal=booking; day+=wednesday; party_size+=2 people; stay_length+=2 nights. C6 party_size+=3 people. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you help me find a very cheap, not shabby hotel that has free parking?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; price: cheap; hotel type: hotel; amenities: parking.", "trace": "domain=hotel; goal=search; price+=cheap; hotel_type+=hotel; amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "itshould be in the centre.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Which one of them has free wifi?", "streaming_reasoning": "As more information arrives, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "book for 2 people for 2 nights from wednesday.", "streaming_reasoning": "As more information arrives, the goal is booking; day: wednesday; party size: 2 people; stay length: 2 nights..", "trace": "goal=booking; day+=wednesday; party_size+=2 people; stay_length+=2 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Sorry, can you actually book it for 3 people for 2 nights, please?", "streaming_reasoning": "As more information arrives, party size: 3 people..", "trace": "party_size+=3 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you that is all I needed.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; price is cheap; party size is 2 people; stay length is 2 nights; amenities is parking; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking; area=centre; price=cheap; party_size=2 people, 3 people; stay_length=2 nights; amenities=parking, free parking, wifi; when=wednesday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003312", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Well, then, will you put this and that into doggie bags?\nChunk 2: Certainly, would you wait for a few minutes?\nChunk 3: Thanks.\nChunk 4: Would you give me another favor?\nChunk 5: Yes, what is it?\nChunk 6: Some more Chinese tea for us, please.", "streaming_reasoning": "C1 question=true. C2 question=true. C3 [SKIP: thanks_only]. C4 question=true. C5 question=true. C6 casual_comment=chinese, tea.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Well, then, will you put this and that into doggie bags?\nChunk 2: Certainly, would you wait for a few minutes?\nChunk 3: Thanks.\nChunk 4: Would you give me another favor?\nChunk 5: Yes, what is it?\nChunk 6: Some more Chinese tea for us, please."}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 question=true. C3 [SKIP: thanks_only]. C4 question=true. C5 question=true. C6 casual_comment=chinese, tea.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Well, then, will you put this and that into doggie bags?\nChunk 2: Certainly, would you wait for a few minutes?\nChunk 3: Thanks.\nChunk 4: Would you give me another favor?\nChunk 5: Yes, what is it?\nChunk 6: Some more Chinese tea for us, please.", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the input provides additional context about question=true. Next, the input provides additional context about question=true. Next, the input provides additional context about question=true. Finally, the user comments on chinese.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 question=true. C2 question=true. C3 [SKIP: thanks_only]. C4 question=true. C5 question=true. C6 casual_comment=chinese, tea.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Well, then, will you put this and that into doggie bags?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Certainly, would you wait for a few minutes?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Would you give me another favor?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, what is it?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Some more Chinese tea for us, please.", "streaming_reasoning": "Finally, the user comments on chinese.", "trace": "casual_comment=chinese, tea."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002645", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should leave after 05:45 and should depart from the missing sock.\nChunk 3: I would like to go to great saint mary's church.\nChunk 4: No that was it.\nChunk 5: Thank you very much!", "streaming_reasoning": "C1 domain=taxi; goal=booking. C2 time+=05:45; departure+=the missing sock. C3 destination+=go to great saint mary's church. C4 goal=modify_constraint. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi; goal=search, booking; destination=go to great saint mary's church; departure=the missing sock; when=05:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i want to book a taxi.\nChunk 2: The taxi should leave after 05:45 and should depart from the missing sock.\nChunk 3: I would like to go to great saint mary's church.\nChunk 4: No that was it.\nChunk 5: Thank you very much!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=booking. C2 time+=05:45; departure+=the missing sock. C3 destination+=go to great saint mary's church. C4 goal=modify_constraint. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi; goal=search, booking; destination=go to great saint mary's church; departure=the missing sock; when=05:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should leave after 05:45 and should depart from the missing sock.\nChunk 3: I would like to go to great saint mary's church.\nChunk 4: No that was it.\nChunk 5: Thank you very much!", "input_token_count": 48, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is booking. Next, time: 05:45; departure point: the missing sock. Next, destination: go to great saint mary's church. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is taxi. the goal is modify constraint.. time: 05:45; departure point: the missing sock.; destination: go to great saint mary's church..", "trace": "C1 domain=taxi; goal=booking. C2 time+=05:45; departure+=the missing sock. C3 destination+=go to great saint mary's church. C4 goal=modify_constraint. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i want to book a taxi.", "streaming_reasoning": "Initially, the topic is taxi; the goal is booking..", "trace": "domain=taxi; goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The taxi should leave after 05:45 and should depart from the missing sock.", "streaming_reasoning": "As more information arrives, time: 05:45; departure point: the missing sock..", "trace": "time+=05:45; departure+=the missing sock."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to go to great saint mary's church.", "streaming_reasoning": "As more information arrives, destination: go to great saint mary's church..", "trace": "destination+=go to great saint mary's church."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No that was it.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you very much!", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is go to great saint mary's church; departure point is the missing sock; timing is 05:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search, booking; destination=go to great saint mary's church; departure=the missing sock; when=05:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002646", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a gastropub then if you have one open.\nChunk 2: What is the price range?\nChunk 3: no, just give me the address.\nChunk 4: I do need to get from Stevenage to Cambridge on Saturday.\nChunk 5: I'd like to leave shortly after 09:45, if possible.\nChunk 6: Yes, that would work out great.\nChunk 7: I need to book the trip for four people.\nChunk 8: Can I get a reference number too please?\nChunk 9: No, that's all I need right now.\nChunk 10: Thank you so much.", "streaming_reasoning": "C1 intent=context_update. C2 goal=request_info; requested_info+=price. C3 requested_info+=address. C4 goal=search; day+=saturday; destination+=cambridge; departure+=stevenage. C5 time+=09:45; destination+=leave shortly after 09:45. C6 acceptance=selected_option. C7 goal=booking; party_size+=4 people. C8 requested_info+=reference_number. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "deep_reasoning": "Need goal=request_info, search, booking; party_size=4 people; destination=cambridge, leave shortly after 09:45; departure=stevenage; requested_info=price, address, reference_number; when=saturday, 09:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a gastropub then if you have one open.\nChunk 2: What is the price range?\nChunk 3: no, just give me the address.\nChunk 4: I do need to get from Stevenage to Cambridge on Saturday.\nChunk 5: I'd like to leave shortly after 09:45, if possible.\nChunk 6: Yes, that would work out great.\nChunk 7: I need to book the trip for four people.\nChunk 8: Can I get a reference number too please?\nChunk 9: No, that's all I need right now.\nChunk 10: Thank you so much."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=request_info; requested_info+=price. C3 requested_info+=address. C4 goal=search; day+=saturday; destination+=cambridge; departure+=stevenage. C5 time+=09:45; destination+=leave shortly after 09:45. C6 acceptance=selected_option. C7 goal=booking; party_size+=4 people. C8 requested_info+=reference_number. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=request_info, search, booking; party_size=4 people; destination=cambridge, leave shortly after 09:45; departure=stevenage; requested_info=price, address, reference_number; when=saturday, 09:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a gastropub then if you have one open.\nChunk 2: What is the price range?\nChunk 3: no, just give me the address.\nChunk 4: I do need to get from Stevenage to Cambridge on Saturday.\nChunk 5: I'd like to leave shortly after 09:45, if possible.\nChunk 6: Yes, that would work out great.\nChunk 7: I need to book the trip for four people.\nChunk 8: Can I get a reference number too please?\nChunk 9: No, that's all I need right now.\nChunk 10: Thank you so much.", "input_token_count": 97, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is request info; requested information: price. Next, requested information: address. Next, the goal is search; day: saturday; destination: cambridge; departure point: stevenage. Next, time: 09:45; destination: leave shortly after 09:45. Next, acceptance: selected_option. Next, the goal is booking; party size: 4 people. Finally, requested information: reference_number.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is booking. intent: context_update.; requested information: price., address., reference_number.; day: saturday; destination: cambridge, leave shortly after 09:45.; departure point: stevenage.; time: 09:45; acceptance: selected_option.; party size: 4 people..", "trace": "C1 intent=context_update. C2 goal=request_info; requested_info+=price. C3 requested_info+=address. C4 goal=search; day+=saturday; destination+=cambridge; departure+=stevenage. C5 time+=09:45; destination+=leave shortly after 09:45. C6 acceptance=selected_option. C7 goal=booking; party_size+=4 people. C8 requested_info+=reference_number. C9 [SKIP: closing_only]. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a gastropub then if you have one open.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the price range?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "no, just give me the address.", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I do need to get from Stevenage to Cambridge on Saturday.", "streaming_reasoning": "As more information arrives, the goal is search; day: saturday; destination: cambridge; departure point: stevenage..", "trace": "goal=search; day+=saturday; destination+=cambridge; departure+=stevenage."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'd like to leave shortly after 09:45, if possible.", "streaming_reasoning": "As more information arrives, time: 09:45; destination: leave shortly after 09:45..", "trace": "time+=09:45; destination+=leave shortly after 09:45."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, that would work out great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need to book the trip for four people.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 4 people..", "trace": "goal=booking; party_size+=4 people."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Can I get a reference number too please?", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No, that's all I need right now.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you so much.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=request_info, search, booking; party_size=4 people; destination=cambridge, leave shortly after 09:45; departure=stevenage; requested_info=price, address, reference_number; when=saturday, 09:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002647", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need it to be in the west and I would prefer a hotel.\nChunk 2: Does it have free parking?\nChunk 3: Can you just tell me the address please?\nChunk 4: I want to find a hotel.\nChunk 5: The time is 14:30.\nChunk 6: Please make a booking.\nChunk 7: Thanks for all your help!\nChunk 8: thanks and great day.", "streaming_reasoning": "C1 domain=hotel; goal=search; area+=west; hotel_type+=hotel; destination+=be in the west and i would prefer a hotel. C2 amenities+=parking, free parking. C3 goal=request_info; requested_info+=address. C4 destination+=find a hotel. C5 time+=14:30. C6 goal=booking. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info, booking; area=west; amenities=parking, free parking; destination=be in the west and i would prefer a hotel, find a hotel; requested_info=address; when=14:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need it to be in the west and I would prefer a hotel.\nChunk 2: Does it have free parking?\nChunk 3: Can you just tell me the address please?\nChunk 4: I want to find a hotel.\nChunk 5: The time is 14:30.\nChunk 6: Please make a booking.\nChunk 7: Thanks for all your help!\nChunk 8: thanks and great day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; area+=west; hotel_type+=hotel; destination+=be in the west and i would prefer a hotel. C2 amenities+=parking, free parking. C3 goal=request_info; requested_info+=address. C4 destination+=find a hotel. C5 time+=14:30. C6 goal=booking. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info, booking; area=west; amenities=parking, free parking; destination=be in the west and i would prefer a hotel, find a hotel; requested_info=address; when=14:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need it to be in the west and I would prefer a hotel.\nChunk 2: Does it have free parking?\nChunk 3: Can you just tell me the address please?\nChunk 4: I want to find a hotel.\nChunk 5: The time is 14:30.\nChunk 6: Please make a booking.\nChunk 7: Thanks for all your help!\nChunk 8: thanks and great day.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: west; hotel type: hotel; destination: be in the west and i would prefer a hotel. Next, amenities: parking. Next, the goal is request info; requested information: address. Next, destination: find a hotel. Next, time: 14:30. Finally, the goal is booking.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is booking.. area: west; hotel type: hotel; destination: be in the west and i would prefer a hotel., find a hotel.; amenities: parking; requested information: address.; time: 14:30..", "trace": "C1 domain=hotel; goal=search; area+=west; hotel_type+=hotel; destination+=be in the west and i would prefer a hotel. C2 amenities+=parking, free parking. C3 goal=request_info; requested_info+=address. C4 destination+=find a hotel. C5 time+=14:30. C6 goal=booking. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need it to be in the west and I would prefer a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: west; hotel type: hotel; destination: be in the west and i would prefer a hotel..", "trace": "domain=hotel; goal=search; area+=west; hotel_type+=hotel; destination+=be in the west and i would prefer a hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Does it have free parking?", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you just tell me the address please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, destination: find a hotel..", "trace": "destination+=find a hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is 14:30.", "streaming_reasoning": "As more information arrives, time: 14:30..", "trace": "time+=14:30."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks for all your help!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "thanks and great day.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is west; amenities is parking; destination is be in the west and i would prefer a hotel; requested information is address; timing is 14:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info, booking; area=west; amenities=parking, free parking; destination=be in the west and i would prefer a hotel, find a hotel; requested_info=address; when=14:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002648", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I need some French food.\nChunk 2: Any price range is fine.\nChunk 3: What is the address and phone number Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=french. C2 intent=context_update. C3 goal=request_info; requested_info+=address, phone.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; food=french; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, I need some French food.\nChunk 2: Any price range is fine.\nChunk 3: What is the address and phone number Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=french. C2 intent=context_update. C3 goal=request_info; requested_info+=address, phone.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; food=french; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I need some French food.\nChunk 2: Any price range is fine.\nChunk 3: What is the address and phone number Thank you, goodbye.", "input_token_count": 27, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: french. Next, intent: context_update. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. cuisine: french.; intent: context_update.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; cuisine+=french. C2 intent=context_update. C3 goal=request_info; requested_info+=address, phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, I need some French food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: french..", "trace": "domain=restaurant; goal=search; cuisine+=french."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Any price range is fine.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the address and phone number Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is french; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; food=french; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002649", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need the train on Thursday.\nChunk 2: I think the 19:35 will work.\nChunk 3: Can I book that for 3 people?\nChunk 4: We were looking to do something in the north, something with the boats Any suggestions?\nChunk 5: What's their address and postcode?\nChunk 6: Yes Thanks, all set Much appreciated Goodbye.", "streaming_reasoning": "C1 domain=train; goal=search; day+=thursday. C2 time+=19:35. C3 goal=request_info; party_size+=3 people. C4 area+=north; destination+=do something in the north. C5 requested_info+=address, postcode. C6 goal=confirm_booking.", "deep_reasoning": "Need domain=train; goal=search, booking, request_info; area=north; party_size=3 people; destination=do something in the north; requested_info=address, postcode; when=thursday, 19:35.", "answer": "I can help with that and include the address, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need the train on Thursday.\nChunk 2: I think the 19:35 will work.\nChunk 3: Can I book that for 3 people?\nChunk 4: We were looking to do something in the north, something with the boats Any suggestions?\nChunk 5: What's their address and postcode?\nChunk 6: Yes Thanks, all set Much appreciated Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=thursday. C2 time+=19:35. C3 goal=request_info; party_size+=3 people. C4 area+=north; destination+=do something in the north. C5 requested_info+=address, postcode. C6 goal=confirm_booking.\n\nDeep reasoning: Need domain=train; goal=search, booking, request_info; area=north; party_size=3 people; destination=do something in the north; requested_info=address, postcode; when=thursday, 19:35.\n\nAnswer: I can help with that and include the address, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need the train on Thursday.\nChunk 2: I think the 19:35 will work.\nChunk 3: Can I book that for 3 people?\nChunk 4: We were looking to do something in the north, something with the boats Any suggestions?\nChunk 5: What's their address and postcode?\nChunk 6: Yes Thanks, all set Much appreciated Goodbye.", "input_token_count": 59, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: thursday. Next, time: 19:35. Next, the goal is request info; party size: 3 people. Next, area: north; destination: do something in the north. Next, requested information: address. Finally, the goal is confirm booking. In summary, The overall topic is train. the goal is confirm booking.. day: thursday.; time: 19:35.; party size: 3 people.; area: north; destination: do something in the north.; requested information: address.", "trace": "C1 domain=train; goal=search; day+=thursday. C2 time+=19:35. C3 goal=request_info; party_size+=3 people. C4 area+=north; destination+=do something in the north. C5 requested_info+=address, postcode. C6 goal=confirm_booking.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need the train on Thursday.", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: thursday..", "trace": "domain=train; goal=search; day+=thursday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I think the 19:35 will work.", "streaming_reasoning": "As more information arrives, time: 19:35..", "trace": "time+=19:35."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I book that for 3 people?", "streaming_reasoning": "As more information arrives, the goal is request info; party size: 3 people..", "trace": "goal=request_info; party_size+=3 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "We were looking to do something in the north, something with the boats Any suggestions?", "streaming_reasoning": "As more information arrives, area: north; destination: do something in the north..", "trace": "area+=north; destination+=do something in the north."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What's their address and postcode?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes Thanks, all set Much appreciated Goodbye.", "streaming_reasoning": "Finally, the goal is confirm booking..", "trace": "goal=confirm_booking."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is north; party size is 3 people; destination is do something in the north; requested information is address; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=search, booking, request_info; area=north; party_size=3 people; destination=do something in the north; requested_info=address, postcode; when=thursday, 19:35."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002650", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you try British food instead?\nChunk 2: It is for 4 people.\nChunk 3: The time is thursday, 4, 15:15.\nChunk 4: Please make a booking.\nChunk 5: I also need a place to go in the centre.\nChunk 6: Are there any boating attractions in the centre of town?\nChunk 7: Which ever one you recommend will work.\nChunk 8: I need the phone number, entrance fee and postcode please Thank you.\nChunk 9: I have all I need Goodnight.", "streaming_reasoning": "C1 domain=restaurant; goal=compare_alternative; cuisine+=british. C2 party_size+=4 people. C3 time+=4, 15:15; day+=thursday. C4 goal=booking. C5 goal=search; area+=centre; destination+=go in the centre. C6 goal=request_info. C7 goal=recommendation. C8 goal=request_info; requested_info+=phone, postcode, entrance_fee. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=compare_alternative, booking, search, recommendation, request_info; area=centre; food=british; party_size=4 people; destination=go in the centre; requested_info=phone, postcode, entrance_fee; when=thursday, 4, 15:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you try British food instead?\nChunk 2: It is for 4 people.\nChunk 3: The time is thursday, 4, 15:15.\nChunk 4: Please make a booking.\nChunk 5: I also need a place to go in the centre.\nChunk 6: Are there any boating attractions in the centre of town?\nChunk 7: Which ever one you recommend will work.\nChunk 8: I need the phone number, entrance fee and postcode please Thank you.\nChunk 9: I have all I need Goodnight."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=compare_alternative; cuisine+=british. C2 party_size+=4 people. C3 time+=4, 15:15; day+=thursday. C4 goal=booking. C5 goal=search; area+=centre; destination+=go in the centre. C6 goal=request_info. C7 goal=recommendation. C8 goal=request_info; requested_info+=phone, postcode, entrance_fee. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=compare_alternative, booking, search, recommendation, request_info; area=centre; food=british; party_size=4 people; destination=go in the centre; requested_info=phone, postcode, entrance_fee; when=thursday, 4, 15:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you try British food instead?\nChunk 2: It is for 4 people.\nChunk 3: The time is thursday, 4, 15:15.\nChunk 4: Please make a booking.\nChunk 5: I also need a place to go in the centre.\nChunk 6: Are there any boating attractions in the centre of town?\nChunk 7: Which ever one you recommend will work.\nChunk 8: I need the phone number, entrance fee and postcode please Thank you.\nChunk 9: I have all I need Goodnight.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is compare alternative; cuisine: british. Next, party size: 4 people. Next, time: 4; day: thursday. Next, the goal is booking. Next, the goal is search; area: centre; destination: go in the centre. Next, the goal is request info. Next, the goal is recommendation. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. cuisine: british.; party size: 4 people.; time: 4; day: thursday.; area: centre; destination: go in the centre.; requested information: phone.", "trace": "C1 domain=restaurant; goal=compare_alternative; cuisine+=british. C2 party_size+=4 people. C3 time+=4, 15:15; day+=thursday. C4 goal=booking. C5 goal=search; area+=centre; destination+=go in the centre. C6 goal=request_info. C7 goal=recommendation. C8 goal=request_info; requested_info+=phone, postcode, entrance_fee. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you try British food instead?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is compare alternative; cuisine: british..", "trace": "domain=restaurant; goal=compare_alternative; cuisine+=british."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It is for 4 people.", "streaming_reasoning": "As more information arrives, party size: 4 people..", "trace": "party_size+=4 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is thursday, 4, 15:15.", "streaming_reasoning": "As more information arrives, time: 4; day: thursday..", "trace": "time+=4, 15:15; day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need a place to go in the centre.", "streaming_reasoning": "As more information arrives, the goal is search; area: centre; destination: go in the centre..", "trace": "goal=search; area+=centre; destination+=go in the centre."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Are there any boating attractions in the centre of town?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Which ever one you recommend will work.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I need the phone number, entrance fee and postcode please Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode, entrance_fee."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I have all I need Goodnight.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of compare alternative. Key information: area is centre; cuisine is british; party size is 4 people; destination is go in the centre; requested information is phone; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=compare_alternative, booking, search, recommendation, request_info; area=centre; food=british; party_size=4 people; destination=go in the centre; requested_info=phone, postcode, entrance_fee; when=thursday, 4, 15:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002652", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train on sunday from cambridge.\nChunk 2: Can you verify that it will arrive in stevenage by 09:00?\nChunk 3: The time is 09:00.\nChunk 4: I also need the travel time.\nChunk 5: I also need the price.\nChunk 6: Thanks, that's all Good bye.", "streaming_reasoning": "C1 domain=train; goal=search; day+=sunday. C2 time+=09:00. C3 intent=context_update. C4 goal=request_info; requested_info+=travel_time. C5 requested_info+=price. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; requested_info=travel_time, price; when=sunday, 09:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a train on sunday from cambridge.\nChunk 2: Can you verify that it will arrive in stevenage by 09:00?\nChunk 3: The time is 09:00.\nChunk 4: I also need the travel time.\nChunk 5: I also need the price.\nChunk 6: Thanks, that's all Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=sunday. C2 time+=09:00. C3 intent=context_update. C4 goal=request_info; requested_info+=travel_time. C5 requested_info+=price. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; requested_info=travel_time, price; when=sunday, 09:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train on sunday from cambridge.\nChunk 2: Can you verify that it will arrive in stevenage by 09:00?\nChunk 3: The time is 09:00.\nChunk 4: I also need the travel time.\nChunk 5: I also need the price.\nChunk 6: Thanks, that's all Good bye.", "input_token_count": 55, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: sunday. Next, time: 09:00. Next, intent: context_update. Next, the goal is request info; requested information: travel_time. Finally, requested information: price.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. day: sunday.; time: 09:00.; intent: context_update.; requested information: travel_time., price..", "trace": "C1 domain=train; goal=search; day+=sunday. C2 time+=09:00. C3 intent=context_update. C4 goal=request_info; requested_info+=travel_time. C5 requested_info+=price. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a train on sunday from cambridge.", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: sunday..", "trace": "domain=train; goal=search; day+=sunday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you verify that it will arrive in stevenage by 09:00?", "streaming_reasoning": "As more information arrives, time: 09:00..", "trace": "time+=09:00."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is 09:00.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the travel time.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks, that's all Good bye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: requested information is travel_time; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; requested_info=travel_time, price; when=sunday, 09:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000549", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Reset an Echo Show.\nChunk 2: Turn the Echo off and then back on.\nChunk 3: If that didn't help, press and hold the mute and volume down buttons.\nChunk 4: Release the buttons when you see the Amazon logo.\nChunk 5: Follow the on-screen instructions to reset.", "streaming_reasoning": "C1 task=reset_an_echo_show. C2 step=turn_the_echo_off. C3 step=if_that_didnt_help. C4 step=release_the_buttons_when. C5 step=follow_the_onscreen_instructions.", "deep_reasoning": "Procedure for Reset an Echo Show: Turn the Echo off and then back on, If that didn't help, press and hold the mute and, Release the buttons when you see the Amazon logo, Follow the on-screen instructions to reset.", "answer": "For Reset an Echo Show, follow the steps in order: Turn the Echo off and then back on, If that didn't help, press and hold the mute and, Release the buttons when you see the Amazon logo, Follow the on-screen instructions to reset.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Reset an Echo Show.\nChunk 2: Turn the Echo off and then back on.\nChunk 3: If that didn't help, press and hold the mute and volume down buttons.\nChunk 4: Release the buttons when you see the Amazon logo.\nChunk 5: Follow the on-screen instructions to reset."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=reset_an_echo_show. C2 step=turn_the_echo_off. C3 step=if_that_didnt_help. C4 step=release_the_buttons_when. C5 step=follow_the_onscreen_instructions.\n\nDeep reasoning: Procedure for Reset an Echo Show: Turn the Echo off and then back on, If that didn't help, press and hold the mute and, Release the buttons when you see the Amazon logo, Follow the on-screen instructions to reset.\n\nAnswer: For Reset an Echo Show, follow the steps in order: Turn the Echo off and then back on, If that didn't help, press and hold the mute and, Release the buttons when you see the Amazon logo, Follow the on-screen instructions to reset."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Reset an Echo Show.\nChunk 2: Turn the Echo off and then back on.\nChunk 3: If that didn't help, press and hold the mute and volume down buttons.\nChunk 4: Release the buttons when you see the Amazon logo.\nChunk 5: Follow the on-screen instructions to reset.", "input_token_count": 51, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, task: reset_an_echo_show. Next, step: turn_the_echo_off. Next, step: if_that_didnt_help. Next, step: release_the_buttons_when. Finally, step: follow_the_onscreen_instructions. In summary, task: reset_an_echo_show.; step: turn_the_echo_off., if_that_didnt_help., release_the_buttons_when., follow_the_onscreen_instructions..", "trace": "C1 task=reset_an_echo_show. C2 step=turn_the_echo_off. C3 step=if_that_didnt_help. C4 step=release_the_buttons_when. C5 step=follow_the_onscreen_instructions.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Reset an Echo Show.", "streaming_reasoning": "Initially, task: reset_an_echo_show..", "trace": "task=reset_an_echo_show."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Turn the Echo off and then back on.", "streaming_reasoning": "As more information arrives, step: turn_the_echo_off..", "trace": "step=turn_the_echo_off."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "If that didn't help, press and hold the mute and volume down buttons.", "streaming_reasoning": "As more information arrives, step: if_that_didnt_help..", "trace": "step=if_that_didnt_help."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Release the buttons when you see the Amazon logo.", "streaming_reasoning": "As more information arrives, step: release_the_buttons_when..", "trace": "step=release_the_buttons_when."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Follow the on-screen instructions to reset.", "streaming_reasoning": "Finally, step: follow_the_onscreen_instructions..", "trace": "step=follow_the_onscreen_instructions."}]}, "output": {"deep_reasoning": "Procedure for Reset an Echo Show: Turn the Echo off and then back on, If that didn't help, press and hold the mute and, Release the buttons when you see the Amazon logo, Follow the on-screen instructions to reset.", "answer": "For Reset an Echo Show, follow the steps in order: Turn the Echo off and then back on, If that didn't help, press and hold the mute and, Release the buttons when you see the Amazon logo, Follow the on-screen instructions to reset."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002653", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I need to book that for 7 people and I need the reference number.\nChunk 3: Yes, I also need a cheap guest house.\nChunk 4: It should be 4 stars in any area.\nChunk 5: Sunday, 2 nights 7 people.\nChunk 6: It will be on Sunday.\nChunk 7: Yes please, can I also have the reference number Great, thank you!\nChunk 8: Have a great day Goodbye.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 goal=request_info; party_size+=7 people; requested_info+=reference_number. C3 domain=hotel; price+=cheap; hotel_type+=guesthouse; goal=confirm_booking. C4 area+=any; stars+=4 stars. C5 day+=sunday; stay_length+=2 nights. C6 intent=context_update. C7 goal=confirm_booking. C8 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=search, booking, request_info; area=any; price=cheap; party_size=7 people; stay_length=2 nights; stars=4 stars; requested_info=reference_number; when=sunday.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I need to book that for 7 people and I need the reference number.\nChunk 3: Yes, I also need a cheap guest house.\nChunk 4: It should be 4 stars in any area.\nChunk 5: Sunday, 2 nights 7 people.\nChunk 6: It will be on Sunday.\nChunk 7: Yes please, can I also have the reference number Great, thank you!\nChunk 8: Have a great day Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 goal=request_info; party_size+=7 people; requested_info+=reference_number. C3 domain=hotel; price+=cheap; hotel_type+=guesthouse; goal=confirm_booking. C4 area+=any; stars+=4 stars. C5 day+=sunday; stay_length+=2 nights. C6 intent=context_update. C7 goal=confirm_booking. C8 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=search, booking, request_info; area=any; price=cheap; party_size=7 people; stay_length=2 nights; stars=4 stars; requested_info=reference_number; when=sunday.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I need to book that for 7 people and I need the reference number.\nChunk 3: Yes, I also need a cheap guest house.\nChunk 4: It should be 4 stars in any area.\nChunk 5: Sunday, 2 nights 7 people.\nChunk 6: It will be on Sunday.\nChunk 7: Yes please, can I also have the reference number Great, thank you!\nChunk 8: Have a great day Goodbye.", "input_token_count": 74, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; party size: 7 people; requested information: reference_number. Next, the topic is hotel; the goal is confirm booking.; price: cheap; hotel type: guesthouse. Next, area: any; star rating: 4 stars. Next, day: sunday; stay length: 2 nights. Next, intent: context_update. Next, the goal is confirm booking. Finally, intent: context_update.  Some chunks were skipped because they contained acknowledgement_only. In summary, The overall topic is hotel. the goal is confirm booking.. party size: 7 people; requested information: reference_number.; price: cheap; hotel type: guesthouse; area: any; star rating: 4 stars.; day: sunday; stay length: 2 nights.; intent: context_update..", "trace": "C1 [SKIP: acknowledgement_only]. C2 goal=request_info; party_size+=7 people; requested_info+=reference_number. C3 domain=hotel; price+=cheap; hotel_type+=guesthouse; goal=confirm_booking. C4 area+=any; stars+=4 stars. C5 day+=sunday; stay_length+=2 nights. C6 intent=context_update. C7 goal=confirm_booking. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to book that for 7 people and I need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; party size: 7 people; requested information: reference_number..", "trace": "goal=request_info; party_size+=7 people; requested_info+=reference_number."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I also need a cheap guest house.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is confirm booking.; price: cheap; hotel type: guesthouse.", "trace": "domain=hotel; price+=cheap; hotel_type+=guesthouse; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It should be 4 stars in any area.", "streaming_reasoning": "As more information arrives, area: any; star rating: 4 stars..", "trace": "area+=any; stars+=4 stars."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Sunday, 2 nights 7 people.", "streaming_reasoning": "As more information arrives, day: sunday; stay length: 2 nights..", "trace": "day+=sunday; stay_length+=2 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It will be on Sunday.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes please, can I also have the reference number Great, thank you!", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Have a great day Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is any; price is cheap; party size is 7 people; stay length is 2 nights; star rating is 4 stars; requested information is reference_number; timing is sunday.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, request_info; area=any; price=cheap; party_size=7 people; stay_length=2 nights; stars=4 stars; requested_info=reference_number; when=sunday."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002654", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to contact the police.\nChunk 2: Thank you, can I also have the post code and the address?\nChunk 3: Thank you so much, good bye.", "streaming_reasoning": "C1 goal=search; destination+=contact the police. C2 goal=request_info; requested_info+=address, postcode. C3 [SKIP: thanks_only].", "deep_reasoning": "Need goal=search, request_info; destination=contact the police; requested_info=address, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to contact the police.\nChunk 2: Thank you, can I also have the post code and the address?\nChunk 3: Thank you so much, good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; destination+=contact the police. C2 goal=request_info; requested_info+=address, postcode. C3 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=search, request_info; destination=contact the police; requested_info=address, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to contact the police.\nChunk 2: Thank you, can I also have the post code and the address?\nChunk 3: Thank you so much, good bye.", "input_token_count": 30, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; destination: contact the police. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, the goal is request info. destination: contact the police.; requested information: address.", "trace": "C1 goal=search; destination+=contact the police. C2 goal=request_info; requested_info+=address, postcode. C3 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to contact the police.", "streaming_reasoning": "Initially, the goal is search; destination: contact the police..", "trace": "goal=search; destination+=contact the police."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thank you, can I also have the post code and the address?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you so much, good bye.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=search, request_info; destination=contact the police; requested_info=address, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002655", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I'm looking for an expensive restaurant serving European Food.\nChunk 2: Does Eraina serve european food?\nChunk 3: If so, what is the phone number and what area is it located in?\nChunk 4: Okay, thank you for the information.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=european; price+=expensive; acceptance=selected_option. C2 goal=request_info. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; food=european; price=expensive; requested_info=phone.", "answer": "I can help with that and include the phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I'm looking for an expensive restaurant serving European Food.\nChunk 2: Does Eraina serve european food?\nChunk 3: If so, what is the phone number and what area is it located in?\nChunk 4: Okay, thank you for the information."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=european; price+=expensive; acceptance=selected_option. C2 goal=request_info. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; food=european; price=expensive; requested_info=phone.\n\nAnswer: I can help with that and include the phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I'm looking for an expensive restaurant serving European Food.\nChunk 2: Does Eraina serve european food?\nChunk 3: If so, what is the phone number and what area is it located in?\nChunk 4: Okay, thank you for the information.", "input_token_count": 43, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: european; price: expensive; acceptance: selected_option. Next, the goal is request info. Next, the goal is request info; requested information: phone. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is request info. cuisine: european; price: expensive; acceptance: selected_option.; requested information: phone.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; cuisine+=european; price+=expensive; acceptance=selected_option. C2 goal=request_info. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I'm looking for an expensive restaurant serving European Food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: european; price: expensive; acceptance: selected_option..", "trace": "domain=restaurant; goal=search; cuisine+=european; price+=expensive; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Does Eraina serve european food?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "If so, what is the phone number and what area is it located in?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Okay, thank you for the information.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is european; price is expensive; requested information is phone.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; food=european; price=expensive; requested_info=phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003315", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Now the coals are just right.\nChunk 2: I can start grilling.\nChunk 3: Here you go.\nChunk 4: I made up the burger patties for you.\nChunk 5: Thanks.\nChunk 6: Smell the hickory chips?\nChunk 7: They give the meat a nice, smoky flavor.\nChunk 8: I'll take over for a while to give you a break Sorry.\nChunk 9: This is a one-man job.\nChunk 10: I've got the grill just how I like it, and I've made up my own special sauce.", "streaming_reasoning": "C1 casual_comment=now, coals. C2 casual_comment=start, grilling. C3 casual_comment=here. C4 casual_comment=made, burger. C5 [SKIP: thanks_only]. C6 question=true. C7 casual_comment=give, meat. C8 casual_comment=i'll, take. C9 casual_comment=one-man, job. C10 preference=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Now the coals are just right.\nChunk 2: I can start grilling.\nChunk 3: Here you go.\nChunk 4: I made up the burger patties for you.\nChunk 5: Thanks.\nChunk 6: Smell the hickory chips?\nChunk 7: They give the meat a nice, smoky flavor.\nChunk 8: I'll take over for a while to give you a break Sorry.\nChunk 9: This is a one-man job.\nChunk 10: I've got the grill just how I like it, and I've made up my own special sauce."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=now, coals. C2 casual_comment=start, grilling. C3 casual_comment=here. C4 casual_comment=made, burger. C5 [SKIP: thanks_only]. C6 question=true. C7 casual_comment=give, meat. C8 casual_comment=i'll, take. C9 casual_comment=one-man, job. C10 preference=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Now the coals are just right.\nChunk 2: I can start grilling.\nChunk 3: Here you go.\nChunk 4: I made up the burger patties for you.\nChunk 5: Thanks.\nChunk 6: Smell the hickory chips?\nChunk 7: They give the meat a nice, smoky flavor.\nChunk 8: I'll take over for a while to give you a break Sorry.\nChunk 9: This is a one-man job.\nChunk 10: I've got the grill just how I like it, and I've made up my own special sauce.", "input_token_count": 88, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on now. Next, the user comments on start. Next, the user comments on here. Next, the user comments on made. Next, the input provides additional context about question=true. Next, the user comments on give. Next, the user comments on i'll. Next, the user comments on one-man. Finally, preference: true.  Some chunks were skipped because they contained thanks_only. In summary, preference: true..", "trace": "C1 casual_comment=now, coals. C2 casual_comment=start, grilling. C3 casual_comment=here. C4 casual_comment=made, burger. C5 [SKIP: thanks_only]. C6 question=true. C7 casual_comment=give, meat. C8 casual_comment=i'll, take. C9 casual_comment=one-man, job. C10 preference=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Now the coals are just right.", "streaming_reasoning": "Initially, the user comments on now.", "trace": "casual_comment=now, coals."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I can start grilling.", "streaming_reasoning": "As more information arrives, the user comments on start.", "trace": "casual_comment=start, grilling."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Here you go.", "streaming_reasoning": "As more information arrives, the user comments on here..", "trace": "casual_comment=here."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I made up the burger patties for you.", "streaming_reasoning": "As more information arrives, the user comments on made.", "trace": "casual_comment=made, burger."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Smell the hickory chips?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "They give the meat a nice, smoky flavor.", "streaming_reasoning": "As more information arrives, the user comments on give.", "trace": "casual_comment=give, meat."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'll take over for a while to give you a break Sorry.", "streaming_reasoning": "As more information arrives, the user comments on i'll.", "trace": "casual_comment=i'll, take."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "This is a one-man job.", "streaming_reasoning": "As more information arrives, the user comments on one-man.", "trace": "casual_comment=one-man, job."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "I've got the grill just how I like it, and I've made up my own special sauce.", "streaming_reasoning": "Finally, preference: true..", "trace": "preference=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002656", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks, I'm looking for something in the east and have 4 stars.\nChunk 2: Actually, I would prefer a hotel rather than a guest house.\nChunk 3: No, I guess a guesthouse will be fine.\nChunk 4: Can you book a room for me for Thursday Yes, sounds perfect.\nChunk 5: I want to book it for 4 nights.\nChunk 6: There will be 8 people and we will be arriving on Thursday.\nChunk 7: i am also looking for a train.\nChunk 8: The train should depart from ely and should go to cambridge.\nChunk 9: I wasn't to arrive by 15:45.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 domain=hotel; hotel_type+=guesthouse, hotel. C3 goal=modify_constraint. C4 goal=confirm_booking; day+=thursday; goal=confirm_booking. C5 goal=search; stay_length+=4 nights. C6 party_size+=8 people. C7 domain=train. C8 destination+=cambridge; departure+=ely and should go, ely and should go to cambridge. C9 time+=15:45; destination+=arrive by 15:45.", "deep_reasoning": "Need domain=hotel, train; goal=booking, confirm_booking, search; party_size=8 people; stay_length=4 nights; destination=cambridge, arrive by 15:45; departure=ely and should go, ely and should go to cambridge; when=thursday, 15:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thanks, I'm looking for something in the east and have 4 stars.\nChunk 2: Actually, I would prefer a hotel rather than a guest house.\nChunk 3: No, I guess a guesthouse will be fine.\nChunk 4: Can you book a room for me for Thursday Yes, sounds perfect.\nChunk 5: I want to book it for 4 nights.\nChunk 6: There will be 8 people and we will be arriving on Thursday.\nChunk 7: i am also looking for a train.\nChunk 8: The train should depart from ely and should go to cambridge.\nChunk 9: I wasn't to arrive by 15:45."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 domain=hotel; hotel_type+=guesthouse, hotel. C3 goal=modify_constraint. C4 goal=confirm_booking; day+=thursday; goal=confirm_booking. C5 goal=search; stay_length+=4 nights. C6 party_size+=8 people. C7 domain=train. C8 destination+=cambridge; departure+=ely and should go, ely and should go to cambridge. C9 time+=15:45; destination+=arrive by 15:45.\n\nDeep reasoning: Need domain=hotel, train; goal=booking, confirm_booking, search; party_size=8 people; stay_length=4 nights; destination=cambridge, arrive by 15:45; departure=ely and should go, ely and should go to cambridge; when=thursday, 15:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks, I'm looking for something in the east and have 4 stars.\nChunk 2: Actually, I would prefer a hotel rather than a guest house.\nChunk 3: No, I guess a guesthouse will be fine.\nChunk 4: Can you book a room for me for Thursday Yes, sounds perfect.\nChunk 5: I want to book it for 4 nights.\nChunk 6: There will be 8 people and we will be arriving on Thursday.\nChunk 7: i am also looking for a train.\nChunk 8: The train should depart from ely and should go to cambridge.\nChunk 9: I wasn't to arrive by 15:45.", "input_token_count": 106, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse. Next, the goal is modify constraint. Next, the goal is confirm booking.; day: thursday. Next, the goal is search; stay length: 4 nights. Next, party size: 8 people. Next, the topic is train. Next, destination: cambridge; departure point: ely and should go. Finally, time: 15:45; destination: arrive by 15:45.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train.. the goal is search. hotel type: guesthouse; day: thursday; stay length: 4 nights.; party size: 8 people.; destination: cambridge, arrive by 15:45.; departure point: ely and should go; time: 15:45.", "trace": "C1 [SKIP: thanks_only]. C2 domain=hotel; hotel_type+=guesthouse, hotel. C3 goal=modify_constraint. C4 goal=confirm_booking; day+=thursday; goal=confirm_booking. C5 goal=search; stay_length+=4 nights. C6 party_size+=8 people. C7 domain=train. C8 destination+=cambridge; departure+=ely and should go, ely and should go to cambridge. C9 time+=15:45; destination+=arrive by 15:45.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thanks, I'm looking for something in the east and have 4 stars.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Actually, I would prefer a hotel rather than a guest house.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse.", "trace": "domain=hotel; hotel_type+=guesthouse, hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, I guess a guesthouse will be fine.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you book a room for me for Thursday Yes, sounds perfect.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; day: thursday.", "trace": "goal=confirm_booking; day+=thursday; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to book it for 4 nights.", "streaming_reasoning": "As more information arrives, the goal is search; stay length: 4 nights..", "trace": "goal=search; stay_length+=4 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "There will be 8 people and we will be arriving on Thursday.", "streaming_reasoning": "As more information arrives, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "i am also looking for a train.", "streaming_reasoning": "As more information arrives, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "The train should depart from ely and should go to cambridge.", "streaming_reasoning": "As more information arrives, destination: cambridge; departure point: ely and should go.", "trace": "destination+=cambridge; departure+=ely and should go, ely and should go to cambridge."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I wasn't to arrive by 15:45.", "streaming_reasoning": "Finally, time: 15:45; destination: arrive by 15:45..", "trace": "time+=15:45; destination+=arrive by 15:45."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: party size is 8 people; stay length is 4 nights; destination is cambridge; departure point is ely and should go; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, train; goal=booking, confirm_booking, search; party_size=8 people; stay_length=4 nights; destination=cambridge, arrive by 15:45; departure=ely and should go, ely and should go to cambridge; when=thursday, 15:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002657", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am also looking for a train into Cambridge from London Kings Cross.\nChunk 2: I will be traveling on Thursday.\nChunk 3: I need to arrive by 14:15.\nChunk 4: Well that will not work.\nChunk 5: Not at this time.\nChunk 6: What is the travel time for that train, please?\nChunk 7: no that will be all thanks.", "streaming_reasoning": "C1 domain=train; goal=search. C2 day+=thursday. C3 time+=14:15; destination+=arrive by 14:15. C4 goal=modify_constraint. C5 [SKIP: repeated_information]. C6 goal=request_info; requested_info+=travel_time. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=arrive by 14:15; requested_info=travel_time; when=thursday, 14:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am also looking for a train into Cambridge from London Kings Cross.\nChunk 2: I will be traveling on Thursday.\nChunk 3: I need to arrive by 14:15.\nChunk 4: Well that will not work.\nChunk 5: Not at this time.\nChunk 6: What is the travel time for that train, please?\nChunk 7: no that will be all thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 day+=thursday. C3 time+=14:15; destination+=arrive by 14:15. C4 goal=modify_constraint. C5 [SKIP: repeated_information]. C6 goal=request_info; requested_info+=travel_time. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=arrive by 14:15; requested_info=travel_time; when=thursday, 14:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am also looking for a train into Cambridge from London Kings Cross.\nChunk 2: I will be traveling on Thursday.\nChunk 3: I need to arrive by 14:15.\nChunk 4: Well that will not work.\nChunk 5: Not at this time.\nChunk 6: What is the travel time for that train, please?\nChunk 7: no that will be all thanks.", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, day: thursday. Next, time: 14:15; destination: arrive by 14:15. Next, the goal is modify constraint. Finally, the goal is request info; requested information: travel_time.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is train. the goal is request info. day: thursday.; time: 14:15; destination: arrive by 14:15.; requested information: travel_time..", "trace": "C1 domain=train; goal=search. C2 day+=thursday. C3 time+=14:15; destination+=arrive by 14:15. C4 goal=modify_constraint. C5 [SKIP: repeated_information]. C6 goal=request_info; requested_info+=travel_time. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am also looking for a train into Cambridge from London Kings Cross.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be traveling on Thursday.", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to arrive by 14:15.", "streaming_reasoning": "As more information arrives, time: 14:15; destination: arrive by 14:15..", "trace": "time+=14:15; destination+=arrive by 14:15."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Well that will not work.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Not at this time.", "streaming_reasoning": "The content at C5 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What is the travel time for that train, please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "no that will be all thanks.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is arrive by 14:15; requested information is travel_time; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=arrive by 14:15; requested_info=travel_time; when=thursday, 14:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002658", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also would like to eat in the center of town.\nChunk 2: Don't really have a food preference but would prefer something expensive.\nChunk 3: None, it is my first time in the town and I like every food, I will go with what you recommend.\nChunk 4: Yes can you book it for 3 people on Wednesday at 17:30?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:30.\nChunk 7: Please make a booking.\nChunk 8: That's all I need for now.\nChunk 9: Thanks for all your help!", "streaming_reasoning": "C1 domain=restaurant; area+=centre; destination+=eat in the center of town. C2 price+=expensive. C3 goal=recommendation. C4 goal=confirm_booking; time+=3, 17:30; day+=wednesday; party_size+=3 people; goal=confirm_booking. C5 goal=search; destination+=find a restaurant. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=recommendation, booking, confirm_booking, search; area=centre; price=expensive; party_size=3 people; destination=eat in the center of town, find a restaurant; when=wednesday, 3, 17:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also would like to eat in the center of town.\nChunk 2: Don't really have a food preference but would prefer something expensive.\nChunk 3: None, it is my first time in the town and I like every food, I will go with what you recommend.\nChunk 4: Yes can you book it for 3 people on Wednesday at 17:30?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:30.\nChunk 7: Please make a booking.\nChunk 8: That's all I need for now.\nChunk 9: Thanks for all your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=centre; destination+=eat in the center of town. C2 price+=expensive. C3 goal=recommendation. C4 goal=confirm_booking; time+=3, 17:30; day+=wednesday; party_size+=3 people; goal=confirm_booking. C5 goal=search; destination+=find a restaurant. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=recommendation, booking, confirm_booking, search; area=centre; price=expensive; party_size=3 people; destination=eat in the center of town, find a restaurant; when=wednesday, 3, 17:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also would like to eat in the center of town.\nChunk 2: Don't really have a food preference but would prefer something expensive.\nChunk 3: None, it is my first time in the town and I like every food, I will go with what you recommend.\nChunk 4: Yes can you book it for 3 people on Wednesday at 17:30?\nChunk 5: I want to find a restaurant.\nChunk 6: The time is 17:30.\nChunk 7: Please make a booking.\nChunk 8: That's all I need for now.\nChunk 9: Thanks for all your help!", "input_token_count": 100, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: centre; destination: eat in the center of town. Next, price: expensive. Next, the goal is recommendation. Next, the goal is confirm booking.; time: 3; day: wednesday; party size: 3 people. Next, the goal is search; destination: find a restaurant. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is search. area: centre; destination: eat in the center of town., find a restaurant.; price: expensive.; time: 3; day: wednesday; party size: 3 people; intent: context_update..", "trace": "C1 domain=restaurant; area+=centre; destination+=eat in the center of town. C2 price+=expensive. C3 goal=recommendation. C4 goal=confirm_booking; time+=3, 17:30; day+=wednesday; party_size+=3 people; goal=confirm_booking. C5 goal=search; destination+=find a restaurant. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also would like to eat in the center of town.", "streaming_reasoning": "Initially, the topic is restaurant; area: centre; destination: eat in the center of town..", "trace": "domain=restaurant; area+=centre; destination+=eat in the center of town."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Don't really have a food preference but would prefer something expensive.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "None, it is my first time in the town and I like every food, I will go with what you recommend.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes can you book it for 3 people on Wednesday at 17:30?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 3; day: wednesday; party size: 3 people.", "trace": "goal=confirm_booking; time+=3, 17:30; day+=wednesday; party_size+=3 people; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, the goal is search; destination: find a restaurant..", "trace": "goal=search; destination+=find a restaurant."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 17:30.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's all I need for now.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks for all your help!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: area is centre; price is expensive; party size is 3 people; destination is eat in the center of town; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=recommendation, booking, confirm_booking, search; area=centre; price=expensive; party_size=3 people; destination=eat in the center of town, find a restaurant; when=wednesday, 3, 17:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002661", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you find me a hospital in town?\nChunk 2: Do they have a transitional care department?\nChunk 3: I would also like to know the postcode and phone number.\nChunk 4: No, I'll just head down, so I don't need anything else at the moment Later!", "streaming_reasoning": "C1 domain=hospital; goal=search. C2 goal=request_info. C3 goal=request_info; destination+=know the postcode and phone number; requested_info+=phone, postcode. C4 goal=compare_alternative.", "deep_reasoning": "Need domain=hospital; goal=search, request_info, compare_alternative; destination=know the postcode and phone number; requested_info=phone, postcode.", "answer": "I can help with that and include the phone, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Could you find me a hospital in town?\nChunk 2: Do they have a transitional care department?\nChunk 3: I would also like to know the postcode and phone number.\nChunk 4: No, I'll just head down, so I don't need anything else at the moment Later!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search. C2 goal=request_info. C3 goal=request_info; destination+=know the postcode and phone number; requested_info+=phone, postcode. C4 goal=compare_alternative.\n\nDeep reasoning: Need domain=hospital; goal=search, request_info, compare_alternative; destination=know the postcode and phone number; requested_info=phone, postcode.\n\nAnswer: I can help with that and include the phone, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you find me a hospital in town?\nChunk 2: Do they have a transitional care department?\nChunk 3: I would also like to know the postcode and phone number.\nChunk 4: No, I'll just head down, so I don't need anything else at the moment Later!", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search. Next, the goal is request info. Next, the goal is request info; destination: know the postcode and phone number; requested information: phone. Finally, the goal is compare alternative. In summary, The overall topic is hospital. the goal is compare alternative.. destination: know the postcode and phone number; requested information: phone.", "trace": "C1 domain=hospital; goal=search. C2 goal=request_info. C3 goal=request_info; destination+=know the postcode and phone number; requested_info+=phone, postcode. C4 goal=compare_alternative.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Could you find me a hospital in town?", "streaming_reasoning": "Initially, the topic is hospital; the goal is search..", "trace": "domain=hospital; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do they have a transitional care department?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would also like to know the postcode and phone number.", "streaming_reasoning": "As more information arrives, the goal is request info; destination: know the postcode and phone number; requested information: phone.", "trace": "goal=request_info; destination+=know the postcode and phone number; requested_info+=phone, postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, I'll just head down, so I don't need anything else at the moment Later!", "streaming_reasoning": "Finally, the goal is compare alternative..", "trace": "goal=compare_alternative."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: destination is know the postcode and phone number; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info, compare_alternative; destination=know the postcode and phone number; requested_info=phone, postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002662", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: After 17:30 please.\nChunk 2: I need help with train.\nChunk 3: It is for 8 people.\nChunk 4: Please make a booking.\nChunk 5: I think I would be interested in the 17:54 and I need to book it for 8 people.\nChunk 6: I'm also looking for a restaurant that serves north american food, in the expensive range.\nChunk 7: Yes.\nChunk 8: That would be great.\nChunk 9: Make it for Saturday for 8 people at 20:30.\nChunk 10: Thank you, that is all I needed.", "streaming_reasoning": "C1 time+=17:30. C2 domain=train; goal=search. C3 party_size+=8 people. C4 goal=booking. C5 time+=17:54. C6 domain=restaurant; area+=north; price+=expensive. C7 goal=confirm_booking. C8 intent=context_update. C9 goal=modify_constraint; time+=8, 20:30; day+=saturday. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, restaurant; goal=search, booking, modify_constraint; area=north; price=expensive; party_size=8 people; when=saturday, 17:30, 17:54, 8, 20:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: After 17:30 please.\nChunk 2: I need help with train.\nChunk 3: It is for 8 people.\nChunk 4: Please make a booking.\nChunk 5: I think I would be interested in the 17:54 and I need to book it for 8 people.\nChunk 6: I'm also looking for a restaurant that serves north american food, in the expensive range.\nChunk 7: Yes.\nChunk 8: That would be great.\nChunk 9: Make it for Saturday for 8 people at 20:30.\nChunk 10: Thank you, that is all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=17:30. C2 domain=train; goal=search. C3 party_size+=8 people. C4 goal=booking. C5 time+=17:54. C6 domain=restaurant; area+=north; price+=expensive. C7 goal=confirm_booking. C8 intent=context_update. C9 goal=modify_constraint; time+=8, 20:30; day+=saturday. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=search, booking, modify_constraint; area=north; price=expensive; party_size=8 people; when=saturday, 17:30, 17:54, 8, 20:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: After 17:30 please.\nChunk 2: I need help with train.\nChunk 3: It is for 8 people.\nChunk 4: Please make a booking.\nChunk 5: I think I would be interested in the 17:54 and I need to book it for 8 people.\nChunk 6: I'm also looking for a restaurant that serves north american food, in the expensive range.\nChunk 7: Yes.\nChunk 8: That would be great.\nChunk 9: Make it for Saturday for 8 people at 20:30.\nChunk 10: Thank you, that is all I needed.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 17:30. Next, the topic is train; the goal is search. Next, party size: 8 people. Next, the goal is booking. Next, time: 17:54. Next, the topic is restaurant; area: north; price: expensive. Next, the goal is confirm booking. Next, intent: context_update. Finally, the goal is modify constraint; time: 8; day: saturday.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is modify constraint. time: 17:30., 17:54., 8; party size: 8 people.; area: north; price: expensive.; intent: context_update.; day: saturday..", "trace": "C1 time+=17:30. C2 domain=train; goal=search. C3 party_size+=8 people. C4 goal=booking. C5 time+=17:54. C6 domain=restaurant; area+=north; price+=expensive. C7 goal=confirm_booking. C8 intent=context_update. C9 goal=modify_constraint; time+=8, 20:30; day+=saturday. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "After 17:30 please.", "streaming_reasoning": "Initially, time: 17:30..", "trace": "time+=17:30."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 8 people.", "streaming_reasoning": "As more information arrives, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I think I would be interested in the 17:54 and I need to book it for 8 people.", "streaming_reasoning": "As more information arrives, time: 17:54..", "trace": "time+=17:54."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'm also looking for a restaurant that serves north american food, in the expensive range.", "streaming_reasoning": "As more information arrives, the topic is restaurant; area: north; price: expensive..", "trace": "domain=restaurant; area+=north; price+=expensive."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That would be great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Make it for Saturday for 8 people at 20:30.", "streaming_reasoning": "As more information arrives, the goal is modify constraint; time: 8; day: saturday..", "trace": "goal=modify_constraint; time+=8, 20:30; day+=saturday."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you, that is all I needed.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is north; price is expensive; party size is 8 people; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=search, booking, modify_constraint; area=north; price=expensive; party_size=8 people; when=saturday, 17:30, 17:54, 8, 20:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002664", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any Japanese restaurants in the same area and price range?\nChunk 2: It is for 6 people.\nChunk 3: The time is tuesday, 6, 17:15.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: I need help with train.\nChunk 7: The time is 19:15.\nChunk 8: I'm sorry I mean to say 9:15.\nChunk 9: I need to arrive by 9:15.\nChunk 10: Yes, please reserve six tickets for us.\nChunk 11: No, that is all, thank you.", "streaming_reasoning": "C1 goal=modify_constraint; cuisine+=japanese. C2 party_size+=6 people. C3 time+=6, 17:15; day+=tuesday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 domain=train. C7 time+=19:15. C8 time+=9:15; destination+=say 9:15. C9 destination+=arrive by 9:15. C10 goal=confirm_booking. C11 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=modify_constraint, booking, search, request_info; food=japanese; party_size=6 people; destination=say 9:15, arrive by 9:15; requested_info=reference_number; when=tuesday, 6, 17:15, 19:15, 9:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Are there any Japanese restaurants in the same area and price range?\nChunk 2: It is for 6 people.\nChunk 3: The time is tuesday, 6, 17:15.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: I need help with train.\nChunk 7: The time is 19:15.\nChunk 8: I'm sorry I mean to say 9:15.\nChunk 9: I need to arrive by 9:15.\nChunk 10: Yes, please reserve six tickets for us.\nChunk 11: No, that is all, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=modify_constraint; cuisine+=japanese. C2 party_size+=6 people. C3 time+=6, 17:15; day+=tuesday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 domain=train. C7 time+=19:15. C8 time+=9:15; destination+=say 9:15. C9 destination+=arrive by 9:15. C10 goal=confirm_booking. C11 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=modify_constraint, booking, search, request_info; food=japanese; party_size=6 people; destination=say 9:15, arrive by 9:15; requested_info=reference_number; when=tuesday, 6, 17:15, 19:15, 9:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any Japanese restaurants in the same area and price range?\nChunk 2: It is for 6 people.\nChunk 3: The time is tuesday, 6, 17:15.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: I need help with train.\nChunk 7: The time is 19:15.\nChunk 8: I'm sorry I mean to say 9:15.\nChunk 9: I need to arrive by 9:15.\nChunk 10: Yes, please reserve six tickets for us.\nChunk 11: No, that is all, thank you.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is modify constraint; cuisine: japanese. Next, party size: 6 people. Next, time: 6; day: tuesday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the topic is train. Next, time: 19:15. Next, time: 9:15; destination: say 9:15. Next, destination: arrive by 9:15. Finally, the goal is confirm booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train.. the goal is confirm booking.. cuisine: japanese.; party size: 6 people.; time: 6, 19:15., 9:15; day: tuesday.; requested information: reference_number.; destination: say 9:15., arrive by 9:15..", "trace": "C1 goal=modify_constraint; cuisine+=japanese. C2 party_size+=6 people. C3 time+=6, 17:15; day+=tuesday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 domain=train. C7 time+=19:15. C8 time+=9:15; destination+=say 9:15. C9 destination+=arrive by 9:15. C10 goal=confirm_booking. C11 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Are there any Japanese restaurants in the same area and price range?", "streaming_reasoning": "Initially, the goal is modify constraint; cuisine: japanese..", "trace": "goal=modify_constraint; cuisine+=japanese."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It is for 6 people.", "streaming_reasoning": "As more information arrives, party size: 6 people..", "trace": "party_size+=6 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is tuesday, 6, 17:15.", "streaming_reasoning": "As more information arrives, time: 6; day: tuesday..", "trace": "time+=6, 17:15; day+=tuesday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 19:15.", "streaming_reasoning": "As more information arrives, time: 19:15..", "trace": "time+=19:15."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'm sorry I mean to say 9:15.", "streaming_reasoning": "As more information arrives, time: 9:15; destination: say 9:15..", "trace": "time+=9:15; destination+=say 9:15."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I need to arrive by 9:15.", "streaming_reasoning": "As more information arrives, destination: arrive by 9:15..", "trace": "destination+=arrive by 9:15."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Yes, please reserve six tickets for us.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "No, that is all, thank you.", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of modify constraint. Key information: cuisine is japanese; party size is 6 people; destination is say 9:15; requested information is reference_number; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=modify_constraint, booking, search, request_info; food=japanese; party_size=6 people; destination=say 9:15, arrive by 9:15; requested_info=reference_number; when=tuesday, 6, 17:15, 19:15, 9:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002665", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: Can you help me find a particular restaurant?\nChunk 3: Yes, I am looking for the Varsity Restaurant.\nChunk 4: Yes, can I get a table for 4 on saturday at 15:15 Excellent.\nChunk 5: I'll need the reference number.", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search. C3 acceptance=selected_option. C4 goal=request_info; time+=4, 15:15; day+=saturday; acceptance=selected_option. C5 requested_info+=reference_number.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; requested_info=reference_number; when=saturday, 4, 15:15.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi!\nChunk 2: Can you help me find a particular restaurant?\nChunk 3: Yes, I am looking for the Varsity Restaurant.\nChunk 4: Yes, can I get a table for 4 on saturday at 15:15 Excellent.\nChunk 5: I'll need the reference number."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search. C3 acceptance=selected_option. C4 goal=request_info; time+=4, 15:15; day+=saturday; acceptance=selected_option. C5 requested_info+=reference_number.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; requested_info=reference_number; when=saturday, 4, 15:15.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: Can you help me find a particular restaurant?\nChunk 3: Yes, I am looking for the Varsity Restaurant.\nChunk 4: Yes, can I get a table for 4 on saturday at 15:15 Excellent.\nChunk 5: I'll need the reference number.", "input_token_count": 46, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, acceptance: selected_option. Next, the goal is request info; time: 4; day: saturday; acceptance: selected_option. Finally, requested information: reference_number.  Some chunks were skipped because they contained greeting_only. In summary, The overall topic is restaurant. the goal is request info. acceptance: selected_option.; time: 4; day: saturday; requested information: reference_number..", "trace": "C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search. C3 acceptance=selected_option. C4 goal=request_info; time+=4, 15:15; day+=saturday; acceptance=selected_option. C5 requested_info+=reference_number.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi!", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you help me find a particular restaurant?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I am looking for the Varsity Restaurant.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, can I get a table for 4 on saturday at 15:15 Excellent.", "streaming_reasoning": "As more information arrives, the goal is request info; time: 4; day: saturday; acceptance: selected_option..", "trace": "goal=request_info; time+=4, 15:15; day+=saturday; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'll need the reference number.", "streaming_reasoning": "Finally, requested information: reference_number..", "trace": "requested_info+=reference_number."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; requested_info=reference_number; when=saturday, 4, 15:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002667", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I have been hurt in an accident, can you provide the nearest hospital?\nChunk 2: I need the postcode, thanks.\nChunk 3: That's all the info I needed today, thank you!", "streaming_reasoning": "C1 domain=hospital. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search, request_info; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I have been hurt in an accident, can you provide the nearest hospital?\nChunk 2: I need the postcode, thanks.\nChunk 3: That's all the info I needed today, thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I have been hurt in an accident, can you provide the nearest hospital?\nChunk 2: I need the postcode, thanks.\nChunk 3: That's all the info I needed today, thank you!", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital. Finally, the goal is request info; requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital.. the goal is request info. requested information: postcode..", "trace": "C1 domain=hospital. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I have been hurt in an accident, can you provide the nearest hospital?", "streaming_reasoning": "Initially, the topic is hospital..", "trace": "domain=hospital."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need the postcode, thanks.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That's all the info I needed today, thank you!", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002668", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Okay, can you check for one that falls in the cheap price range instead?\nChunk 2: I want to find a hotel.\nChunk 3: It is for 8 people.\nChunk 4: The time is wednesday.\nChunk 5: Please make a booking.\nChunk 6: Yes, i am looking for places to visit near my hotel Any recommendations?\nChunk 7: Great, can you please provide the address.\nChunk 8: That is all I need today, thank you Thank You Goodbye!", "streaming_reasoning": "C1 goal=compare_alternative; price+=cheap; requested_info+=price. C2 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C3 party_size+=8 people. C4 day+=wednesday. C5 goal=booking. C6 destination+=visit near my hotel any recommendations; goal=confirm_booking. C7 goal=request_info; requested_info+=address. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=compare_alternative, search, booking, request_info; price=cheap; party_size=8 people; destination=find a hotel, visit near my hotel any recommendations; requested_info=price, address; when=wednesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Okay, can you check for one that falls in the cheap price range instead?\nChunk 2: I want to find a hotel.\nChunk 3: It is for 8 people.\nChunk 4: The time is wednesday.\nChunk 5: Please make a booking.\nChunk 6: Yes, i am looking for places to visit near my hotel Any recommendations?\nChunk 7: Great, can you please provide the address.\nChunk 8: That is all I need today, thank you Thank You Goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=compare_alternative; price+=cheap; requested_info+=price. C2 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C3 party_size+=8 people. C4 day+=wednesday. C5 goal=booking. C6 destination+=visit near my hotel any recommendations; goal=confirm_booking. C7 goal=request_info; requested_info+=address. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=compare_alternative, search, booking, request_info; price=cheap; party_size=8 people; destination=find a hotel, visit near my hotel any recommendations; requested_info=price, address; when=wednesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Okay, can you check for one that falls in the cheap price range instead?\nChunk 2: I want to find a hotel.\nChunk 3: It is for 8 people.\nChunk 4: The time is wednesday.\nChunk 5: Please make a booking.\nChunk 6: Yes, i am looking for places to visit near my hotel Any recommendations?\nChunk 7: Great, can you please provide the address.\nChunk 8: That is all I need today, thank you Thank You Goodbye!", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is compare alternative; price: cheap; requested information: price. Next, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, party size: 8 people. Next, day: wednesday. Next, the goal is booking. Next, the goal is confirm booking.; destination: visit near my hotel any recommendations. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. price: cheap; requested information: price., address.; hotel type: hotel; destination: find a hotel., visit near my hotel any recommendations; party size: 8 people.; day: wednesday..", "trace": "C1 goal=compare_alternative; price+=cheap; requested_info+=price. C2 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C3 party_size+=8 people. C4 day+=wednesday. C5 goal=booking. C6 destination+=visit near my hotel any recommendations; goal=confirm_booking. C7 goal=request_info; requested_info+=address. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Okay, can you check for one that falls in the cheap price range instead?", "streaming_reasoning": "Initially, the goal is compare alternative; price: cheap; requested information: price..", "trace": "goal=compare_alternative; price+=cheap; requested_info+=price."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 8 people.", "streaming_reasoning": "As more information arrives, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is wednesday.", "streaming_reasoning": "As more information arrives, day: wednesday..", "trace": "day+=wednesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, i am looking for places to visit near my hotel Any recommendations?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; destination: visit near my hotel any recommendations.", "trace": "destination+=visit near my hotel any recommendations; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Great, can you please provide the address.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all I need today, thank you Thank You Goodbye!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of compare alternative. Key information: price is cheap; party size is 8 people; destination is find a hotel; requested information is price; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=compare_alternative, search, booking, request_info; price=cheap; party_size=8 people; destination=find a hotel, visit near my hotel any recommendations; requested_info=price, address; when=wednesday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002669", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I got into a car accident and need help figuring out what to do next Ok thanks.\nChunk 2: I'd also like to know where the nearest police station is.\nChunk 3: Thanks, that's all Good bye.", "streaming_reasoning": "C1 goal=search; destination+=do next ok thanks. C2 domain=train; destination+=know where the nearest police station is. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search; destination=do next ok thanks, know where the nearest police station is; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I got into a car accident and need help figuring out what to do next Ok thanks.\nChunk 2: I'd also like to know where the nearest police station is.\nChunk 3: Thanks, that's all Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; destination+=do next ok thanks. C2 domain=train; destination+=know where the nearest police station is. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search; destination=do next ok thanks, know where the nearest police station is; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I got into a car accident and need help figuring out what to do next Ok thanks.\nChunk 2: I'd also like to know where the nearest police station is.\nChunk 3: Thanks, that's all Good bye.", "input_token_count": 39, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; destination: do next ok thanks. Finally, the topic is train; destination: know where the nearest police station is.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is search. destination: do next ok thanks., know where the nearest police station is..", "trace": "C1 goal=search; destination+=do next ok thanks. C2 domain=train; destination+=know where the nearest police station is. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I got into a car accident and need help figuring out what to do next Ok thanks.", "streaming_reasoning": "Initially, the goal is search; destination: do next ok thanks..", "trace": "goal=search; destination+=do next ok thanks."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd also like to know where the nearest police station is.", "streaming_reasoning": "As more information arrives, the topic is train; destination: know where the nearest police station is..", "trace": "domain=train; destination+=know where the nearest police station is."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks, that's all Good bye.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is do next ok thanks. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search; destination=do next ok thanks, know where the nearest police station is; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002670", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi there!\nChunk 2: I need a place to stay in Cambridge, and I'm wondering if you have any recommendations for good 2 star hotels in town?\nChunk 3: I would prefer Lovell Lodge, thank you.\nChunk 4: Yes, that would be great.\nChunk 5: I need accommodations for 6 people starting Sunday for 3 nights.\nChunk 6: Yeah, can you try for 2 nights then?\nChunk 7: Thanks, I'm going to need some info on the Cambridge Punter as well.\nChunk 8: Thank you for all your help.\nChunk 9: That's all I need today.", "streaming_reasoning": "C1 [SKIP: low_information]. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=2 stars; destination+=stay in cambridge. C3 intent=context_update. C4 acceptance=selected_option. C5 time+=6, 3; day+=sunday; party_size+=6 people; stay_length+=3 nights. C6 stay_length+=2 nights. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search; party_size=6 people; stay_length=3 nights, 2 nights; stars=2 stars; destination=stay in cambridge; when=sunday, 6, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi there!\nChunk 2: I need a place to stay in Cambridge, and I'm wondering if you have any recommendations for good 2 star hotels in town?\nChunk 3: I would prefer Lovell Lodge, thank you.\nChunk 4: Yes, that would be great.\nChunk 5: I need accommodations for 6 people starting Sunday for 3 nights.\nChunk 6: Yeah, can you try for 2 nights then?\nChunk 7: Thanks, I'm going to need some info on the Cambridge Punter as well.\nChunk 8: Thank you for all your help.\nChunk 9: That's all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: low_information]. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=2 stars; destination+=stay in cambridge. C3 intent=context_update. C4 acceptance=selected_option. C5 time+=6, 3; day+=sunday; party_size+=6 people; stay_length+=3 nights. C6 stay_length+=2 nights. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search; party_size=6 people; stay_length=3 nights, 2 nights; stars=2 stars; destination=stay in cambridge; when=sunday, 6, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi there!\nChunk 2: I need a place to stay in Cambridge, and I'm wondering if you have any recommendations for good 2 star hotels in town?\nChunk 3: I would prefer Lovell Lodge, thank you.\nChunk 4: Yes, that would be great.\nChunk 5: I need accommodations for 6 people starting Sunday for 3 nights.\nChunk 6: Yeah, can you try for 2 nights then?\nChunk 7: Thanks, I'm going to need some info on the Cambridge Punter as well.\nChunk 8: Thank you for all your help.\nChunk 9: That's all I need today.", "input_token_count": 98, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; star rating: 2 stars; destination: stay in cambridge. Next, intent: context_update. Next, acceptance: selected_option. Next, time: 6; day: sunday; party size: 6 people; stay length: 3 nights. Finally, stay length: 2 nights.  Some chunks were skipped because they contained closing_only or low_information or thanks_only. In summary, The overall topic is hotel. the goal is search. hotel type: hotel; star rating: 2 stars; destination: stay in cambridge.; intent: context_update.; acceptance: selected_option.; time: 6; day: sunday; party size: 6 people; stay length: 3 nights., 2 nights..", "trace": "C1 [SKIP: low_information]. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=2 stars; destination+=stay in cambridge. C3 intent=context_update. C4 acceptance=selected_option. C5 time+=6, 3; day+=sunday; party_size+=6 people; stay_length+=3 nights. C6 stay_length+=2 nights. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi there!", "streaming_reasoning": "The content at C1 was skipped (low_information).", "trace": "[SKIP: low_information]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need a place to stay in Cambridge, and I'm wondering if you have any recommendations for good 2 star hotels in town?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: hotel; star rating: 2 stars; destination: stay in cambridge..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; stars+=2 stars; destination+=stay in cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would prefer Lovell Lodge, thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, that would be great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need accommodations for 6 people starting Sunday for 3 nights.", "streaming_reasoning": "As more information arrives, time: 6; day: sunday; party size: 6 people; stay length: 3 nights..", "trace": "time+=6, 3; day+=sunday; party_size+=6 people; stay_length+=3 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yeah, can you try for 2 nights then?", "streaming_reasoning": "As more information arrives, stay length: 2 nights..", "trace": "stay_length+=2 nights."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks, I'm going to need some info on the Cambridge Punter as well.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That's all I need today.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 6 people; stay length is 3 nights; star rating is 2 stars; destination is stay in cambridge; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search; party_size=6 people; stay_length=3 nights, 2 nights; stars=2 stars; destination=stay in cambridge; when=sunday, 6, 3; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002673", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What area of town is that in?\nChunk 2: Can you tell me what the entrance fee is?\nChunk 3: May i also have their postcode please Great, thank you.\nChunk 4: Can you also help me find a place to stay?\nChunk 5: I'd like an expensive hotel with free parking.\nChunk 6: I would like a hotel in the expensive price range.\nChunk 7: Could you book it for 3 people and for 3 nights starting on sunday?\nChunk 8: Thank you I'm all set Goodbye!", "streaming_reasoning": "C1 goal=request_info. C2 goal=request_info; requested_info+=entrance_fee. C3 requested_info+=postcode. C4 domain=hotel; goal=search; destination+=stay. C5 price+=expensive; hotel_type+=hotel; amenities+=parking, free parking. C6 intent=context_update. C7 goal=booking; time+=3; day+=sunday; party_size+=3 people; stay_length+=3 nights. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=request_info, search, booking; price=expensive; party_size=3 people; stay_length=3 nights; amenities=parking, free parking; destination=stay; requested_info=entrance_fee, postcode; when=sunday, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What area of town is that in?\nChunk 2: Can you tell me what the entrance fee is?\nChunk 3: May i also have their postcode please Great, thank you.\nChunk 4: Can you also help me find a place to stay?\nChunk 5: I'd like an expensive hotel with free parking.\nChunk 6: I would like a hotel in the expensive price range.\nChunk 7: Could you book it for 3 people and for 3 nights starting on sunday?\nChunk 8: Thank you I'm all set Goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 goal=request_info; requested_info+=entrance_fee. C3 requested_info+=postcode. C4 domain=hotel; goal=search; destination+=stay. C5 price+=expensive; hotel_type+=hotel; amenities+=parking, free parking. C6 intent=context_update. C7 goal=booking; time+=3; day+=sunday; party_size+=3 people; stay_length+=3 nights. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info, search, booking; price=expensive; party_size=3 people; stay_length=3 nights; amenities=parking, free parking; destination=stay; requested_info=entrance_fee, postcode; when=sunday, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What area of town is that in?\nChunk 2: Can you tell me what the entrance fee is?\nChunk 3: May i also have their postcode please Great, thank you.\nChunk 4: Can you also help me find a place to stay?\nChunk 5: I'd like an expensive hotel with free parking.\nChunk 6: I would like a hotel in the expensive price range.\nChunk 7: Could you book it for 3 people and for 3 nights starting on sunday?\nChunk 8: Thank you I'm all set Goodbye!", "input_token_count": 90, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, the goal is request info; requested information: entrance_fee. Next, requested information: postcode. Next, the topic is hotel; the goal is search; destination: stay. Next, price: expensive; hotel type: hotel; amenities: parking. Next, intent: context_update. Finally, the goal is booking; time: 3; day: sunday; party size: 3 people; stay length: 3 nights.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is booking. requested information: entrance_fee., postcode.; destination: stay.; price: expensive; hotel type: hotel; amenities: parking; intent: context_update.; time: 3; day: sunday; party size: 3 people; stay length: 3 nights..", "trace": "C1 goal=request_info. C2 goal=request_info; requested_info+=entrance_fee. C3 requested_info+=postcode. C4 domain=hotel; goal=search; destination+=stay. C5 price+=expensive; hotel_type+=hotel; amenities+=parking, free parking. C6 intent=context_update. C7 goal=booking; time+=3; day+=sunday; party_size+=3 people; stay_length+=3 nights. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What area of town is that in?", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you tell me what the entrance fee is?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "May i also have their postcode please Great, thank you.", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you also help me find a place to stay?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'd like an expensive hotel with free parking.", "streaming_reasoning": "As more information arrives, price: expensive; hotel type: hotel; amenities: parking.", "trace": "price+=expensive; hotel_type+=hotel; amenities+=parking, free parking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I would like a hotel in the expensive price range.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Could you book it for 3 people and for 3 nights starting on sunday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 3; day: sunday; party size: 3 people; stay length: 3 nights..", "trace": "goal=booking; time+=3; day+=sunday; party_size+=3 people; stay_length+=3 nights."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you I'm all set Goodbye!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: price is expensive; party size is 3 people; stay length is 3 nights; amenities is parking; destination is stay; requested information is entrance_fee; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search, booking; price=expensive; party_size=3 people; stay_length=3 nights; amenities=parking, free parking; destination=stay; requested_info=entrance_fee, postcode; when=sunday, 3; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002676", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What is the postcode of that resturant?\nChunk 2: I was wondering the price range of the riverside brasserie.\nChunk 3: Thanks.\nChunk 4: Could you check on a train for me from london kings cross?\nChunk 5: I would like to leave after 11:15 on a Tuesday.\nChunk 6: Yes I'd like to book that train for 5 and I'd like the reference number as well please.\nChunk 7: I think that will be all for today Thank you.", "streaming_reasoning": "C1 goal=request_info; requested_info+=postcode. C2 intent=context_update. C3 [SKIP: thanks_only]. C4 domain=train. C5 time+=11:15; day+=tuesday; destination+=leave after 11:15 on a tuesday. C6 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=request_info, booking, confirm_booking; destination=leave after 11:15 on a tuesday; requested_info=postcode, reference_number; when=tuesday, 11:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What is the postcode of that resturant?\nChunk 2: I was wondering the price range of the riverside brasserie.\nChunk 3: Thanks.\nChunk 4: Could you check on a train for me from london kings cross?\nChunk 5: I would like to leave after 11:15 on a Tuesday.\nChunk 6: Yes I'd like to book that train for 5 and I'd like the reference number as well please.\nChunk 7: I think that will be all for today Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=postcode. C2 intent=context_update. C3 [SKIP: thanks_only]. C4 domain=train. C5 time+=11:15; day+=tuesday; destination+=leave after 11:15 on a tuesday. C6 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=request_info, booking, confirm_booking; destination=leave after 11:15 on a tuesday; requested_info=postcode, reference_number; when=tuesday, 11:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What is the postcode of that resturant?\nChunk 2: I was wondering the price range of the riverside brasserie.\nChunk 3: Thanks.\nChunk 4: Could you check on a train for me from london kings cross?\nChunk 5: I would like to leave after 11:15 on a Tuesday.\nChunk 6: Yes I'd like to book that train for 5 and I'd like the reference number as well please.\nChunk 7: I think that will be all for today Thank you.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: postcode. Next, intent: context_update. Next, the topic is train. Next, time: 11:15; day: tuesday; destination: leave after 11:15 on a tuesday. Finally, the goal is confirm booking.; requested information: reference_number.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train.. the goal is confirm booking.. requested information: postcode., reference_number; intent: context_update.; time: 11:15; day: tuesday; destination: leave after 11:15 on a tuesday..", "trace": "C1 goal=request_info; requested_info+=postcode. C2 intent=context_update. C3 [SKIP: thanks_only]. C4 domain=train. C5 time+=11:15; day+=tuesday; destination+=leave after 11:15 on a tuesday. C6 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What is the postcode of that resturant?", "streaming_reasoning": "Initially, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I was wondering the price range of the riverside brasserie.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you check on a train for me from london kings cross?", "streaming_reasoning": "As more information arrives, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like to leave after 11:15 on a Tuesday.", "streaming_reasoning": "As more information arrives, time: 11:15; day: tuesday; destination: leave after 11:15 on a tuesday..", "trace": "time+=11:15; day+=tuesday; destination+=leave after 11:15 on a tuesday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes I'd like to book that train for 5 and I'd like the reference number as well please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I think that will be all for today Thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: destination is leave after 11:15 on a tuesday; requested information is postcode; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, booking, confirm_booking; destination=leave after 11:15 on a tuesday; requested_info=postcode, reference_number; when=tuesday, 11:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002678", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am going to visit and was told about the a and b guest house.\nChunk 2: Could you help me with that?\nChunk 3: What's the phone number and how many stars is it?\nChunk 4: I want to find a expensive restaurant.\nChunk 5: It should be in the centre part of town.\nChunk 6: I'd love to try some European food.\nChunk 7: Yes, I need a table for 7 please at 18:00.\nChunk 8: I want to find a restaurant.\nChunk 9: The time is thursday.\nChunk 10: I also need the reference number.", "streaming_reasoning": "C1 domain=hotel; hotel_type+=guesthouse; destination+=visit and was told about the a and b gues. C2 goal=search. C3 goal=request_info; requested_info+=phone. C4 domain=restaurant; price+=expensive; destination+=find a expensive restaurant. C5 area+=centre. C6 cuisine+=european; destination+=try some european food. C7 time+=7, 18:00; acceptance=selected_option. C8 [SKIP: repeated_information]. C9 day+=thursday. C10 requested_info+=reference_number.", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=european; price=expensive; destination=visit and was told about the a and b gues, find a expensive restaurant, try some european food; requested_info=phone, reference_number; when=thursday, 7, 18:00.", "answer": "I can help with that and include the phone, reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am going to visit and was told about the a and b guest house.\nChunk 2: Could you help me with that?\nChunk 3: What's the phone number and how many stars is it?\nChunk 4: I want to find a expensive restaurant.\nChunk 5: It should be in the centre part of town.\nChunk 6: I'd love to try some European food.\nChunk 7: Yes, I need a table for 7 please at 18:00.\nChunk 8: I want to find a restaurant.\nChunk 9: The time is thursday.\nChunk 10: I also need the reference number."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=guesthouse; destination+=visit and was told about the a and b gues. C2 goal=search. C3 goal=request_info; requested_info+=phone. C4 domain=restaurant; price+=expensive; destination+=find a expensive restaurant. C5 area+=centre. C6 cuisine+=european; destination+=try some european food. C7 time+=7, 18:00; acceptance=selected_option. C8 [SKIP: repeated_information]. C9 day+=thursday. C10 requested_info+=reference_number.\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=european; price=expensive; destination=visit and was told about the a and b gues, find a expensive restaurant, try some european food; requested_info=phone, reference_number; when=thursday, 7, 18:00.\n\nAnswer: I can help with that and include the phone, reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am going to visit and was told about the a and b guest house.\nChunk 2: Could you help me with that?\nChunk 3: What's the phone number and how many stars is it?\nChunk 4: I want to find a expensive restaurant.\nChunk 5: It should be in the centre part of town.\nChunk 6: I'd love to try some European food.\nChunk 7: Yes, I need a table for 7 please at 18:00.\nChunk 8: I want to find a restaurant.\nChunk 9: The time is thursday.\nChunk 10: I also need the reference number.", "input_token_count": 101, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse; destination: visit and was told about the a and b gues. Next, the goal is search. Next, the goal is request info; requested information: phone. Next, the topic is restaurant; price: expensive; destination: find a expensive restaurant. Next, area: centre. Next, cuisine: european; destination: try some european food. Next, time: 7; acceptance: selected_option. Next, day: thursday. Finally, requested information: reference_number.  Some chunks were skipped because they contained repeated_information. In summary, The overall topic is restaurant. the goal is request info. hotel type: guesthouse; destination: visit and was told about the a and b gues., find a expensive restaurant., try some european food.; requested information: phone., reference_number.; price: expensive; area: centre.; cuisine: european; time: 7; acceptance: selected_option.; day: thursday..", "trace": "C1 domain=hotel; hotel_type+=guesthouse; destination+=visit and was told about the a and b gues. C2 goal=search. C3 goal=request_info; requested_info+=phone. C4 domain=restaurant; price+=expensive; destination+=find a expensive restaurant. C5 area+=centre. C6 cuisine+=european; destination+=try some european food. C7 time+=7, 18:00; acceptance=selected_option. C8 [SKIP: repeated_information]. C9 day+=thursday. C10 requested_info+=reference_number.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am going to visit and was told about the a and b guest house.", "streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse; destination: visit and was told about the a and b gues..", "trace": "domain=hotel; hotel_type+=guesthouse; destination+=visit and was told about the a and b gues."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Could you help me with that?", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What's the phone number and how many stars is it?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want to find a expensive restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; price: expensive; destination: find a expensive restaurant..", "trace": "domain=restaurant; price+=expensive; destination+=find a expensive restaurant."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'd love to try some European food.", "streaming_reasoning": "As more information arrives, cuisine: european; destination: try some european food..", "trace": "cuisine+=european; destination+=try some european food."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, I need a table for 7 please at 18:00.", "streaming_reasoning": "As more information arrives, time: 7; acceptance: selected_option..", "trace": "time+=7, 18:00; acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "The content at C8 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "The time is thursday.", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "I also need the reference number.", "streaming_reasoning": "Finally, requested information: reference_number..", "trace": "requested_info+=reference_number."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; cuisine is european; price is expensive; destination is visit and was told about the a and b gues; requested information is phone; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=european; price=expensive; destination=visit and was told about the a and b gues, find a expensive restaurant, try some european food; requested_info=phone, reference_number; when=thursday, 7, 18:00."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002679", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure, I want some help finding a restaurant in Cambridge, please.\nChunk 2: I don't have a specific restaurant in mind.\nChunk 3: I'm looking for an Indian restaurant.\nChunk 4: I want an expensive one in the centre.", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 intent=context_update. C3 cuisine+=indian. C4 area+=centre; price+=expensive.", "deep_reasoning": "Need domain=restaurant; goal=search; area=centre; food=indian; price=expensive.", "answer": "Got it. I will use restaurant, centre, indian, expensive and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sure, I want some help finding a restaurant in Cambridge, please.\nChunk 2: I don't have a specific restaurant in mind.\nChunk 3: I'm looking for an Indian restaurant.\nChunk 4: I want an expensive one in the centre."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 intent=context_update. C3 cuisine+=indian. C4 area+=centre; price+=expensive.\n\nDeep reasoning: Need domain=restaurant; goal=search; area=centre; food=indian; price=expensive.\n\nAnswer: Got it. I will use restaurant, centre, indian, expensive and move the task forward."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure, I want some help finding a restaurant in Cambridge, please.\nChunk 2: I don't have a specific restaurant in mind.\nChunk 3: I'm looking for an Indian restaurant.\nChunk 4: I want an expensive one in the centre.", "input_token_count": 41, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, intent: context_update. Next, cuisine: indian. Finally, area: centre; price: expensive. In summary, The overall topic is restaurant. the goal is search.. intent: context_update.; cuisine: indian.; area: centre; price: expensive..", "trace": "C1 domain=restaurant; goal=search. C2 intent=context_update. C3 cuisine+=indian. C4 area+=centre; price+=expensive.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sure, I want some help finding a restaurant in Cambridge, please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I don't have a specific restaurant in mind.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm looking for an Indian restaurant.", "streaming_reasoning": "As more information arrives, cuisine: indian..", "trace": "cuisine+=indian."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want an expensive one in the centre.", "streaming_reasoning": "Finally, area: centre; price: expensive..", "trace": "area+=centre; price+=expensive."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is indian; price is expensive.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use restaurant, centre, indian, expensive and move the task forward.", "deep_reasoning_trace": "Need domain=restaurant; goal=search; area=centre; food=indian; price=expensive."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001801", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: When a tornado touched down a few hundred feet from my property, I was pretty scared.\nChunk 2: I was really scared when a tornado came down a few hundred feet from my house.\nChunk 3: Oh that is scary, that happened to us a couple months ago!\nChunk 4: Yeah, there is really nothing you can do about it I guess.\nChunk 5: I suppose find the safest spot to bunker down, it's hard not to panic though.", "streaming_reasoning": "C1 emotion=anxious; cause=a tornado touched down a few hundred feet from my property, I; need=reassurance. C2 emotion=anxious; cause=a tornado came down a few hundred feet from my house. C3 emotion=anxious. C4 support_signal=received. C5 emotion=anxious; cause=I suppose find the safest spot to bunker down, it's hard not.", "deep_reasoning": "User feels anxious after I suppose find the safest spot to bunker down, it's hard not and needs reassurance.", "answer": "It makes sense to feel anxious after I suppose find the safest spot to bunker down, it's hard not. Slow down, check what is actually known, and take one small step before deciding what comes next.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: When a tornado touched down a few hundred feet from my property, I was pretty scared.\nChunk 2: I was really scared when a tornado came down a few hundred feet from my house.\nChunk 3: Oh that is scary, that happened to us a couple months ago!\nChunk 4: Yeah, there is really nothing you can do about it I guess.\nChunk 5: I suppose find the safest spot to bunker down, it's hard not to panic though."}, {"role": "assistant", "content": "Streaming reasoning: C1 emotion=anxious; cause=a tornado touched down a few hundred feet from my property, I; need=reassurance. C2 emotion=anxious; cause=a tornado came down a few hundred feet from my house. C3 emotion=anxious. C4 support_signal=received. C5 emotion=anxious; cause=I suppose find the safest spot to bunker down, it's hard not.\n\nDeep reasoning: User feels anxious after I suppose find the safest spot to bunker down, it's hard not and needs reassurance.\n\nAnswer: It makes sense to feel anxious after I suppose find the safest spot to bunker down, it's hard not. Slow down, check what is actually known, and take one small step before deciding what comes next."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: When a tornado touched down a few hundred feet from my property, I was pretty scared.\nChunk 2: I was really scared when a tornado came down a few hundred feet from my house.\nChunk 3: Oh that is scary, that happened to us a couple months ago!\nChunk 4: Yeah, there is really nothing you can do about it I guess.\nChunk 5: I suppose find the safest spot to bunker down, it's hard not to panic though.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user expresses anxious about a tornado touched down a few hundred feet from my property; the user needs reassurance. Next, the user expresses anxious about a tornado came down a few hundred feet from my house. Next, the user expresses anxious. Next, the user signals support or acknowledgment. Finally, the user expresses anxious about I suppose find the safest spot to bunker down.", "trace": "C1 emotion=anxious; cause=a tornado touched down a few hundred feet from my property, I; need=reassurance. C2 emotion=anxious; cause=a tornado came down a few hundred feet from my house. C3 emotion=anxious. C4 support_signal=received. C5 emotion=anxious; cause=I suppose find the safest spot to bunker down, it's hard not.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "When a tornado touched down a few hundred feet from my property, I was pretty scared.", "streaming_reasoning": "Initially, the user expresses anxious about a tornado touched down a few hundred feet from my property; the user needs reassurance..", "trace": "emotion=anxious; cause=a tornado touched down a few hundred feet from my property, I; need=reassurance."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I was really scared when a tornado came down a few hundred feet from my house.", "streaming_reasoning": "As more information arrives, the user expresses anxious about a tornado came down a few hundred feet from my house..", "trace": "emotion=anxious; cause=a tornado came down a few hundred feet from my house."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Oh that is scary, that happened to us a couple months ago!", "streaming_reasoning": "As more information arrives, the user expresses anxious..", "trace": "emotion=anxious."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yeah, there is really nothing you can do about it I guess.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I suppose find the safest spot to bunker down, it's hard not to panic though.", "streaming_reasoning": "Finally, the user expresses anxious about I suppose find the safest spot to bunker down.", "trace": "emotion=anxious; cause=I suppose find the safest spot to bunker down, it's hard not."}]}, "output": {"deep_reasoning": "User feels anxious after I suppose find the safest spot to bunker down, it's hard not and needs reassurance.", "answer": "It makes sense to feel anxious after I suppose find the safest spot to bunker down, it's hard not. Slow down, check what is actually known, and take one small step before deciding what comes next."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002681", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That won't be necessary.\nChunk 2: I just need to look for a train now.\nChunk 3: I would like to go from Stansted to Cambridge, please.\nChunk 4: Yes the train should leave on Monday and arrive by 10:30.\nChunk 5: Yes, please book six tickets.\nChunk 6: Thank you that was all i needed No, good bye.", "streaming_reasoning": "C1 intent=context_update. C2 domain=train; goal=search; destination+=look for a train now. C3 destination+=cambridge; departure+=stansted. C4 time+=10:30; day+=monday; acceptance=selected_option. C5 goal=confirm_booking; goal=confirm_booking. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, booking, confirm_booking; destination=look for a train now, cambridge; departure=stansted; when=monday, 10:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: That won't be necessary.\nChunk 2: I just need to look for a train now.\nChunk 3: I would like to go from Stansted to Cambridge, please.\nChunk 4: Yes the train should leave on Monday and arrive by 10:30.\nChunk 5: Yes, please book six tickets.\nChunk 6: Thank you that was all i needed No, good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 domain=train; goal=search; destination+=look for a train now. C3 destination+=cambridge; departure+=stansted. C4 time+=10:30; day+=monday; acceptance=selected_option. C5 goal=confirm_booking; goal=confirm_booking. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, booking, confirm_booking; destination=look for a train now, cambridge; departure=stansted; when=monday, 10:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That won't be necessary.\nChunk 2: I just need to look for a train now.\nChunk 3: I would like to go from Stansted to Cambridge, please.\nChunk 4: Yes the train should leave on Monday and arrive by 10:30.\nChunk 5: Yes, please book six tickets.\nChunk 6: Thank you that was all i needed No, good bye.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the topic is train; the goal is search; destination: look for a train now. Next, destination: cambridge; departure point: stansted. Next, time: 10:30; day: monday; acceptance: selected_option. Finally, the goal is confirm booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is confirm booking.. intent: context_update.; destination: look for a train now., cambridge; departure point: stansted.; time: 10:30; day: monday; acceptance: selected_option..", "trace": "C1 intent=context_update. C2 domain=train; goal=search; destination+=look for a train now. C3 destination+=cambridge; departure+=stansted. C4 time+=10:30; day+=monday; acceptance=selected_option. C5 goal=confirm_booking; goal=confirm_booking. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "That won't be necessary.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I just need to look for a train now.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; destination: look for a train now..", "trace": "domain=train; goal=search; destination+=look for a train now."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to go from Stansted to Cambridge, please.", "streaming_reasoning": "As more information arrives, destination: cambridge; departure point: stansted..", "trace": "destination+=cambridge; departure+=stansted."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes the train should leave on Monday and arrive by 10:30.", "streaming_reasoning": "As more information arrives, time: 10:30; day: monday; acceptance: selected_option..", "trace": "time+=10:30; day+=monday; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, please book six tickets.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you that was all i needed No, good bye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is look for a train now; departure point is stansted; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, booking, confirm_booking; destination=look for a train now, cambridge; departure=stansted; when=monday, 10:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003339", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Good morning, Jerry How's everything Fine, just fine.\nChunk 2: Thanks.\nChunk 3: Doing anything for lunch?", "streaming_reasoning": "C1 casual_comment=morning, jerry. C2 [SKIP: thanks_only]. C3 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Good morning, Jerry How's everything Fine, just fine.\nChunk 2: Thanks.\nChunk 3: Doing anything for lunch?"}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=morning, jerry. C2 [SKIP: thanks_only]. C3 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Good morning, Jerry How's everything Fine, just fine.\nChunk 2: Thanks.\nChunk 3: Doing anything for lunch?", "input_token_count": 19, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on morning. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=morning, jerry. C2 [SKIP: thanks_only]. C3 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Good morning, Jerry How's everything Fine, just fine.", "streaming_reasoning": "Initially, the user comments on morning.", "trace": "casual_comment=morning, jerry."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Doing anything for lunch?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003340", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sweet.Can you tell me where it is?\nChunk 2: Oh no, I can't tell you It's a secret.\nChunk 3: Say, why don't you go over by the lily pads and try fishing there?\nChunk 4: Do you think that's a good spot?\nChunk 5: Sure, I used to catch my legal limit of bass there all the time.\nChunk 6: Thanks.\nChunk 7: I think I'll go check that out now.", "streaming_reasoning": "C1 question=true. C2 schedule_conflict=true. C3 question=true. C4 question=true. C5 casual_comment=used, catch. C6 [SKIP: thanks_only]. C7 casual_comment=think, i'll.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sweet.Can you tell me where it is?\nChunk 2: Oh no, I can't tell you It's a secret.\nChunk 3: Say, why don't you go over by the lily pads and try fishing there?\nChunk 4: Do you think that's a good spot?\nChunk 5: Sure, I used to catch my legal limit of bass there all the time.\nChunk 6: Thanks.\nChunk 7: I think I'll go check that out now."}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 schedule_conflict=true. C3 question=true. C4 question=true. C5 casual_comment=used, catch. C6 [SKIP: thanks_only]. C7 casual_comment=think, i'll.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sweet.Can you tell me where it is?\nChunk 2: Oh no, I can't tell you It's a secret.\nChunk 3: Say, why don't you go over by the lily pads and try fishing there?\nChunk 4: Do you think that's a good spot?\nChunk 5: Sure, I used to catch my legal limit of bass there all the time.\nChunk 6: Thanks.\nChunk 7: I think I'll go check that out now.", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, schedule conflict: true. Next, the input provides additional context about question=true. Next, the input provides additional context about question=true. Next, the user comments on used. Finally, the user comments on think.  Some chunks were skipped because they contained thanks_only. In summary, schedule conflict: true..", "trace": "C1 question=true. C2 schedule_conflict=true. C3 question=true. C4 question=true. C5 casual_comment=used, catch. C6 [SKIP: thanks_only]. C7 casual_comment=think, i'll.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sweet.Can you tell me where it is?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Oh no, I can't tell you It's a secret.", "streaming_reasoning": "As more information arrives, schedule conflict: true..", "trace": "schedule_conflict=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Say, why don't you go over by the lily pads and try fishing there?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Do you think that's a good spot?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Sure, I used to catch my legal limit of bass there all the time.", "streaming_reasoning": "As more information arrives, the user comments on used.", "trace": "casual_comment=used, catch."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I think I'll go check that out now.", "streaming_reasoning": "Finally, the user comments on think.", "trace": "casual_comment=think, i'll."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002682", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: looking for places to go in town.\nChunk 2: The attraction should be in the same area as the restaurant.\nChunk 3: Can you make a recommendation?\nChunk 4: Actually, I just need to know what the entrance fee is.\nChunk 5: No that will be all.\nChunk 6: I don't need you to book but I would like the postcode for india house, please.\nChunk 7: Yeah that will be all Bye, thanks.", "streaming_reasoning": "C1 goal=search; destination+=go in town. C2 domain=attraction; goal=modify_constraint. C3 requested_info+=recommendation. C4 goal=request_info; destination+=know what the entrance fee is; requested_info+=entrance_fee. C5 [SKIP: closing_only]. C6 goal=booking; requested_info+=postcode. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, attraction; goal=search, modify_constraint, request_info, booking; destination=go in town, know what the entrance fee is; requested_info=recommendation, entrance_fee, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: looking for places to go in town.\nChunk 2: The attraction should be in the same area as the restaurant.\nChunk 3: Can you make a recommendation?\nChunk 4: Actually, I just need to know what the entrance fee is.\nChunk 5: No that will be all.\nChunk 6: I don't need you to book but I would like the postcode for india house, please.\nChunk 7: Yeah that will be all Bye, thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; destination+=go in town. C2 domain=attraction; goal=modify_constraint. C3 requested_info+=recommendation. C4 goal=request_info; destination+=know what the entrance fee is; requested_info+=entrance_fee. C5 [SKIP: closing_only]. C6 goal=booking; requested_info+=postcode. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, attraction; goal=search, modify_constraint, request_info, booking; destination=go in town, know what the entrance fee is; requested_info=recommendation, entrance_fee, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: looking for places to go in town.\nChunk 2: The attraction should be in the same area as the restaurant.\nChunk 3: Can you make a recommendation?\nChunk 4: Actually, I just need to know what the entrance fee is.\nChunk 5: No that will be all.\nChunk 6: I don't need you to book but I would like the postcode for india house, please.\nChunk 7: Yeah that will be all Bye, thanks.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; destination: go in town. Next, the topic is attraction; the goal is modify constraint. Next, requested information: recommendation. Next, the goal is request info; destination: know what the entrance fee is; requested information: entrance_fee. Finally, the goal is booking; requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is booking. destination: go in town., know what the entrance fee is; requested information: recommendation., entrance_fee., postcode..", "trace": "C1 goal=search; destination+=go in town. C2 domain=attraction; goal=modify_constraint. C3 requested_info+=recommendation. C4 goal=request_info; destination+=know what the entrance fee is; requested_info+=entrance_fee. C5 [SKIP: closing_only]. C6 goal=booking; requested_info+=postcode. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "looking for places to go in town.", "streaming_reasoning": "Initially, the goal is search; destination: go in town..", "trace": "goal=search; destination+=go in town."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The attraction should be in the same area as the restaurant.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is modify constraint..", "trace": "domain=attraction; goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you make a recommendation?", "streaming_reasoning": "As more information arrives, requested information: recommendation..", "trace": "requested_info+=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Actually, I just need to know what the entrance fee is.", "streaming_reasoning": "As more information arrives, the goal is request info; destination: know what the entrance fee is; requested information: entrance_fee..", "trace": "goal=request_info; destination+=know what the entrance fee is; requested_info+=entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No that will be all.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I don't need you to book but I would like the postcode for india house, please.", "streaming_reasoning": "As more information arrives, the goal is booking; requested information: postcode..", "trace": "goal=booking; requested_info+=postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yeah that will be all Bye, thanks.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: destination is go in town; requested information is recommendation. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction; goal=search, modify_constraint, request_info, booking; destination=go in town, know what the entrance fee is; requested_info=recommendation, entrance_fee, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002683", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a train to broxbourne.\nChunk 2: I'm going to be leaving from Cambridge.\nChunk 3: I need to leave on Tuesday by 13:00.\nChunk 4: I don't have an arrival preference.\nChunk 5: Actually, I'd like to arrive by 13:00.\nChunk 6: Could you give me the train ID for the train arriving closest to that time?", "streaming_reasoning": "C1 domain=train; goal=search; destination+=broxbourne. C2 intent=context_update. C3 time+=13:00; day+=tuesday; destination+=leave on tuesday by 13:00. C4 intent=context_update. C5 destination+=arrive by 13:00. C6 goal=request_info; destination+=that time.", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=broxbourne, leave on tuesday by 13:00, arrive by 13:00, that time; when=tuesday, 13:00.", "answer": "What departure should I use for the search?", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a train to broxbourne.\nChunk 2: I'm going to be leaving from Cambridge.\nChunk 3: I need to leave on Tuesday by 13:00.\nChunk 4: I don't have an arrival preference.\nChunk 5: Actually, I'd like to arrive by 13:00.\nChunk 6: Could you give me the train ID for the train arriving closest to that time?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=broxbourne. C2 intent=context_update. C3 time+=13:00; day+=tuesday; destination+=leave on tuesday by 13:00. C4 intent=context_update. C5 destination+=arrive by 13:00. C6 goal=request_info; destination+=that time.\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=broxbourne, leave on tuesday by 13:00, arrive by 13:00, that time; when=tuesday, 13:00.\n\nAnswer: What departure should I use for the search?"}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a train to broxbourne.\nChunk 2: I'm going to be leaving from Cambridge.\nChunk 3: I need to leave on Tuesday by 13:00.\nChunk 4: I don't have an arrival preference.\nChunk 5: Actually, I'd like to arrive by 13:00.\nChunk 6: Could you give me the train ID for the train arriving closest to that time?", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: broxbourne. Next, intent: context_update. Next, time: 13:00; day: tuesday; destination: leave on tuesday by 13:00. Next, intent: context_update. Next, destination: arrive by 13:00. Finally, the goal is request info; destination: that time. In summary, The overall topic is train. the goal is request info. destination: broxbourne., leave on tuesday by 13:00., arrive by 13:00., that time.; intent: context_update.; time: 13:00; day: tuesday.", "trace": "C1 domain=train; goal=search; destination+=broxbourne. C2 intent=context_update. C3 time+=13:00; day+=tuesday; destination+=leave on tuesday by 13:00. C4 intent=context_update. C5 destination+=arrive by 13:00. C6 goal=request_info; destination+=that time.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a train to broxbourne.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: broxbourne..", "trace": "domain=train; goal=search; destination+=broxbourne."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm going to be leaving from Cambridge.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to leave on Tuesday by 13:00.", "streaming_reasoning": "As more information arrives, time: 13:00; day: tuesday; destination: leave on tuesday by 13:00..", "trace": "time+=13:00; day+=tuesday; destination+=leave on tuesday by 13:00."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't have an arrival preference.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Actually, I'd like to arrive by 13:00.", "streaming_reasoning": "As more information arrives, destination: arrive by 13:00..", "trace": "destination+=arrive by 13:00."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could you give me the train ID for the train arriving closest to that time?", "streaming_reasoning": "Finally, the goal is request info; destination: that time..", "trace": "goal=request_info; destination+=that time."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is broxbourne; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "What departure should I use for the search?", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=broxbourne, leave on tuesday by 13:00, arrive by 13:00, that time; when=tuesday, 13:00."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000554", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Kill Mold With Vinegar.\nChunk 2: • Rubber gloves • Naturally distilled white vinegar (don't use artificial vinegar) • Spray bottle (mixture of 80% vinegar and 20% water) • Water • A bucket with clean water to wash your brush in.\nChunk 3: • Microfibre cloth and/or a stiff brush • Protective glasses and a dust mask should be used if you think you are affected by mould and the brush might raise spore laden dust or flick moldy material into your face.", "streaming_reasoning": "C1 task=kill_mold_with_vinegar. C2 step=rubber_gloves_naturally_distilled; safety=true. C3 step=microfibre_cloth_andor_a.", "deep_reasoning": "Procedure for Kill Mold With Vinegar: Rubber gloves Naturally distilled white vinegar Spray bottle Water A, Microfibre cloth and/or a stiff brush Protective glasses and a; keep safety/order constraints.", "answer": "For Kill Mold With Vinegar, follow the steps in order: Rubber gloves Naturally distilled white vinegar Spray bottle Water A, Microfibre cloth and/or a stiff brush Protective glasses and a. Keep the order and pause if a step seems unsafe.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Kill Mold With Vinegar.\nChunk 2: • Rubber gloves • Naturally distilled white vinegar (don't use artificial vinegar) • Spray bottle (mixture of 80% vinegar and 20% water) • Water • A bucket with clean water to wash your brush in.\nChunk 3: • Microfibre cloth and/or a stiff brush • Protective glasses and a dust mask should be used if you think you are affected by mould and the brush might raise spore laden dust or flick moldy material into your face."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=kill_mold_with_vinegar. C2 step=rubber_gloves_naturally_distilled; safety=true. C3 step=microfibre_cloth_andor_a.\n\nDeep reasoning: Procedure for Kill Mold With Vinegar: Rubber gloves Naturally distilled white vinegar Spray bottle Water A, Microfibre cloth and/or a stiff brush Protective glasses and a; keep safety/order constraints.\n\nAnswer: For Kill Mold With Vinegar, follow the steps in order: Rubber gloves Naturally distilled white vinegar Spray bottle Water A, Microfibre cloth and/or a stiff brush Protective glasses and a. Keep the order and pause if a step seems unsafe."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Kill Mold With Vinegar.\nChunk 2: • Rubber gloves • Naturally distilled white vinegar (don't use artificial vinegar) • Spray bottle (mixture of 80% vinegar and 20% water) • Water • A bucket with clean water to wash your brush in.\nChunk 3: • Microfibre cloth and/or a stiff brush • Protective glasses and a dust mask should be used if you think you are affected by mould and the brush might raise spore laden dust or flick moldy material into your face.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, task: kill_mold_with_vinegar. Next, step: rubber_gloves_naturally_distilled; safety: true. Finally, step: microfibre_cloth_andor_a. In summary, task: kill_mold_with_vinegar.; step: rubber_gloves_naturally_distilled, microfibre_cloth_andor_a.; safety: true..", "trace": "C1 task=kill_mold_with_vinegar. C2 step=rubber_gloves_naturally_distilled; safety=true. C3 step=microfibre_cloth_andor_a.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Kill Mold With Vinegar.", "streaming_reasoning": "Initially, task: kill_mold_with_vinegar..", "trace": "task=kill_mold_with_vinegar."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• Rubber gloves • Naturally distilled white vinegar (don't use artificial vinegar) • Spray bottle (mixture of 80% vinegar and 20% water) • Water • A bucket with clean water to wash your brush in.", "streaming_reasoning": "As more information arrives, step: rubber_gloves_naturally_distilled; safety: true..", "trace": "step=rubber_gloves_naturally_distilled; safety=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "• Microfibre cloth and/or a stiff brush • Protective glasses and a dust mask should be used if you think you are affected by mould and the brush might raise spore laden dust or flick moldy material into your face.", "streaming_reasoning": "Finally, step: microfibre_cloth_andor_a..", "trace": "step=microfibre_cloth_andor_a."}]}, "output": {"deep_reasoning": "Procedure for Kill Mold With Vinegar: Rubber gloves Naturally distilled white vinegar Spray bottle Water A, Microfibre cloth and/or a stiff brush Protective glasses and a; keep safety/order constraints.", "answer": "For Kill Mold With Vinegar, follow the steps in order: Rubber gloves Naturally distilled white vinegar Spray bottle Water A, Microfibre cloth and/or a stiff brush Protective glasses and a. Keep the order and pause if a step seems unsafe."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002684", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you try for 11:30 and give me a reference number please.\nChunk 2: Thanks I also need to find a hotel with a 5 star rating Are you sure?\nChunk 3: I would prefer a 5 star hotel with free wifi.\nChunk 4: A 4 star rating is fine, what do you have for that?\nChunk 5: It should be in the centre part of town.\nChunk 6: It is for 3 people.\nChunk 7: The time is wednesday, 3, 4.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number Wonderful!\nChunk 10: That's all I need.\nChunk 11: Thank you very much for your help!", "streaming_reasoning": "C1 goal=request_info; time+=11:30; requested_info+=reference_number. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=5 stars; destination+=find a hotel with a 5 star rating are you. C3 amenities+=wifi. C4 stars+=4 stars. C5 area+=centre. C6 party_size+=3 people. C7 time+=3, 4; day+=wednesday. C8 goal=booking. C9 intent=context_update. C10 [SKIP: closing_only]. C11 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=request_info, search, booking; area=centre; party_size=3 people; stars=5 stars, 4 stars; amenities=wifi; destination=find a hotel with a 5 star rating are you; requested_info=reference_number; when=wednesday, 11:30, 3, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you try for 11:30 and give me a reference number please.\nChunk 2: Thanks I also need to find a hotel with a 5 star rating Are you sure?\nChunk 3: I would prefer a 5 star hotel with free wifi.\nChunk 4: A 4 star rating is fine, what do you have for that?\nChunk 5: It should be in the centre part of town.\nChunk 6: It is for 3 people.\nChunk 7: The time is wednesday, 3, 4.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number Wonderful!\nChunk 10: That's all I need.\nChunk 11: Thank you very much for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; time+=11:30; requested_info+=reference_number. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=5 stars; destination+=find a hotel with a 5 star rating are you. C3 amenities+=wifi. C4 stars+=4 stars. C5 area+=centre. C6 party_size+=3 people. C7 time+=3, 4; day+=wednesday. C8 goal=booking. C9 intent=context_update. C10 [SKIP: closing_only]. C11 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=request_info, search, booking; area=centre; party_size=3 people; stars=5 stars, 4 stars; amenities=wifi; destination=find a hotel with a 5 star rating are you; requested_info=reference_number; when=wednesday, 11:30, 3, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you try for 11:30 and give me a reference number please.\nChunk 2: Thanks I also need to find a hotel with a 5 star rating Are you sure?\nChunk 3: I would prefer a 5 star hotel with free wifi.\nChunk 4: A 4 star rating is fine, what do you have for that?\nChunk 5: It should be in the centre part of town.\nChunk 6: It is for 3 people.\nChunk 7: The time is wednesday, 3, 4.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number Wonderful!\nChunk 10: That's all I need.\nChunk 11: Thank you very much for your help!", "input_token_count": 115, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; time: 11:30; requested information: reference_number. Next, the topic is hotel; the goal is search; hotel type: hotel; star rating: 5 stars; destination: find a hotel with a 5 star rating are you. Next, amenities: wifi. Next, star rating: 4 stars. Next, area: centre. Next, party size: 3 people. Next, time: 3; day: wednesday. Next, the goal is booking. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is booking.. time: 11:30, 3; requested information: reference_number.; hotel type: hotel; star rating: 5 stars, 4 stars.; destination: find a hotel with a 5 star rating are you.; amenities: wifi.; area: centre.; party size: 3 people.; day: wednesday.; intent: context_update..", "trace": "C1 goal=request_info; time+=11:30; requested_info+=reference_number. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=5 stars; destination+=find a hotel with a 5 star rating are you. C3 amenities+=wifi. C4 stars+=4 stars. C5 area+=centre. C6 party_size+=3 people. C7 time+=3, 4; day+=wednesday. C8 goal=booking. C9 intent=context_update. C10 [SKIP: closing_only]. C11 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you try for 11:30 and give me a reference number please.", "streaming_reasoning": "Initially, the goal is request info; time: 11:30; requested information: reference_number..", "trace": "goal=request_info; time+=11:30; requested_info+=reference_number."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks I also need to find a hotel with a 5 star rating Are you sure?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: hotel; star rating: 5 stars; destination: find a hotel with a 5 star rating are you..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; stars+=5 stars; destination+=find a hotel with a 5 star rating are you."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would prefer a 5 star hotel with free wifi.", "streaming_reasoning": "As more information arrives, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "A 4 star rating is fine, what do you have for that?", "streaming_reasoning": "As more information arrives, star rating: 4 stars..", "trace": "stars+=4 stars."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It is for 3 people.", "streaming_reasoning": "As more information arrives, party size: 3 people..", "trace": "party_size+=3 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is wednesday, 3, 4.", "streaming_reasoning": "As more information arrives, time: 3; day: wednesday..", "trace": "time+=3, 4; day+=wednesday."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need the reference number Wonderful!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That's all I need.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Thank you very much for your help!", "streaming_reasoning": "The content at C11 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: area is centre; party size is 3 people; star rating is 5 stars; amenities is wifi; destination is find a hotel with a 5 star rating are you; requested information is reference_number; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search, booking; area=centre; party_size=3 people; stars=5 stars, 4 stars; amenities=wifi; destination=find a hotel with a 5 star rating are you; requested_info=reference_number; when=wednesday, 11:30, 3, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002685", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: I also need the address.\nChunk 3: I also need the phone.\nChunk 4: I also need the price Thank you goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 goal=request_info; requested_info+=address. C3 requested_info+=phone. C4 requested_info+=price.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; destination=find a restaurant; requested_info=address, phone, price.", "answer": "I can help with that and include the address, phone, price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a restaurant.\nChunk 2: I also need the address.\nChunk 3: I also need the phone.\nChunk 4: I also need the price Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 goal=request_info; requested_info+=address. C3 requested_info+=phone. C4 requested_info+=price.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; destination=find a restaurant; requested_info=address, phone, price.\n\nAnswer: I can help with that and include the address, phone, price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: I also need the address.\nChunk 3: I also need the phone.\nChunk 4: I also need the price Thank you goodbye.", "input_token_count": 32, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant. Next, the goal is request info; requested information: address. Next, requested information: phone. Finally, requested information: price. In summary, The overall topic is restaurant. the goal is request info. destination: find a restaurant.; requested information: address., phone., price..", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 goal=request_info; requested_info+=address. C3 requested_info+=phone. C4 requested_info+=price.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need the address.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the price Thank you goodbye.", "streaming_reasoning": "Finally, requested information: price..", "trace": "requested_info+=price."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: destination is find a restaurant; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone, price once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; destination=find a restaurant; requested_info=address, phone, price."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002686", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to find a restaurant in the east part of town that serves gastropub food.\nChunk 2: What is the phone number?\nChunk 3: thank you very much, bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=east; destination+=find a restaurant in the east part of tow. C2 goal=request_info; requested_info+=phone. C3 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=east; destination=find a restaurant in the east part of tow; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to find a restaurant in the east part of town that serves gastropub food.\nChunk 2: What is the phone number?\nChunk 3: thank you very much, bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=east; destination+=find a restaurant in the east part of tow. C2 goal=request_info; requested_info+=phone. C3 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=east; destination=find a restaurant in the east part of tow; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to find a restaurant in the east part of town that serves gastropub food.\nChunk 2: What is the phone number?\nChunk 3: thank you very much, bye.", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: east; destination: find a restaurant in the east part of tow. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: east; destination: find a restaurant in the east part of tow.; requested information: phone..", "trace": "C1 domain=restaurant; goal=search; area+=east; destination+=find a restaurant in the east part of tow. C2 goal=request_info; requested_info+=phone. C3 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to find a restaurant in the east part of town that serves gastropub food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: east; destination: find a restaurant in the east part of tow..", "trace": "domain=restaurant; goal=search; area+=east; destination+=find a restaurant in the east part of tow."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "thank you very much, bye.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is east; destination is find a restaurant in the east part of tow; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=east; destination=find a restaurant in the east part of tow; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002687", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to leave from London and travel to Cambridge on Saturday around 15:00.\nChunk 2: I would like to depart from Cambridge.\nChunk 3: I am leaving from cambridge going to broxbourne and want to arrive by 8:30.\nChunk 4: As long as it arrives by 8:30 that sounds good.\nChunk 5: I'll need 7 seats please Reference number please?\nChunk 6: That is all, thank you.", "streaming_reasoning": "C1 time+=15:00; day+=saturday; destination+=cambridge; departure+=london and travel. C2 departure+=cambridge. C3 goal=search; time+=8:30; destination+=broxbourne and want to arrive by 8:30. C4 acceptance=selected_option. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only].", "deep_reasoning": "Need goal=search, request_info; destination=cambridge, broxbourne and want to arrive by 8:30; departure=london and travel, cambridge; requested_info=reference_number; when=saturday, 15:00, 8:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like to leave from London and travel to Cambridge on Saturday around 15:00.\nChunk 2: I would like to depart from Cambridge.\nChunk 3: I am leaving from cambridge going to broxbourne and want to arrive by 8:30.\nChunk 4: As long as it arrives by 8:30 that sounds good.\nChunk 5: I'll need 7 seats please Reference number please?\nChunk 6: That is all, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=15:00; day+=saturday; destination+=cambridge; departure+=london and travel. C2 departure+=cambridge. C3 goal=search; time+=8:30; destination+=broxbourne and want to arrive by 8:30. C4 acceptance=selected_option. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search, request_info; destination=cambridge, broxbourne and want to arrive by 8:30; departure=london and travel, cambridge; requested_info=reference_number; when=saturday, 15:00, 8:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to leave from London and travel to Cambridge on Saturday around 15:00.\nChunk 2: I would like to depart from Cambridge.\nChunk 3: I am leaving from cambridge going to broxbourne and want to arrive by 8:30.\nChunk 4: As long as it arrives by 8:30 that sounds good.\nChunk 5: I'll need 7 seats please Reference number please?\nChunk 6: That is all, thank you.", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 15:00; day: saturday; destination: cambridge; departure point: london and travel. Next, departure point: cambridge. Next, the goal is search; time: 8:30; destination: broxbourne and want to arrive by 8:30. Next, acceptance: selected_option. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained closing_only. In summary, the goal is request info. time: 15:00, 8:30; day: saturday; destination: cambridge, broxbourne and want to arrive by 8:30.; departure point: london and travel., cambridge.; acceptance: selected_option.; requested information: reference_number..", "trace": "C1 time+=15:00; day+=saturday; destination+=cambridge; departure+=london and travel. C2 departure+=cambridge. C3 goal=search; time+=8:30; destination+=broxbourne and want to arrive by 8:30. C4 acceptance=selected_option. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like to leave from London and travel to Cambridge on Saturday around 15:00.", "streaming_reasoning": "Initially, time: 15:00; day: saturday; destination: cambridge; departure point: london and travel..", "trace": "time+=15:00; day+=saturday; destination+=cambridge; departure+=london and travel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to depart from Cambridge.", "streaming_reasoning": "As more information arrives, departure point: cambridge..", "trace": "departure+=cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am leaving from cambridge going to broxbourne and want to arrive by 8:30.", "streaming_reasoning": "As more information arrives, the goal is search; time: 8:30; destination: broxbourne and want to arrive by 8:30..", "trace": "goal=search; time+=8:30; destination+=broxbourne and want to arrive by 8:30."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "As long as it arrives by 8:30 that sounds good.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'll need 7 seats please Reference number please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all, thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search, request_info; destination=cambridge, broxbourne and want to arrive by 8:30; departure=london and travel, cambridge; requested_info=reference_number; when=saturday, 15:00, 8:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002688", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am in need of a taxi to the cambridge punter please.\nChunk 2: I will be leaving from Magdalene college.\nChunk 3: I want to leave after 16:45.\nChunk 4: Great, thanks for your help.\nChunk 5: No I am actually all set now thanks though.", "streaming_reasoning": "C1 domain=taxi; goal=search; destination+=the cambridge punter please. C2 domain=attraction. C3 time+=16:45; destination+=leave after 16:45. C4 [SKIP: thanks_only]. C5 goal=modify_constraint.", "deep_reasoning": "Need domain=taxi, attraction; goal=search; destination=the cambridge punter please, leave after 16:45; when=16:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am in need of a taxi to the cambridge punter please.\nChunk 2: I will be leaving from Magdalene college.\nChunk 3: I want to leave after 16:45.\nChunk 4: Great, thanks for your help.\nChunk 5: No I am actually all set now thanks though."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search; destination+=the cambridge punter please. C2 domain=attraction. C3 time+=16:45; destination+=leave after 16:45. C4 [SKIP: thanks_only]. C5 goal=modify_constraint.\n\nDeep reasoning: Need domain=taxi, attraction; goal=search; destination=the cambridge punter please, leave after 16:45; when=16:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am in need of a taxi to the cambridge punter please.\nChunk 2: I will be leaving from Magdalene college.\nChunk 3: I want to leave after 16:45.\nChunk 4: Great, thanks for your help.\nChunk 5: No I am actually all set now thanks though.", "input_token_count": 50, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search; destination: the cambridge punter please. Next, the topic is attraction. Next, time: 16:45; destination: leave after 16:45. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction.. the goal is modify constraint.. destination: the cambridge punter please., leave after 16:45.; time: 16:45.", "trace": "C1 domain=taxi; goal=search; destination+=the cambridge punter please. C2 domain=attraction. C3 time+=16:45; destination+=leave after 16:45. C4 [SKIP: thanks_only]. C5 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am in need of a taxi to the cambridge punter please.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search; destination: the cambridge punter please..", "trace": "domain=taxi; goal=search; destination+=the cambridge punter please."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be leaving from Magdalene college.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to leave after 16:45.", "streaming_reasoning": "As more information arrives, time: 16:45; destination: leave after 16:45..", "trace": "time+=16:45; destination+=leave after 16:45."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Great, thanks for your help.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No I am actually all set now thanks though.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is the cambridge punter please; timing is 16:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, attraction; goal=search; destination=the cambridge punter please, leave after 16:45; when=16:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002689", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is there an email I can contact them at?\nChunk 2: That would be all thanks you very much Actually, I'm sorry.\nChunk 3: Would you be able to confirm that the hotel you've booked has wifi?\nChunk 4: I don't have that in my notes.\nChunk 5: I don't actually need the train booked yet, I just needed to know the price.\nChunk 6: I think I have everything I need now, thanks for your help!\nChunk 7: Thank you for looking that up for me.\nChunk 8: Yes that is everything thank you for all your help Goodbye.", "streaming_reasoning": "C1 goal=request_info. C2 intent=context_update. C3 domain=hotel; hotel_type+=hotel; amenities+=wifi. C4 intent=context_update. C5 domain=train; goal=search; destination+=know the price; requested_info+=price. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 acceptance=selected_option.", "deep_reasoning": "Need domain=hotel, train; goal=search; amenities=wifi; destination=know the price; requested_info=price; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Is there an email I can contact them at?\nChunk 2: That would be all thanks you very much Actually, I'm sorry.\nChunk 3: Would you be able to confirm that the hotel you've booked has wifi?\nChunk 4: I don't have that in my notes.\nChunk 5: I don't actually need the train booked yet, I just needed to know the price.\nChunk 6: I think I have everything I need now, thanks for your help!\nChunk 7: Thank you for looking that up for me.\nChunk 8: Yes that is everything thank you for all your help Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 intent=context_update. C3 domain=hotel; hotel_type+=hotel; amenities+=wifi. C4 intent=context_update. C5 domain=train; goal=search; destination+=know the price; requested_info+=price. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 acceptance=selected_option.\n\nDeep reasoning: Need domain=hotel, train; goal=search; amenities=wifi; destination=know the price; requested_info=price; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is there an email I can contact them at?\nChunk 2: That would be all thanks you very much Actually, I'm sorry.\nChunk 3: Would you be able to confirm that the hotel you've booked has wifi?\nChunk 4: I don't have that in my notes.\nChunk 5: I don't actually need the train booked yet, I just needed to know the price.\nChunk 6: I think I have everything I need now, thanks for your help!\nChunk 7: Thank you for looking that up for me.\nChunk 8: Yes that is everything thank you for all your help Goodbye.", "input_token_count": 102, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, intent: context_update. Next, the topic is hotel; hotel type: hotel; amenities: wifi. Next, intent: context_update. Next, the topic is train; the goal is search; destination: know the price; requested information: price. Finally, acceptance: selected_option.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is search. intent: context_update.; hotel type: hotel; amenities: wifi.; destination: know the price; requested information: price.; acceptance: selected_option..", "trace": "C1 goal=request_info. C2 intent=context_update. C3 domain=hotel; hotel_type+=hotel; amenities+=wifi. C4 intent=context_update. C5 domain=train; goal=search; destination+=know the price; requested_info+=price. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 acceptance=selected_option.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Is there an email I can contact them at?", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "That would be all thanks you very much Actually, I'm sorry.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Would you be able to confirm that the hotel you've booked has wifi?", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; amenities: wifi..", "trace": "domain=hotel; hotel_type+=hotel; amenities+=wifi."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't have that in my notes.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I don't actually need the train booked yet, I just needed to know the price.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; destination: know the price; requested information: price..", "trace": "domain=train; goal=search; destination+=know the price; requested_info+=price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I think I have everything I need now, thanks for your help!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for looking that up for me.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Yes that is everything thank you for all your help Goodbye.", "streaming_reasoning": "Finally, acceptance: selected_option..", "trace": "acceptance=selected_option."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: amenities is wifi; destination is know the price; requested information is price. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, train; goal=search; amenities=wifi; destination=know the price; requested_info=price; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002690", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to find a hospital in town.\nChunk 2: Thanks for the help, bye!", "streaming_reasoning": "C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hospital; goal=search; destination=find a hospital in town; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i want to find a hospital in town.\nChunk 2: Thanks for the help, bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hospital; goal=search; destination=find a hospital in town; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to find a hospital in town.\nChunk 2: Thanks for the help, bye!", "input_token_count": 17, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital in town.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hospital. the goal is search. destination: find a hospital in town..", "trace": "C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i want to find a hospital in town.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital in town..", "trace": "domain=hospital; goal=search; destination+=find a hospital in town."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks for the help, bye!", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: destination is find a hospital in town. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search; destination=find a hospital in town; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002691", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would you also find me a hotel in the same area No, that's OK.\nChunk 2: The Allenbell is great.\nChunk 3: What i need is information on boat attraction in the same pay off town.\nChunk 4: I'd just like the phone number and postcode for now Thank you.\nChunk 5: Yes I will need a taxi to get me to the attraction by 08:15.\nChunk 6: No I want to leave Camboats at 08:15 and go to the hotel Thank you.\nChunk 7: That is all I need.", "streaming_reasoning": "C1 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C2 intent=context_update. C3 domain=attraction. C4 goal=request_info; requested_info+=phone, postcode. C5 domain=taxi; time+=08:15; acceptance=selected_option. C6 destination+=leave camboats at 08:15 and go to the hot. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, attraction, taxi; goal=search, modify_constraint, request_info; destination=leave camboats at 08:15 and go to the hot; requested_info=phone, postcode; when=08:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Would you also find me a hotel in the same area No, that's OK.\nChunk 2: The Allenbell is great.\nChunk 3: What i need is information on boat attraction in the same pay off town.\nChunk 4: I'd just like the phone number and postcode for now Thank you.\nChunk 5: Yes I will need a taxi to get me to the attraction by 08:15.\nChunk 6: No I want to leave Camboats at 08:15 and go to the hotel Thank you.\nChunk 7: That is all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C2 intent=context_update. C3 domain=attraction. C4 goal=request_info; requested_info+=phone, postcode. C5 domain=taxi; time+=08:15; acceptance=selected_option. C6 destination+=leave camboats at 08:15 and go to the hot. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, attraction, taxi; goal=search, modify_constraint, request_info; destination=leave camboats at 08:15 and go to the hot; requested_info=phone, postcode; when=08:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would you also find me a hotel in the same area No, that's OK.\nChunk 2: The Allenbell is great.\nChunk 3: What i need is information on boat attraction in the same pay off town.\nChunk 4: I'd just like the phone number and postcode for now Thank you.\nChunk 5: Yes I will need a taxi to get me to the attraction by 08:15.\nChunk 6: No I want to leave Camboats at 08:15 and go to the hotel Thank you.\nChunk 7: That is all I need.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is modify constraint; hotel type: hotel. Next, intent: context_update. Next, the topic is attraction. Next, the goal is request info; requested information: phone. Next, the topic is taxi; time: 08:15; acceptance: selected_option. Finally, destination: leave camboats at 08:15 and go to the hot.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is request info. hotel type: hotel.; intent: context_update.; requested information: phone; time: 08:15; acceptance: selected_option.; destination: leave camboats at 08:15 and go to the hot..", "trace": "C1 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C2 intent=context_update. C3 domain=attraction. C4 goal=request_info; requested_info+=phone, postcode. C5 domain=taxi; time+=08:15; acceptance=selected_option. C6 destination+=leave camboats at 08:15 and go to the hot. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Would you also find me a hotel in the same area No, that's OK.", "streaming_reasoning": "Initially, the topic is hotel; the goal is modify constraint; hotel type: hotel..", "trace": "domain=hotel; goal=modify_constraint; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The Allenbell is great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What i need is information on boat attraction in the same pay off town.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd just like the phone number and postcode for now Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes I will need a taxi to get me to the attraction by 08:15.", "streaming_reasoning": "As more information arrives, the topic is taxi; time: 08:15; acceptance: selected_option..", "trace": "domain=taxi; time+=08:15; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No I want to leave Camboats at 08:15 and go to the hotel Thank you.", "streaming_reasoning": "As more information arrives, destination: leave camboats at 08:15 and go to the hot..", "trace": "destination+=leave camboats at 08:15 and go to the hot."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: destination is leave camboats at 08:15 and go to the hot; requested information is phone; timing is 08:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, attraction, taxi; goal=search, modify_constraint, request_info; destination=leave camboats at 08:15 and go to the hot; requested_info=phone, postcode; when=08:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002692", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to travel on Monday evening Cambridge.\nChunk 2: And I'd like to leave after 18:00.\nChunk 3: Yes.\nChunk 4: I'm also looking for a museum on the East side of town please.\nChunk 5: I would like Cambridge Artworks.\nChunk 6: Can you give me the phone number and postcode for it?\nChunk 7: Thank you for your help.\nChunk 8: No, I don't think so.\nChunk 9: Thanks for your help!", "streaming_reasoning": "C1 day+=monday; destination+=travel on monday evening cambridge. C2 time+=18:00; destination+=leave after 18:00. C3 [SKIP: acknowledgement_only]. C4 domain=attraction; goal=search; area+=east. C5 intent=context_update. C6 goal=request_info; requested_info+=phone, postcode. C7 [SKIP: thanks_only]. C8 goal=modify_constraint. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction; goal=search, request_info; area=east; destination=travel on monday evening cambridge, leave after 18:00; requested_info=phone, postcode; when=monday, 18:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to travel on Monday evening Cambridge.\nChunk 2: And I'd like to leave after 18:00.\nChunk 3: Yes.\nChunk 4: I'm also looking for a museum on the East side of town please.\nChunk 5: I would like Cambridge Artworks.\nChunk 6: Can you give me the phone number and postcode for it?\nChunk 7: Thank you for your help.\nChunk 8: No, I don't think so.\nChunk 9: Thanks for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=monday; destination+=travel on monday evening cambridge. C2 time+=18:00; destination+=leave after 18:00. C3 [SKIP: acknowledgement_only]. C4 domain=attraction; goal=search; area+=east. C5 intent=context_update. C6 goal=request_info; requested_info+=phone, postcode. C7 [SKIP: thanks_only]. C8 goal=modify_constraint. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; area=east; destination=travel on monday evening cambridge, leave after 18:00; requested_info=phone, postcode; when=monday, 18:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to travel on Monday evening Cambridge.\nChunk 2: And I'd like to leave after 18:00.\nChunk 3: Yes.\nChunk 4: I'm also looking for a museum on the East side of town please.\nChunk 5: I would like Cambridge Artworks.\nChunk 6: Can you give me the phone number and postcode for it?\nChunk 7: Thank you for your help.\nChunk 8: No, I don't think so.\nChunk 9: Thanks for your help!", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, day: monday; destination: travel on monday evening cambridge. Next, time: 18:00; destination: leave after 18:00. Next, the topic is attraction; the goal is search; area: east. Next, intent: context_update. Next, the goal is request info; requested information: phone. Finally, the goal is modify constraint.  Some chunks were skipped because they contained acknowledgement_only or thanks_only. In summary, The overall topic is attraction. the goal is modify constraint.. day: monday; destination: travel on monday evening cambridge., leave after 18:00.; time: 18:00; area: east.; intent: context_update.; requested information: phone.", "trace": "C1 day+=monday; destination+=travel on monday evening cambridge. C2 time+=18:00; destination+=leave after 18:00. C3 [SKIP: acknowledgement_only]. C4 domain=attraction; goal=search; area+=east. C5 intent=context_update. C6 goal=request_info; requested_info+=phone, postcode. C7 [SKIP: thanks_only]. C8 goal=modify_constraint. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to travel on Monday evening Cambridge.", "streaming_reasoning": "Initially, day: monday; destination: travel on monday evening cambridge..", "trace": "day+=monday; destination+=travel on monday evening cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "And I'd like to leave after 18:00.", "streaming_reasoning": "As more information arrives, time: 18:00; destination: leave after 18:00..", "trace": "time+=18:00; destination+=leave after 18:00."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes.", "streaming_reasoning": "The content at C3 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm also looking for a museum on the East side of town please.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is search; area: east..", "trace": "domain=attraction; goal=search; area+=east."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like Cambridge Artworks.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you give me the phone number and postcode for it?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, I don't think so.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks for your help!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is east; destination is travel on monday evening cambridge; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; area=east; destination=travel on monday evening cambridge, leave after 18:00; requested_info=phone, postcode; when=monday, 18:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002693", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, not today.\nChunk 2: Can you just give me the train ID and travel time?\nChunk 3: I guess I will need that departure time too.\nChunk 4: Thanks.\nChunk 5: Thanks, I also need an expensive thai restaurant.\nChunk 6: Which one has thai food?\nChunk 7: Could you give me the phone number and address of sala thong?\nChunk 8: Can I also get the postcode please?\nChunk 9: No that will be all, thanks.", "streaming_reasoning": "C1 day+=today. C2 domain=train; goal=request_info; requested_info+=travel_time. C3 goal=search. C4 [SKIP: thanks_only]. C5 domain=restaurant; cuisine+=thai; price+=expensive. C6 goal=request_info. C7 requested_info+=address, phone. C8 requested_info+=postcode. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, restaurant; goal=request_info, search; food=thai; price=expensive; requested_info=travel_time, address, phone, postcode; when=today; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, not today.\nChunk 2: Can you just give me the train ID and travel time?\nChunk 3: I guess I will need that departure time too.\nChunk 4: Thanks.\nChunk 5: Thanks, I also need an expensive thai restaurant.\nChunk 6: Which one has thai food?\nChunk 7: Could you give me the phone number and address of sala thong?\nChunk 8: Can I also get the postcode please?\nChunk 9: No that will be all, thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=today. C2 domain=train; goal=request_info; requested_info+=travel_time. C3 goal=search. C4 [SKIP: thanks_only]. C5 domain=restaurant; cuisine+=thai; price+=expensive. C6 goal=request_info. C7 requested_info+=address, phone. C8 requested_info+=postcode. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=request_info, search; food=thai; price=expensive; requested_info=travel_time, address, phone, postcode; when=today; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, not today.\nChunk 2: Can you just give me the train ID and travel time?\nChunk 3: I guess I will need that departure time too.\nChunk 4: Thanks.\nChunk 5: Thanks, I also need an expensive thai restaurant.\nChunk 6: Which one has thai food?\nChunk 7: Could you give me the phone number and address of sala thong?\nChunk 8: Can I also get the postcode please?\nChunk 9: No that will be all, thanks.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, day: today. Next, the topic is train; the goal is request info; requested information: travel_time. Next, the goal is search. Next, the topic is restaurant; cuisine: thai; price: expensive. Next, the goal is request info. Next, requested information: address. Finally, requested information: postcode.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is request info.. day: today.; requested information: travel_time., address, postcode.; cuisine: thai; price: expensive..", "trace": "C1 day+=today. C2 domain=train; goal=request_info; requested_info+=travel_time. C3 goal=search. C4 [SKIP: thanks_only]. C5 domain=restaurant; cuisine+=thai; price+=expensive. C6 goal=request_info. C7 requested_info+=address, phone. C8 requested_info+=postcode. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, not today.", "streaming_reasoning": "Initially, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you just give me the train ID and travel time?", "streaming_reasoning": "As more information arrives, the topic is train; the goal is request info; requested information: travel_time..", "trace": "domain=train; goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I guess I will need that departure time too.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks, I also need an expensive thai restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: thai; price: expensive..", "trace": "domain=restaurant; cuisine+=thai; price+=expensive."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Which one has thai food?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Could you give me the phone number and address of sala thong?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, phone."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Can I also get the postcode please?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No that will be all, thanks.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: cuisine is thai; price is expensive; requested information is travel_time; timing is today. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=request_info, search; food=thai; price=expensive; requested_info=travel_time, address, phone, postcode; when=today; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002694", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you tell me about the 4 star hotel instead?\nChunk 2: I am also interested in a place to dine.\nChunk 3: I would like to have Asian Oriental cuisine.\nChunk 4: I want to find a expensive restaurant.\nChunk 5: I also need the address.\nChunk 6: I also need the postcode.\nChunk 7: I also need the recommendation.\nChunk 8: I'm looking for an Asian Oriental place in the same area as the hotel.\nChunk 9: 4 expensive asian restaurants?\nChunk 10: Well if so pick the one you'd recommend.\nChunk 11: Oh and get me the postcode and address.\nChunk 12: Thanks, that's all I needed today.", "streaming_reasoning": "C1 domain=hotel; goal=request_info; hotel_type+=hotel; stars+=4 stars. C2 destination+=dine. C3 domain=restaurant; destination+=have asian oriental cuisine. C4 goal=search; price+=expensive; destination+=find a expensive restaurant. C5 requested_info+=address. C6 requested_info+=postcode. C7 requested_info+=recommendation. C8 goal=modify_constraint. C9 goal=request_info. C10 goal=recommendation. C11 [SKIP: repeated_information]. C12 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=compare_alternative, request_info, search, modify_constraint, recommendation; price=expensive; stars=4 stars; destination=dine, have asian oriental cuisine, find a expensive restaurant; requested_info=address, postcode, recommendation; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you tell me about the 4 star hotel instead?\nChunk 2: I am also interested in a place to dine.\nChunk 3: I would like to have Asian Oriental cuisine.\nChunk 4: I want to find a expensive restaurant.\nChunk 5: I also need the address.\nChunk 6: I also need the postcode.\nChunk 7: I also need the recommendation.\nChunk 8: I'm looking for an Asian Oriental place in the same area as the hotel.\nChunk 9: 4 expensive asian restaurants?\nChunk 10: Well if so pick the one you'd recommend.\nChunk 11: Oh and get me the postcode and address.\nChunk 12: Thanks, that's all I needed today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=request_info; hotel_type+=hotel; stars+=4 stars. C2 destination+=dine. C3 domain=restaurant; destination+=have asian oriental cuisine. C4 goal=search; price+=expensive; destination+=find a expensive restaurant. C5 requested_info+=address. C6 requested_info+=postcode. C7 requested_info+=recommendation. C8 goal=modify_constraint. C9 goal=request_info. C10 goal=recommendation. C11 [SKIP: repeated_information]. C12 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=compare_alternative, request_info, search, modify_constraint, recommendation; price=expensive; stars=4 stars; destination=dine, have asian oriental cuisine, find a expensive restaurant; requested_info=address, postcode, recommendation; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you tell me about the 4 star hotel instead?\nChunk 2: I am also interested in a place to dine.\nChunk 3: I would like to have Asian Oriental cuisine.\nChunk 4: I want to find a expensive restaurant.\nChunk 5: I also need the address.\nChunk 6: I also need the postcode.\nChunk 7: I also need the recommendation.\nChunk 8: I'm looking for an Asian Oriental place in the same area as the hotel.\nChunk 9: 4 expensive asian restaurants?\nChunk 10: Well if so pick the one you'd recommend.\nChunk 11: Oh and get me the postcode and address.\nChunk 12: Thanks, that's all I needed today.", "input_token_count": 113, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is request info; hotel type: hotel; star rating: 4 stars. Next, destination: dine. Next, the topic is restaurant; destination: have asian oriental cuisine. Next, the goal is search; price: expensive; destination: find a expensive restaurant. Next, requested information: address. Next, requested information: postcode. Next, requested information: recommendation. Next, the goal is modify constraint. Next, the goal is request info. Finally, the goal is recommendation.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is restaurant. the goal is recommendation.. hotel type: hotel; star rating: 4 stars.; destination: dine., have asian oriental cuisine., find a expensive restaurant.; price: expensive; requested information: address., postcode., recommendation..", "trace": "C1 domain=hotel; goal=request_info; hotel_type+=hotel; stars+=4 stars. C2 destination+=dine. C3 domain=restaurant; destination+=have asian oriental cuisine. C4 goal=search; price+=expensive; destination+=find a expensive restaurant. C5 requested_info+=address. C6 requested_info+=postcode. C7 requested_info+=recommendation. C8 goal=modify_constraint. C9 goal=request_info. C10 goal=recommendation. C11 [SKIP: repeated_information]. C12 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you tell me about the 4 star hotel instead?", "streaming_reasoning": "Initially, the topic is hotel; the goal is request info; hotel type: hotel; star rating: 4 stars..", "trace": "domain=hotel; goal=request_info; hotel_type+=hotel; stars+=4 stars."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also interested in a place to dine.", "streaming_reasoning": "As more information arrives, destination: dine..", "trace": "destination+=dine."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to have Asian Oriental cuisine.", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: have asian oriental cuisine..", "trace": "domain=restaurant; destination+=have asian oriental cuisine."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want to find a expensive restaurant.", "streaming_reasoning": "As more information arrives, the goal is search; price: expensive; destination: find a expensive restaurant..", "trace": "goal=search; price+=expensive; destination+=find a expensive restaurant."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the address.", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need the postcode.", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the recommendation.", "streaming_reasoning": "As more information arrives, requested information: recommendation..", "trace": "requested_info+=recommendation."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'm looking for an Asian Oriental place in the same area as the hotel.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "4 expensive asian restaurants?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Well if so pick the one you'd recommend.", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Oh and get me the postcode and address.", "streaming_reasoning": "The content at C11 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C12", "chunk_index": 11, "observed_text": "Thanks, that's all I needed today.", "streaming_reasoning": "The content at C12 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of compare alternative. Key information: price is expensive; star rating is 4 stars; destination is dine; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=compare_alternative, request_info, search, modify_constraint, recommendation; price=expensive; stars=4 stars; destination=dine, have asian oriental cuisine, find a expensive restaurant; requested_info=address, postcode, recommendation; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002695", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That is all I needed Thank you.\nChunk 2: I need help with train.\nChunk 3: I also need the travel time.\nChunk 4: I would like a train leaving after 18:15 on the same day as my hotel booking Thank you.\nChunk 5: Can you book it for me?\nChunk 6: I won't need a ticket.\nChunk 7: Can I just have the price, please?\nChunk 8: no thanks i'm done.\nChunk 9: have a nice day.\nChunk 10: bye.", "streaming_reasoning": "C1 [SKIP: closing_only]. C2 domain=train; goal=search. C3 goal=request_info; requested_info+=travel_time. C4 domain=hotel; goal=booking; time+=18:15; hotel_type+=hotel. C5 goal=request_info. C6 intent=context_update. C7 goal=request_info. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, hotel; goal=search, request_info, booking; requested_info=travel_time; when=18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: That is all I needed Thank you.\nChunk 2: I need help with train.\nChunk 3: I also need the travel time.\nChunk 4: I would like a train leaving after 18:15 on the same day as my hotel booking Thank you.\nChunk 5: Can you book it for me?\nChunk 6: I won't need a ticket.\nChunk 7: Can I just have the price, please?\nChunk 8: no thanks i'm done.\nChunk 9: have a nice day.\nChunk 10: bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: closing_only]. C2 domain=train; goal=search. C3 goal=request_info; requested_info+=travel_time. C4 domain=hotel; goal=booking; time+=18:15; hotel_type+=hotel. C5 goal=request_info. C6 intent=context_update. C7 goal=request_info. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, hotel; goal=search, request_info, booking; requested_info=travel_time; when=18:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That is all I needed Thank you.\nChunk 2: I need help with train.\nChunk 3: I also need the travel time.\nChunk 4: I would like a train leaving after 18:15 on the same day as my hotel booking Thank you.\nChunk 5: Can you book it for me?\nChunk 6: I won't need a ticket.\nChunk 7: Can I just have the price, please?\nChunk 8: no thanks i'm done.\nChunk 9: have a nice day.\nChunk 10: bye.", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, the goal is request info; requested information: travel_time. Next, the topic is hotel; the goal is booking; time: 18:15; hotel type: hotel. Next, the goal is request info. Next, intent: context_update. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is request info.. requested information: travel_time.; time: 18:15; hotel type: hotel.; intent: context_update..", "trace": "C1 [SKIP: closing_only]. C2 domain=train; goal=search. C3 goal=request_info; requested_info+=travel_time. C4 domain=hotel; goal=booking; time+=18:15; hotel_type+=hotel. C5 goal=request_info. C6 intent=context_update. C7 goal=request_info. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "That is all I needed Thank you.", "streaming_reasoning": "The content at C1 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the travel time.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like a train leaving after 18:15 on the same day as my hotel booking Thank you.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is booking; time: 18:15; hotel type: hotel..", "trace": "domain=hotel; goal=booking; time+=18:15; hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you book it for me?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I won't need a ticket.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can I just have the price, please?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "no thanks i'm done.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "have a nice day.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "bye.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: requested information is travel_time; timing is 18:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, request_info, booking; requested_info=travel_time; when=18:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002696", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a train.\nChunk 2: The train should depart from cambridge and should go to broxbourne.\nChunk 3: I'm traveling on tuesday and I want to arrive by 16:15.\nChunk 4: No, but I do need the price.\nChunk 5: Nope, that's all I needed.\nChunk 6: Thanks!", "streaming_reasoning": "C1 domain=train; goal=search. C2 destination+=broxbourne; departure+=cambridge and should go, cambridge and should go to broxbourne. C3 time+=16:15; day+=tuesday; destination+=arrive by 16:15. C4 requested_info+=price. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search; destination=broxbourne, arrive by 16:15; departure=cambridge and should go, cambridge and should go to broxbourne; requested_info=price; when=tuesday, 16:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a train.\nChunk 2: The train should depart from cambridge and should go to broxbourne.\nChunk 3: I'm traveling on tuesday and I want to arrive by 16:15.\nChunk 4: No, but I do need the price.\nChunk 5: Nope, that's all I needed.\nChunk 6: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 destination+=broxbourne; departure+=cambridge and should go, cambridge and should go to broxbourne. C3 time+=16:15; day+=tuesday; destination+=arrive by 16:15. C4 requested_info+=price. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search; destination=broxbourne, arrive by 16:15; departure=cambridge and should go, cambridge and should go to broxbourne; requested_info=price; when=tuesday, 16:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a train.\nChunk 2: The train should depart from cambridge and should go to broxbourne.\nChunk 3: I'm traveling on tuesday and I want to arrive by 16:15.\nChunk 4: No, but I do need the price.\nChunk 5: Nope, that's all I needed.\nChunk 6: Thanks!", "input_token_count": 53, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, destination: broxbourne; departure point: cambridge and should go. Next, time: 16:15; day: tuesday; destination: arrive by 16:15. Finally, requested information: price.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is search.. destination: broxbourne, arrive by 16:15.; departure point: cambridge and should go; time: 16:15; day: tuesday; requested information: price..", "trace": "C1 domain=train; goal=search. C2 destination+=broxbourne; departure+=cambridge and should go, cambridge and should go to broxbourne. C3 time+=16:15; day+=tuesday; destination+=arrive by 16:15. C4 requested_info+=price. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The train should depart from cambridge and should go to broxbourne.", "streaming_reasoning": "As more information arrives, destination: broxbourne; departure point: cambridge and should go.", "trace": "destination+=broxbourne; departure+=cambridge and should go, cambridge and should go to broxbourne."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm traveling on tuesday and I want to arrive by 16:15.", "streaming_reasoning": "As more information arrives, time: 16:15; day: tuesday; destination: arrive by 16:15..", "trace": "time+=16:15; day+=tuesday; destination+=arrive by 16:15."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, but I do need the price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Nope, that's all I needed.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is broxbourne; departure point is cambridge and should go; requested information is price; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search; destination=broxbourne, arrive by 16:15; departure=cambridge and should go, cambridge and should go to broxbourne; requested_info=price; when=tuesday, 16:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002697", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi I'm looking for some interesting attractions, especially museums on the west side.\nChunk 2: yes and could like to get the post code That sounds nice.\nChunk 3: Also, can you give me information about The Lensfield Hotel?\nChunk 4: I actually need a reservation for 1 person for 5 nights on wednesday.\nChunk 5: That is everything I need.", "streaming_reasoning": "C1 goal=search; area+=west. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 domain=hotel; hotel_type+=hotel. C4 goal=booking; day+=wednesday; stay_length+=5 nights. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info, booking; area=west; stay_length=5 nights; requested_info=postcode; when=wednesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi I'm looking for some interesting attractions, especially museums on the west side.\nChunk 2: yes and could like to get the post code That sounds nice.\nChunk 3: Also, can you give me information about The Lensfield Hotel?\nChunk 4: I actually need a reservation for 1 person for 5 nights on wednesday.\nChunk 5: That is everything I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=west. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 domain=hotel; hotel_type+=hotel. C4 goal=booking; day+=wednesday; stay_length+=5 nights. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info, booking; area=west; stay_length=5 nights; requested_info=postcode; when=wednesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi I'm looking for some interesting attractions, especially museums on the west side.\nChunk 2: yes and could like to get the post code That sounds nice.\nChunk 3: Also, can you give me information about The Lensfield Hotel?\nChunk 4: I actually need a reservation for 1 person for 5 nights on wednesday.\nChunk 5: That is everything I need.", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: west. Next, the goal is request info; requested information: postcode; acceptance: selected_option. Next, the topic is hotel; hotel type: hotel. Finally, the goal is booking; day: wednesday; stay length: 5 nights.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking. area: west.; requested information: postcode; acceptance: selected_option.; hotel type: hotel.; day: wednesday; stay length: 5 nights..", "trace": "C1 goal=search; area+=west. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 domain=hotel; hotel_type+=hotel. C4 goal=booking; day+=wednesday; stay_length+=5 nights. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi I'm looking for some interesting attractions, especially museums on the west side.", "streaming_reasoning": "Initially, the goal is search; area: west..", "trace": "goal=search; area+=west."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "yes and could like to get the post code That sounds nice.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=postcode; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Also, can you give me information about The Lensfield Hotel?", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel..", "trace": "domain=hotel; hotel_type+=hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I actually need a reservation for 1 person for 5 nights on wednesday.", "streaming_reasoning": "As more information arrives, the goal is booking; day: wednesday; stay length: 5 nights..", "trace": "goal=booking; day+=wednesday; stay_length+=5 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That is everything I need.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is west; stay length is 5 nights; requested information is postcode; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info, booking; area=west; stay_length=5 nights; requested_info=postcode; when=wednesday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002698", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What about one that has Chinese food?\nChunk 2: It is for 3 people.\nChunk 3: The time is thursday, 17:15, 3.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: I will also need a taxi.\nChunk 7: I need picked up at the hotel.\nChunk 8: I need to get to the restaurant by the reservation time, isn't it obvious?\nChunk 9: Thank you, and I apologize for getting snappy with you.\nChunk 10: That is all I need for today.", "streaming_reasoning": "C1 domain=restaurant; goal=recommendation; cuisine+=chinese. C2 party_size+=3 people. C3 time+=17:15, 3; day+=thursday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 domain=taxi. C7 domain=hotel; hotel_type+=hotel. C8 goal=request_info. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi, hotel; goal=recommendation, booking, search, request_info; food=chinese; party_size=3 people; requested_info=reference_number; when=thursday, 17:15, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What about one that has Chinese food?\nChunk 2: It is for 3 people.\nChunk 3: The time is thursday, 17:15, 3.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: I will also need a taxi.\nChunk 7: I need picked up at the hotel.\nChunk 8: I need to get to the restaurant by the reservation time, isn't it obvious?\nChunk 9: Thank you, and I apologize for getting snappy with you.\nChunk 10: That is all I need for today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=recommendation; cuisine+=chinese. C2 party_size+=3 people. C3 time+=17:15, 3; day+=thursday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 domain=taxi. C7 domain=hotel; hotel_type+=hotel. C8 goal=request_info. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi, hotel; goal=recommendation, booking, search, request_info; food=chinese; party_size=3 people; requested_info=reference_number; when=thursday, 17:15, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What about one that has Chinese food?\nChunk 2: It is for 3 people.\nChunk 3: The time is thursday, 17:15, 3.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: I will also need a taxi.\nChunk 7: I need picked up at the hotel.\nChunk 8: I need to get to the restaurant by the reservation time, isn't it obvious?\nChunk 9: Thank you, and I apologize for getting snappy with you.\nChunk 10: That is all I need for today.", "input_token_count": 93, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is recommendation; cuisine: chinese. Next, party size: 3 people. Next, time: 17:15; day: thursday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the topic is taxi. Next, the topic is hotel; hotel type: hotel. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is request info.. cuisine: chinese.; party size: 3 people.; time: 17:15; day: thursday.; requested information: reference_number.; hotel type: hotel..", "trace": "C1 domain=restaurant; goal=recommendation; cuisine+=chinese. C2 party_size+=3 people. C3 time+=17:15, 3; day+=thursday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 domain=taxi. C7 domain=hotel; hotel_type+=hotel. C8 goal=request_info. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What about one that has Chinese food?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is recommendation; cuisine: chinese..", "trace": "domain=restaurant; goal=recommendation; cuisine+=chinese."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It is for 3 people.", "streaming_reasoning": "As more information arrives, party size: 3 people..", "trace": "party_size+=3 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is thursday, 17:15, 3.", "streaming_reasoning": "As more information arrives, time: 17:15; day: thursday..", "trace": "time+=17:15, 3; day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I will also need a taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need picked up at the hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel..", "trace": "domain=hotel; hotel_type+=hotel."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I need to get to the restaurant by the reservation time, isn't it obvious?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you, and I apologize for getting snappy with you.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That is all I need for today.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: cuisine is chinese; party size is 3 people; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi, hotel; goal=recommendation, booking, search, request_info; food=chinese; party_size=3 people; requested_info=reference_number; when=thursday, 17:15, 3; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002699", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any places in the north that have free parking?\nChunk 2: Any price range is fine.\nChunk 3: But if you can see if there is one that has 4 stars?\nChunk 4: Does The Acorn Guest House have internet?\nChunk 5: I don't need free wifi.\nChunk 6: Yes, I would like to book.\nChunk 7: Can you get me a room there for Sunday?\nChunk 8: I will need a room for 8 for 5 nights.\nChunk 9: No, that's all I need Thank you!", "streaming_reasoning": "C1 area+=north; amenities+=parking, free parking. C2 intent=context_update. C3 stars+=4 stars. C4 domain=hotel; hotel_type+=guesthouse; amenities+=internet. C5 goal=search; amenities+=wifi. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; day+=sunday. C8 stay_length+=5 nights. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking, confirm_booking, request_info; area=north; stay_length=5 nights; stars=4 stars; amenities=parking, free parking, internet, wifi; when=sunday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Are there any places in the north that have free parking?\nChunk 2: Any price range is fine.\nChunk 3: But if you can see if there is one that has 4 stars?\nChunk 4: Does The Acorn Guest House have internet?\nChunk 5: I don't need free wifi.\nChunk 6: Yes, I would like to book.\nChunk 7: Can you get me a room there for Sunday?\nChunk 8: I will need a room for 8 for 5 nights.\nChunk 9: No, that's all I need Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=north; amenities+=parking, free parking. C2 intent=context_update. C3 stars+=4 stars. C4 domain=hotel; hotel_type+=guesthouse; amenities+=internet. C5 goal=search; amenities+=wifi. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; day+=sunday. C8 stay_length+=5 nights. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking, confirm_booking, request_info; area=north; stay_length=5 nights; stars=4 stars; amenities=parking, free parking, internet, wifi; when=sunday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any places in the north that have free parking?\nChunk 2: Any price range is fine.\nChunk 3: But if you can see if there is one that has 4 stars?\nChunk 4: Does The Acorn Guest House have internet?\nChunk 5: I don't need free wifi.\nChunk 6: Yes, I would like to book.\nChunk 7: Can you get me a room there for Sunday?\nChunk 8: I will need a room for 8 for 5 nights.\nChunk 9: No, that's all I need Thank you!", "input_token_count": 91, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: north; amenities: parking. Next, intent: context_update. Next, star rating: 4 stars. Next, the topic is hotel; hotel type: guesthouse; amenities: internet. Next, the goal is search; amenities: wifi. Next, the goal is confirm booking. Next, the goal is request info; day: sunday. Finally, stay length: 5 nights.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. area: north; amenities: parking, internet., wifi.; intent: context_update.; star rating: 4 stars.; hotel type: guesthouse; day: sunday.; stay length: 5 nights..", "trace": "C1 area+=north; amenities+=parking, free parking. C2 intent=context_update. C3 stars+=4 stars. C4 domain=hotel; hotel_type+=guesthouse; amenities+=internet. C5 goal=search; amenities+=wifi. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; day+=sunday. C8 stay_length+=5 nights. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Are there any places in the north that have free parking?", "streaming_reasoning": "Initially, area: north; amenities: parking.", "trace": "area+=north; amenities+=parking, free parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Any price range is fine.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "But if you can see if there is one that has 4 stars?", "streaming_reasoning": "As more information arrives, star rating: 4 stars..", "trace": "stars+=4 stars."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Does The Acorn Guest House have internet?", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse; amenities: internet..", "trace": "domain=hotel; hotel_type+=guesthouse; amenities+=internet."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I don't need free wifi.", "streaming_reasoning": "As more information arrives, the goal is search; amenities: wifi..", "trace": "goal=search; amenities+=wifi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, I would like to book.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can you get me a room there for Sunday?", "streaming_reasoning": "As more information arrives, the goal is request info; day: sunday..", "trace": "goal=request_info; day+=sunday."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I will need a room for 8 for 5 nights.", "streaming_reasoning": "As more information arrives, stay length: 5 nights..", "trace": "stay_length+=5 nights."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No, that's all I need Thank you!", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; stay length is 5 nights; star rating is 4 stars; amenities is parking; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, confirm_booking, request_info; area=north; stay_length=5 nights; stars=4 stars; amenities=parking, free parking, internet, wifi; when=sunday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002700", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a entertainment in the south area.\nChunk 2: Yes, what's their postcode?\nChunk 3: And while you're at it, maybe their phone number, too.\nChunk 4: I was also wondering if you can help me find a restaurant called tandoori palace.\nChunk 5: Can you give me the postal code for tandoori palace?\nChunk 6: No need to book a table at this time.\nChunk 7: Thank you for your help Good bye.", "streaming_reasoning": "C1 goal=search; area+=south. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 requested_info+=phone. C4 domain=restaurant. C5 goal=request_info. C6 goal=booking. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, booking; area=south; requested_info=postcode, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a entertainment in the south area.\nChunk 2: Yes, what's their postcode?\nChunk 3: And while you're at it, maybe their phone number, too.\nChunk 4: I was also wondering if you can help me find a restaurant called tandoori palace.\nChunk 5: Can you give me the postal code for tandoori palace?\nChunk 6: No need to book a table at this time.\nChunk 7: Thank you for your help Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=south. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 requested_info+=phone. C4 domain=restaurant. C5 goal=request_info. C6 goal=booking. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, booking; area=south; requested_info=postcode, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a entertainment in the south area.\nChunk 2: Yes, what's their postcode?\nChunk 3: And while you're at it, maybe their phone number, too.\nChunk 4: I was also wondering if you can help me find a restaurant called tandoori palace.\nChunk 5: Can you give me the postal code for tandoori palace?\nChunk 6: No need to book a table at this time.\nChunk 7: Thank you for your help Good bye.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: south. Next, the goal is request info; requested information: postcode; acceptance: selected_option. Next, requested information: phone. Next, the topic is restaurant. Next, the goal is request info. Finally, the goal is booking.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant.. the goal is booking.. area: south.; requested information: postcode, phone.; acceptance: selected_option..", "trace": "C1 goal=search; area+=south. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 requested_info+=phone. C4 domain=restaurant. C5 goal=request_info. C6 goal=booking. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a entertainment in the south area.", "streaming_reasoning": "Initially, the goal is search; area: south..", "trace": "goal=search; area+=south."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, what's their postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=postcode; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "And while you're at it, maybe their phone number, too.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I was also wondering if you can help me find a restaurant called tandoori palace.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you give me the postal code for tandoori palace?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No need to book a table at this time.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your help Good bye.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, booking; area=south; requested_info=postcode, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002701", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a guesthouse.\nChunk 2: I also need the phone.\nChunk 3: Can you recommend a chinese restaurant in the centre area?\nChunk 4: I don't care about the price.\nChunk 5: Can you recommend anything That sounds great.\nChunk 6: Can I get a table for 8 people at 16:45 on Saturday?\nChunk 7: I need a taxi also to get to the restaurant on time.\nChunk 8: From the guesthouse to the restaurant.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 goal=request_info; requested_info+=phone. C3 domain=restaurant; goal=recommendation; area+=centre; cuisine+=chinese. C4 intent=context_update. C5 intent=context_update. C6 time+=8, 16:45; day+=saturday; party_size+=8 people. C7 domain=taxi. C8 [SKIP: repeated_information].", "deep_reasoning": "Need domain=hotel, restaurant, taxi; goal=search, request_info, recommendation; area=centre; food=chinese; party_size=8 people; destination=find a guesthouse; requested_info=phone; when=saturday, 8, 16:45.", "answer": "I can help with that and include the phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a guesthouse.\nChunk 2: I also need the phone.\nChunk 3: Can you recommend a chinese restaurant in the centre area?\nChunk 4: I don't care about the price.\nChunk 5: Can you recommend anything That sounds great.\nChunk 6: Can I get a table for 8 people at 16:45 on Saturday?\nChunk 7: I need a taxi also to get to the restaurant on time.\nChunk 8: From the guesthouse to the restaurant."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 goal=request_info; requested_info+=phone. C3 domain=restaurant; goal=recommendation; area+=centre; cuisine+=chinese. C4 intent=context_update. C5 intent=context_update. C6 time+=8, 16:45; day+=saturday; party_size+=8 people. C7 domain=taxi. C8 [SKIP: repeated_information].\n\nDeep reasoning: Need domain=hotel, restaurant, taxi; goal=search, request_info, recommendation; area=centre; food=chinese; party_size=8 people; destination=find a guesthouse; requested_info=phone; when=saturday, 8, 16:45.\n\nAnswer: I can help with that and include the phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a guesthouse.\nChunk 2: I also need the phone.\nChunk 3: Can you recommend a chinese restaurant in the centre area?\nChunk 4: I don't care about the price.\nChunk 5: Can you recommend anything That sounds great.\nChunk 6: Can I get a table for 8 people at 16:45 on Saturday?\nChunk 7: I need a taxi also to get to the restaurant on time.\nChunk 8: From the guesthouse to the restaurant.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; destination: find a guesthouse. Next, the goal is request info; requested information: phone. Next, the topic is restaurant; the goal is recommendation; area: centre; cuisine: chinese. Next, intent: context_update. Next, intent: context_update. Next, time: 8; day: saturday; party size: 8 people. Finally, the topic is taxi.  Some chunks were skipped because they contained repeated_information. In summary, The overall topic is taxi.. the goal is recommendation. hotel type: guesthouse; destination: find a guesthouse.; requested information: phone.; area: centre; cuisine: chinese.; intent: context_update.; time: 8; day: saturday; party size: 8 people..", "trace": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 goal=request_info; requested_info+=phone. C3 domain=restaurant; goal=recommendation; area+=centre; cuisine+=chinese. C4 intent=context_update. C5 intent=context_update. C6 time+=8, 16:45; day+=saturday; party_size+=8 people. C7 domain=taxi. C8 [SKIP: repeated_information].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a guesthouse.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; destination: find a guesthouse..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you recommend a chinese restaurant in the centre area?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is recommendation; area: centre; cuisine: chinese..", "trace": "domain=restaurant; goal=recommendation; area+=centre; cuisine+=chinese."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't care about the price.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you recommend anything That sounds great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I get a table for 8 people at 16:45 on Saturday?", "streaming_reasoning": "As more information arrives, time: 8; day: saturday; party size: 8 people..", "trace": "time+=8, 16:45; day+=saturday; party_size+=8 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need a taxi also to get to the restaurant on time.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "From the guesthouse to the restaurant.", "streaming_reasoning": "The content at C8 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; cuisine is chinese; party size is 8 people; destination is find a guesthouse; requested information is phone; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel, restaurant, taxi; goal=search, request_info, recommendation; area=centre; food=chinese; party_size=8 people; destination=find a guesthouse; requested_info=phone; when=saturday, 8, 16:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002702", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need a guesthouse with 4 stars.\nChunk 2: In the same area as the restaurant, centre.\nChunk 3: In prefer a cheap price range.\nChunk 4: Can I have the number to the hotel?\nChunk 5: Can you tell me their address and let me know whether or not they have internet there?\nChunk 6: That sounds great thank you.\nChunk 7: No,that's all.Thanks and have a good day.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars. C2 domain=restaurant; goal=modify_constraint; area+=centre. C3 price+=cheap. C4 goal=request_info; hotel_type+=hotel; destination+=the hotel. C5 amenities+=internet; requested_info+=address. C6 intent=context_update. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, modify_constraint, request_info; area=centre; price=cheap; stars=4 stars; amenities=internet; destination=the hotel; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also need a guesthouse with 4 stars.\nChunk 2: In the same area as the restaurant, centre.\nChunk 3: In prefer a cheap price range.\nChunk 4: Can I have the number to the hotel?\nChunk 5: Can you tell me their address and let me know whether or not they have internet there?\nChunk 6: That sounds great thank you.\nChunk 7: No,that's all.Thanks and have a good day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars. C2 domain=restaurant; goal=modify_constraint; area+=centre. C3 price+=cheap. C4 goal=request_info; hotel_type+=hotel; destination+=the hotel. C5 amenities+=internet; requested_info+=address. C6 intent=context_update. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, modify_constraint, request_info; area=centre; price=cheap; stars=4 stars; amenities=internet; destination=the hotel; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need a guesthouse with 4 stars.\nChunk 2: In the same area as the restaurant, centre.\nChunk 3: In prefer a cheap price range.\nChunk 4: Can I have the number to the hotel?\nChunk 5: Can you tell me their address and let me know whether or not they have internet there?\nChunk 6: That sounds great thank you.\nChunk 7: No,that's all.Thanks and have a good day.", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; star rating: 4 stars. Next, the topic is restaurant; the goal is modify constraint; area: centre. Next, price: cheap. Next, the goal is request info; hotel type: hotel; destination: the hotel. Next, amenities: internet; requested information: address. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. hotel type: guesthouse, hotel; star rating: 4 stars.; area: centre.; price: cheap.; destination: the hotel.; amenities: internet; requested information: address.; intent: context_update..", "trace": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars. C2 domain=restaurant; goal=modify_constraint; area+=centre. C3 price+=cheap. C4 goal=request_info; hotel_type+=hotel; destination+=the hotel. C5 amenities+=internet; requested_info+=address. C6 intent=context_update. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also need a guesthouse with 4 stars.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; star rating: 4 stars..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "In the same area as the restaurant, centre.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint; area: centre..", "trace": "domain=restaurant; goal=modify_constraint; area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "In prefer a cheap price range.", "streaming_reasoning": "As more information arrives, price: cheap..", "trace": "price+=cheap."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I have the number to the hotel?", "streaming_reasoning": "As more information arrives, the goal is request info; hotel type: hotel; destination: the hotel..", "trace": "goal=request_info; hotel_type+=hotel; destination+=the hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you tell me their address and let me know whether or not they have internet there?", "streaming_reasoning": "As more information arrives, amenities: internet; requested information: address..", "trace": "amenities+=internet; requested_info+=address."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That sounds great thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No,that's all.Thanks and have a good day.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; price is cheap; star rating is 4 stars; amenities is internet; destination is the hotel; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, modify_constraint, request_info; area=centre; price=cheap; stars=4 stars; amenities=internet; destination=the hotel; requested_info=address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002704", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok, well thanks anyway.\nChunk 2: Can you help me find a restaurant in the centre of town also?\nChunk 3: I prefer something moderately priced.\nChunk 4: I'm not too picky on what kind of food as long as it is good.\nChunk 5: Can you make a few suggestions please Galleria sounds good.\nChunk 6: Could I get the postcode for that please?\nChunk 7: Thank you, I also need a taxi to commute between the two places.\nChunk 8: I'd like to leave the man on the moon by 04:45, can you set that up for me?\nChunk 9: Thanks.\nChunk 10: That was all I needed Goodbye.", "streaming_reasoning": "C1 intent=context_update. C2 domain=restaurant; goal=search; area+=centre. C3 price+=moderate. C4 goal=modify_constraint. C5 acceptance=selected_option. C6 goal=request_info; requested_info+=postcode. C7 domain=taxi; destination+=commute between the two places. C8 time+=04:45; destination+=leave the man on the moon by 04:45. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi; goal=search, request_info; area=centre; price=moderate; destination=commute between the two places, leave the man on the moon by 04:45; requested_info=postcode; when=04:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Ok, well thanks anyway.\nChunk 2: Can you help me find a restaurant in the centre of town also?\nChunk 3: I prefer something moderately priced.\nChunk 4: I'm not too picky on what kind of food as long as it is good.\nChunk 5: Can you make a few suggestions please Galleria sounds good.\nChunk 6: Could I get the postcode for that please?\nChunk 7: Thank you, I also need a taxi to commute between the two places.\nChunk 8: I'd like to leave the man on the moon by 04:45, can you set that up for me?\nChunk 9: Thanks.\nChunk 10: That was all I needed Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 domain=restaurant; goal=search; area+=centre. C3 price+=moderate. C4 goal=modify_constraint. C5 acceptance=selected_option. C6 goal=request_info; requested_info+=postcode. C7 domain=taxi; destination+=commute between the two places. C8 time+=04:45; destination+=leave the man on the moon by 04:45. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi; goal=search, request_info; area=centre; price=moderate; destination=commute between the two places, leave the man on the moon by 04:45; requested_info=postcode; when=04:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok, well thanks anyway.\nChunk 2: Can you help me find a restaurant in the centre of town also?\nChunk 3: I prefer something moderately priced.\nChunk 4: I'm not too picky on what kind of food as long as it is good.\nChunk 5: Can you make a few suggestions please Galleria sounds good.\nChunk 6: Could I get the postcode for that please?\nChunk 7: Thank you, I also need a taxi to commute between the two places.\nChunk 8: I'd like to leave the man on the moon by 04:45, can you set that up for me?\nChunk 9: Thanks.\nChunk 10: That was all I needed Goodbye.", "input_token_count": 114, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the topic is restaurant; the goal is search; area: centre. Next, price: moderate. Next, the goal is modify constraint. Next, acceptance: selected_option. Next, the goal is request info; requested information: postcode. Next, the topic is taxi; destination: commute between the two places. Finally, time: 04:45; destination: leave the man on the moon by 04:45.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is request info. intent: context_update.; area: centre.; price: moderate.; acceptance: selected_option.; requested information: postcode.; destination: commute between the two places., leave the man on the moon by 04:45.; time: 04:45.", "trace": "C1 intent=context_update. C2 domain=restaurant; goal=search; area+=centre. C3 price+=moderate. C4 goal=modify_constraint. C5 acceptance=selected_option. C6 goal=request_info; requested_info+=postcode. C7 domain=taxi; destination+=commute between the two places. C8 time+=04:45; destination+=leave the man on the moon by 04:45. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Ok, well thanks anyway.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you help me find a restaurant in the centre of town also?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; area: centre..", "trace": "domain=restaurant; goal=search; area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I prefer something moderately priced.", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm not too picky on what kind of food as long as it is good.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you make a few suggestions please Galleria sounds good.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could I get the postcode for that please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you, I also need a taxi to commute between the two places.", "streaming_reasoning": "As more information arrives, the topic is taxi; destination: commute between the two places..", "trace": "domain=taxi; destination+=commute between the two places."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'd like to leave the man on the moon by 04:45, can you set that up for me?", "streaming_reasoning": "As more information arrives, time: 04:45; destination: leave the man on the moon by 04:45..", "trace": "time+=04:45; destination+=leave the man on the moon by 04:45."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That was all I needed Goodbye.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is moderate; destination is commute between the two places; requested information is postcode; timing is 04:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi; goal=search, request_info; area=centre; price=moderate; destination=commute between the two places, leave the man on the moon by 04:45; requested_info=postcode; when=04:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002705", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: I'd like to find a seafood restaurant in the centre of town, please.\nChunk 3: Is it an expensive restaurant?\nChunk 4: I'm really looking to break the bank here.\nChunk 5: It is for 3 people.\nChunk 6: The time is monday, 3, 17:15.\nChunk 7: Please make a booking.\nChunk 8: I also need the reference number.\nChunk 9: No thank you, that is all I needed.", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search; area+=centre; cuisine+=seafood; destination+=find a seafood restaurant in the centre o. C3 price+=expensive. C4 destination+=break the bank here. C5 party_size+=3 people. C6 time+=3, 17:15; day+=monday. C7 goal=booking. C8 goal=request_info; requested_info+=reference_number. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, request_info; area=centre; food=seafood; price=expensive; party_size=3 people; destination=find a seafood restaurant in the centre o, break the bank here; requested_info=reference_number; when=monday, 3, 17:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi!\nChunk 2: I'd like to find a seafood restaurant in the centre of town, please.\nChunk 3: Is it an expensive restaurant?\nChunk 4: I'm really looking to break the bank here.\nChunk 5: It is for 3 people.\nChunk 6: The time is monday, 3, 17:15.\nChunk 7: Please make a booking.\nChunk 8: I also need the reference number.\nChunk 9: No thank you, that is all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search; area+=centre; cuisine+=seafood; destination+=find a seafood restaurant in the centre o. C3 price+=expensive. C4 destination+=break the bank here. C5 party_size+=3 people. C6 time+=3, 17:15; day+=monday. C7 goal=booking. C8 goal=request_info; requested_info+=reference_number. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, request_info; area=centre; food=seafood; price=expensive; party_size=3 people; destination=find a seafood restaurant in the centre o, break the bank here; requested_info=reference_number; when=monday, 3, 17:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: I'd like to find a seafood restaurant in the centre of town, please.\nChunk 3: Is it an expensive restaurant?\nChunk 4: I'm really looking to break the bank here.\nChunk 5: It is for 3 people.\nChunk 6: The time is monday, 3, 17:15.\nChunk 7: Please make a booking.\nChunk 8: I also need the reference number.\nChunk 9: No thank you, that is all I needed.", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: seafood; destination: find a seafood restaurant in the centre o. Next, price: expensive. Next, destination: break the bank here. Next, party size: 3 people. Next, time: 3; day: monday. Next, the goal is booking. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained closing_only or greeting_only. In summary, The overall topic is restaurant. the goal is request info. area: centre; cuisine: seafood; destination: find a seafood restaurant in the centre o., break the bank here.; price: expensive.; party size: 3 people.; time: 3; day: monday.; requested information: reference_number..", "trace": "C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search; area+=centre; cuisine+=seafood; destination+=find a seafood restaurant in the centre o. C3 price+=expensive. C4 destination+=break the bank here. C5 party_size+=3 people. C6 time+=3, 17:15; day+=monday. C7 goal=booking. C8 goal=request_info; requested_info+=reference_number. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi!", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to find a seafood restaurant in the centre of town, please.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; area: centre; cuisine: seafood; destination: find a seafood restaurant in the centre o..", "trace": "domain=restaurant; goal=search; area+=centre; cuisine+=seafood; destination+=find a seafood restaurant in the centre o."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Is it an expensive restaurant?", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm really looking to break the bank here.", "streaming_reasoning": "As more information arrives, destination: break the bank here..", "trace": "destination+=break the bank here."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It is for 3 people.", "streaming_reasoning": "As more information arrives, party size: 3 people..", "trace": "party_size+=3 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is monday, 3, 17:15.", "streaming_reasoning": "As more information arrives, time: 3; day: monday..", "trace": "time+=3, 17:15; day+=monday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No thank you, that is all I needed.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is seafood; price is expensive; party size is 3 people; destination is find a seafood restaurant in the centre o; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, request_info; area=centre; food=seafood; price=expensive; party_size=3 people; destination=find a seafood restaurant in the centre o, break the bank here; requested_info=reference_number; when=monday, 3, 17:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002706", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for expensive Corsica food.\nChunk 2: How about Indian food instead?\nChunk 3: How about the west?\nChunk 4: Could you give me their postcode and telephone number?\nChunk 5: That will be fine as long as it's expensive.\nChunk 6: Can you tell me the postcode and phone number?\nChunk 7: No, I don't need anything else at the moment.", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=expensive. C2 goal=compare_alternative; cuisine+=indian. C3 area+=west. C4 goal=request_info; requested_info+=phone, postcode. C5 acceptance=selected_option. C6 goal=request_info. C7 goal=modify_constraint.", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, compare_alternative, request_info; area=west; food=indian; price=expensive; requested_info=phone, postcode.", "answer": "I can help with that and include the phone, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for expensive Corsica food.\nChunk 2: How about Indian food instead?\nChunk 3: How about the west?\nChunk 4: Could you give me their postcode and telephone number?\nChunk 5: That will be fine as long as it's expensive.\nChunk 6: Can you tell me the postcode and phone number?\nChunk 7: No, I don't need anything else at the moment."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=expensive. C2 goal=compare_alternative; cuisine+=indian. C3 area+=west. C4 goal=request_info; requested_info+=phone, postcode. C5 acceptance=selected_option. C6 goal=request_info. C7 goal=modify_constraint.\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, compare_alternative, request_info; area=west; food=indian; price=expensive; requested_info=phone, postcode.\n\nAnswer: I can help with that and include the phone, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for expensive Corsica food.\nChunk 2: How about Indian food instead?\nChunk 3: How about the west?\nChunk 4: Could you give me their postcode and telephone number?\nChunk 5: That will be fine as long as it's expensive.\nChunk 6: Can you tell me the postcode and phone number?\nChunk 7: No, I don't need anything else at the moment.", "input_token_count": 66, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: expensive. Next, the goal is compare alternative; cuisine: indian. Next, area: west. Next, the goal is request info; requested information: phone. Next, acceptance: selected_option. Next, the goal is request info. Finally, the goal is modify constraint. In summary, The overall topic is restaurant. the goal is modify constraint.. price: expensive.; cuisine: indian.; area: west.; requested information: phone; acceptance: selected_option..", "trace": "C1 domain=restaurant; goal=search; price+=expensive. C2 goal=compare_alternative; cuisine+=indian. C3 area+=west. C4 goal=request_info; requested_info+=phone, postcode. C5 acceptance=selected_option. C6 goal=request_info. C7 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for expensive Corsica food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: expensive..", "trace": "domain=restaurant; goal=search; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How about Indian food instead?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; cuisine: indian..", "trace": "goal=compare_alternative; cuisine+=indian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about the west?", "streaming_reasoning": "As more information arrives, area: west..", "trace": "area+=west."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you give me their postcode and telephone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That will be fine as long as it's expensive.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you tell me the postcode and phone number?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, I don't need anything else at the moment.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is west; cuisine is indian; price is expensive; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, compare_alternative, request_info; area=west; food=indian; price=expensive; requested_info=phone, postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002707", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train to Cambridge.\nChunk 2: I need to arrive by 20:00.\nChunk 3: I'll be heading in from Leicester on Thursday.\nChunk 4: Yes, please book it for me.\nChunk 5: I just want to know the price of the ticket.\nChunk 6: Thanks!\nChunk 7: I'm also looking for a guesthouse in the east.\nChunk 8: It doesn't need to have free wifi.", "streaming_reasoning": "C1 domain=train; goal=search; destination+=cambridge. C2 time+=20:00; destination+=arrive by 20:00. C3 day+=thursday. C4 goal=confirm_booking; goal=confirm_booking. C5 destination+=know the price of the ticket. C6 [SKIP: thanks_only]. C7 domain=hotel; area+=east; hotel_type+=guesthouse. C8 amenities+=wifi; destination+=have free wifi.", "deep_reasoning": "Need domain=train, hotel; goal=search, booking, confirm_booking; area=east; amenities=wifi; destination=cambridge, arrive by 20:00, know the price of the ticket, have free wifi; when=thursday, 20:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a train to Cambridge.\nChunk 2: I need to arrive by 20:00.\nChunk 3: I'll be heading in from Leicester on Thursday.\nChunk 4: Yes, please book it for me.\nChunk 5: I just want to know the price of the ticket.\nChunk 6: Thanks!\nChunk 7: I'm also looking for a guesthouse in the east.\nChunk 8: It doesn't need to have free wifi."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=cambridge. C2 time+=20:00; destination+=arrive by 20:00. C3 day+=thursday. C4 goal=confirm_booking; goal=confirm_booking. C5 destination+=know the price of the ticket. C6 [SKIP: thanks_only]. C7 domain=hotel; area+=east; hotel_type+=guesthouse. C8 amenities+=wifi; destination+=have free wifi.\n\nDeep reasoning: Need domain=train, hotel; goal=search, booking, confirm_booking; area=east; amenities=wifi; destination=cambridge, arrive by 20:00, know the price of the ticket, have free wifi; when=thursday, 20:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train to Cambridge.\nChunk 2: I need to arrive by 20:00.\nChunk 3: I'll be heading in from Leicester on Thursday.\nChunk 4: Yes, please book it for me.\nChunk 5: I just want to know the price of the ticket.\nChunk 6: Thanks!\nChunk 7: I'm also looking for a guesthouse in the east.\nChunk 8: It doesn't need to have free wifi.", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge. Next, time: 20:00; destination: arrive by 20:00. Next, day: thursday. Next, the goal is confirm booking. Next, destination: know the price of the ticket. Next, the topic is hotel; area: east; hotel type: guesthouse. Finally, amenities: wifi; destination: have free wifi.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is confirm booking.. destination: cambridge., arrive by 20:00., know the price of the ticket., have free wifi.; time: 20:00; day: thursday.; area: east; hotel type: guesthouse.; amenities: wifi.", "trace": "C1 domain=train; goal=search; destination+=cambridge. C2 time+=20:00; destination+=arrive by 20:00. C3 day+=thursday. C4 goal=confirm_booking; goal=confirm_booking. C5 destination+=know the price of the ticket. C6 [SKIP: thanks_only]. C7 domain=hotel; area+=east; hotel_type+=guesthouse. C8 amenities+=wifi; destination+=have free wifi.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a train to Cambridge.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge..", "trace": "domain=train; goal=search; destination+=cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to arrive by 20:00.", "streaming_reasoning": "As more information arrives, time: 20:00; destination: arrive by 20:00..", "trace": "time+=20:00; destination+=arrive by 20:00."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'll be heading in from Leicester on Thursday.", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, please book it for me.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I just want to know the price of the ticket.", "streaming_reasoning": "As more information arrives, destination: know the price of the ticket..", "trace": "destination+=know the price of the ticket."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'm also looking for a guesthouse in the east.", "streaming_reasoning": "As more information arrives, the topic is hotel; area: east; hotel type: guesthouse..", "trace": "domain=hotel; area+=east; hotel_type+=guesthouse."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "It doesn't need to have free wifi.", "streaming_reasoning": "Finally, amenities: wifi; destination: have free wifi..", "trace": "amenities+=wifi; destination+=have free wifi."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is east; amenities is wifi; destination is cambridge; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, booking, confirm_booking; area=east; amenities=wifi; destination=cambridge, arrive by 20:00, know the price of the ticket, have free wifi; when=thursday, 20:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002708", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a museum to visit in the centre of town.\nChunk 2: Tell me more about the anthropology museum please.\nChunk 3: What is their postcode?\nChunk 4: No, that is all Thanks so much.", "streaming_reasoning": "C1 domain=attraction; goal=search; area+=centre; destination+=visit in the centre of town. C2 goal=request_info. C3 requested_info+=postcode. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction; goal=search, request_info; area=centre; destination=visit in the centre of town; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a museum to visit in the centre of town.\nChunk 2: Tell me more about the anthropology museum please.\nChunk 3: What is their postcode?\nChunk 4: No, that is all Thanks so much."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search; area+=centre; destination+=visit in the centre of town. C2 goal=request_info. C3 requested_info+=postcode. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; area=centre; destination=visit in the centre of town; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a museum to visit in the centre of town.\nChunk 2: Tell me more about the anthropology museum please.\nChunk 3: What is their postcode?\nChunk 4: No, that is all Thanks so much.", "input_token_count": 39, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; area: centre; destination: visit in the centre of town. Next, the goal is request info. Finally, requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is request info.. area: centre; destination: visit in the centre of town.; requested information: postcode..", "trace": "C1 domain=attraction; goal=search; area+=centre; destination+=visit in the centre of town. C2 goal=request_info. C3 requested_info+=postcode. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a museum to visit in the centre of town.", "streaming_reasoning": "Initially, the topic is attraction; the goal is search; area: centre; destination: visit in the centre of town..", "trace": "domain=attraction; goal=search; area+=centre; destination+=visit in the centre of town."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Tell me more about the anthropology museum please.", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is their postcode?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, that is all Thanks so much.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; destination is visit in the centre of town; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; area=centre; destination=visit in the centre of town; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002709", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am interested in the Express by Holiday Inn - Cambridge.\nChunk 2: I want to book 3 nights there, please.\nChunk 3: Three days starting from Saturday, for 6 people.\nChunk 4: Can you tell me a little bit of info on the Cambridge Corn Exchange?\nChunk 5: It's supposed to be an attraction place or something.\nChunk 6: What type of attraction is this?\nChunk 7: Maybe I'll call them and find out the entrance fee.\nChunk 8: Thank you for your time!", "streaming_reasoning": "C1 intent=context_update. C2 goal=booking; stay_length+=3 nights. C3 time+=6; day+=saturday; party_size+=6 people. C4 goal=request_info. C5 domain=attraction; destination+=be an attraction place or something. C6 goal=request_info. C7 requested_info+=entrance_fee. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction; goal=search, booking, request_info; party_size=6 people; stay_length=3 nights; destination=be an attraction place or something; requested_info=entrance_fee; when=saturday, 6; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am interested in the Express by Holiday Inn - Cambridge.\nChunk 2: I want to book 3 nights there, please.\nChunk 3: Three days starting from Saturday, for 6 people.\nChunk 4: Can you tell me a little bit of info on the Cambridge Corn Exchange?\nChunk 5: It's supposed to be an attraction place or something.\nChunk 6: What type of attraction is this?\nChunk 7: Maybe I'll call them and find out the entrance fee.\nChunk 8: Thank you for your time!"}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=booking; stay_length+=3 nights. C3 time+=6; day+=saturday; party_size+=6 people. C4 goal=request_info. C5 domain=attraction; destination+=be an attraction place or something. C6 goal=request_info. C7 requested_info+=entrance_fee. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction; goal=search, booking, request_info; party_size=6 people; stay_length=3 nights; destination=be an attraction place or something; requested_info=entrance_fee; when=saturday, 6; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am interested in the Express by Holiday Inn - Cambridge.\nChunk 2: I want to book 3 nights there, please.\nChunk 3: Three days starting from Saturday, for 6 people.\nChunk 4: Can you tell me a little bit of info on the Cambridge Corn Exchange?\nChunk 5: It's supposed to be an attraction place or something.\nChunk 6: What type of attraction is this?\nChunk 7: Maybe I'll call them and find out the entrance fee.\nChunk 8: Thank you for your time!", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is booking; stay length: 3 nights. Next, time: 6; day: saturday; party size: 6 people. Next, the goal is request info. Next, the topic is attraction; destination: be an attraction place or something. Next, the goal is request info. Finally, requested information: entrance_fee.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction. the goal is request info.. intent: context_update.; stay length: 3 nights.; time: 6; day: saturday; party size: 6 people.; destination: be an attraction place or something.; requested information: entrance_fee..", "trace": "C1 intent=context_update. C2 goal=booking; stay_length+=3 nights. C3 time+=6; day+=saturday; party_size+=6 people. C4 goal=request_info. C5 domain=attraction; destination+=be an attraction place or something. C6 goal=request_info. C7 requested_info+=entrance_fee. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am interested in the Express by Holiday Inn - Cambridge.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to book 3 nights there, please.", "streaming_reasoning": "As more information arrives, the goal is booking; stay length: 3 nights..", "trace": "goal=booking; stay_length+=3 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Three days starting from Saturday, for 6 people.", "streaming_reasoning": "As more information arrives, time: 6; day: saturday; party size: 6 people..", "trace": "time+=6; day+=saturday; party_size+=6 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you tell me a little bit of info on the Cambridge Corn Exchange?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It's supposed to be an attraction place or something.", "streaming_reasoning": "As more information arrives, the topic is attraction; destination: be an attraction place or something..", "trace": "domain=attraction; destination+=be an attraction place or something."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What type of attraction is this?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Maybe I'll call them and find out the entrance fee.", "streaming_reasoning": "As more information arrives, requested information: entrance_fee..", "trace": "requested_info+=entrance_fee."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for your time!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: party size is 6 people; stay length is 3 nights; destination is be an attraction place or something; requested information is entrance_fee; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, booking, request_info; party_size=6 people; stay_length=3 nights; destination=be an attraction place or something; requested_info=entrance_fee; when=saturday, 6; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002710", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a place to eat in the north area of the city I don't care.\nChunk 2: In the moderate price range.\nChunk 3: What is the phone number and address?\nChunk 4: No thank you Goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=north; destination+=eat in the north area of the city i don't. C2 price+=moderate. C3 goal=request_info; requested_info+=address, phone. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=north; price=moderate; destination=eat in the north area of the city i don't; requested_info=address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a place to eat in the north area of the city I don't care.\nChunk 2: In the moderate price range.\nChunk 3: What is the phone number and address?\nChunk 4: No thank you Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=north; destination+=eat in the north area of the city i don't. C2 price+=moderate. C3 goal=request_info; requested_info+=address, phone. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=north; price=moderate; destination=eat in the north area of the city i don't; requested_info=address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a place to eat in the north area of the city I don't care.\nChunk 2: In the moderate price range.\nChunk 3: What is the phone number and address?\nChunk 4: No thank you Goodbye.", "input_token_count": 40, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: north; destination: eat in the north area of the city i don't. Next, price: moderate. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: north; destination: eat in the north area of the city i don't.; price: moderate.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; area+=north; destination+=eat in the north area of the city i don't. C2 price+=moderate. C3 goal=request_info; requested_info+=address, phone. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a place to eat in the north area of the city I don't care.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: north; destination: eat in the north area of the city i don't..", "trace": "domain=restaurant; goal=search; area+=north; destination+=eat in the north area of the city i don't."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "In the moderate price range.", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the phone number and address?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No thank you Goodbye.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; price is moderate; destination is eat in the north area of the city i don't; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=north; price=moderate; destination=eat in the north area of the city i don't; requested_info=address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002711", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a place to stay.\nChunk 2: A 0-star hotel is fine with me as long as it fits my moderate budget.\nChunk 3: Yes, could you book me a room there please?\nChunk 4: Actually, can I have the hotel type, phone number, and address instead?\nChunk 5: Thanks!\nChunk 6: I've also heard great things about a restaurant called Anatolia.\nChunk 7: What can you tell me about them That sounds perfect.\nChunk 8: Can you book me a table there for 3 at 14:45 on Friday?\nChunk 9: Thank you so much!", "streaming_reasoning": "C1 domain=hotel; goal=search; destination+=stay. C2 price+=moderate, affordable; hotel_type+=hotel. C3 goal=confirm_booking; goal=confirm_booking. C4 goal=request_info; requested_info+=address, phone. C5 [SKIP: thanks_only]. C6 domain=restaurant. C7 goal=confirm_booking. C8 time+=3, 14:45; day+=friday. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, booking, confirm_booking, compare_alternative, request_info; price=moderate, affordable; destination=stay; requested_info=address, phone; when=friday, 3, 14:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a place to stay.\nChunk 2: A 0-star hotel is fine with me as long as it fits my moderate budget.\nChunk 3: Yes, could you book me a room there please?\nChunk 4: Actually, can I have the hotel type, phone number, and address instead?\nChunk 5: Thanks!\nChunk 6: I've also heard great things about a restaurant called Anatolia.\nChunk 7: What can you tell me about them That sounds perfect.\nChunk 8: Can you book me a table there for 3 at 14:45 on Friday?\nChunk 9: Thank you so much!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; destination+=stay. C2 price+=moderate, affordable; hotel_type+=hotel. C3 goal=confirm_booking; goal=confirm_booking. C4 goal=request_info; requested_info+=address, phone. C5 [SKIP: thanks_only]. C6 domain=restaurant. C7 goal=confirm_booking. C8 time+=3, 14:45; day+=friday. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, booking, confirm_booking, compare_alternative, request_info; price=moderate, affordable; destination=stay; requested_info=address, phone; when=friday, 3, 14:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a place to stay.\nChunk 2: A 0-star hotel is fine with me as long as it fits my moderate budget.\nChunk 3: Yes, could you book me a room there please?\nChunk 4: Actually, can I have the hotel type, phone number, and address instead?\nChunk 5: Thanks!\nChunk 6: I've also heard great things about a restaurant called Anatolia.\nChunk 7: What can you tell me about them That sounds perfect.\nChunk 8: Can you book me a table there for 3 at 14:45 on Friday?\nChunk 9: Thank you so much!", "input_token_count": 100, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay. Next, price: moderate; hotel type: hotel. Next, the goal is confirm booking. Next, the goal is request info; requested information: address. Next, the topic is restaurant. Next, the goal is confirm booking. Finally, time: 3; day: friday.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant.. the goal is confirm booking.. destination: stay.; price: moderate; hotel type: hotel.; requested information: address; time: 3; day: friday..", "trace": "C1 domain=hotel; goal=search; destination+=stay. C2 price+=moderate, affordable; hotel_type+=hotel. C3 goal=confirm_booking; goal=confirm_booking. C4 goal=request_info; requested_info+=address, phone. C5 [SKIP: thanks_only]. C6 domain=restaurant. C7 goal=confirm_booking. C8 time+=3, 14:45; day+=friday. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a place to stay.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "A 0-star hotel is fine with me as long as it fits my moderate budget.", "streaming_reasoning": "As more information arrives, price: moderate; hotel type: hotel..", "trace": "price+=moderate, affordable; hotel_type+=hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, could you book me a room there please?", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Actually, can I have the hotel type, phone number, and address instead?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks!", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I've also heard great things about a restaurant called Anatolia.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "What can you tell me about them That sounds perfect.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Can you book me a table there for 3 at 14:45 on Friday?", "streaming_reasoning": "As more information arrives, time: 3; day: friday..", "trace": "time+=3, 14:45; day+=friday."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you so much!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is moderate; destination is stay; requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, booking, confirm_booking, compare_alternative, request_info; price=moderate, affordable; destination=stay; requested_info=address, phone; when=friday, 3, 14:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002712", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a police station.\nChunk 2: It has something to do with parkside, although I don't know if that's a name or a location.\nChunk 3: Thank you, that's all I need.", "streaming_reasoning": "C1 domain=train; goal=search. C2 destination+=do with parkside. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search; destination=do with parkside; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a police station.\nChunk 2: It has something to do with parkside, although I don't know if that's a name or a location.\nChunk 3: Thank you, that's all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 destination+=do with parkside. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search; destination=do with parkside; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a police station.\nChunk 2: It has something to do with parkside, although I don't know if that's a name or a location.\nChunk 3: Thank you, that's all I need.", "input_token_count": 36, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Finally, destination: do with parkside.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is search.. destination: do with parkside..", "trace": "C1 domain=train; goal=search. C2 destination+=do with parkside. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a police station.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It has something to do with parkside, although I don't know if that's a name or a location.", "streaming_reasoning": "As more information arrives, destination: do with parkside..", "trace": "destination+=do with parkside."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you, that's all I need.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is do with parkside. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search; destination=do with parkside; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002713", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: It should be in the centre part of town.\nChunk 3: Yes.\nChunk 4: I am interested to know the postcode, and if it is a hotel or guesthouse.\nChunk 5: Yes, I'm looking for a chinese restaurant in the same part of town as the hotel What's around?\nChunk 6: I want to find a restaurant.\nChunk 7: I also need the address.\nChunk 8: I also need the phone.\nChunk 9: I also need the postcode That's great.\nChunk 10: Thank you so much for all of your help today.\nChunk 11: I think that will be all.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=centre. C3 [SKIP: acknowledgement_only]. C4 goal=request_info; hotel_type+=guesthouse; destination+=know the postcode; requested_info+=postcode. C5 domain=restaurant; cuisine+=chinese; acceptance=selected_option. C6 [SKIP: repeated_information]. C7 requested_info+=address. C8 requested_info+=phone. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=chinese; destination=find a hotel, know the postcode; requested_info=postcode, address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a hotel.\nChunk 2: It should be in the centre part of town.\nChunk 3: Yes.\nChunk 4: I am interested to know the postcode, and if it is a hotel or guesthouse.\nChunk 5: Yes, I'm looking for a chinese restaurant in the same part of town as the hotel What's around?\nChunk 6: I want to find a restaurant.\nChunk 7: I also need the address.\nChunk 8: I also need the phone.\nChunk 9: I also need the postcode That's great.\nChunk 10: Thank you so much for all of your help today.\nChunk 11: I think that will be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=centre. C3 [SKIP: acknowledgement_only]. C4 goal=request_info; hotel_type+=guesthouse; destination+=know the postcode; requested_info+=postcode. C5 domain=restaurant; cuisine+=chinese; acceptance=selected_option. C6 [SKIP: repeated_information]. C7 requested_info+=address. C8 requested_info+=phone. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=chinese; destination=find a hotel, know the postcode; requested_info=postcode, address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: It should be in the centre part of town.\nChunk 3: Yes.\nChunk 4: I am interested to know the postcode, and if it is a hotel or guesthouse.\nChunk 5: Yes, I'm looking for a chinese restaurant in the same part of town as the hotel What's around?\nChunk 6: I want to find a restaurant.\nChunk 7: I also need the address.\nChunk 8: I also need the phone.\nChunk 9: I also need the postcode That's great.\nChunk 10: Thank you so much for all of your help today.\nChunk 11: I think that will be all.", "input_token_count": 110, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, area: centre. Next, the goal is request info; hotel type: guesthouse; destination: know the postcode; requested information: postcode. Next, the topic is restaurant; cuisine: chinese; acceptance: selected_option. Next, requested information: address. Next, requested information: phone. Finally, intent: context_update.  Some chunks were skipped because they contained acknowledgement_only or closing_only or repeated_information or thanks_only. In summary, The overall topic is restaurant. the goal is request info. hotel type: hotel, guesthouse; destination: find a hotel., know the postcode; area: centre.; requested information: postcode., address., phone.; cuisine: chinese; acceptance: selected_option.; intent: context_update..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=centre. C3 [SKIP: acknowledgement_only]. C4 goal=request_info; hotel_type+=guesthouse; destination+=know the postcode; requested_info+=postcode. C5 domain=restaurant; cuisine+=chinese; acceptance=selected_option. C6 [SKIP: repeated_information]. C7 requested_info+=address. C8 requested_info+=phone. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes.", "streaming_reasoning": "The content at C3 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am interested to know the postcode, and if it is a hotel or guesthouse.", "streaming_reasoning": "As more information arrives, the goal is request info; hotel type: guesthouse; destination: know the postcode; requested information: postcode..", "trace": "goal=request_info; hotel_type+=guesthouse; destination+=know the postcode; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, I'm looking for a chinese restaurant in the same part of town as the hotel What's around?", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: chinese; acceptance: selected_option..", "trace": "domain=restaurant; cuisine+=chinese; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the address.", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need the postcode That's great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you so much for all of your help today.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "I think that will be all.", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; cuisine is chinese; destination is find a hotel; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=chinese; destination=find a hotel, know the postcode; requested_info=postcode, address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002714", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Am looking for the Addenbrookes Hospital.\nChunk 2: No, but do you have the postal code by any chance?\nChunk 3: No, that's all good bye.", "streaming_reasoning": "C1 domain=hospital; goal=search. C2 requested_info+=postcode. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Am looking for the Addenbrookes Hospital.\nChunk 2: No, but do you have the postal code by any chance?\nChunk 3: No, that's all good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search. C2 requested_info+=postcode. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Am looking for the Addenbrookes Hospital.\nChunk 2: No, but do you have the postal code by any chance?\nChunk 3: No, that's all good bye.", "input_token_count": 28, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search. Finally, requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital. the goal is search.. requested information: postcode..", "trace": "C1 domain=hospital; goal=search. C2 requested_info+=postcode. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Am looking for the Addenbrookes Hospital.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search..", "trace": "domain=hospital; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, but do you have the postal code by any chance?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, that's all good bye.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003382", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd better be going So soon?\nChunk 2: Why don't you stay a little longer?\nChunk 3: I wish I could, but it's already late.\nChunk 4: Oh, it's a pity that you have to leave.\nChunk 5: Thank you for a wonderful meal.", "streaming_reasoning": "C1 question=true. C2 question=true. C3 casual_comment=wish, already. C4 leaving_reason=needs_to_go. C5 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd better be going So soon?\nChunk 2: Why don't you stay a little longer?\nChunk 3: I wish I could, but it's already late.\nChunk 4: Oh, it's a pity that you have to leave.\nChunk 5: Thank you for a wonderful meal."}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 question=true. C3 casual_comment=wish, already. C4 leaving_reason=needs_to_go. C5 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd better be going So soon?\nChunk 2: Why don't you stay a little longer?\nChunk 3: I wish I could, but it's already late.\nChunk 4: Oh, it's a pity that you have to leave.\nChunk 5: Thank you for a wonderful meal.", "input_token_count": 46, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the input provides additional context about question=true. Next, the user comments on wish. Finally, leaving reason: needs_to_go.  Some chunks were skipped because they contained thanks_only. In summary, leaving reason: needs_to_go..", "trace": "C1 question=true. C2 question=true. C3 casual_comment=wish, already. C4 leaving_reason=needs_to_go. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd better be going So soon?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Why don't you stay a little longer?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I wish I could, but it's already late.", "streaming_reasoning": "As more information arrives, the user comments on wish.", "trace": "casual_comment=wish, already."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Oh, it's a pity that you have to leave.", "streaming_reasoning": "As more information arrives, leaving reason: needs_to_go..", "trace": "leaving_reason=needs_to_go."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you for a wonderful meal.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002715", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: The restaurant should serve chinese food and should be in the moderate price range.\nChunk 2: Is there a Yelp rating for the restaurant?\nChunk 3: ok.\nChunk 4: book what you deem best and get me the reference number.\nChunk 5: The reservation is just for me this Saturday at 15:45, please.\nChunk 6: Yes, I would like a reservation for the Golden Wok, for one person at 15:45 this Saturday.\nChunk 7: Please give me the reference number as well.\nChunk 8: That is all, thank you.", "streaming_reasoning": "C1 domain=restaurant; cuisine+=chinese; price+=moderate. C2 goal=request_info. C3 [SKIP: backchannel_only]. C4 goal=request_info; requested_info+=reference_number. C5 time+=15:45; day+=saturday. C6 goal=confirm_booking; goal=confirm_booking. C7 intent=context_update. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, request_info, confirm_booking; food=chinese; price=moderate; requested_info=reference_number; when=saturday, 15:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: The restaurant should serve chinese food and should be in the moderate price range.\nChunk 2: Is there a Yelp rating for the restaurant?\nChunk 3: ok.\nChunk 4: book what you deem best and get me the reference number.\nChunk 5: The reservation is just for me this Saturday at 15:45, please.\nChunk 6: Yes, I would like a reservation for the Golden Wok, for one person at 15:45 this Saturday.\nChunk 7: Please give me the reference number as well.\nChunk 8: That is all, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; cuisine+=chinese; price+=moderate. C2 goal=request_info. C3 [SKIP: backchannel_only]. C4 goal=request_info; requested_info+=reference_number. C5 time+=15:45; day+=saturday. C6 goal=confirm_booking; goal=confirm_booking. C7 intent=context_update. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, request_info, confirm_booking; food=chinese; price=moderate; requested_info=reference_number; when=saturday, 15:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: The restaurant should serve chinese food and should be in the moderate price range.\nChunk 2: Is there a Yelp rating for the restaurant?\nChunk 3: ok.\nChunk 4: book what you deem best and get me the reference number.\nChunk 5: The reservation is just for me this Saturday at 15:45, please.\nChunk 6: Yes, I would like a reservation for the Golden Wok, for one person at 15:45 this Saturday.\nChunk 7: Please give me the reference number as well.\nChunk 8: That is all, thank you.", "input_token_count": 93, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; cuisine: chinese; price: moderate. Next, the goal is request info. Next, the goal is request info; requested information: reference_number. Next, time: 15:45; day: saturday. Next, the goal is confirm booking. Finally, intent: context_update.  Some chunks were skipped because they contained backchannel_only or closing_only. In summary, The overall topic is restaurant. the goal is confirm booking.. cuisine: chinese; price: moderate.; requested information: reference_number.; time: 15:45; day: saturday.; intent: context_update..", "trace": "C1 domain=restaurant; cuisine+=chinese; price+=moderate. C2 goal=request_info. C3 [SKIP: backchannel_only]. C4 goal=request_info; requested_info+=reference_number. C5 time+=15:45; day+=saturday. C6 goal=confirm_booking; goal=confirm_booking. C7 intent=context_update. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "The restaurant should serve chinese food and should be in the moderate price range.", "streaming_reasoning": "Initially, the topic is restaurant; cuisine: chinese; price: moderate..", "trace": "domain=restaurant; cuisine+=chinese; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there a Yelp rating for the restaurant?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "ok.", "streaming_reasoning": "The content at C3 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "book what you deem best and get me the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The reservation is just for me this Saturday at 15:45, please.", "streaming_reasoning": "As more information arrives, time: 15:45; day: saturday..", "trace": "time+=15:45; day+=saturday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, I would like a reservation for the Golden Wok, for one person at 15:45 this Saturday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please give me the reference number as well.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all, thank you.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is chinese; price is moderate; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, request_info, confirm_booking; food=chinese; price=moderate; requested_info=reference_number; when=saturday, 15:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002716", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a guesthouse.\nChunk 2: It should be in the north part of town.\nChunk 3: Yes please, for 6 people and five nights on Monday.\nChunk 4: I'm looking for a restaurant called saffron brasserie Yes, please.\nChunk 5: I'd also like to know what area of town it's in and what type of food it serves.\nChunk 6: I want to find a hotel.\nChunk 7: The time is 16:30 Ok, great.\nChunk 8: Thanks for your help, you have covered everything I needed!", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 area+=north. C3 day+=monday; party_size+=6 people; acceptance=selected_option. C4 domain=restaurant; acceptance=selected_option. C5 destination+=know what area of town it's in and what t. C6 hotel_type+=hotel; destination+=find a hotel. C7 time+=16:30. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search; area=north; party_size=6 people; destination=find a guesthouse, know what area of town it's in and what t, find a hotel; when=monday, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a guesthouse.\nChunk 2: It should be in the north part of town.\nChunk 3: Yes please, for 6 people and five nights on Monday.\nChunk 4: I'm looking for a restaurant called saffron brasserie Yes, please.\nChunk 5: I'd also like to know what area of town it's in and what type of food it serves.\nChunk 6: I want to find a hotel.\nChunk 7: The time is 16:30 Ok, great.\nChunk 8: Thanks for your help, you have covered everything I needed!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 area+=north. C3 day+=monday; party_size+=6 people; acceptance=selected_option. C4 domain=restaurant; acceptance=selected_option. C5 destination+=know what area of town it's in and what t. C6 hotel_type+=hotel; destination+=find a hotel. C7 time+=16:30. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search; area=north; party_size=6 people; destination=find a guesthouse, know what area of town it's in and what t, find a hotel; when=monday, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a guesthouse.\nChunk 2: It should be in the north part of town.\nChunk 3: Yes please, for 6 people and five nights on Monday.\nChunk 4: I'm looking for a restaurant called saffron brasserie Yes, please.\nChunk 5: I'd also like to know what area of town it's in and what type of food it serves.\nChunk 6: I want to find a hotel.\nChunk 7: The time is 16:30 Ok, great.\nChunk 8: Thanks for your help, you have covered everything I needed!", "input_token_count": 92, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; destination: find a guesthouse. Next, area: north. Next, day: monday; party size: 6 people; acceptance: selected_option. Next, the topic is restaurant; acceptance: selected_option. Next, destination: know what area of town it's in and what t. Next, hotel type: hotel; destination: find a hotel. Finally, time: 16:30.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is search. hotel type: guesthouse, hotel; destination: find a guesthouse., know what area of town it's in and what t., find a hotel.; area: north.; day: monday; party size: 6 people; acceptance: selected_option.; time: 16:30..", "trace": "C1 domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse. C2 area+=north. C3 day+=monday; party_size+=6 people; acceptance=selected_option. C4 domain=restaurant; acceptance=selected_option. C5 destination+=know what area of town it's in and what t. C6 hotel_type+=hotel; destination+=find a hotel. C7 time+=16:30. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a guesthouse.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: guesthouse; destination: find a guesthouse..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; destination+=find a guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes please, for 6 people and five nights on Monday.", "streaming_reasoning": "As more information arrives, day: monday; party size: 6 people; acceptance: selected_option..", "trace": "day+=monday; party_size+=6 people; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm looking for a restaurant called saffron brasserie Yes, please.", "streaming_reasoning": "As more information arrives, the topic is restaurant; acceptance: selected_option..", "trace": "domain=restaurant; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'd also like to know what area of town it's in and what type of food it serves.", "streaming_reasoning": "As more information arrives, destination: know what area of town it's in and what t..", "trace": "destination+=know what area of town it's in and what t."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, hotel type: hotel; destination: find a hotel..", "trace": "hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 16:30 Ok, great.", "streaming_reasoning": "As more information arrives, time: 16:30..", "trace": "time+=16:30."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks for your help, you have covered everything I needed!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; party size is 6 people; destination is find a guesthouse; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search; area=north; party_size=6 people; destination=find a guesthouse, know what area of town it's in and what t, find a hotel; when=monday, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002717", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Departure time doesn't matter, just want to arrive by 10:45 so whatever is closest to that arrival time.\nChunk 2: Wait, does this train go to Cambridge That's my destination.\nChunk 3: Yes please book it Just one please.\nChunk 4: I didn't actually need to reserve a seat.\nChunk 5: Could you comfirm the departure time of that train?\nChunk 6: No, that's all I need for now, thanks!", "streaming_reasoning": "C1 goal=search; time+=10:45; destination+=arrive by 10:45 so whatever is closest to. C2 domain=train; destination+=cambridge that's my destination. C3 goal=confirm_booking; goal=confirm_booking. C4 destination+=reserve a seat. C5 goal=request_info. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, booking, confirm_booking; destination=arrive by 10:45 so whatever is closest to, cambridge that's my destination, reserve a seat; when=10:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Departure time doesn't matter, just want to arrive by 10:45 so whatever is closest to that arrival time.\nChunk 2: Wait, does this train go to Cambridge That's my destination.\nChunk 3: Yes please book it Just one please.\nChunk 4: I didn't actually need to reserve a seat.\nChunk 5: Could you comfirm the departure time of that train?\nChunk 6: No, that's all I need for now, thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; time+=10:45; destination+=arrive by 10:45 so whatever is closest to. C2 domain=train; destination+=cambridge that's my destination. C3 goal=confirm_booking; goal=confirm_booking. C4 destination+=reserve a seat. C5 goal=request_info. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, booking, confirm_booking; destination=arrive by 10:45 so whatever is closest to, cambridge that's my destination, reserve a seat; when=10:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Departure time doesn't matter, just want to arrive by 10:45 so whatever is closest to that arrival time.\nChunk 2: Wait, does this train go to Cambridge That's my destination.\nChunk 3: Yes please book it Just one please.\nChunk 4: I didn't actually need to reserve a seat.\nChunk 5: Could you comfirm the departure time of that train?\nChunk 6: No, that's all I need for now, thanks!", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; time: 10:45; destination: arrive by 10:45 so whatever is closest to. Next, the topic is train; destination: cambridge that's my destination. Next, the goal is confirm booking. Next, destination: reserve a seat. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info.. time: 10:45; destination: arrive by 10:45 so whatever is closest to., cambridge that's my destination., reserve a seat..", "trace": "C1 goal=search; time+=10:45; destination+=arrive by 10:45 so whatever is closest to. C2 domain=train; destination+=cambridge that's my destination. C3 goal=confirm_booking; goal=confirm_booking. C4 destination+=reserve a seat. C5 goal=request_info. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Departure time doesn't matter, just want to arrive by 10:45 so whatever is closest to that arrival time.", "streaming_reasoning": "Initially, the goal is search; time: 10:45; destination: arrive by 10:45 so whatever is closest to..", "trace": "goal=search; time+=10:45; destination+=arrive by 10:45 so whatever is closest to."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Wait, does this train go to Cambridge That's my destination.", "streaming_reasoning": "As more information arrives, the topic is train; destination: cambridge that's my destination..", "trace": "domain=train; destination+=cambridge that's my destination."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes please book it Just one please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I didn't actually need to reserve a seat.", "streaming_reasoning": "As more information arrives, destination: reserve a seat..", "trace": "destination+=reserve a seat."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Could you comfirm the departure time of that train?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, that's all I need for now, thanks!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is arrive by 10:45 so whatever is closest to; timing is 10:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, booking, confirm_booking; destination=arrive by 10:45 so whatever is closest to, cambridge that's my destination, reserve a seat; when=10:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002718", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need a restaurant in the center of town that serves chinese food.\nChunk 2: Price doesn't matter to me.\nChunk 3: Do you have any recommendations?\nChunk 4: Yes, please book a table for 4 people at 12:15 on tuesday.\nChunk 5: I also need a taxi to commute between the two places.\nChunk 6: I want a taxi between the hotel and Ugly Duckling in time for my booking.\nChunk 7: That is all I will need Thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=chinese. C2 intent=context_update. C3 goal=request_info. C4 goal=confirm_booking; time+=4, 12:15; day+=tuesday; party_size+=4 people; goal=confirm_booking. C5 domain=taxi; destination+=commute between the two places. C6 domain=hotel; hotel_type+=hotel. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi, hotel; goal=search, booking, confirm_booking; area=centre; food=chinese; party_size=4 people; destination=commute between the two places; when=tuesday, 4, 12:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also need a restaurant in the center of town that serves chinese food.\nChunk 2: Price doesn't matter to me.\nChunk 3: Do you have any recommendations?\nChunk 4: Yes, please book a table for 4 people at 12:15 on tuesday.\nChunk 5: I also need a taxi to commute between the two places.\nChunk 6: I want a taxi between the hotel and Ugly Duckling in time for my booking.\nChunk 7: That is all I will need Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; cuisine+=chinese. C2 intent=context_update. C3 goal=request_info. C4 goal=confirm_booking; time+=4, 12:15; day+=tuesday; party_size+=4 people; goal=confirm_booking. C5 domain=taxi; destination+=commute between the two places. C6 domain=hotel; hotel_type+=hotel. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi, hotel; goal=search, booking, confirm_booking; area=centre; food=chinese; party_size=4 people; destination=commute between the two places; when=tuesday, 4, 12:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need a restaurant in the center of town that serves chinese food.\nChunk 2: Price doesn't matter to me.\nChunk 3: Do you have any recommendations?\nChunk 4: Yes, please book a table for 4 people at 12:15 on tuesday.\nChunk 5: I also need a taxi to commute between the two places.\nChunk 6: I want a taxi between the hotel and Ugly Duckling in time for my booking.\nChunk 7: That is all I will need Thank you.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: chinese. Next, intent: context_update. Next, the goal is request info. Next, the goal is confirm booking.; time: 4; day: tuesday; party size: 4 people. Next, the topic is taxi; destination: commute between the two places. Finally, the topic is hotel; hotel type: hotel.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is confirm booking.. area: centre; cuisine: chinese.; intent: context_update.; time: 4; day: tuesday; party size: 4 people; destination: commute between the two places.; hotel type: hotel..", "trace": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=chinese. C2 intent=context_update. C3 goal=request_info. C4 goal=confirm_booking; time+=4, 12:15; day+=tuesday; party_size+=4 people; goal=confirm_booking. C5 domain=taxi; destination+=commute between the two places. C6 domain=hotel; hotel_type+=hotel. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also need a restaurant in the center of town that serves chinese food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: chinese..", "trace": "domain=restaurant; goal=search; area+=centre; cuisine+=chinese."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Price doesn't matter to me.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Do you have any recommendations?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, please book a table for 4 people at 12:15 on tuesday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 4; day: tuesday; party size: 4 people.", "trace": "goal=confirm_booking; time+=4, 12:15; day+=tuesday; party_size+=4 people; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need a taxi to commute between the two places.", "streaming_reasoning": "As more information arrives, the topic is taxi; destination: commute between the two places..", "trace": "domain=taxi; destination+=commute between the two places."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want a taxi between the hotel and Ugly Duckling in time for my booking.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel..", "trace": "domain=hotel; hotel_type+=hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I will need Thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; party size is 4 people; destination is commute between the two places; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi, hotel; goal=search, booking, confirm_booking; area=centre; food=chinese; party_size=4 people; destination=commute between the two places; when=tuesday, 4, 12:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002719", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Well I want a hotel not food.\nChunk 2: I would like something in the east with 4 stars.\nChunk 3: I would like it to be a guesthouse.\nChunk 4: Yes, I would like to book for 8 people for 4 nights starting Tuesday Please do so.\nChunk 5: thank you that is all I need goodbye.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=east; stars+=4 stars. C3 hotel_type+=guesthouse; destination+=be a guesthouse. C4 goal=confirm_booking; time+=8, 4; day+=tuesday; party_size+=8 people; stay_length+=4 nights; goal=confirm_booking. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel; goal=search, booking, confirm_booking; area=east; party_size=8 people; stay_length=4 nights; stars=4 stars; destination=be a guesthouse; when=tuesday, 8, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Well I want a hotel not food.\nChunk 2: I would like something in the east with 4 stars.\nChunk 3: I would like it to be a guesthouse.\nChunk 4: Yes, I would like to book for 8 people for 4 nights starting Tuesday Please do so.\nChunk 5: thank you that is all I need goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=east; stars+=4 stars. C3 hotel_type+=guesthouse; destination+=be a guesthouse. C4 goal=confirm_booking; time+=8, 4; day+=tuesday; party_size+=8 people; stay_length+=4 nights; goal=confirm_booking. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel; goal=search, booking, confirm_booking; area=east; party_size=8 people; stay_length=4 nights; stars=4 stars; destination=be a guesthouse; when=tuesday, 8, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Well I want a hotel not food.\nChunk 2: I would like something in the east with 4 stars.\nChunk 3: I would like it to be a guesthouse.\nChunk 4: Yes, I would like to book for 8 people for 4 nights starting Tuesday Please do so.\nChunk 5: thank you that is all I need goodbye.", "input_token_count": 60, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel. Next, area: east; star rating: 4 stars. Next, hotel type: guesthouse; destination: be a guesthouse. Finally, the goal is confirm booking.; time: 8; day: tuesday; party size: 8 people; stay length: 4 nights.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is confirm booking.. hotel type: hotel., guesthouse; area: east; star rating: 4 stars.; destination: be a guesthouse.; time: 8; day: tuesday; party size: 8 people; stay length: 4 nights.", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=east; stars+=4 stars. C3 hotel_type+=guesthouse; destination+=be a guesthouse. C4 goal=confirm_booking; time+=8, 4; day+=tuesday; party_size+=8 people; stay_length+=4 nights; goal=confirm_booking. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Well I want a hotel not food.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like something in the east with 4 stars.", "streaming_reasoning": "As more information arrives, area: east; star rating: 4 stars..", "trace": "area+=east; stars+=4 stars."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like it to be a guesthouse.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse; destination: be a guesthouse..", "trace": "hotel_type+=guesthouse; destination+=be a guesthouse."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I would like to book for 8 people for 4 nights starting Tuesday Please do so.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 8; day: tuesday; party size: 8 people; stay length: 4 nights.", "trace": "goal=confirm_booking; time+=8, 4; day+=tuesday; party_size+=8 people; stay_length+=4 nights; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "thank you that is all I need goodbye.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is east; party size is 8 people; stay length is 4 nights; star rating is 4 stars; destination is be a guesthouse; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=search, booking, confirm_booking; area=east; party_size=8 people; stay_length=4 nights; stars=4 stars; destination=be a guesthouse; when=tuesday, 8, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002720", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like the east please.\nChunk 2: Is it in the expensive price range?\nChunk 3: Not at this time but what is their address and postcode?\nChunk 4: i also need a taxi to commute between the two places.\nChunk 5: I need to leave the attraction by 03:00.\nChunk 6: That will be all, thank you.", "streaming_reasoning": "C1 area+=east. C2 price+=expensive. C3 goal=request_info; requested_info+=address, postcode. C4 domain=taxi; goal=search; destination+=commute between the two places. C5 domain=attraction; time+=03:00; destination+=leave the attraction by 03:00. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi, attraction; goal=request_info, search; area=east; price=expensive; destination=commute between the two places, leave the attraction by 03:00; requested_info=address, postcode; when=03:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like the east please.\nChunk 2: Is it in the expensive price range?\nChunk 3: Not at this time but what is their address and postcode?\nChunk 4: i also need a taxi to commute between the two places.\nChunk 5: I need to leave the attraction by 03:00.\nChunk 6: That will be all, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=east. C2 price+=expensive. C3 goal=request_info; requested_info+=address, postcode. C4 domain=taxi; goal=search; destination+=commute between the two places. C5 domain=attraction; time+=03:00; destination+=leave the attraction by 03:00. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi, attraction; goal=request_info, search; area=east; price=expensive; destination=commute between the two places, leave the attraction by 03:00; requested_info=address, postcode; when=03:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like the east please.\nChunk 2: Is it in the expensive price range?\nChunk 3: Not at this time but what is their address and postcode?\nChunk 4: i also need a taxi to commute between the two places.\nChunk 5: I need to leave the attraction by 03:00.\nChunk 6: That will be all, thank you.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: east. Next, price: expensive. Next, the goal is request info; requested information: address. Next, the topic is taxi; the goal is search; destination: commute between the two places. Finally, the topic is attraction; time: 03:00; destination: leave the attraction by 03:00.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is search. area: east.; price: expensive.; requested information: address; destination: commute between the two places., leave the attraction by 03:00.; time: 03:00.", "trace": "C1 area+=east. C2 price+=expensive. C3 goal=request_info; requested_info+=address, postcode. C4 domain=taxi; goal=search; destination+=commute between the two places. C5 domain=attraction; time+=03:00; destination+=leave the attraction by 03:00. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like the east please.", "streaming_reasoning": "Initially, area: east..", "trace": "area+=east."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is it in the expensive price range?", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Not at this time but what is their address and postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "i also need a taxi to commute between the two places.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is search; destination: commute between the two places..", "trace": "domain=taxi; goal=search; destination+=commute between the two places."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need to leave the attraction by 03:00.", "streaming_reasoning": "As more information arrives, the topic is attraction; time: 03:00; destination: leave the attraction by 03:00..", "trace": "domain=attraction; time+=03:00; destination+=leave the attraction by 03:00."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That will be all, thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of request info. Key information: area is east; price is expensive; destination is commute between the two places; requested information is address; timing is 03:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, attraction; goal=request_info, search; area=east; price=expensive; destination=commute between the two places, leave the attraction by 03:00; requested_info=address, postcode; when=03:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002721", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to find an expensive place to dine in the south.\nChunk 2: Is there any Morrocan food?\nChunk 3: I would be interested in Indian food.\nChunk 4: That place sounds great.\nChunk 5: Can I get the phone number please?\nChunk 6: No, that is all I need Thanks so much.\nChunk 7: Bye.", "streaming_reasoning": "C1 goal=search; area+=south; price+=expensive; destination+=find an expensive place to dine in the so. C2 domain=restaurant. C3 cuisine+=indian. C4 intent=context_update. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=south; food=indian; price=expensive; destination=find an expensive place to dine in the so; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like to find an expensive place to dine in the south.\nChunk 2: Is there any Morrocan food?\nChunk 3: I would be interested in Indian food.\nChunk 4: That place sounds great.\nChunk 5: Can I get the phone number please?\nChunk 6: No, that is all I need Thanks so much.\nChunk 7: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=south; price+=expensive; destination+=find an expensive place to dine in the so. C2 domain=restaurant. C3 cuisine+=indian. C4 intent=context_update. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=south; food=indian; price=expensive; destination=find an expensive place to dine in the so; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to find an expensive place to dine in the south.\nChunk 2: Is there any Morrocan food?\nChunk 3: I would be interested in Indian food.\nChunk 4: That place sounds great.\nChunk 5: Can I get the phone number please?\nChunk 6: No, that is all I need Thanks so much.\nChunk 7: Bye.", "input_token_count": 59, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: south; price: expensive; destination: find an expensive place to dine in the so. Next, the topic is restaurant. Next, cuisine: indian. Next, intent: context_update. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant.. the goal is request info. area: south; price: expensive; destination: find an expensive place to dine in the so.; cuisine: indian.; intent: context_update.; requested information: phone..", "trace": "C1 goal=search; area+=south; price+=expensive; destination+=find an expensive place to dine in the so. C2 domain=restaurant. C3 cuisine+=indian. C4 intent=context_update. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like to find an expensive place to dine in the south.", "streaming_reasoning": "Initially, the goal is search; area: south; price: expensive; destination: find an expensive place to dine in the so..", "trace": "goal=search; area+=south; price+=expensive; destination+=find an expensive place to dine in the so."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there any Morrocan food?", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would be interested in Indian food.", "streaming_reasoning": "As more information arrives, cuisine: indian..", "trace": "cuisine+=indian."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That place sounds great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get the phone number please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, that is all I need Thanks so much.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Bye.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; cuisine is indian; price is expensive; destination is find an expensive place to dine in the so; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=south; food=indian; price=expensive; destination=find an expensive place to dine in the so; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002722", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you that will be all.\nChunk 2: Have a great day.\nChunk 3: I would also like to find a museum.\nChunk 4: How about you just choose the one you like best and give me the postcode, entrance fee, and area information for it.\nChunk 5: I need help with taxi.\nChunk 6: The time is 18:30.\nChunk 7: Great thank you so much for all the help!\nChunk 8: That's all I needed.\nChunk 9: Thanks for all your help.", "streaming_reasoning": "C1 [SKIP: closing_only]. C2 [SKIP: closing_only]. C3 domain=attraction; goal=search; destination+=find a museum. C4 goal=request_info; requested_info+=postcode, entrance_fee. C5 domain=taxi. C6 time+=18:30. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, taxi; goal=search, recommendation, request_info; destination=find a museum; requested_info=postcode, entrance_fee; when=18:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you that will be all.\nChunk 2: Have a great day.\nChunk 3: I would also like to find a museum.\nChunk 4: How about you just choose the one you like best and give me the postcode, entrance fee, and area information for it.\nChunk 5: I need help with taxi.\nChunk 6: The time is 18:30.\nChunk 7: Great thank you so much for all the help!\nChunk 8: That's all I needed.\nChunk 9: Thanks for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: closing_only]. C2 [SKIP: closing_only]. C3 domain=attraction; goal=search; destination+=find a museum. C4 goal=request_info; requested_info+=postcode, entrance_fee. C5 domain=taxi. C6 time+=18:30. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, taxi; goal=search, recommendation, request_info; destination=find a museum; requested_info=postcode, entrance_fee; when=18:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you that will be all.\nChunk 2: Have a great day.\nChunk 3: I would also like to find a museum.\nChunk 4: How about you just choose the one you like best and give me the postcode, entrance fee, and area information for it.\nChunk 5: I need help with taxi.\nChunk 6: The time is 18:30.\nChunk 7: Great thank you so much for all the help!\nChunk 8: That's all I needed.\nChunk 9: Thanks for all your help.", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; destination: find a museum. Next, the goal is request info; requested information: postcode. Next, the topic is taxi. Finally, time: 18:30.  Some chunks were skipped because they contained closing_only or repeated_information or thanks_only. In summary, The overall topic is taxi.. the goal is request info. destination: find a museum.; requested information: postcode; time: 18:30..", "trace": "C1 [SKIP: closing_only]. C2 [SKIP: closing_only]. C3 domain=attraction; goal=search; destination+=find a museum. C4 goal=request_info; requested_info+=postcode, entrance_fee. C5 domain=taxi. C6 time+=18:30. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you that will be all.", "streaming_reasoning": "The content at C1 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C2 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would also like to find a museum.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is search; destination: find a museum..", "trace": "domain=attraction; goal=search; destination+=find a museum."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "How about you just choose the one you like best and give me the postcode, entrance fee, and area information for it.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode.", "trace": "goal=request_info; requested_info+=postcode, entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need help with taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 18:30.", "streaming_reasoning": "As more information arrives, time: 18:30..", "trace": "time+=18:30."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Great thank you so much for all the help!", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's all I needed.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks for all your help.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: destination is find a museum; requested information is postcode; timing is 18:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, taxi; goal=search, recommendation, request_info; destination=find a museum; requested_info=postcode, entrance_fee; when=18:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002724", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi I need a cheap hotel in the three star range, please.\nChunk 2: Ok.\nChunk 3: I would like it to be a hotel and have free wifi please.\nChunk 4: I am really looking for a hotel that is expensive.\nChunk 5: Does the Cambridge Belfry fit that description?", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel. C2 [SKIP: backchannel_only]. C3 amenities+=wifi; destination+=be a hotel and have free wifi please. C4 price+=expensive. C5 goal=request_info.", "deep_reasoning": "Need domain=hotel; goal=search; price=cheap, expensive; amenities=wifi; destination=be a hotel and have free wifi please.", "answer": "What area, date should I use for the search?", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi I need a cheap hotel in the three star range, please.\nChunk 2: Ok.\nChunk 3: I would like it to be a hotel and have free wifi please.\nChunk 4: I am really looking for a hotel that is expensive.\nChunk 5: Does the Cambridge Belfry fit that description?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel. C2 [SKIP: backchannel_only]. C3 amenities+=wifi; destination+=be a hotel and have free wifi please. C4 price+=expensive. C5 goal=request_info.\n\nDeep reasoning: Need domain=hotel; goal=search; price=cheap, expensive; amenities=wifi; destination=be a hotel and have free wifi please.\n\nAnswer: What area, date should I use for the search?"}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi I need a cheap hotel in the three star range, please.\nChunk 2: Ok.\nChunk 3: I would like it to be a hotel and have free wifi please.\nChunk 4: I am really looking for a hotel that is expensive.\nChunk 5: Does the Cambridge Belfry fit that description?", "input_token_count": 53, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: cheap; hotel type: hotel. Next, amenities: wifi; destination: be a hotel and have free wifi please. Next, price: expensive. Finally, the goal is request info.  Some chunks were skipped because they contained backchannel_only. In summary, The overall topic is hotel. the goal is request info.. price: cheap, expensive.; hotel type: hotel.; amenities: wifi; destination: be a hotel and have free wifi please..", "trace": "C1 domain=hotel; goal=search; price+=cheap; hotel_type+=hotel. C2 [SKIP: backchannel_only]. C3 amenities+=wifi; destination+=be a hotel and have free wifi please. C4 price+=expensive. C5 goal=request_info.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi I need a cheap hotel in the three star range, please.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: cheap; hotel type: hotel..", "trace": "domain=hotel; goal=search; price+=cheap; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Ok.", "streaming_reasoning": "The content at C2 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like it to be a hotel and have free wifi please.", "streaming_reasoning": "As more information arrives, amenities: wifi; destination: be a hotel and have free wifi please..", "trace": "amenities+=wifi; destination+=be a hotel and have free wifi please."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am really looking for a hotel that is expensive.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Does the Cambridge Belfry fit that description?", "streaming_reasoning": "Finally, the goal is request info..", "trace": "goal=request_info."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is cheap; amenities is wifi; destination is be a hotel and have free wifi please.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "What area, date should I use for the search?", "deep_reasoning_trace": "Need domain=hotel; goal=search; price=cheap, expensive; amenities=wifi; destination=be a hotel and have free wifi please."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002725", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm also looking for a train that departs from cambridge and leave on Monday.\nChunk 2: I'd like to arrive at Leicester by 17:45.\nChunk 3: And what was that postcode for Whale of a Time again?\nChunk 4: Yes, I would like to make a booking for 8 people.\nChunk 5: Just want to make sure, that reference number is for the train, TR5465?\nChunk 6: postcode, phone number, and area.\nChunk 7: Thank you for all your help.\nChunk 8: You have a great day.", "streaming_reasoning": "C1 domain=train; goal=search; day+=monday. C2 time+=17:45; destination+=arrive at leicester by 17:45. C3 goal=request_info; requested_info+=postcode. C4 goal=booking; party_size+=8 people; goal=confirm_booking. C5 destination+=make sure; requested_info+=reference_number. C6 requested_info+=phone. C7 [SKIP: thanks_only]. C8 intent=context_update.", "deep_reasoning": "Need domain=train; goal=search, request_info, booking; party_size=8 people; destination=arrive at leicester by 17:45, make sure; requested_info=postcode, reference_number, phone; when=monday, 17:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm also looking for a train that departs from cambridge and leave on Monday.\nChunk 2: I'd like to arrive at Leicester by 17:45.\nChunk 3: And what was that postcode for Whale of a Time again?\nChunk 4: Yes, I would like to make a booking for 8 people.\nChunk 5: Just want to make sure, that reference number is for the train, TR5465?\nChunk 6: postcode, phone number, and area.\nChunk 7: Thank you for all your help.\nChunk 8: You have a great day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=monday. C2 time+=17:45; destination+=arrive at leicester by 17:45. C3 goal=request_info; requested_info+=postcode. C4 goal=booking; party_size+=8 people; goal=confirm_booking. C5 destination+=make sure; requested_info+=reference_number. C6 requested_info+=phone. C7 [SKIP: thanks_only]. C8 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking; party_size=8 people; destination=arrive at leicester by 17:45, make sure; requested_info=postcode, reference_number, phone; when=monday, 17:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm also looking for a train that departs from cambridge and leave on Monday.\nChunk 2: I'd like to arrive at Leicester by 17:45.\nChunk 3: And what was that postcode for Whale of a Time again?\nChunk 4: Yes, I would like to make a booking for 8 people.\nChunk 5: Just want to make sure, that reference number is for the train, TR5465?\nChunk 6: postcode, phone number, and area.\nChunk 7: Thank you for all your help.\nChunk 8: You have a great day.", "input_token_count": 90, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: monday. Next, time: 17:45; destination: arrive at leicester by 17:45. Next, the goal is request info; requested information: postcode. Next, the goal is confirm booking.; party size: 8 people. Next, destination: make sure; requested information: reference_number. Next, requested information: phone. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is confirm booking.. day: monday.; time: 17:45; destination: arrive at leicester by 17:45., make sure; requested information: postcode., reference_number., phone.; party size: 8 people; intent: context_update..", "trace": "C1 domain=train; goal=search; day+=monday. C2 time+=17:45; destination+=arrive at leicester by 17:45. C3 goal=request_info; requested_info+=postcode. C4 goal=booking; party_size+=8 people; goal=confirm_booking. C5 destination+=make sure; requested_info+=reference_number. C6 requested_info+=phone. C7 [SKIP: thanks_only]. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm also looking for a train that departs from cambridge and leave on Monday.", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: monday..", "trace": "domain=train; goal=search; day+=monday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to arrive at Leicester by 17:45.", "streaming_reasoning": "As more information arrives, time: 17:45; destination: arrive at leicester by 17:45..", "trace": "time+=17:45; destination+=arrive at leicester by 17:45."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "And what was that postcode for Whale of a Time again?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I would like to make a booking for 8 people.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; party size: 8 people.", "trace": "goal=booking; party_size+=8 people; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Just want to make sure, that reference number is for the train, TR5465?", "streaming_reasoning": "As more information arrives, destination: make sure; requested information: reference_number..", "trace": "destination+=make sure; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "postcode, phone number, and area.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "You have a great day.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 8 people; destination is arrive at leicester by 17:45; requested information is postcode; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking; party_size=8 people; destination=arrive at leicester by 17:45, make sure; requested_info=postcode, reference_number, phone; when=monday, 17:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002726", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Nothing specific.Recommend one and send me their phone number Thanks so much.\nChunk 2: I am also looking for a place to dine.\nChunk 3: Can you help me?\nChunk 4: I don't care, just something good in the same area as Broughton House is.\nChunk 5: Try and stay in the moderate price range though The centre please.\nChunk 6: Could you tell me the phone number and food type Great, thank you.\nChunk 7: No that will be all for today, I appreciate all your help No thank you.", "streaming_reasoning": "C1 goal=request_info; requested_info+=phone. C2 goal=search; destination+=dine. C3 goal=request_info. C4 goal=modify_constraint. C5 domain=hotel; area+=centre; price+=moderate. C6 domain=restaurant. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=recommendation, request_info, search, modify_constraint; area=centre; price=moderate; destination=dine; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Nothing specific.Recommend one and send me their phone number Thanks so much.\nChunk 2: I am also looking for a place to dine.\nChunk 3: Can you help me?\nChunk 4: I don't care, just something good in the same area as Broughton House is.\nChunk 5: Try and stay in the moderate price range though The centre please.\nChunk 6: Could you tell me the phone number and food type Great, thank you.\nChunk 7: No that will be all for today, I appreciate all your help No thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=phone. C2 goal=search; destination+=dine. C3 goal=request_info. C4 goal=modify_constraint. C5 domain=hotel; area+=centre; price+=moderate. C6 domain=restaurant. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=recommendation, request_info, search, modify_constraint; area=centre; price=moderate; destination=dine; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Nothing specific.Recommend one and send me their phone number Thanks so much.\nChunk 2: I am also looking for a place to dine.\nChunk 3: Can you help me?\nChunk 4: I don't care, just something good in the same area as Broughton House is.\nChunk 5: Try and stay in the moderate price range though The centre please.\nChunk 6: Could you tell me the phone number and food type Great, thank you.\nChunk 7: No that will be all for today, I appreciate all your help No thank you.", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: phone. Next, the goal is search; destination: dine. Next, the goal is request info. Next, the goal is modify constraint. Next, the topic is hotel; area: centre; price: moderate. Finally, the topic is restaurant.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant.. the goal is modify constraint.. requested information: phone.; destination: dine.; area: centre; price: moderate..", "trace": "C1 goal=request_info; requested_info+=phone. C2 goal=search; destination+=dine. C3 goal=request_info. C4 goal=modify_constraint. C5 domain=hotel; area+=centre; price+=moderate. C6 domain=restaurant. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Nothing specific.Recommend one and send me their phone number Thanks so much.", "streaming_reasoning": "Initially, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also looking for a place to dine.", "streaming_reasoning": "As more information arrives, the goal is search; destination: dine..", "trace": "goal=search; destination+=dine."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you help me?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't care, just something good in the same area as Broughton House is.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Try and stay in the moderate price range though The centre please.", "streaming_reasoning": "As more information arrives, the topic is hotel; area: centre; price: moderate..", "trace": "domain=hotel; area+=centre; price+=moderate."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could you tell me the phone number and food type Great, thank you.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No that will be all for today, I appreciate all your help No thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of recommendation. Key information: area is centre; price is moderate; destination is dine; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=recommendation, request_info, search, modify_constraint; area=centre; price=moderate; destination=dine; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002727", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a moderately priced guesthouse for the night.\nChunk 2: Yes, I'd really like to stay on the west end of the city Anything available there?\nChunk 3: Does that place have free wifi?\nChunk 4: Thank you, can you book me for 7 people and two nights, beginning on Sunday?\nChunk 5: May I also get a reference number?\nChunk 6: No thanks, that is all.", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=moderate; hotel_type+=guesthouse. C2 area+=west; destination+=stay on the west end of the city anything; acceptance=selected_option. C3 amenities+=wifi. C4 goal=booking; day+=sunday; party_size+=7 people. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking, request_info; area=west; price=moderate; party_size=7 people; amenities=wifi; destination=stay on the west end of the city anything; requested_info=reference_number; when=sunday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a moderately priced guesthouse for the night.\nChunk 2: Yes, I'd really like to stay on the west end of the city Anything available there?\nChunk 3: Does that place have free wifi?\nChunk 4: Thank you, can you book me for 7 people and two nights, beginning on Sunday?\nChunk 5: May I also get a reference number?\nChunk 6: No thanks, that is all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=moderate; hotel_type+=guesthouse. C2 area+=west; destination+=stay on the west end of the city anything; acceptance=selected_option. C3 amenities+=wifi. C4 goal=booking; day+=sunday; party_size+=7 people. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking, request_info; area=west; price=moderate; party_size=7 people; amenities=wifi; destination=stay on the west end of the city anything; requested_info=reference_number; when=sunday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a moderately priced guesthouse for the night.\nChunk 2: Yes, I'd really like to stay on the west end of the city Anything available there?\nChunk 3: Does that place have free wifi?\nChunk 4: Thank you, can you book me for 7 people and two nights, beginning on Sunday?\nChunk 5: May I also get a reference number?\nChunk 6: No thanks, that is all.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: moderate; hotel type: guesthouse. Next, area: west; destination: stay on the west end of the city anything; acceptance: selected_option. Next, amenities: wifi. Next, the goal is booking; day: sunday; party size: 7 people. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. price: moderate; hotel type: guesthouse.; area: west; destination: stay on the west end of the city anything; acceptance: selected_option.; amenities: wifi.; day: sunday; party size: 7 people.; requested information: reference_number..", "trace": "C1 domain=hotel; goal=search; price+=moderate; hotel_type+=guesthouse. C2 area+=west; destination+=stay on the west end of the city anything; acceptance=selected_option. C3 amenities+=wifi. C4 goal=booking; day+=sunday; party_size+=7 people. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a moderately priced guesthouse for the night.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: moderate; hotel type: guesthouse..", "trace": "domain=hotel; goal=search; price+=moderate; hotel_type+=guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I'd really like to stay on the west end of the city Anything available there?", "streaming_reasoning": "As more information arrives, area: west; destination: stay on the west end of the city anything; acceptance: selected_option..", "trace": "area+=west; destination+=stay on the west end of the city anything; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Does that place have free wifi?", "streaming_reasoning": "As more information arrives, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you, can you book me for 7 people and two nights, beginning on Sunday?", "streaming_reasoning": "As more information arrives, the goal is booking; day: sunday; party size: 7 people..", "trace": "goal=booking; day+=sunday; party_size+=7 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "May I also get a reference number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No thanks, that is all.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is west; price is moderate; party size is 7 people; amenities is wifi; destination is stay on the west end of the city anything; requested information is reference_number; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, request_info; area=west; price=moderate; party_size=7 people; amenities=wifi; destination=stay on the west end of the city anything; requested_info=reference_number; when=sunday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002728", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I got injured and I am looking for a hospital nearby.\nChunk 2: Thanks, what is the phone number and postcode?\nChunk 3: What is the address so I can find the hospital?\nChunk 4: Thanks, that's all I need Good bye.", "streaming_reasoning": "C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=phone, postcode. C3 requested_info+=address. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search, request_info; requested_info=phone, postcode, address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I got injured and I am looking for a hospital nearby.\nChunk 2: Thanks, what is the phone number and postcode?\nChunk 3: What is the address so I can find the hospital?\nChunk 4: Thanks, that's all I need Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=phone, postcode. C3 requested_info+=address. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; requested_info=phone, postcode, address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I got injured and I am looking for a hospital nearby.\nChunk 2: Thanks, what is the phone number and postcode?\nChunk 3: What is the address so I can find the hospital?\nChunk 4: Thanks, that's all I need Good bye.", "input_token_count": 44, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search. Next, the goal is request info; requested information: phone. Finally, requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital. the goal is request info. requested information: phone, address..", "trace": "C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=phone, postcode. C3 requested_info+=address. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I got injured and I am looking for a hospital nearby.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search..", "trace": "domain=hospital; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks, what is the phone number and postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the address so I can find the hospital?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks, that's all I need Good bye.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; requested_info=phone, postcode, address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002729", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you give me the address, please?\nChunk 2: Nah, not right now.\nChunk 3: I do need info on a train though.\nChunk 4: What's the schedule like on Sunday trains leaving cambridge?\nChunk 5: How about a train that will arrive by 12:15 heading to london liverpool street?\nChunk 6: Yes, that sounds perfect.\nChunk 7: Can you make me a booking for 1 person please Excellent, thank you!\nChunk 8: Thank you for your help.", "streaming_reasoning": "C1 goal=request_info; requested_info+=address. C2 goal=modify_constraint. C3 domain=train; goal=search. C4 day+=sunday. C5 goal=recommendation; time+=12:15; amenities+=pool; destination+=london liverpool street. C6 acceptance=selected_option. C7 goal=booking. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=request_info, search, recommendation, booking; amenities=pool; destination=london liverpool street; requested_info=address; when=sunday, 12:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Could you give me the address, please?\nChunk 2: Nah, not right now.\nChunk 3: I do need info on a train though.\nChunk 4: What's the schedule like on Sunday trains leaving cambridge?\nChunk 5: How about a train that will arrive by 12:15 heading to london liverpool street?\nChunk 6: Yes, that sounds perfect.\nChunk 7: Can you make me a booking for 1 person please Excellent, thank you!\nChunk 8: Thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address. C2 goal=modify_constraint. C3 domain=train; goal=search. C4 day+=sunday. C5 goal=recommendation; time+=12:15; amenities+=pool; destination+=london liverpool street. C6 acceptance=selected_option. C7 goal=booking. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search, recommendation, booking; amenities=pool; destination=london liverpool street; requested_info=address; when=sunday, 12:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you give me the address, please?\nChunk 2: Nah, not right now.\nChunk 3: I do need info on a train though.\nChunk 4: What's the schedule like on Sunday trains leaving cambridge?\nChunk 5: How about a train that will arrive by 12:15 heading to london liverpool street?\nChunk 6: Yes, that sounds perfect.\nChunk 7: Can you make me a booking for 1 person please Excellent, thank you!\nChunk 8: Thank you for your help.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the goal is modify constraint. Next, the topic is train; the goal is search. Next, day: sunday. Next, the goal is recommendation; time: 12:15; amenities: pool; destination: london liverpool street. Next, acceptance: selected_option. Finally, the goal is booking.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is booking.. requested information: address.; day: sunday.; time: 12:15; amenities: pool; destination: london liverpool street.; acceptance: selected_option..", "trace": "C1 goal=request_info; requested_info+=address. C2 goal=modify_constraint. C3 domain=train; goal=search. C4 day+=sunday. C5 goal=recommendation; time+=12:15; amenities+=pool; destination+=london liverpool street. C6 acceptance=selected_option. C7 goal=booking. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Could you give me the address, please?", "streaming_reasoning": "Initially, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Nah, not right now.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I do need info on a train though.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What's the schedule like on Sunday trains leaving cambridge?", "streaming_reasoning": "As more information arrives, day: sunday..", "trace": "day+=sunday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "How about a train that will arrive by 12:15 heading to london liverpool street?", "streaming_reasoning": "As more information arrives, the goal is recommendation; time: 12:15; amenities: pool; destination: london liverpool street..", "trace": "goal=recommendation; time+=12:15; amenities+=pool; destination+=london liverpool street."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, that sounds perfect.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can you make me a booking for 1 person please Excellent, thank you!", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: amenities is pool; destination is london liverpool street; requested information is address; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search, recommendation, booking; amenities=pool; destination=london liverpool street; requested_info=address; when=sunday, 12:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002730", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like more information on a hotel called cityroomz for my trip to Cambridge.\nChunk 2: No, I just need to know if they have free internet.\nChunk 3: I also would like information on a place to eat in the centre of town.\nChunk 4: Yes I was interested in European food in expensive price range.\nChunk 5: Yes please, I would like their phone number.\nChunk 6: That's all I needed today, thank you.", "streaming_reasoning": "C1 domain=hotel; hotel_type+=hotel; destination+=cambridge. C2 goal=search; amenities+=internet; destination+=know if they have free internet. C3 domain=restaurant; area+=centre; destination+=eat in the centre of town. C4 cuisine+=european; price+=expensive; acceptance=selected_option. C5 goal=request_info; requested_info+=phone; acceptance=selected_option. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=european; price=expensive; amenities=internet; destination=cambridge, know if they have free internet, eat in the centre of town; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like more information on a hotel called cityroomz for my trip to Cambridge.\nChunk 2: No, I just need to know if they have free internet.\nChunk 3: I also would like information on a place to eat in the centre of town.\nChunk 4: Yes I was interested in European food in expensive price range.\nChunk 5: Yes please, I would like their phone number.\nChunk 6: That's all I needed today, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=hotel; destination+=cambridge. C2 goal=search; amenities+=internet; destination+=know if they have free internet. C3 domain=restaurant; area+=centre; destination+=eat in the centre of town. C4 cuisine+=european; price+=expensive; acceptance=selected_option. C5 goal=request_info; requested_info+=phone; acceptance=selected_option. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=european; price=expensive; amenities=internet; destination=cambridge, know if they have free internet, eat in the centre of town; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like more information on a hotel called cityroomz for my trip to Cambridge.\nChunk 2: No, I just need to know if they have free internet.\nChunk 3: I also would like information on a place to eat in the centre of town.\nChunk 4: Yes I was interested in European food in expensive price range.\nChunk 5: Yes please, I would like their phone number.\nChunk 6: That's all I needed today, thank you.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: hotel; destination: cambridge. Next, the goal is search; amenities: internet; destination: know if they have free internet. Next, the topic is restaurant; area: centre; destination: eat in the centre of town. Next, cuisine: european; price: expensive; acceptance: selected_option. Finally, the goal is request info; requested information: phone; acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. hotel type: hotel; destination: cambridge., know if they have free internet., eat in the centre of town.; amenities: internet; area: centre; cuisine: european; price: expensive; acceptance: selected_option.; requested information: phone.", "trace": "C1 domain=hotel; hotel_type+=hotel; destination+=cambridge. C2 goal=search; amenities+=internet; destination+=know if they have free internet. C3 domain=restaurant; area+=centre; destination+=eat in the centre of town. C4 cuisine+=european; price+=expensive; acceptance=selected_option. C5 goal=request_info; requested_info+=phone; acceptance=selected_option. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like more information on a hotel called cityroomz for my trip to Cambridge.", "streaming_reasoning": "Initially, the topic is hotel; hotel type: hotel; destination: cambridge..", "trace": "domain=hotel; hotel_type+=hotel; destination+=cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, I just need to know if they have free internet.", "streaming_reasoning": "As more information arrives, the goal is search; amenities: internet; destination: know if they have free internet..", "trace": "goal=search; amenities+=internet; destination+=know if they have free internet."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also would like information on a place to eat in the centre of town.", "streaming_reasoning": "As more information arrives, the topic is restaurant; area: centre; destination: eat in the centre of town..", "trace": "domain=restaurant; area+=centre; destination+=eat in the centre of town."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes I was interested in European food in expensive price range.", "streaming_reasoning": "As more information arrives, cuisine: european; price: expensive; acceptance: selected_option..", "trace": "cuisine+=european; price+=expensive; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes please, I would like their phone number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=phone; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all I needed today, thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; cuisine is european; price is expensive; amenities is internet; destination is cambridge; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, request_info; area=centre; food=european; price=expensive; amenities=internet; destination=cambridge, know if they have free internet, eat in the centre of town; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002731", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a taxi to Shiraz Restaurant, leaving after 2:45.\nChunk 2: I would like to be picked up from addenbrookes hospital.\nChunk 3: Thanks, that's all I needed.", "streaming_reasoning": "C1 domain=taxi; time+=2:45; destination+=shiraz restaurant. C2 domain=hospital. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi, hospital; destination=shiraz restaurant; when=2:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a taxi to Shiraz Restaurant, leaving after 2:45.\nChunk 2: I would like to be picked up from addenbrookes hospital.\nChunk 3: Thanks, that's all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; time+=2:45; destination+=shiraz restaurant. C2 domain=hospital. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi, hospital; destination=shiraz restaurant; when=2:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a taxi to Shiraz Restaurant, leaving after 2:45.\nChunk 2: I would like to be picked up from addenbrookes hospital.\nChunk 3: Thanks, that's all I needed.", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; time: 2:45; destination: shiraz restaurant. Finally, the topic is hospital.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital.. time: 2:45; destination: shiraz restaurant..", "trace": "C1 domain=taxi; time+=2:45; destination+=shiraz restaurant. C2 domain=hospital. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a taxi to Shiraz Restaurant, leaving after 2:45.", "streaming_reasoning": "Initially, the topic is taxi; time: 2:45; destination: shiraz restaurant..", "trace": "domain=taxi; time+=2:45; destination+=shiraz restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to be picked up from addenbrookes hospital.", "streaming_reasoning": "As more information arrives, the topic is hospital..", "trace": "domain=hospital."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks, that's all I needed.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user's request falls within the restaurant domain. Key information: destination is shiraz restaurant; timing is 2:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi, hospital; destination=shiraz restaurant; when=2:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002732", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to leave on Tuesday after 18:15.\nChunk 2: Can I have an arrival time and price?\nChunk 3: Can I get the price for that?\nChunk 4: i'm also looking for places to go in the east.\nChunk 5: I'm open to anything.\nChunk 6: How about the boating?\nChunk 7: Can I have the postcode please?\nChunk 8: no thanks that is enough for today.", "streaming_reasoning": "C1 time+=18:15; day+=tuesday; destination+=leave on tuesday after 18:15. C2 goal=request_info. C3 [SKIP: repeated_information]. C4 goal=search; area+=east; destination+=go in the east. C5 destination+=anything. C6 goal=recommendation. C7 requested_info+=postcode. C8 [SKIP: thanks_only].", "deep_reasoning": "Need goal=request_info, search, recommendation; area=east; destination=leave on tuesday after 18:15, go in the east, anything; requested_info=postcode; when=tuesday, 18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like to leave on Tuesday after 18:15.\nChunk 2: Can I have an arrival time and price?\nChunk 3: Can I get the price for that?\nChunk 4: i'm also looking for places to go in the east.\nChunk 5: I'm open to anything.\nChunk 6: How about the boating?\nChunk 7: Can I have the postcode please?\nChunk 8: no thanks that is enough for today."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=18:15; day+=tuesday; destination+=leave on tuesday after 18:15. C2 goal=request_info. C3 [SKIP: repeated_information]. C4 goal=search; area+=east; destination+=go in the east. C5 destination+=anything. C6 goal=recommendation. C7 requested_info+=postcode. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=request_info, search, recommendation; area=east; destination=leave on tuesday after 18:15, go in the east, anything; requested_info=postcode; when=tuesday, 18:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to leave on Tuesday after 18:15.\nChunk 2: Can I have an arrival time and price?\nChunk 3: Can I get the price for that?\nChunk 4: i'm also looking for places to go in the east.\nChunk 5: I'm open to anything.\nChunk 6: How about the boating?\nChunk 7: Can I have the postcode please?\nChunk 8: no thanks that is enough for today.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 18:15; day: tuesday; destination: leave on tuesday after 18:15. Next, the goal is request info. Next, the goal is search; area: east; destination: go in the east. Next, destination: anything. Next, the goal is recommendation. Finally, requested information: postcode.  Some chunks were skipped because they contained repeated_information or thanks_only. In summary, the goal is recommendation.. time: 18:15; day: tuesday; destination: leave on tuesday after 18:15., go in the east., anything.; area: east; requested information: postcode..", "trace": "C1 time+=18:15; day+=tuesday; destination+=leave on tuesday after 18:15. C2 goal=request_info. C3 [SKIP: repeated_information]. C4 goal=search; area+=east; destination+=go in the east. C5 destination+=anything. C6 goal=recommendation. C7 requested_info+=postcode. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like to leave on Tuesday after 18:15.", "streaming_reasoning": "Initially, time: 18:15; day: tuesday; destination: leave on tuesday after 18:15..", "trace": "time+=18:15; day+=tuesday; destination+=leave on tuesday after 18:15."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I have an arrival time and price?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I get the price for that?", "streaming_reasoning": "The content at C3 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "i'm also looking for places to go in the east.", "streaming_reasoning": "As more information arrives, the goal is search; area: east; destination: go in the east..", "trace": "goal=search; area+=east; destination+=go in the east."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm open to anything.", "streaming_reasoning": "As more information arrives, destination: anything..", "trace": "destination+=anything."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "How about the boating?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can I have the postcode please?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "no thanks that is enough for today.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=request_info, search, recommendation; area=east; destination=leave on tuesday after 18:15, go in the east, anything; requested_info=postcode; when=tuesday, 18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002733", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No but can I make a booking for 8 people at 18:30 on sunday.\nChunk 2: Thank you so much for your help.\nChunk 3: Yes, get me some more information on magdalene college please.\nChunk 4: What is their postcode?\nChunk 5: Can I get a taxi from Magdalene to Hakka, please?\nChunk 6: I need to make sure I get there for that reservation Great!\nChunk 7: Thanks for all your help today Goodbye.", "streaming_reasoning": "C1 goal=request_info; time+=8, 18:30; day+=sunday; party_size+=8 people. C2 [SKIP: thanks_only]. C3 domain=attraction; goal=search; goal=confirm_booking. C4 requested_info+=postcode. C5 domain=taxi; destination+=hakka; departure+=magdalene. C6 intent=context_update. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, taxi; goal=booking, request_info, search; party_size=8 people; destination=hakka; departure=magdalene; requested_info=postcode; when=sunday, 8, 18:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No but can I make a booking for 8 people at 18:30 on sunday.\nChunk 2: Thank you so much for your help.\nChunk 3: Yes, get me some more information on magdalene college please.\nChunk 4: What is their postcode?\nChunk 5: Can I get a taxi from Magdalene to Hakka, please?\nChunk 6: I need to make sure I get there for that reservation Great!\nChunk 7: Thanks for all your help today Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; time+=8, 18:30; day+=sunday; party_size+=8 people. C2 [SKIP: thanks_only]. C3 domain=attraction; goal=search; goal=confirm_booking. C4 requested_info+=postcode. C5 domain=taxi; destination+=hakka; departure+=magdalene. C6 intent=context_update. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, taxi; goal=booking, request_info, search; party_size=8 people; destination=hakka; departure=magdalene; requested_info=postcode; when=sunday, 8, 18:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No but can I make a booking for 8 people at 18:30 on sunday.\nChunk 2: Thank you so much for your help.\nChunk 3: Yes, get me some more information on magdalene college please.\nChunk 4: What is their postcode?\nChunk 5: Can I get a taxi from Magdalene to Hakka, please?\nChunk 6: I need to make sure I get there for that reservation Great!\nChunk 7: Thanks for all your help today Goodbye.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; time: 8; day: sunday; party size: 8 people. Next, the topic is attraction; the goal is confirm booking. Next, requested information: postcode. Next, the topic is taxi; destination: hakka; departure point: magdalene. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is taxi. the goal is confirm booking.. time: 8; day: sunday; party size: 8 people.; requested information: postcode.; destination: hakka; departure point: magdalene.; intent: context_update..", "trace": "C1 goal=request_info; time+=8, 18:30; day+=sunday; party_size+=8 people. C2 [SKIP: thanks_only]. C3 domain=attraction; goal=search; goal=confirm_booking. C4 requested_info+=postcode. C5 domain=taxi; destination+=hakka; departure+=magdalene. C6 intent=context_update. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No but can I make a booking for 8 people at 18:30 on sunday.", "streaming_reasoning": "Initially, the goal is request info; time: 8; day: sunday; party size: 8 people..", "trace": "goal=request_info; time+=8, 18:30; day+=sunday; party_size+=8 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thank you so much for your help.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, get me some more information on magdalene college please.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is confirm booking..", "trace": "domain=attraction; goal=search; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is their postcode?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get a taxi from Magdalene to Hakka, please?", "streaming_reasoning": "As more information arrives, the topic is taxi; destination: hakka; departure point: magdalene..", "trace": "domain=taxi; destination+=hakka; departure+=magdalene."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need to make sure I get there for that reservation Great!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks for all your help today Goodbye.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of booking. Key information: party size is 8 people; destination is hakka; departure point is magdalene; requested information is postcode; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, taxi; goal=booking, request_info, search; party_size=8 people; destination=hakka; departure=magdalene; requested_info=postcode; when=sunday, 8, 18:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002734", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would prefer it in the centre area.\nChunk 2: Yes modern european food No preference.\nChunk 3: Just book a table for 5 on Thursday at 20:15.\nChunk 4: Thanks!\nChunk 5: I need the reference number please.\nChunk 6: Perfect, that's all I need today.\nChunk 7: Have a great day.\nChunk 8: Have a nice day.", "streaming_reasoning": "C1 area+=centre. C2 domain=restaurant; cuisine+=european; acceptance=selected_option. C3 goal=booking; time+=5, 20:15; day+=thursday. C4 [SKIP: thanks_only]. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only]. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=booking, search, request_info; area=centre; food=european; requested_info=reference_number; when=thursday, 5, 20:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would prefer it in the centre area.\nChunk 2: Yes modern european food No preference.\nChunk 3: Just book a table for 5 on Thursday at 20:15.\nChunk 4: Thanks!\nChunk 5: I need the reference number please.\nChunk 6: Perfect, that's all I need today.\nChunk 7: Have a great day.\nChunk 8: Have a nice day."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre. C2 domain=restaurant; cuisine+=european; acceptance=selected_option. C3 goal=booking; time+=5, 20:15; day+=thursday. C4 [SKIP: thanks_only]. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only]. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=booking, search, request_info; area=centre; food=european; requested_info=reference_number; when=thursday, 5, 20:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would prefer it in the centre area.\nChunk 2: Yes modern european food No preference.\nChunk 3: Just book a table for 5 on Thursday at 20:15.\nChunk 4: Thanks!\nChunk 5: I need the reference number please.\nChunk 6: Perfect, that's all I need today.\nChunk 7: Have a great day.\nChunk 8: Have a nice day.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: centre. Next, the topic is restaurant; cuisine: european; acceptance: selected_option. Next, the goal is booking; time: 5; day: thursday. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: centre.; cuisine: european; acceptance: selected_option.; time: 5; day: thursday.; requested information: reference_number..", "trace": "C1 area+=centre. C2 domain=restaurant; cuisine+=european; acceptance=selected_option. C3 goal=booking; time+=5, 20:15; day+=thursday. C4 [SKIP: thanks_only]. C5 goal=request_info; requested_info+=reference_number. C6 [SKIP: closing_only]. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would prefer it in the centre area.", "streaming_reasoning": "Initially, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes modern european food No preference.", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: european; acceptance: selected_option..", "trace": "domain=restaurant; cuisine+=european; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Just book a table for 5 on Thursday at 20:15.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 5; day: thursday..", "trace": "goal=booking; time+=5, 20:15; day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks!", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need the reference number please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Perfect, that's all I need today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Have a nice day.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: area is centre; cuisine is european; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=booking, search, request_info; area=centre; food=european; requested_info=reference_number; when=thursday, 5, 20:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003408", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Then what about spring?\nChunk 2: Spring is warm and short in Beijing.\nChunk 3: It must be cold in the winter, though You got it.\nChunk 4: Oh, by the way, it may be really cool in the evening around this time of the year.\nChunk 5: Don't forget to put on more clothes, or you might catch a cold.\nChunk 6: Thanks for reminding me.", "streaming_reasoning": "C1 question=true. C2 casual_comment=spring, warm. C3 casual_comment=must, cold. C4 casual_comment=way, may. C5 casual_comment=don't, forget. C6 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Then what about spring?\nChunk 2: Spring is warm and short in Beijing.\nChunk 3: It must be cold in the winter, though You got it.\nChunk 4: Oh, by the way, it may be really cool in the evening around this time of the year.\nChunk 5: Don't forget to put on more clothes, or you might catch a cold.\nChunk 6: Thanks for reminding me."}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 casual_comment=spring, warm. C3 casual_comment=must, cold. C4 casual_comment=way, may. C5 casual_comment=don't, forget. C6 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Then what about spring?\nChunk 2: Spring is warm and short in Beijing.\nChunk 3: It must be cold in the winter, though You got it.\nChunk 4: Oh, by the way, it may be really cool in the evening around this time of the year.\nChunk 5: Don't forget to put on more clothes, or you might catch a cold.\nChunk 6: Thanks for reminding me.", "input_token_count": 69, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on spring. Next, the user comments on must. Next, the user comments on way. Finally, the user comments on don't.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 question=true. C2 casual_comment=spring, warm. C3 casual_comment=must, cold. C4 casual_comment=way, may. C5 casual_comment=don't, forget. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Then what about spring?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Spring is warm and short in Beijing.", "streaming_reasoning": "As more information arrives, the user comments on spring.", "trace": "casual_comment=spring, warm."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It must be cold in the winter, though You got it.", "streaming_reasoning": "As more information arrives, the user comments on must.", "trace": "casual_comment=must, cold."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Oh, by the way, it may be really cool in the evening around this time of the year.", "streaming_reasoning": "As more information arrives, the user comments on way.", "trace": "casual_comment=way, may."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Don't forget to put on more clothes, or you might catch a cold.", "streaming_reasoning": "As more information arrives, the user comments on don't.", "trace": "casual_comment=don't, forget."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks for reminding me.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002735", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: yeah, i need eight tickets.\nChunk 2: I also need a guesthouse located in the north.\nChunk 3: Are there any with a star of 4?\nChunk 4: I'd like free parking as well if that is available.\nChunk 5: Yes info on the cheap price range.\nChunk 6: Thanks, for now I just need their postcode and whether or not they have free internet Yes, that's all.\nChunk 7: Thanks!", "streaming_reasoning": "C1 goal=search. C2 domain=hotel; area+=north; hotel_type+=guesthouse. C3 goal=request_info. C4 amenities+=parking, free parking. C5 price+=cheap; acceptance=selected_option. C6 goal=request_info; amenities+=internet; requested_info+=postcode; acceptance=selected_option. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info; area=north; price=cheap; amenities=parking, free parking, internet; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: yeah, i need eight tickets.\nChunk 2: I also need a guesthouse located in the north.\nChunk 3: Are there any with a star of 4?\nChunk 4: I'd like free parking as well if that is available.\nChunk 5: Yes info on the cheap price range.\nChunk 6: Thanks, for now I just need their postcode and whether or not they have free internet Yes, that's all.\nChunk 7: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 domain=hotel; area+=north; hotel_type+=guesthouse. C3 goal=request_info. C4 amenities+=parking, free parking. C5 price+=cheap; acceptance=selected_option. C6 goal=request_info; amenities+=internet; requested_info+=postcode; acceptance=selected_option. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info; area=north; price=cheap; amenities=parking, free parking, internet; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: yeah, i need eight tickets.\nChunk 2: I also need a guesthouse located in the north.\nChunk 3: Are there any with a star of 4?\nChunk 4: I'd like free parking as well if that is available.\nChunk 5: Yes info on the cheap price range.\nChunk 6: Thanks, for now I just need their postcode and whether or not they have free internet Yes, that's all.\nChunk 7: Thanks!", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, the topic is hotel; area: north; hotel type: guesthouse. Next, the goal is request info. Next, amenities: parking. Next, price: cheap; acceptance: selected_option. Finally, the goal is request info; amenities: internet; requested information: postcode; acceptance: selected_option.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is request info. area: north; hotel type: guesthouse.; amenities: parking, internet; price: cheap; acceptance: selected_option.; requested information: postcode.", "trace": "C1 goal=search. C2 domain=hotel; area+=north; hotel_type+=guesthouse. C3 goal=request_info. C4 amenities+=parking, free parking. C5 price+=cheap; acceptance=selected_option. C6 goal=request_info; amenities+=internet; requested_info+=postcode; acceptance=selected_option. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "yeah, i need eight tickets.", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need a guesthouse located in the north.", "streaming_reasoning": "As more information arrives, the topic is hotel; area: north; hotel type: guesthouse..", "trace": "domain=hotel; area+=north; hotel_type+=guesthouse."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Are there any with a star of 4?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd like free parking as well if that is available.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes info on the cheap price range.", "streaming_reasoning": "As more information arrives, price: cheap; acceptance: selected_option..", "trace": "price+=cheap; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks, for now I just need their postcode and whether or not they have free internet Yes, that's all.", "streaming_reasoning": "As more information arrives, the goal is request info; amenities: internet; requested information: postcode; acceptance: selected_option..", "trace": "goal=request_info; amenities+=internet; requested_info+=postcode; acceptance=selected_option."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; price is cheap; amenities is parking; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info; area=north; price=cheap; amenities=parking, free parking, internet; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003413", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I'd like to know more about it.\nChunk 3: Can you come to my office this afternoon at 3 o'clock?\nChunk 4: OK.\nChunk 5: I will be there.\nChunk 6: Thank you for calling.Goodbye.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 preference=true. C3 question=true. C4 [SKIP: backchannel_only]. C5 casual_comment=will. C6 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I'd like to know more about it.\nChunk 3: Can you come to my office this afternoon at 3 o'clock?\nChunk 4: OK.\nChunk 5: I will be there.\nChunk 6: Thank you for calling.Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 preference=true. C3 question=true. C4 [SKIP: backchannel_only]. C5 casual_comment=will. C6 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I'd like to know more about it.\nChunk 3: Can you come to my office this afternoon at 3 o'clock?\nChunk 4: OK.\nChunk 5: I will be there.\nChunk 6: Thank you for calling.Goodbye.", "input_token_count": 41, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, preference: true. Next, the input provides additional context about question=true. Finally, the user comments on will.  Some chunks were skipped because they contained acknowledgement_only or backchannel_only or thanks_only. In summary, preference: true..", "trace": "C1 [SKIP: acknowledgement_only]. C2 preference=true. C3 question=true. C4 [SKIP: backchannel_only]. C5 casual_comment=will. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to know more about it.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you come to my office this afternoon at 3 o'clock?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "OK.", "streaming_reasoning": "The content at C4 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will be there.", "streaming_reasoning": "As more information arrives, the user comments on will..", "trace": "casual_comment=will."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for calling.Goodbye.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002736", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any colleges in the west of town that I could go to?\nChunk 2: Thanks.\nChunk 3: What is the address to Churchhill College thank you!\nChunk 4: I also am looking for carolina bed and breakfast.\nChunk 5: No thanks, just gathering information.\nChunk 6: Can I get the hotel type, phone number and postal code please?\nChunk 7: Thank you for the info.\nChunk 8: No that will be all thank you.", "streaming_reasoning": "C1 area+=west. C2 [SKIP: thanks_only]. C3 domain=attraction; goal=request_info; destination+=churchhill college thank you!; requested_info+=address. C4 domain=restaurant; goal=search; amenities+=breakfast. C5 [SKIP: thanks_only]. C6 domain=hotel; hotel_type+=hotel; requested_info+=phone, postcode. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, restaurant, hotel; goal=request_info, search; area=west; amenities=breakfast; destination=churchhill college thank you!; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Are there any colleges in the west of town that I could go to?\nChunk 2: Thanks.\nChunk 3: What is the address to Churchhill College thank you!\nChunk 4: I also am looking for carolina bed and breakfast.\nChunk 5: No thanks, just gathering information.\nChunk 6: Can I get the hotel type, phone number and postal code please?\nChunk 7: Thank you for the info.\nChunk 8: No that will be all thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=west. C2 [SKIP: thanks_only]. C3 domain=attraction; goal=request_info; destination+=churchhill college thank you!; requested_info+=address. C4 domain=restaurant; goal=search; amenities+=breakfast. C5 [SKIP: thanks_only]. C6 domain=hotel; hotel_type+=hotel; requested_info+=phone, postcode. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, restaurant, hotel; goal=request_info, search; area=west; amenities=breakfast; destination=churchhill college thank you!; requested_info=address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are there any colleges in the west of town that I could go to?\nChunk 2: Thanks.\nChunk 3: What is the address to Churchhill College thank you!\nChunk 4: I also am looking for carolina bed and breakfast.\nChunk 5: No thanks, just gathering information.\nChunk 6: Can I get the hotel type, phone number and postal code please?\nChunk 7: Thank you for the info.\nChunk 8: No that will be all thank you.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: west. Next, the topic is attraction; the goal is request info; destination: churchhill college thank you!; requested information: address. Next, the topic is restaurant; the goal is search; amenities: breakfast. Finally, the topic is hotel; hotel type: hotel; requested information: phone.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is search. area: west.; destination: churchhill college thank you!; requested information: address., phone; amenities: breakfast.; hotel type: hotel.", "trace": "C1 area+=west. C2 [SKIP: thanks_only]. C3 domain=attraction; goal=request_info; destination+=churchhill college thank you!; requested_info+=address. C4 domain=restaurant; goal=search; amenities+=breakfast. C5 [SKIP: thanks_only]. C6 domain=hotel; hotel_type+=hotel; requested_info+=phone, postcode. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Are there any colleges in the west of town that I could go to?", "streaming_reasoning": "Initially, area: west..", "trace": "area+=west."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the address to Churchhill College thank you!", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is request info; destination: churchhill college thank you!; requested information: address..", "trace": "domain=attraction; goal=request_info; destination+=churchhill college thank you!; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also am looking for carolina bed and breakfast.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; amenities: breakfast..", "trace": "domain=restaurant; goal=search; amenities+=breakfast."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No thanks, just gathering information.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I get the hotel type, phone number and postal code please?", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; requested information: phone.", "trace": "domain=hotel; hotel_type+=hotel; requested_info+=phone, postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for the info.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No that will be all thank you.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: area is west; amenities is breakfast; destination is churchhill college thank you!; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant, hotel; goal=request_info, search; area=west; amenities=breakfast; destination=churchhill college thank you!; requested_info=address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002737", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can I get the address for the cinema?\nChunk 2: I need help with train.\nChunk 3: I also need the address.\nChunk 4: I need to go on Sunday, sometime after 16:00.\nChunk 5: I take the first one at 17:59.\nChunk 6: May I have the price and train ID?\nChunk 7: Yes I would like you to book a ticket and may I have the reference number please.\nChunk 8: Thank you for your help, that is everything I needed.", "streaming_reasoning": "C1 goal=request_info; requested_info+=address. C2 domain=train; goal=search. C3 [SKIP: repeated_information]. C4 time+=16:00; day+=sunday; destination+=go on sunday. C5 time+=17:59. C6 goal=request_info. C7 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=request_info, search, booking, confirm_booking; destination=go on sunday; requested_info=address, reference_number; when=sunday, 16:00, 17:59; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can I get the address for the cinema?\nChunk 2: I need help with train.\nChunk 3: I also need the address.\nChunk 4: I need to go on Sunday, sometime after 16:00.\nChunk 5: I take the first one at 17:59.\nChunk 6: May I have the price and train ID?\nChunk 7: Yes I would like you to book a ticket and may I have the reference number please.\nChunk 8: Thank you for your help, that is everything I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address. C2 domain=train; goal=search. C3 [SKIP: repeated_information]. C4 time+=16:00; day+=sunday; destination+=go on sunday. C5 time+=17:59. C6 goal=request_info. C7 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search, booking, confirm_booking; destination=go on sunday; requested_info=address, reference_number; when=sunday, 16:00, 17:59; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can I get the address for the cinema?\nChunk 2: I need help with train.\nChunk 3: I also need the address.\nChunk 4: I need to go on Sunday, sometime after 16:00.\nChunk 5: I take the first one at 17:59.\nChunk 6: May I have the price and train ID?\nChunk 7: Yes I would like you to book a ticket and may I have the reference number please.\nChunk 8: Thank you for your help, that is everything I needed.", "input_token_count": 87, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the topic is train; the goal is search. Next, time: 16:00; day: sunday; destination: go on sunday. Next, time: 17:59. Next, the goal is request info. Finally, the goal is confirm booking.; requested information: reference_number.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is train. the goal is confirm booking.. requested information: address., reference_number; time: 16:00, 17:59.; day: sunday; destination: go on sunday..", "trace": "C1 goal=request_info; requested_info+=address. C2 domain=train; goal=search. C3 [SKIP: repeated_information]. C4 time+=16:00; day+=sunday; destination+=go on sunday. C5 time+=17:59. C6 goal=request_info. C7 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can I get the address for the cinema?", "streaming_reasoning": "Initially, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the address.", "streaming_reasoning": "The content at C3 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to go on Sunday, sometime after 16:00.", "streaming_reasoning": "As more information arrives, time: 16:00; day: sunday; destination: go on sunday..", "trace": "time+=16:00; day+=sunday; destination+=go on sunday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I take the first one at 17:59.", "streaming_reasoning": "As more information arrives, time: 17:59..", "trace": "time+=17:59."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "May I have the price and train ID?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes I would like you to book a ticket and may I have the reference number please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for your help, that is everything I needed.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: destination is go on sunday; requested information is address; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search, booking, confirm_booking; destination=go on sunday; requested_info=address, reference_number; when=sunday, 16:00, 17:59; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002738", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you book me a table for 6 at 15:00 on sunday?\nChunk 2: Can you see if there is a table for 6 at 14:00 on Sunday, then?\nChunk 3: Thank you, can you please help me find a train on Sunday that will arrive in Cambridge on time for my reservation?\nChunk 4: I actually need a train from Leicester to Cambridge on Sunday that arrives by 10:45.\nChunk 5: Yes, that would work.\nChunk 6: Can you go ahead and book me 6 tickets and provide me with the reference number, please?\nChunk 7: Awesome, you have been very helpful.\nChunk 8: That's all I need.", "streaming_reasoning": "C1 goal=booking; time+=6, 15:00; day+=sunday. C2 time+=14:00. C3 domain=train; goal=search. C4 time+=10:45; destination+=cambridge; departure+=leicester. C5 goal=confirm_booking. C6 goal=request_info; requested_info+=reference_number. C7 intent=context_update. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=booking, search, request_info; destination=cambridge; departure=leicester; requested_info=reference_number; when=sunday, 6, 15:00, 14:00, 10:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you book me a table for 6 at 15:00 on sunday?\nChunk 2: Can you see if there is a table for 6 at 14:00 on Sunday, then?\nChunk 3: Thank you, can you please help me find a train on Sunday that will arrive in Cambridge on time for my reservation?\nChunk 4: I actually need a train from Leicester to Cambridge on Sunday that arrives by 10:45.\nChunk 5: Yes, that would work.\nChunk 6: Can you go ahead and book me 6 tickets and provide me with the reference number, please?\nChunk 7: Awesome, you have been very helpful.\nChunk 8: That's all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=6, 15:00; day+=sunday. C2 time+=14:00. C3 domain=train; goal=search. C4 time+=10:45; destination+=cambridge; departure+=leicester. C5 goal=confirm_booking. C6 goal=request_info; requested_info+=reference_number. C7 intent=context_update. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=booking, search, request_info; destination=cambridge; departure=leicester; requested_info=reference_number; when=sunday, 6, 15:00, 14:00, 10:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you book me a table for 6 at 15:00 on sunday?\nChunk 2: Can you see if there is a table for 6 at 14:00 on Sunday, then?\nChunk 3: Thank you, can you please help me find a train on Sunday that will arrive in Cambridge on time for my reservation?\nChunk 4: I actually need a train from Leicester to Cambridge on Sunday that arrives by 10:45.\nChunk 5: Yes, that would work.\nChunk 6: Can you go ahead and book me 6 tickets and provide me with the reference number, please?\nChunk 7: Awesome, you have been very helpful.\nChunk 8: That's all I need.", "input_token_count": 114, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 6; day: sunday. Next, time: 14:00. Next, the topic is train; the goal is search. Next, time: 10:45; destination: cambridge; departure point: leicester. Next, the goal is confirm booking. Next, the goal is request info; requested information: reference_number. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. time: 6, 14:00., 10:45; day: sunday.; destination: cambridge; departure point: leicester.; requested information: reference_number.; intent: context_update..", "trace": "C1 goal=booking; time+=6, 15:00; day+=sunday. C2 time+=14:00. C3 domain=train; goal=search. C4 time+=10:45; destination+=cambridge; departure+=leicester. C5 goal=confirm_booking. C6 goal=request_info; requested_info+=reference_number. C7 intent=context_update. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you book me a table for 6 at 15:00 on sunday?", "streaming_reasoning": "Initially, the goal is booking; time: 6; day: sunday..", "trace": "goal=booking; time+=6, 15:00; day+=sunday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you see if there is a table for 6 at 14:00 on Sunday, then?", "streaming_reasoning": "As more information arrives, time: 14:00..", "trace": "time+=14:00."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you, can you please help me find a train on Sunday that will arrive in Cambridge on time for my reservation?", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I actually need a train from Leicester to Cambridge on Sunday that arrives by 10:45.", "streaming_reasoning": "As more information arrives, time: 10:45; destination: cambridge; departure point: leicester..", "trace": "time+=10:45; destination+=cambridge; departure+=leicester."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, that would work.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you go ahead and book me 6 tickets and provide me with the reference number, please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Awesome, you have been very helpful.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's all I need.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: destination is cambridge; departure point is leicester; requested information is reference_number; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, search, request_info; destination=cambridge; departure=leicester; requested_info=reference_number; when=sunday, 6, 15:00, 14:00, 10:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002739", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you help me find an expensive asian oriental restaurant?\nChunk 2: Let's go with the centre.\nChunk 3: I need a reservation for 2 at 13:30 on Thursday.\nChunk 4: I need a different restaurant in the same area and price range please.\nChunk 5: Does the HK Fusion Chinese restaurant have availability on Thursday at 13:30?\nChunk 6: That is all, thanks, bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=expensive. C2 area+=centre. C3 goal=booking; time+=2, 13:30; day+=thursday. C4 goal=modify_constraint; requested_info+=price. C5 cuisine+=chinese. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, compare_alternative, modify_constraint; area=centre; food=chinese; price=expensive; requested_info=price; when=thursday, 2, 13:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Could you help me find an expensive asian oriental restaurant?\nChunk 2: Let's go with the centre.\nChunk 3: I need a reservation for 2 at 13:30 on Thursday.\nChunk 4: I need a different restaurant in the same area and price range please.\nChunk 5: Does the HK Fusion Chinese restaurant have availability on Thursday at 13:30?\nChunk 6: That is all, thanks, bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=expensive. C2 area+=centre. C3 goal=booking; time+=2, 13:30; day+=thursday. C4 goal=modify_constraint; requested_info+=price. C5 cuisine+=chinese. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, compare_alternative, modify_constraint; area=centre; food=chinese; price=expensive; requested_info=price; when=thursday, 2, 13:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you help me find an expensive asian oriental restaurant?\nChunk 2: Let's go with the centre.\nChunk 3: I need a reservation for 2 at 13:30 on Thursday.\nChunk 4: I need a different restaurant in the same area and price range please.\nChunk 5: Does the HK Fusion Chinese restaurant have availability on Thursday at 13:30?\nChunk 6: That is all, thanks, bye.", "input_token_count": 69, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: expensive. Next, area: centre. Next, the goal is booking; time: 2; day: thursday. Next, the goal is modify constraint; requested information: price. Finally, cuisine: chinese.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is modify constraint. price: expensive.; area: centre.; time: 2; day: thursday.; requested information: price.; cuisine: chinese..", "trace": "C1 domain=restaurant; goal=search; price+=expensive. C2 area+=centre. C3 goal=booking; time+=2, 13:30; day+=thursday. C4 goal=modify_constraint; requested_info+=price. C5 cuisine+=chinese. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Could you help me find an expensive asian oriental restaurant?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: expensive..", "trace": "domain=restaurant; goal=search; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Let's go with the centre.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need a reservation for 2 at 13:30 on Thursday.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 2; day: thursday..", "trace": "goal=booking; time+=2, 13:30; day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need a different restaurant in the same area and price range please.", "streaming_reasoning": "As more information arrives, the goal is modify constraint; requested information: price..", "trace": "goal=modify_constraint; requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Does the HK Fusion Chinese restaurant have availability on Thursday at 13:30?", "streaming_reasoning": "As more information arrives, cuisine: chinese..", "trace": "cuisine+=chinese."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all, thanks, bye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; price is expensive; requested information is price; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, compare_alternative, modify_constraint; area=centre; food=chinese; price=expensive; requested_info=price; when=thursday, 2, 13:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002740", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Oh wait.\nChunk 2: I really want to find a museum.\nChunk 3: What do you suggest?\nChunk 4: I don't know the town, so I don't have any idea where to go No, thanks!\nChunk 5: But will you please find me an expensive restaurant in the Centre part of town?\nChunk 6: an expensive British restaurant, what would be one you would recommend?\nChunk 7: Sounds nice, I will book for 2 people at 14:30 on Wednesday No thank you.", "streaming_reasoning": "C1 [SKIP: low_information]. C2 domain=attraction; goal=search; destination+=find a museum. C3 goal=recommendation. C4 destination+=go no. C5 domain=restaurant; area+=centre; price+=expensive. C6 cuisine+=british. C7 goal=booking; time+=2, 14:30; day+=wednesday; party_size+=2 people.", "deep_reasoning": "Need domain=attraction, restaurant; goal=search, recommendation, booking; area=centre; food=british; price=expensive; party_size=2 people; destination=find a museum, go no; when=wednesday, 2, 14:30.", "answer": "Got it. I will use attraction, restaurant, centre, british, expensive, 2 people, wednesday, 2, 14:30 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Oh wait.\nChunk 2: I really want to find a museum.\nChunk 3: What do you suggest?\nChunk 4: I don't know the town, so I don't have any idea where to go No, thanks!\nChunk 5: But will you please find me an expensive restaurant in the Centre part of town?\nChunk 6: an expensive British restaurant, what would be one you would recommend?\nChunk 7: Sounds nice, I will book for 2 people at 14:30 on Wednesday No thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: low_information]. C2 domain=attraction; goal=search; destination+=find a museum. C3 goal=recommendation. C4 destination+=go no. C5 domain=restaurant; area+=centre; price+=expensive. C6 cuisine+=british. C7 goal=booking; time+=2, 14:30; day+=wednesday; party_size+=2 people.\n\nDeep reasoning: Need domain=attraction, restaurant; goal=search, recommendation, booking; area=centre; food=british; price=expensive; party_size=2 people; destination=find a museum, go no; when=wednesday, 2, 14:30.\n\nAnswer: Got it. I will use attraction, restaurant, centre, british, expensive, 2 people, wednesday, 2, 14:30 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Oh wait.\nChunk 2: I really want to find a museum.\nChunk 3: What do you suggest?\nChunk 4: I don't know the town, so I don't have any idea where to go No, thanks!\nChunk 5: But will you please find me an expensive restaurant in the Centre part of town?\nChunk 6: an expensive British restaurant, what would be one you would recommend?\nChunk 7: Sounds nice, I will book for 2 people at 14:30 on Wednesday No thank you.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; destination: find a museum. Next, the goal is recommendation. Next, destination: go no. Next, the topic is restaurant; area: centre; price: expensive. Next, cuisine: british. Finally, the goal is booking; time: 2; day: wednesday; party size: 2 people.  Some chunks were skipped because they contained low_information. In summary, The overall topic is restaurant. the goal is booking. destination: find a museum., go no.; area: centre; price: expensive.; cuisine: british.; time: 2; day: wednesday; party size: 2 people..", "trace": "C1 [SKIP: low_information]. C2 domain=attraction; goal=search; destination+=find a museum. C3 goal=recommendation. C4 destination+=go no. C5 domain=restaurant; area+=centre; price+=expensive. C6 cuisine+=british. C7 goal=booking; time+=2, 14:30; day+=wednesday; party_size+=2 people.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Oh wait.", "streaming_reasoning": "The content at C1 was skipped (low_information).", "trace": "[SKIP: low_information]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I really want to find a museum.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is search; destination: find a museum..", "trace": "domain=attraction; goal=search; destination+=find a museum."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What do you suggest?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't know the town, so I don't have any idea where to go No, thanks!", "streaming_reasoning": "As more information arrives, destination: go no..", "trace": "destination+=go no."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "But will you please find me an expensive restaurant in the Centre part of town?", "streaming_reasoning": "As more information arrives, the topic is restaurant; area: centre; price: expensive..", "trace": "domain=restaurant; area+=centre; price+=expensive."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "an expensive British restaurant, what would be one you would recommend?", "streaming_reasoning": "As more information arrives, cuisine: british..", "trace": "cuisine+=british."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Sounds nice, I will book for 2 people at 14:30 on Wednesday No thank you.", "streaming_reasoning": "Finally, the goal is booking; time: 2; day: wednesday; party size: 2 people..", "trace": "goal=booking; time+=2, 14:30; day+=wednesday; party_size+=2 people."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; cuisine is british; price is expensive; party size is 2 people; destination is find a museum; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use attraction, restaurant, centre, british, expensive, 2 people, wednesday, 2, 14:30 and move the task forward.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=search, recommendation, booking; area=centre; food=british; price=expensive; party_size=2 people; destination=find a museum, go no; when=wednesday, 2, 14:30."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002741", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: That would be fine.\nChunk 3: Do you need to book it?\nChunk 4: Actually, can you please book a taxi from the boats to my hotel.\nChunk 5: Thank you SO MUCH, I know I was confusing.\nChunk 6: Can you just tell me the entrance fee for the boats?\nChunk 7: That is all I still need to know.\nChunk 8: Yes, could I get the postcode for Camboats?\nChunk 9: Will you tell me the car type?\nChunk 10: Thank you so much!", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 intent=context_update. C3 goal=booking. C4 domain=taxi; hotel_type+=hotel; destination+=my hotel; departure+=the boats. C5 [SKIP: thanks_only]. C6 goal=request_info; requested_info+=entrance_fee. C7 [SKIP: closing_only]. C8 requested_info+=postcode; goal=confirm_booking. C9 goal=request_info. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel, taxi; goal=search, booking, request_info; destination=my hotel; departure=the boats; requested_info=entrance_fee, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: That would be fine.\nChunk 3: Do you need to book it?\nChunk 4: Actually, can you please book a taxi from the boats to my hotel.\nChunk 5: Thank you SO MUCH, I know I was confusing.\nChunk 6: Can you just tell me the entrance fee for the boats?\nChunk 7: That is all I still need to know.\nChunk 8: Yes, could I get the postcode for Camboats?\nChunk 9: Will you tell me the car type?\nChunk 10: Thank you so much!"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 intent=context_update. C3 goal=booking. C4 domain=taxi; hotel_type+=hotel; destination+=my hotel; departure+=the boats. C5 [SKIP: thanks_only]. C6 goal=request_info; requested_info+=entrance_fee. C7 [SKIP: closing_only]. C8 requested_info+=postcode; goal=confirm_booking. C9 goal=request_info. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel, taxi; goal=search, booking, request_info; destination=my hotel; departure=the boats; requested_info=entrance_fee, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: That would be fine.\nChunk 3: Do you need to book it?\nChunk 4: Actually, can you please book a taxi from the boats to my hotel.\nChunk 5: Thank you SO MUCH, I know I was confusing.\nChunk 6: Can you just tell me the entrance fee for the boats?\nChunk 7: That is all I still need to know.\nChunk 8: Yes, could I get the postcode for Camboats?\nChunk 9: Will you tell me the car type?\nChunk 10: Thank you so much!", "input_token_count": 91, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is booking. Next, the topic is taxi; hotel type: hotel; destination: my hotel; departure point: the boats. Next, the goal is request info; requested information: entrance_fee. Next, the goal is confirm booking.; requested information: postcode. Finally, the goal is request info.  Some chunks were skipped because they contained acknowledgement_only or closing_only or thanks_only. In summary, The overall topic is taxi. the goal is request info.. intent: context_update.; hotel type: hotel; destination: my hotel; departure point: the boats.; requested information: entrance_fee., postcode.", "trace": "C1 [SKIP: acknowledgement_only]. C2 intent=context_update. C3 goal=booking. C4 domain=taxi; hotel_type+=hotel; destination+=my hotel; departure+=the boats. C5 [SKIP: thanks_only]. C6 goal=request_info; requested_info+=entrance_fee. C7 [SKIP: closing_only]. C8 requested_info+=postcode; goal=confirm_booking. C9 goal=request_info. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "That would be fine.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Do you need to book it?", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Actually, can you please book a taxi from the boats to my hotel.", "streaming_reasoning": "As more information arrives, the topic is taxi; hotel type: hotel; destination: my hotel; departure point: the boats..", "trace": "domain=taxi; hotel_type+=hotel; destination+=my hotel; departure+=the boats."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you SO MUCH, I know I was confusing.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you just tell me the entrance fee for the boats?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I still need to know.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Yes, could I get the postcode for Camboats?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: postcode.", "trace": "requested_info+=postcode; goal=confirm_booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Will you tell me the car type?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you so much!", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: destination is my hotel; departure point is the boats; requested information is entrance_fee. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, taxi; goal=search, booking, request_info; destination=my hotel; departure=the boats; requested_info=entrance_fee, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002742", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Any one will do.\nChunk 2: I would just need to know how much it costs and the address and phone number for it.\nChunk 3: Well, the phone numbers and addresses of these boat attractions would be helpful.\nChunk 4: I also need the entrance fee.\nChunk 5: Okay I will give them a call.\nChunk 6: That is all thank you.\nChunk 7: Thanks again Good bye.", "streaming_reasoning": "C1 intent=context_update. C2 goal=request_info; destination+=know how much it costs and the address an; requested_info+=address, phone. C3 intent=context_update. C4 requested_info+=entrance_fee. C5 intent=context_update. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "deep_reasoning": "Need goal=search, request_info; destination=know how much it costs and the address an; requested_info=address, phone, entrance_fee; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Any one will do.\nChunk 2: I would just need to know how much it costs and the address and phone number for it.\nChunk 3: Well, the phone numbers and addresses of these boat attractions would be helpful.\nChunk 4: I also need the entrance fee.\nChunk 5: Okay I will give them a call.\nChunk 6: That is all thank you.\nChunk 7: Thanks again Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=request_info; destination+=know how much it costs and the address an; requested_info+=address, phone. C3 intent=context_update. C4 requested_info+=entrance_fee. C5 intent=context_update. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=search, request_info; destination=know how much it costs and the address an; requested_info=address, phone, entrance_fee; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Any one will do.\nChunk 2: I would just need to know how much it costs and the address and phone number for it.\nChunk 3: Well, the phone numbers and addresses of these boat attractions would be helpful.\nChunk 4: I also need the entrance fee.\nChunk 5: Okay I will give them a call.\nChunk 6: That is all thank you.\nChunk 7: Thanks again Good bye.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is request info; destination: know how much it costs and the address an; requested information: address. Next, intent: context_update. Next, requested information: entrance_fee. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is request info. intent: context_update.; destination: know how much it costs and the address an; requested information: address, entrance_fee..", "trace": "C1 intent=context_update. C2 goal=request_info; destination+=know how much it costs and the address an; requested_info+=address, phone. C3 intent=context_update. C4 requested_info+=entrance_fee. C5 intent=context_update. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Any one will do.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would just need to know how much it costs and the address and phone number for it.", "streaming_reasoning": "As more information arrives, the goal is request info; destination: know how much it costs and the address an; requested information: address.", "trace": "goal=request_info; destination+=know how much it costs and the address an; requested_info+=address, phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Well, the phone numbers and addresses of these boat attractions would be helpful.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the entrance fee.", "streaming_reasoning": "As more information arrives, requested information: entrance_fee..", "trace": "requested_info+=entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Okay I will give them a call.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks again Good bye.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=search, request_info; destination=know how much it costs and the address an; requested_info=address, phone, entrance_fee; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002743", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: A 3 star rating would be perfect.\nChunk 2: Great, can you help me find some place to go in the Centre, maybe a college?\nChunk 3: That doesn't actually matter.\nChunk 4: You can choose the one you most recommend and then please tell me the phone number and postcode.\nChunk 5: Yeah that is fine, can I get their phone number and zip code?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 20:45.\nChunk 8: That's it for me today Thanks so much!\nChunk 9: Bye!", "streaming_reasoning": "C1 stars+=3 stars; acceptance=selected_option. C2 domain=attraction; goal=search; area+=centre; destination+=go in the centre. C3 intent=context_update. C4 goal=request_info; requested_info+=phone, postcode. C5 goal=request_info. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 time+=20:45. C8 day+=today. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, hotel; goal=search, recommendation, request_info; area=centre; stars=3 stars; destination=go in the centre, find a hotel; requested_info=phone, postcode; when=today, 20:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: A 3 star rating would be perfect.\nChunk 2: Great, can you help me find some place to go in the Centre, maybe a college?\nChunk 3: That doesn't actually matter.\nChunk 4: You can choose the one you most recommend and then please tell me the phone number and postcode.\nChunk 5: Yeah that is fine, can I get their phone number and zip code?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 20:45.\nChunk 8: That's it for me today Thanks so much!\nChunk 9: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 stars+=3 stars; acceptance=selected_option. C2 domain=attraction; goal=search; area+=centre; destination+=go in the centre. C3 intent=context_update. C4 goal=request_info; requested_info+=phone, postcode. C5 goal=request_info. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 time+=20:45. C8 day+=today. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, hotel; goal=search, recommendation, request_info; area=centre; stars=3 stars; destination=go in the centre, find a hotel; requested_info=phone, postcode; when=today, 20:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: A 3 star rating would be perfect.\nChunk 2: Great, can you help me find some place to go in the Centre, maybe a college?\nChunk 3: That doesn't actually matter.\nChunk 4: You can choose the one you most recommend and then please tell me the phone number and postcode.\nChunk 5: Yeah that is fine, can I get their phone number and zip code?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 20:45.\nChunk 8: That's it for me today Thanks so much!\nChunk 9: Bye!", "input_token_count": 96, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, star rating: 3 stars; acceptance: selected_option. Next, the topic is attraction; the goal is search; area: centre; destination: go in the centre. Next, intent: context_update. Next, the goal is request info; requested information: phone. Next, the goal is request info. Next, the topic is hotel; hotel type: hotel; destination: find a hotel. Next, time: 20:45. Finally, day: today.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info.. star rating: 3 stars; acceptance: selected_option.; area: centre; destination: go in the centre., find a hotel.; intent: context_update.; requested information: phone; hotel type: hotel; time: 20:45.; day: today..", "trace": "C1 stars+=3 stars; acceptance=selected_option. C2 domain=attraction; goal=search; area+=centre; destination+=go in the centre. C3 intent=context_update. C4 goal=request_info; requested_info+=phone, postcode. C5 goal=request_info. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 time+=20:45. C8 day+=today. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "A 3 star rating would be perfect.", "streaming_reasoning": "Initially, star rating: 3 stars; acceptance: selected_option..", "trace": "stars+=3 stars; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Great, can you help me find some place to go in the Centre, maybe a college?", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is search; area: centre; destination: go in the centre..", "trace": "domain=attraction; goal=search; area+=centre; destination+=go in the centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That doesn't actually matter.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "You can choose the one you most recommend and then please tell me the phone number and postcode.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yeah that is fine, can I get their phone number and zip code?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 20:45.", "streaming_reasoning": "As more information arrives, time: 20:45..", "trace": "time+=20:45."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's it for me today Thanks so much!", "streaming_reasoning": "As more information arrives, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Bye!", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; star rating is 3 stars; destination is go in the centre; requested information is phone; timing is today. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, hotel; goal=search, recommendation, request_info; area=centre; stars=3 stars; destination=go in the centre, find a hotel; requested_info=phone, postcode; when=today, 20:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002744", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking in town for a hospital with a paediatric clinic.\nChunk 2: I need the address and phone number and postal code.", "streaming_reasoning": "C1 domain=hospital. C2 goal=request_info; requested_info+=address, phone, postcode.", "deep_reasoning": "Need domain=hospital; goal=search, request_info; requested_info=address, phone, postcode.", "answer": "I can help with that and include the address, phone, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking in town for a hospital with a paediatric clinic.\nChunk 2: I need the address and phone number and postal code."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital. C2 goal=request_info; requested_info+=address, phone, postcode.\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; requested_info=address, phone, postcode.\n\nAnswer: I can help with that and include the address, phone, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking in town for a hospital with a paediatric clinic.\nChunk 2: I need the address and phone number and postal code.", "input_token_count": 26, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital. Finally, the goal is request info; requested information: address. In summary, The overall topic is hospital.. the goal is request info. requested information: address.", "trace": "C1 domain=hospital. C2 goal=request_info; requested_info+=address, phone, postcode.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking in town for a hospital with a paediatric clinic.", "streaming_reasoning": "Initially, the topic is hospital..", "trace": "domain=hospital."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need the address and phone number and postal code.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, postcode."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; requested_info=address, phone, postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002745", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes the university arms would you be able to book that?\nChunk 2: 6 people, five nights, starting on Thursday, please.\nChunk 3: Yes please book that That's perfect.\nChunk 4: Thank you so much.\nChunk 5: I'm sorry, I made a mistake!\nChunk 6: I need for it to start on Tuesday not Thursday!!!!\nChunk 7: Can you fix that for me No, thank you.\nChunk 8: I think that's it.", "streaming_reasoning": "C1 goal=confirm_booking; goal=confirm_booking. C2 day+=thursday; party_size+=6 people. C3 goal=confirm_booking. C4 [SKIP: thanks_only]. C5 intent=context_update. C6 goal=search; day+=tuesday; destination+=start on tuesday not thursday!!!!. C7 goal=modify_constraint. C8 intent=context_update.", "deep_reasoning": "Need goal=booking, confirm_booking, search; party_size=6 people; destination=start on tuesday not thursday!!!!; when=thursday, tuesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes the university arms would you be able to book that?\nChunk 2: 6 people, five nights, starting on Thursday, please.\nChunk 3: Yes please book that That's perfect.\nChunk 4: Thank you so much.\nChunk 5: I'm sorry, I made a mistake!\nChunk 6: I need for it to start on Tuesday not Thursday!!!!\nChunk 7: Can you fix that for me No, thank you.\nChunk 8: I think that's it."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=confirm_booking; goal=confirm_booking. C2 day+=thursday; party_size+=6 people. C3 goal=confirm_booking. C4 [SKIP: thanks_only]. C5 intent=context_update. C6 goal=search; day+=tuesday; destination+=start on tuesday not thursday!!!!. C7 goal=modify_constraint. C8 intent=context_update.\n\nDeep reasoning: Need goal=booking, confirm_booking, search; party_size=6 people; destination=start on tuesday not thursday!!!!; when=thursday, tuesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes the university arms would you be able to book that?\nChunk 2: 6 people, five nights, starting on Thursday, please.\nChunk 3: Yes please book that That's perfect.\nChunk 4: Thank you so much.\nChunk 5: I'm sorry, I made a mistake!\nChunk 6: I need for it to start on Tuesday not Thursday!!!!\nChunk 7: Can you fix that for me No, thank you.\nChunk 8: I think that's it.", "input_token_count": 74, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is confirm booking. Next, day: thursday; party size: 6 people. Next, the goal is confirm booking. Next, intent: context_update. Next, the goal is search; day: tuesday; destination: start on tuesday not thursday!!!!. Next, the goal is modify constraint. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, the goal is modify constraint.. day: thursday, tuesday; party size: 6 people.; intent: context_update.; destination: start on tuesday not thursday!!!!..", "trace": "C1 goal=confirm_booking; goal=confirm_booking. C2 day+=thursday; party_size+=6 people. C3 goal=confirm_booking. C4 [SKIP: thanks_only]. C5 intent=context_update. C6 goal=search; day+=tuesday; destination+=start on tuesday not thursday!!!!. C7 goal=modify_constraint. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes the university arms would you be able to book that?", "streaming_reasoning": "Initially, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "6 people, five nights, starting on Thursday, please.", "streaming_reasoning": "As more information arrives, day: thursday; party size: 6 people..", "trace": "day+=thursday; party_size+=6 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes please book that That's perfect.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you so much.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm sorry, I made a mistake!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need for it to start on Tuesday not Thursday!!!!", "streaming_reasoning": "As more information arrives, the goal is search; day: tuesday; destination: start on tuesday not thursday!!!!..", "trace": "goal=search; day+=tuesday; destination+=start on tuesday not thursday!!!!."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can you fix that for me No, thank you.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I think that's it.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "Need goal=booking, confirm_booking, search; party_size=6 people; destination=start on tuesday not thursday!!!!; when=thursday, tuesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002746", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for ALexeander b&b.\nChunk 2: It is for 5 people.\nChunk 3: The time is thursday, 2.\nChunk 4: Please make a booking.\nChunk 5: No,lets try for next Friday?\nChunk 6: Another hotel then, same price range.\nChunk 7: Thank you so much!\nChunk 8: That was all, thank you for your help today.", "streaming_reasoning": "C1 goal=search. C2 party_size+=5 people. C3 time+=2; day+=thursday. C4 goal=booking. C5 day+=friday. C6 domain=hotel; goal=modify_constraint; price+=same price; hotel_type+=hotel. C7 [SKIP: thanks_only]. C8 day+=today.", "deep_reasoning": "Need domain=hotel; goal=search, booking, compare_alternative, modify_constraint; price=same price; party_size=5 people; when=thursday, friday, today, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for ALexeander b&b.\nChunk 2: It is for 5 people.\nChunk 3: The time is thursday, 2.\nChunk 4: Please make a booking.\nChunk 5: No,lets try for next Friday?\nChunk 6: Another hotel then, same price range.\nChunk 7: Thank you so much!\nChunk 8: That was all, thank you for your help today."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 party_size+=5 people. C3 time+=2; day+=thursday. C4 goal=booking. C5 day+=friday. C6 domain=hotel; goal=modify_constraint; price+=same price; hotel_type+=hotel. C7 [SKIP: thanks_only]. C8 day+=today.\n\nDeep reasoning: Need domain=hotel; goal=search, booking, compare_alternative, modify_constraint; price=same price; party_size=5 people; when=thursday, friday, today, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for ALexeander b&b.\nChunk 2: It is for 5 people.\nChunk 3: The time is thursday, 2.\nChunk 4: Please make a booking.\nChunk 5: No,lets try for next Friday?\nChunk 6: Another hotel then, same price range.\nChunk 7: Thank you so much!\nChunk 8: That was all, thank you for your help today.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, party size: 5 people. Next, time: 2; day: thursday. Next, the goal is booking. Next, day: friday. Next, the topic is hotel; the goal is modify constraint; price: same price; hotel type: hotel. Finally, day: today.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is modify constraint. party size: 5 people.; time: 2; day: thursday., friday., today.; price: same price; hotel type: hotel..", "trace": "C1 goal=search. C2 party_size+=5 people. C3 time+=2; day+=thursday. C4 goal=booking. C5 day+=friday. C6 domain=hotel; goal=modify_constraint; price+=same price; hotel_type+=hotel. C7 [SKIP: thanks_only]. C8 day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for ALexeander b&b.", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It is for 5 people.", "streaming_reasoning": "As more information arrives, party size: 5 people..", "trace": "party_size+=5 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is thursday, 2.", "streaming_reasoning": "As more information arrives, time: 2; day: thursday..", "trace": "time+=2; day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No,lets try for next Friday?", "streaming_reasoning": "As more information arrives, day: friday..", "trace": "day+=friday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Another hotel then, same price range.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is modify constraint; price: same price; hotel type: hotel..", "trace": "domain=hotel; goal=modify_constraint; price+=same price; hotel_type+=hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you so much!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That was all, thank you for your help today.", "streaming_reasoning": "Finally, day: today..", "trace": "day+=today."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is same price; party size is 5 people; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, compare_alternative, modify_constraint; price=same price; party_size=5 people; when=thursday, friday, today, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002747", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi.\nChunk 2: I'm looking for a restaurant that serves Irish food.\nChunk 3: Can you help me?\nChunk 4: Can i have a thai restaurant instead?", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search. C3 goal=request_info. C4 goal=request_info; cuisine+=thai.", "deep_reasoning": "Need domain=restaurant; goal=search, compare_alternative, request_info; food=thai.", "answer": "What area, price range should I use for the search?", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi.\nChunk 2: I'm looking for a restaurant that serves Irish food.\nChunk 3: Can you help me?\nChunk 4: Can i have a thai restaurant instead?"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search. C3 goal=request_info. C4 goal=request_info; cuisine+=thai.\n\nDeep reasoning: Need domain=restaurant; goal=search, compare_alternative, request_info; food=thai.\n\nAnswer: What area, price range should I use for the search?"}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi.\nChunk 2: I'm looking for a restaurant that serves Irish food.\nChunk 3: Can you help me?\nChunk 4: Can i have a thai restaurant instead?", "input_token_count": 29, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, the goal is request info. Finally, the goal is request info; cuisine: thai.  Some chunks were skipped because they contained greeting_only. In summary, The overall topic is restaurant. the goal is request info. cuisine: thai..", "trace": "C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=search. C3 goal=request_info. C4 goal=request_info; cuisine+=thai.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi.", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm looking for a restaurant that serves Irish food.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you help me?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can i have a thai restaurant instead?", "streaming_reasoning": "Finally, the goal is request info; cuisine: thai..", "trace": "goal=request_info; cuisine+=thai."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is thai.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "What area, price range should I use for the search?", "deep_reasoning_trace": "Need domain=restaurant; goal=search, compare_alternative, request_info; food=thai."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002748", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It is for 8 people.\nChunk 2: The time is saturday, 8, 19:15.\nChunk 3: Please make a booking.\nChunk 4: I also need the reference number.\nChunk 5: I would like a train, arriving by 1500 and departing from birmingham new street Cambridge, of course!\nChunk 6: I need the make it to the restaurant booking!\nChunk 7: I would like to leave at 11:40 please.\nChunk 8: Can you confirm that the train booing is for 8 people, please Wonderful!\nChunk 9: You have been incredibly helpful.\nChunk 10: That will be all I need today.", "streaming_reasoning": "C1 party_size+=8 people. C2 time+=8, 19:15; day+=saturday. C3 goal=booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=train; departure+=birmingham new street cambridge. C6 domain=restaurant; goal=modify_constraint. C7 time+=11:40; destination+=leave at 11:40 please. C8 intent=context_update. C9 intent=context_update. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, restaurant; goal=booking, search, request_info, modify_constraint; party_size=8 people; destination=leave at 11:40 please; departure=birmingham new street cambridge; requested_info=reference_number; when=saturday, 8, 19:15, 11:40; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: It is for 8 people.\nChunk 2: The time is saturday, 8, 19:15.\nChunk 3: Please make a booking.\nChunk 4: I also need the reference number.\nChunk 5: I would like a train, arriving by 1500 and departing from birmingham new street Cambridge, of course!\nChunk 6: I need the make it to the restaurant booking!\nChunk 7: I would like to leave at 11:40 please.\nChunk 8: Can you confirm that the train booing is for 8 people, please Wonderful!\nChunk 9: You have been incredibly helpful.\nChunk 10: That will be all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 party_size+=8 people. C2 time+=8, 19:15; day+=saturday. C3 goal=booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=train; departure+=birmingham new street cambridge. C6 domain=restaurant; goal=modify_constraint. C7 time+=11:40; destination+=leave at 11:40 please. C8 intent=context_update. C9 intent=context_update. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=booking, search, request_info, modify_constraint; party_size=8 people; destination=leave at 11:40 please; departure=birmingham new street cambridge; requested_info=reference_number; when=saturday, 8, 19:15, 11:40; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It is for 8 people.\nChunk 2: The time is saturday, 8, 19:15.\nChunk 3: Please make a booking.\nChunk 4: I also need the reference number.\nChunk 5: I would like a train, arriving by 1500 and departing from birmingham new street Cambridge, of course!\nChunk 6: I need the make it to the restaurant booking!\nChunk 7: I would like to leave at 11:40 please.\nChunk 8: Can you confirm that the train booing is for 8 people, please Wonderful!\nChunk 9: You have been incredibly helpful.\nChunk 10: That will be all I need today.", "input_token_count": 102, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, party size: 8 people. Next, time: 8; day: saturday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the topic is train; departure point: birmingham new street cambridge. Next, the topic is restaurant; the goal is modify constraint. Next, time: 11:40; destination: leave at 11:40 please. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is modify constraint.. party size: 8 people.; time: 8, 11:40; day: saturday.; requested information: reference_number.; departure point: birmingham new street cambridge.; destination: leave at 11:40 please.; intent: context_update..", "trace": "C1 party_size+=8 people. C2 time+=8, 19:15; day+=saturday. C3 goal=booking. C4 goal=request_info; requested_info+=reference_number. C5 domain=train; departure+=birmingham new street cambridge. C6 domain=restaurant; goal=modify_constraint. C7 time+=11:40; destination+=leave at 11:40 please. C8 intent=context_update. C9 intent=context_update. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "It is for 8 people.", "streaming_reasoning": "Initially, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is saturday, 8, 19:15.", "streaming_reasoning": "As more information arrives, time: 8; day: saturday..", "trace": "time+=8, 19:15; day+=saturday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like a train, arriving by 1500 and departing from birmingham new street Cambridge, of course!", "streaming_reasoning": "As more information arrives, the topic is train; departure point: birmingham new street cambridge..", "trace": "domain=train; departure+=birmingham new street cambridge."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need the make it to the restaurant booking!", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint..", "trace": "domain=restaurant; goal=modify_constraint."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I would like to leave at 11:40 please.", "streaming_reasoning": "As more information arrives, time: 11:40; destination: leave at 11:40 please..", "trace": "time+=11:40; destination+=leave at 11:40 please."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Can you confirm that the train booing is for 8 people, please Wonderful!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "You have been incredibly helpful.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That will be all I need today.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: party size is 8 people; destination is leave at 11:40 please; departure point is birmingham new street cambridge; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=booking, search, request_info, modify_constraint; party_size=8 people; destination=leave at 11:40 please; departure=birmingham new street cambridge; requested_info=reference_number; when=saturday, 8, 19:15, 11:40; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002749", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you please tell me the arrival time on that train?\nChunk 2: i'm also interested in a particular attraction.\nChunk 3: The Cambridge Museum of Technology, do you know of it?\nChunk 4: What area is it in?\nChunk 5: Can I get the phone number and post code for the museum?\nChunk 6: Thanks for your help!", "streaming_reasoning": "C1 domain=train; goal=request_info. C2 domain=attraction. C3 goal=request_info. C4 goal=request_info. C5 requested_info+=phone, postcode. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, attraction; goal=request_info; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you please tell me the arrival time on that train?\nChunk 2: i'm also interested in a particular attraction.\nChunk 3: The Cambridge Museum of Technology, do you know of it?\nChunk 4: What area is it in?\nChunk 5: Can I get the phone number and post code for the museum?\nChunk 6: Thanks for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=request_info. C2 domain=attraction. C3 goal=request_info. C4 goal=request_info. C5 requested_info+=phone, postcode. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, attraction; goal=request_info; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you please tell me the arrival time on that train?\nChunk 2: i'm also interested in a particular attraction.\nChunk 3: The Cambridge Museum of Technology, do you know of it?\nChunk 4: What area is it in?\nChunk 5: Can I get the phone number and post code for the museum?\nChunk 6: Thanks for your help!", "input_token_count": 61, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is request info. Next, the topic is attraction. Next, the goal is request info. Next, the goal is request info. Finally, requested information: phone.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction.. the goal is request info.. requested information: phone.", "trace": "C1 domain=train; goal=request_info. C2 domain=attraction. C3 goal=request_info. C4 goal=request_info. C5 requested_info+=phone, postcode. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you please tell me the arrival time on that train?", "streaming_reasoning": "Initially, the topic is train; the goal is request info..", "trace": "domain=train; goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "i'm also interested in a particular attraction.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The Cambridge Museum of Technology, do you know of it?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What area is it in?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get the phone number and post code for the museum?", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks for your help!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=request_info; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002750", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, what can you tell me about de luca cucina and bar?\nChunk 2: Yes, I need it booked for 7 people on Tuesday at 19:30.\nChunk 3: Thank you so much.\nChunk 4: And yes, I also need to find a train to Bishops Stortford, please.\nChunk 5: I will be leaving from Cambridge on Tuesday.\nChunk 6: I want it to arrive by 16:00.\nChunk 7: Yes please book tickets on that train for 7 people and send me the reference number.\nChunk 8: Thank you thats all I need for now.", "streaming_reasoning": "C1 goal=request_info. C2 goal=search; time+=7, 19:30; day+=tuesday; party_size+=7 people; acceptance=selected_option. C3 [SKIP: thanks_only]. C4 domain=train; destination+=find a train to bishops stortford; acceptance=selected_option. C5 intent=context_update. C6 time+=16:00; destination+=arrive by 16:00. C7 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=request_info, search, booking, confirm_booking; party_size=7 people; destination=find a train to bishops stortford, arrive by 16:00; requested_info=reference_number; when=tuesday, 7, 19:30, 16:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, what can you tell me about de luca cucina and bar?\nChunk 2: Yes, I need it booked for 7 people on Tuesday at 19:30.\nChunk 3: Thank you so much.\nChunk 4: And yes, I also need to find a train to Bishops Stortford, please.\nChunk 5: I will be leaving from Cambridge on Tuesday.\nChunk 6: I want it to arrive by 16:00.\nChunk 7: Yes please book tickets on that train for 7 people and send me the reference number.\nChunk 8: Thank you thats all I need for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 goal=search; time+=7, 19:30; day+=tuesday; party_size+=7 people; acceptance=selected_option. C3 [SKIP: thanks_only]. C4 domain=train; destination+=find a train to bishops stortford; acceptance=selected_option. C5 intent=context_update. C6 time+=16:00; destination+=arrive by 16:00. C7 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search, booking, confirm_booking; party_size=7 people; destination=find a train to bishops stortford, arrive by 16:00; requested_info=reference_number; when=tuesday, 7, 19:30, 16:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, what can you tell me about de luca cucina and bar?\nChunk 2: Yes, I need it booked for 7 people on Tuesday at 19:30.\nChunk 3: Thank you so much.\nChunk 4: And yes, I also need to find a train to Bishops Stortford, please.\nChunk 5: I will be leaving from Cambridge on Tuesday.\nChunk 6: I want it to arrive by 16:00.\nChunk 7: Yes please book tickets on that train for 7 people and send me the reference number.\nChunk 8: Thank you thats all I need for now.", "input_token_count": 98, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, the goal is search; time: 7; day: tuesday; party size: 7 people; acceptance: selected_option. Next, the topic is train; destination: find a train to bishops stortford; acceptance: selected_option. Next, intent: context_update. Next, time: 16:00; destination: arrive by 16:00. Finally, the goal is confirm booking.; requested information: reference_number.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is confirm booking.. time: 7, 16:00; day: tuesday; party size: 7 people; acceptance: selected_option.; destination: find a train to bishops stortford, arrive by 16:00.; intent: context_update.; requested information: reference_number.", "trace": "C1 goal=request_info. C2 goal=search; time+=7, 19:30; day+=tuesday; party_size+=7 people; acceptance=selected_option. C3 [SKIP: thanks_only]. C4 domain=train; destination+=find a train to bishops stortford; acceptance=selected_option. C5 intent=context_update. C6 time+=16:00; destination+=arrive by 16:00. C7 goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, what can you tell me about de luca cucina and bar?", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I need it booked for 7 people on Tuesday at 19:30.", "streaming_reasoning": "As more information arrives, the goal is search; time: 7; day: tuesday; party size: 7 people; acceptance: selected_option..", "trace": "goal=search; time+=7, 19:30; day+=tuesday; party_size+=7 people; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you so much.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "And yes, I also need to find a train to Bishops Stortford, please.", "streaming_reasoning": "As more information arrives, the topic is train; destination: find a train to bishops stortford; acceptance: selected_option..", "trace": "domain=train; destination+=find a train to bishops stortford; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will be leaving from Cambridge on Tuesday.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want it to arrive by 16:00.", "streaming_reasoning": "As more information arrives, time: 16:00; destination: arrive by 16:00..", "trace": "time+=16:00; destination+=arrive by 16:00."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes please book tickets on that train for 7 people and send me the reference number.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "goal=confirm_booking; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you thats all I need for now.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: party size is 7 people; destination is find a train to bishops stortford; requested information is reference_number; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search, booking, confirm_booking; party_size=7 people; destination=find a train to bishops stortford, arrive by 16:00; requested_info=reference_number; when=tuesday, 7, 19:30, 16:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002751", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What is their address?\nChunk 2: Can you book it for me and get a reference number?\nChunk 3: Can you find a train for me as well?\nChunk 4: I also need a train.\nChunk 5: I need help with train.\nChunk 6: The time is friday, 12:45.\nChunk 7: I also need the travel time.\nChunk 8: Nope, that's all I needed thanks.", "streaming_reasoning": "C1 goal=request_info; requested_info+=address. C2 goal=booking; requested_info+=reference_number. C3 domain=train; goal=search. C4 [SKIP: repeated_information]. C5 intent=context_update. C6 time+=12:45; day+=friday. C7 requested_info+=travel_time. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=request_info, booking, search; requested_info=address, reference_number, travel_time; when=friday, 12:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What is their address?\nChunk 2: Can you book it for me and get a reference number?\nChunk 3: Can you find a train for me as well?\nChunk 4: I also need a train.\nChunk 5: I need help with train.\nChunk 6: The time is friday, 12:45.\nChunk 7: I also need the travel time.\nChunk 8: Nope, that's all I needed thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address. C2 goal=booking; requested_info+=reference_number. C3 domain=train; goal=search. C4 [SKIP: repeated_information]. C5 intent=context_update. C6 time+=12:45; day+=friday. C7 requested_info+=travel_time. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=request_info, booking, search; requested_info=address, reference_number, travel_time; when=friday, 12:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What is their address?\nChunk 2: Can you book it for me and get a reference number?\nChunk 3: Can you find a train for me as well?\nChunk 4: I also need a train.\nChunk 5: I need help with train.\nChunk 6: The time is friday, 12:45.\nChunk 7: I also need the travel time.\nChunk 8: Nope, that's all I needed thanks.", "input_token_count": 68, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the goal is booking; requested information: reference_number. Next, the topic is train; the goal is search. Next, intent: context_update. Next, time: 12:45; day: friday. Finally, requested information: travel_time.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is train. the goal is search.. requested information: address., reference_number., travel_time.; intent: context_update.; time: 12:45; day: friday..", "trace": "C1 goal=request_info; requested_info+=address. C2 goal=booking; requested_info+=reference_number. C3 domain=train; goal=search. C4 [SKIP: repeated_information]. C5 intent=context_update. C6 time+=12:45; day+=friday. C7 requested_info+=travel_time. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What is their address?", "streaming_reasoning": "Initially, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you book it for me and get a reference number?", "streaming_reasoning": "As more information arrives, the goal is booking; requested information: reference_number..", "trace": "goal=booking; requested_info+=reference_number."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you find a train for me as well?", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need a train.", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is friday, 12:45.", "streaming_reasoning": "As more information arrives, time: 12:45; day: friday..", "trace": "time+=12:45; day+=friday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the travel time.", "streaming_reasoning": "As more information arrives, requested information: travel_time..", "trace": "requested_info+=travel_time."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Nope, that's all I needed thanks.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, booking, search; requested_info=address, reference_number, travel_time; when=friday, 12:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002752", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you just pick one and give me the phone number?\nChunk 2: find me a place to go in the west and give me their phone numbers.\nChunk 3: Great, I'll need to find another restaurant also, in the same area of town as Clare Hall.\nChunk 4: I like British pub cuisine Sounds great.\nChunk 5: I need it for monday at 14:15.\nChunk 6: There will be 3 in our party.\nChunk 7: That is all I need today thank you.", "streaming_reasoning": "C1 goal=request_info; requested_info+=phone. C2 goal=search; area+=west; destination+=go in the west and give me their phone nu. C3 domain=restaurant; goal=modify_constraint; destination+=find another restaurant also. C4 cuisine+=british. C5 time+=14:15; day+=monday. C6 intent=context_update. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=request_info, search, compare_alternative, modify_constraint; area=west; food=british; destination=go in the west and give me their phone nu, find another restaurant also; requested_info=phone; when=monday, 14:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you just pick one and give me the phone number?\nChunk 2: find me a place to go in the west and give me their phone numbers.\nChunk 3: Great, I'll need to find another restaurant also, in the same area of town as Clare Hall.\nChunk 4: I like British pub cuisine Sounds great.\nChunk 5: I need it for monday at 14:15.\nChunk 6: There will be 3 in our party.\nChunk 7: That is all I need today thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=phone. C2 goal=search; area+=west; destination+=go in the west and give me their phone nu. C3 domain=restaurant; goal=modify_constraint; destination+=find another restaurant also. C4 cuisine+=british. C5 time+=14:15; day+=monday. C6 intent=context_update. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=request_info, search, compare_alternative, modify_constraint; area=west; food=british; destination=go in the west and give me their phone nu, find another restaurant also; requested_info=phone; when=monday, 14:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you just pick one and give me the phone number?\nChunk 2: find me a place to go in the west and give me their phone numbers.\nChunk 3: Great, I'll need to find another restaurant also, in the same area of town as Clare Hall.\nChunk 4: I like British pub cuisine Sounds great.\nChunk 5: I need it for monday at 14:15.\nChunk 6: There will be 3 in our party.\nChunk 7: That is all I need today thank you.", "input_token_count": 87, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: phone. Next, the goal is search; area: west; destination: go in the west and give me their phone nu. Next, the topic is restaurant; the goal is modify constraint; destination: find another restaurant also. Next, cuisine: british. Next, time: 14:15; day: monday. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is modify constraint. requested information: phone.; area: west; destination: go in the west and give me their phone nu., find another restaurant also.; cuisine: british.; time: 14:15; day: monday.; intent: context_update..", "trace": "C1 goal=request_info; requested_info+=phone. C2 goal=search; area+=west; destination+=go in the west and give me their phone nu. C3 domain=restaurant; goal=modify_constraint; destination+=find another restaurant also. C4 cuisine+=british. C5 time+=14:15; day+=monday. C6 intent=context_update. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you just pick one and give me the phone number?", "streaming_reasoning": "Initially, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "find me a place to go in the west and give me their phone numbers.", "streaming_reasoning": "As more information arrives, the goal is search; area: west; destination: go in the west and give me their phone nu..", "trace": "goal=search; area+=west; destination+=go in the west and give me their phone nu."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Great, I'll need to find another restaurant also, in the same area of town as Clare Hall.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint; destination: find another restaurant also..", "trace": "domain=restaurant; goal=modify_constraint; destination+=find another restaurant also."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I like British pub cuisine Sounds great.", "streaming_reasoning": "As more information arrives, cuisine: british..", "trace": "cuisine+=british."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need it for monday at 14:15.", "streaming_reasoning": "As more information arrives, time: 14:15; day: monday..", "trace": "time+=14:15; day+=monday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "There will be 3 in our party.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I need today thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is west; cuisine is british; destination is go in the west and give me their phone nu; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info, search, compare_alternative, modify_constraint; area=west; food=british; destination=go in the west and give me their phone nu, find another restaurant also; requested_info=phone; when=monday, 14:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002753", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find a train going to cambridge that arrives by 18:30?\nChunk 2: I will be departing kings lynn.\nChunk 3: Yes for 2 people on a Tuesday please.\nChunk 4: And I would like the reference number Thanks so much.\nChunk 5: Can you also help me look for the Carolina Bed and Breakfast Yes please.\nChunk 6: Two nights from Tuesday for two people.\nChunk 7: I need a room for the same group of people for 1 night on the same day.\nChunk 8: And I need the reference number then too please.", "streaming_reasoning": "C1 domain=train; goal=search; time+=18:30; destination+=cambridge that arrives by 18:30. C2 intent=context_update. C3 day+=tuesday; party_size+=2 people; acceptance=selected_option. C4 goal=request_info; requested_info+=reference_number. C5 domain=restaurant; amenities+=breakfast; acceptance=selected_option. C6 intent=context_update. C7 domain=hotel; stay_length+=1 nights. C8 intent=context_update.", "deep_reasoning": "Need domain=train, restaurant, hotel; goal=search, request_info; party_size=2 people; stay_length=1 nights; amenities=breakfast; destination=cambridge that arrives by 18:30; requested_info=reference_number; when=tuesday, 18:30.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you help me find a train going to cambridge that arrives by 18:30?\nChunk 2: I will be departing kings lynn.\nChunk 3: Yes for 2 people on a Tuesday please.\nChunk 4: And I would like the reference number Thanks so much.\nChunk 5: Can you also help me look for the Carolina Bed and Breakfast Yes please.\nChunk 6: Two nights from Tuesday for two people.\nChunk 7: I need a room for the same group of people for 1 night on the same day.\nChunk 8: And I need the reference number then too please."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; time+=18:30; destination+=cambridge that arrives by 18:30. C2 intent=context_update. C3 day+=tuesday; party_size+=2 people; acceptance=selected_option. C4 goal=request_info; requested_info+=reference_number. C5 domain=restaurant; amenities+=breakfast; acceptance=selected_option. C6 intent=context_update. C7 domain=hotel; stay_length+=1 nights. C8 intent=context_update.\n\nDeep reasoning: Need domain=train, restaurant, hotel; goal=search, request_info; party_size=2 people; stay_length=1 nights; amenities=breakfast; destination=cambridge that arrives by 18:30; requested_info=reference_number; when=tuesday, 18:30.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find a train going to cambridge that arrives by 18:30?\nChunk 2: I will be departing kings lynn.\nChunk 3: Yes for 2 people on a Tuesday please.\nChunk 4: And I would like the reference number Thanks so much.\nChunk 5: Can you also help me look for the Carolina Bed and Breakfast Yes please.\nChunk 6: Two nights from Tuesday for two people.\nChunk 7: I need a room for the same group of people for 1 night on the same day.\nChunk 8: And I need the reference number then too please.", "input_token_count": 102, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 18:30; destination: cambridge that arrives by 18:30. Next, intent: context_update. Next, day: tuesday; party size: 2 people; acceptance: selected_option. Next, the goal is request info; requested information: reference_number. Next, the topic is restaurant; amenities: breakfast; acceptance: selected_option. Next, intent: context_update. Next, the topic is hotel; stay length: 1 nights. Finally, intent: context_update. In summary, The overall topic is hotel. the goal is request info. time: 18:30; destination: cambridge that arrives by 18:30.; intent: context_update.; day: tuesday; party size: 2 people; acceptance: selected_option.; requested information: reference_number.; amenities: breakfast; stay length: 1 nights..", "trace": "C1 domain=train; goal=search; time+=18:30; destination+=cambridge that arrives by 18:30. C2 intent=context_update. C3 day+=tuesday; party_size+=2 people; acceptance=selected_option. C4 goal=request_info; requested_info+=reference_number. C5 domain=restaurant; amenities+=breakfast; acceptance=selected_option. C6 intent=context_update. C7 domain=hotel; stay_length+=1 nights. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you help me find a train going to cambridge that arrives by 18:30?", "streaming_reasoning": "Initially, the topic is train; the goal is search; time: 18:30; destination: cambridge that arrives by 18:30..", "trace": "domain=train; goal=search; time+=18:30; destination+=cambridge that arrives by 18:30."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be departing kings lynn.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes for 2 people on a Tuesday please.", "streaming_reasoning": "As more information arrives, day: tuesday; party size: 2 people; acceptance: selected_option..", "trace": "day+=tuesday; party_size+=2 people; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "And I would like the reference number Thanks so much.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you also help me look for the Carolina Bed and Breakfast Yes please.", "streaming_reasoning": "As more information arrives, the topic is restaurant; amenities: breakfast; acceptance: selected_option..", "trace": "domain=restaurant; amenities+=breakfast; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Two nights from Tuesday for two people.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need a room for the same group of people for 1 night on the same day.", "streaming_reasoning": "As more information arrives, the topic is hotel; stay length: 1 nights..", "trace": "domain=hotel; stay_length+=1 nights."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "And I need the reference number then too please.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 2 people; stay length is 1 nights; amenities is breakfast; destination is cambridge that arrives by 18:30; requested information is reference_number; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=train, restaurant, hotel; goal=search, request_info; party_size=2 people; stay_length=1 nights; amenities=breakfast; destination=cambridge that arrives by 18:30; requested_info=reference_number; when=tuesday, 18:30."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002754", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I am looking for a moderately priced restaurant on the south side of town.\nChunk 2: Is there anything else?\nChunk 3: Can I get the phone number please Thank you goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=south; price+=moderate. C2 goal=compare_alternative. C3 goal=request_info; requested_info+=phone.", "deep_reasoning": "Need domain=restaurant; goal=search, compare_alternative, request_info; area=south; price=moderate; requested_info=phone.", "answer": "I can help with that and include the phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, I am looking for a moderately priced restaurant on the south side of town.\nChunk 2: Is there anything else?\nChunk 3: Can I get the phone number please Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=south; price+=moderate. C2 goal=compare_alternative. C3 goal=request_info; requested_info+=phone.\n\nDeep reasoning: Need domain=restaurant; goal=search, compare_alternative, request_info; area=south; price=moderate; requested_info=phone.\n\nAnswer: I can help with that and include the phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I am looking for a moderately priced restaurant on the south side of town.\nChunk 2: Is there anything else?\nChunk 3: Can I get the phone number please Thank you goodbye.", "input_token_count": 35, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: south; price: moderate. Next, the goal is compare alternative. Finally, the goal is request info; requested information: phone. In summary, The overall topic is restaurant. the goal is request info. area: south; price: moderate.; requested information: phone..", "trace": "C1 domain=restaurant; goal=search; area+=south; price+=moderate. C2 goal=compare_alternative. C3 goal=request_info; requested_info+=phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, I am looking for a moderately priced restaurant on the south side of town.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: south; price: moderate..", "trace": "domain=restaurant; goal=search; area+=south; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there anything else?", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I get the phone number please Thank you goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; price is moderate; requested information is phone.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, compare_alternative, request_info; area=south; price=moderate; requested_info=phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002756", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will prefer restaurant that serve Chinese food.\nChunk 2: Actually, no booking is necessary.\nChunk 3: But, can you suggest one and provide me the address.\nChunk 4: Thanks.\nChunk 5: Great thank you, I also need a train to arrive by 20:15 and traveling on monday.\nChunk 6: I'm leaving from Norwich and heading for Cambridge That doesn't matter.\nChunk 7: The 18:16 will do.\nChunk 8: Book it for 4.\nChunk 9: Thank you so much for your help, that's all I need today.", "streaming_reasoning": "C1 domain=restaurant; cuisine+=chinese. C2 goal=booking. C3 goal=request_info; requested_info+=address. C4 [SKIP: thanks_only]. C5 domain=train; goal=search; time+=20:15; day+=monday; destination+=arrive by 20:15 and traveling on monday. C6 intent=context_update. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, train; goal=booking, recommendation, request_info, search; food=chinese; destination=arrive by 20:15 and traveling on monday; requested_info=address; when=monday, 20:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I will prefer restaurant that serve Chinese food.\nChunk 2: Actually, no booking is necessary.\nChunk 3: But, can you suggest one and provide me the address.\nChunk 4: Thanks.\nChunk 5: Great thank you, I also need a train to arrive by 20:15 and traveling on monday.\nChunk 6: I'm leaving from Norwich and heading for Cambridge That doesn't matter.\nChunk 7: The 18:16 will do.\nChunk 8: Book it for 4.\nChunk 9: Thank you so much for your help, that's all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; cuisine+=chinese. C2 goal=booking. C3 goal=request_info; requested_info+=address. C4 [SKIP: thanks_only]. C5 domain=train; goal=search; time+=20:15; day+=monday; destination+=arrive by 20:15 and traveling on monday. C6 intent=context_update. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, train; goal=booking, recommendation, request_info, search; food=chinese; destination=arrive by 20:15 and traveling on monday; requested_info=address; when=monday, 20:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will prefer restaurant that serve Chinese food.\nChunk 2: Actually, no booking is necessary.\nChunk 3: But, can you suggest one and provide me the address.\nChunk 4: Thanks.\nChunk 5: Great thank you, I also need a train to arrive by 20:15 and traveling on monday.\nChunk 6: I'm leaving from Norwich and heading for Cambridge That doesn't matter.\nChunk 7: The 18:16 will do.\nChunk 8: Book it for 4.\nChunk 9: Thank you so much for your help, that's all I need today.", "input_token_count": 91, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; cuisine: chinese. Next, the goal is booking. Next, the goal is request info; requested information: address. Next, the topic is train; the goal is search; time: 20:15; day: monday; destination: arrive by 20:15 and traveling on monday. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or repeated_information or thanks_only. In summary, The overall topic is train. the goal is search. cuisine: chinese.; requested information: address.; time: 20:15; day: monday; destination: arrive by 20:15 and traveling on monday.; intent: context_update..", "trace": "C1 domain=restaurant; cuisine+=chinese. C2 goal=booking. C3 goal=request_info; requested_info+=address. C4 [SKIP: thanks_only]. C5 domain=train; goal=search; time+=20:15; day+=monday; destination+=arrive by 20:15 and traveling on monday. C6 intent=context_update. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I will prefer restaurant that serve Chinese food.", "streaming_reasoning": "Initially, the topic is restaurant; cuisine: chinese..", "trace": "domain=restaurant; cuisine+=chinese."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Actually, no booking is necessary.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "But, can you suggest one and provide me the address.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Great thank you, I also need a train to arrive by 20:15 and traveling on monday.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; time: 20:15; day: monday; destination: arrive by 20:15 and traveling on monday..", "trace": "domain=train; goal=search; time+=20:15; day+=monday; destination+=arrive by 20:15 and traveling on monday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'm leaving from Norwich and heading for Cambridge That doesn't matter.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The 18:16 will do.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Book it for 4.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you so much for your help, that's all I need today.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: cuisine is chinese; destination is arrive by 20:15 and traveling on monday; requested information is address; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, train; goal=booking, recommendation, request_info, search; food=chinese; destination=arrive by 20:15 and traveling on monday; requested_info=address; when=monday, 20:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000572", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Send a WhatsApp Message to an Unsaved Number.\nChunk 2: Open your preferred browser on your phone or tablet.\nChunk 3: Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you want to contact.\nChunk 4: Tap Message when prompted.\nChunk 5: Tap the airplane icon to send.", "streaming_reasoning": "C1 task=send_a_whatsapp_message. C2 step=open_your_preferred_browser. C3 step=go_to_httpsapiwhatsappcomsendphonexxxxxxxxxxx_where. C4 step=tap_message_when_prompted. C5 step=tap_the_airplane_icon.", "deep_reasoning": "Procedure for Send a WhatsApp Message to an Unsaved Number: Open your preferred browser on your phone or tablet, Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you, Tap Message when prompted, Tap the airplane icon to send.", "answer": "For Send a WhatsApp Message to an Unsaved Number, follow the steps in order: Open your preferred browser on your phone or tablet, Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you, Tap Message when prompted, Tap the airplane icon to send.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Send a WhatsApp Message to an Unsaved Number.\nChunk 2: Open your preferred browser on your phone or tablet.\nChunk 3: Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you want to contact.\nChunk 4: Tap Message when prompted.\nChunk 5: Tap the airplane icon to send."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=send_a_whatsapp_message. C2 step=open_your_preferred_browser. C3 step=go_to_httpsapiwhatsappcomsendphonexxxxxxxxxxx_where. C4 step=tap_message_when_prompted. C5 step=tap_the_airplane_icon.\n\nDeep reasoning: Procedure for Send a WhatsApp Message to an Unsaved Number: Open your preferred browser on your phone or tablet, Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you, Tap Message when prompted, Tap the airplane icon to send.\n\nAnswer: For Send a WhatsApp Message to an Unsaved Number, follow the steps in order: Open your preferred browser on your phone or tablet, Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you, Tap Message when prompted, Tap the airplane icon to send."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Send a WhatsApp Message to an Unsaved Number.\nChunk 2: Open your preferred browser on your phone or tablet.\nChunk 3: Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you want to contact.\nChunk 4: Tap Message when prompted.\nChunk 5: Tap the airplane icon to send.", "input_token_count": 57, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, task: send_a_whatsapp_message. Next, step: open_your_preferred_browser. Next, step: go_to_httpsapiwhatsappcomsendphonexxxxxxxxxxx_where. Next, step: tap_message_when_prompted. Finally, step: tap_the_airplane_icon. In summary, task: send_a_whatsapp_message.; step: open_your_preferred_browser., go_to_httpsapiwhatsappcomsendphonexxxxxxxxxxx_where., tap_message_when_prompted., tap_the_airplane_icon..", "trace": "C1 task=send_a_whatsapp_message. C2 step=open_your_preferred_browser. C3 step=go_to_httpsapiwhatsappcomsendphonexxxxxxxxxxx_where. C4 step=tap_message_when_prompted. C5 step=tap_the_airplane_icon.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Send a WhatsApp Message to an Unsaved Number.", "streaming_reasoning": "Initially, task: send_a_whatsapp_message..", "trace": "task=send_a_whatsapp_message."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Open your preferred browser on your phone or tablet.", "streaming_reasoning": "As more information arrives, step: open_your_preferred_browser..", "trace": "step=open_your_preferred_browser."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you want to contact.", "streaming_reasoning": "As more information arrives, step: go_to_httpsapiwhatsappcomsendphonexxxxxxxxxxx_where..", "trace": "step=go_to_httpsapiwhatsappcomsendphonexxxxxxxxxxx_where."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Tap Message when prompted.", "streaming_reasoning": "As more information arrives, step: tap_message_when_prompted..", "trace": "step=tap_message_when_prompted."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Tap the airplane icon to send.", "streaming_reasoning": "Finally, step: tap_the_airplane_icon..", "trace": "step=tap_the_airplane_icon."}]}, "output": {"deep_reasoning": "Procedure for Send a WhatsApp Message to an Unsaved Number: Open your preferred browser on your phone or tablet, Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you, Tap Message when prompted, Tap the airplane icon to send.", "answer": "For Send a WhatsApp Message to an Unsaved Number, follow the steps in order: Open your preferred browser on your phone or tablet, Go to https://api.whatsapp.com/send?phone=XXXXXXXXXXX where X is the phone number you, Tap Message when prompted, Tap the airplane icon to send."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002757", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a same price british restaurant.\nChunk 2: I also need the price.\nChunk 3: Yes, please look in another part of town.\nChunk 4: Yes please for one person at 17:45 on Thursday.\nChunk 5: No, can you also help me book a taxi?\nChunk 6: I want to find a guesthouse.\nChunk 7: The time is 17:45, 4.\nChunk 8: Nope That's all Thank you Bye now.", "streaming_reasoning": "C1 domain=restaurant; goal=modify_constraint; cuisine+=british; price+=same price; destination+=find a same price british restaurant. C2 [SKIP: repeated_information]. C3 goal=compare_alternative; acceptance=selected_option. C4 goal=confirm_booking; time+=17:45; day+=thursday; acceptance=selected_option. C5 domain=taxi; goal=booking. C6 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C7 time+=4. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi, hotel; goal=search, modify_constraint, compare_alternative, confirm_booking, booking; food=british; price=same price; destination=find a same price british restaurant, find a guesthouse; when=thursday, 17:45, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a same price british restaurant.\nChunk 2: I also need the price.\nChunk 3: Yes, please look in another part of town.\nChunk 4: Yes please for one person at 17:45 on Thursday.\nChunk 5: No, can you also help me book a taxi?\nChunk 6: I want to find a guesthouse.\nChunk 7: The time is 17:45, 4.\nChunk 8: Nope That's all Thank you Bye now."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=modify_constraint; cuisine+=british; price+=same price; destination+=find a same price british restaurant. C2 [SKIP: repeated_information]. C3 goal=compare_alternative; acceptance=selected_option. C4 goal=confirm_booking; time+=17:45; day+=thursday; acceptance=selected_option. C5 domain=taxi; goal=booking. C6 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C7 time+=4. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi, hotel; goal=search, modify_constraint, compare_alternative, confirm_booking, booking; food=british; price=same price; destination=find a same price british restaurant, find a guesthouse; when=thursday, 17:45, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a same price british restaurant.\nChunk 2: I also need the price.\nChunk 3: Yes, please look in another part of town.\nChunk 4: Yes please for one person at 17:45 on Thursday.\nChunk 5: No, can you also help me book a taxi?\nChunk 6: I want to find a guesthouse.\nChunk 7: The time is 17:45, 4.\nChunk 8: Nope That's all Thank you Bye now.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is modify constraint; cuisine: british; price: same price; destination: find a same price british restaurant. Next, the goal is compare alternative; acceptance: selected_option. Next, the goal is confirm booking; time: 17:45; day: thursday; acceptance: selected_option. Next, the topic is taxi; the goal is booking. Next, the topic is hotel; hotel type: guesthouse; destination: find a guesthouse. Finally, time: 4.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is hotel. the goal is booking.. cuisine: british; price: same price; destination: find a same price british restaurant., find a guesthouse.; acceptance: selected_option.; time: 17:45, 4.; day: thursday; hotel type: guesthouse.", "trace": "C1 domain=restaurant; goal=modify_constraint; cuisine+=british; price+=same price; destination+=find a same price british restaurant. C2 [SKIP: repeated_information]. C3 goal=compare_alternative; acceptance=selected_option. C4 goal=confirm_booking; time+=17:45; day+=thursday; acceptance=selected_option. C5 domain=taxi; goal=booking. C6 domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse. C7 time+=4. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a same price british restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is modify constraint; cuisine: british; price: same price; destination: find a same price british restaurant..", "trace": "domain=restaurant; goal=modify_constraint; cuisine+=british; price+=same price; destination+=find a same price british restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need the price.", "streaming_reasoning": "The content at C2 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, please look in another part of town.", "streaming_reasoning": "As more information arrives, the goal is compare alternative; acceptance: selected_option..", "trace": "goal=compare_alternative; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes please for one person at 17:45 on Thursday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking; time: 17:45; day: thursday; acceptance: selected_option..", "trace": "goal=confirm_booking; time+=17:45; day+=thursday; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, can you also help me book a taxi?", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is booking..", "trace": "domain=taxi; goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a guesthouse.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse; destination: find a guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse; destination+=find a guesthouse."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 17:45, 4.", "streaming_reasoning": "As more information arrives, time: 4..", "trace": "time+=4."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Nope That's all Thank you Bye now.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is british; price is same price; destination is find a same price british restaurant; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi, hotel; goal=search, modify_constraint, compare_alternative, confirm_booking, booking; food=british; price=same price; destination=find a same price british restaurant, find a guesthouse; when=thursday, 17:45, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002758", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a taxi that leaves from kettle's yard and leaves after 15:15.\nChunk 2: I am going to Yu Garden.\nChunk 3: Thank you so much!\nChunk 4: That is all I need today.", "streaming_reasoning": "C1 domain=taxi; goal=search; time+=15:15. C2 destination+=yu garden. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi; goal=search; destination=yu garden; when=15:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a taxi that leaves from kettle's yard and leaves after 15:15.\nChunk 2: I am going to Yu Garden.\nChunk 3: Thank you so much!\nChunk 4: That is all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search; time+=15:15. C2 destination+=yu garden. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi; goal=search; destination=yu garden; when=15:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a taxi that leaves from kettle's yard and leaves after 15:15.\nChunk 2: I am going to Yu Garden.\nChunk 3: Thank you so much!\nChunk 4: That is all I need today.", "input_token_count": 38, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search; time: 15:15. Finally, destination: yu garden.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is search. time: 15:15.; destination: yu garden..", "trace": "C1 domain=taxi; goal=search; time+=15:15. C2 destination+=yu garden. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a taxi that leaves from kettle's yard and leaves after 15:15.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search; time: 15:15..", "trace": "domain=taxi; goal=search; time+=15:15."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am going to Yu Garden.", "streaming_reasoning": "As more information arrives, destination: yu garden..", "trace": "destination+=yu garden."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you so much!", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That is all I need today.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is yu garden; timing is 15:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search; destination=yu garden; when=15:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002759", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I would like a table for 7 on Sunday.\nChunk 2: I want to eat at 18:15.\nChunk 3: Yes, I'm interested in visiting the broughton house gallery.\nChunk 4: do they have enough parking?\nChunk 5: I need help with taxi.\nChunk 6: The time is 18:15.\nChunk 7: There are 7 in my group.\nChunk 8: Thanks a lot, goodbye!", "streaming_reasoning": "C1 day+=sunday; acceptance=selected_option. C2 domain=restaurant; goal=search; time+=18:15; destination+=eat at 18:15. C3 domain=attraction; acceptance=selected_option. C4 amenities+=parking. C5 domain=taxi. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, attraction, taxi; goal=search; amenities=parking; destination=eat at 18:15; when=sunday, 18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I would like a table for 7 on Sunday.\nChunk 2: I want to eat at 18:15.\nChunk 3: Yes, I'm interested in visiting the broughton house gallery.\nChunk 4: do they have enough parking?\nChunk 5: I need help with taxi.\nChunk 6: The time is 18:15.\nChunk 7: There are 7 in my group.\nChunk 8: Thanks a lot, goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=sunday; acceptance=selected_option. C2 domain=restaurant; goal=search; time+=18:15; destination+=eat at 18:15. C3 domain=attraction; acceptance=selected_option. C4 amenities+=parking. C5 domain=taxi. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, attraction, taxi; goal=search; amenities=parking; destination=eat at 18:15; when=sunday, 18:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I would like a table for 7 on Sunday.\nChunk 2: I want to eat at 18:15.\nChunk 3: Yes, I'm interested in visiting the broughton house gallery.\nChunk 4: do they have enough parking?\nChunk 5: I need help with taxi.\nChunk 6: The time is 18:15.\nChunk 7: There are 7 in my group.\nChunk 8: Thanks a lot, goodbye!", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, day: sunday; acceptance: selected_option. Next, the topic is restaurant; the goal is search; time: 18:15; destination: eat at 18:15. Next, the topic is attraction; acceptance: selected_option. Next, amenities: parking. Next, the topic is taxi. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is taxi.. the goal is search. day: sunday; acceptance: selected_option.; time: 18:15; destination: eat at 18:15.; amenities: parking.; intent: context_update..", "trace": "C1 day+=sunday; acceptance=selected_option. C2 domain=restaurant; goal=search; time+=18:15; destination+=eat at 18:15. C3 domain=attraction; acceptance=selected_option. C4 amenities+=parking. C5 domain=taxi. C6 intent=context_update. C7 intent=context_update. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I would like a table for 7 on Sunday.", "streaming_reasoning": "Initially, day: sunday; acceptance: selected_option..", "trace": "day+=sunday; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to eat at 18:15.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; time: 18:15; destination: eat at 18:15..", "trace": "domain=restaurant; goal=search; time+=18:15; destination+=eat at 18:15."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I'm interested in visiting the broughton house gallery.", "streaming_reasoning": "As more information arrives, the topic is attraction; acceptance: selected_option..", "trace": "domain=attraction; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "do they have enough parking?", "streaming_reasoning": "As more information arrives, amenities: parking..", "trace": "amenities+=parking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need help with taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 18:15.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "There are 7 in my group.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks a lot, goodbye!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: amenities is parking; destination is eat at 18:15; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction, taxi; goal=search; amenities=parking; destination=eat at 18:15; when=sunday, 18:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002760", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: It should be in the centre part of town.\nChunk 3: The time is 2.\nChunk 4: Do you have anything that is 2 star rated in the centre?\nChunk 5: That is all I need.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=centre. C3 time+=2. C4 stars+=2 stars. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search; area=centre; stars=2 stars; destination=find a hotel; when=2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a hotel.\nChunk 2: It should be in the centre part of town.\nChunk 3: The time is 2.\nChunk 4: Do you have anything that is 2 star rated in the centre?\nChunk 5: That is all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=centre. C3 time+=2. C4 stars+=2 stars. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search; area=centre; stars=2 stars; destination=find a hotel; when=2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: It should be in the centre part of town.\nChunk 3: The time is 2.\nChunk 4: Do you have anything that is 2 star rated in the centre?\nChunk 5: That is all I need.", "input_token_count": 46, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, area: centre. Next, time: 2. Finally, star rating: 2 stars.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is search. hotel type: hotel; destination: find a hotel.; area: centre.; time: 2.; star rating: 2 stars..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 area+=centre. C3 time+=2. C4 stars+=2 stars. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is 2.", "streaming_reasoning": "As more information arrives, time: 2..", "trace": "time+=2."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Do you have anything that is 2 star rated in the centre?", "streaming_reasoning": "As more information arrives, star rating: 2 stars..", "trace": "stars+=2 stars."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That is all I need.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; star rating is 2 stars; destination is find a hotel; timing is 2. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search; area=centre; stars=2 stars; destination=find a hotel; when=2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002761", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I was actually looking for an Indian restaurant Is there one?\nChunk 2: Can you please book me a table for one at 16:30 on Sunday Yes, please.\nChunk 3: I need a train to broxbourne.\nChunk 4: Yes, I will leave Cambridge on Monday sometime after 18:15.\nChunk 5: Yes please book me a seat and I will need a reference number please.\nChunk 6: No, that will be all.\nChunk 7: Thank you for your help.\nChunk 8: Have a great day!", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=indian. C2 goal=confirm_booking; time+=16:30; day+=sunday; goal=confirm_booking. C3 domain=train; destination+=broxbourne. C4 time+=18:15; day+=monday; goal=confirm_booking. C5 goal=request_info; requested_info+=reference_number; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, train; goal=search, booking, confirm_booking, request_info; food=indian; destination=broxbourne; requested_info=reference_number; when=sunday, monday, 16:30, 18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, I was actually looking for an Indian restaurant Is there one?\nChunk 2: Can you please book me a table for one at 16:30 on Sunday Yes, please.\nChunk 3: I need a train to broxbourne.\nChunk 4: Yes, I will leave Cambridge on Monday sometime after 18:15.\nChunk 5: Yes please book me a seat and I will need a reference number please.\nChunk 6: No, that will be all.\nChunk 7: Thank you for your help.\nChunk 8: Have a great day!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=indian. C2 goal=confirm_booking; time+=16:30; day+=sunday; goal=confirm_booking. C3 domain=train; destination+=broxbourne. C4 time+=18:15; day+=monday; goal=confirm_booking. C5 goal=request_info; requested_info+=reference_number; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, train; goal=search, booking, confirm_booking, request_info; food=indian; destination=broxbourne; requested_info=reference_number; when=sunday, monday, 16:30, 18:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I was actually looking for an Indian restaurant Is there one?\nChunk 2: Can you please book me a table for one at 16:30 on Sunday Yes, please.\nChunk 3: I need a train to broxbourne.\nChunk 4: Yes, I will leave Cambridge on Monday sometime after 18:15.\nChunk 5: Yes please book me a seat and I will need a reference number please.\nChunk 6: No, that will be all.\nChunk 7: Thank you for your help.\nChunk 8: Have a great day!", "input_token_count": 89, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: indian. Next, the goal is confirm booking.; time: 16:30; day: sunday. Next, the topic is train; destination: broxbourne. Next, the goal is confirm booking.; time: 18:15; day: monday. Finally, the goal is confirm booking.; requested information: reference_number.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is confirm booking.. cuisine: indian.; time: 16:30, 18:15; day: sunday, monday; destination: broxbourne.; requested information: reference_number.", "trace": "C1 domain=restaurant; goal=search; cuisine+=indian. C2 goal=confirm_booking; time+=16:30; day+=sunday; goal=confirm_booking. C3 domain=train; destination+=broxbourne. C4 time+=18:15; day+=monday; goal=confirm_booking. C5 goal=request_info; requested_info+=reference_number; goal=confirm_booking. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, I was actually looking for an Indian restaurant Is there one?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: indian..", "trace": "domain=restaurant; goal=search; cuisine+=indian."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you please book me a table for one at 16:30 on Sunday Yes, please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 16:30; day: sunday.", "trace": "goal=confirm_booking; time+=16:30; day+=sunday; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need a train to broxbourne.", "streaming_reasoning": "As more information arrives, the topic is train; destination: broxbourne..", "trace": "domain=train; destination+=broxbourne."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I will leave Cambridge on Monday sometime after 18:15.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 18:15; day: monday.", "trace": "time+=18:15; day+=monday; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes please book me a seat and I will need a reference number please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "goal=request_info; requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, that will be all.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Have a great day!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is indian; destination is broxbourne; requested information is reference_number; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, train; goal=search, booking, confirm_booking, request_info; food=indian; destination=broxbourne; requested_info=reference_number; when=sunday, monday, 16:30, 18:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002763", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm leaving from Ely, and I should be in Cambridge no later than 9:00, on Monday.\nChunk 2: I have a meeting in town.\nChunk 3: I would prefer TR0755.\nChunk 4: Yes, that would be great.\nChunk 5: Thank you very much.\nChunk 6: I would like two tickets please.\nChunk 7: I just need to know the id.\nChunk 8: I do not need to book it.\nChunk 9: No, that's all Thank you.", "streaming_reasoning": "C1 time+=9:00; day+=monday. C2 intent=context_update. C3 intent=context_update. C4 acceptance=selected_option. C5 [SKIP: thanks_only]. C6 intent=context_update. C7 goal=search; destination+=know the id. C8 goal=booking. C9 [SKIP: closing_only].", "deep_reasoning": "Need goal=search, booking; destination=know the id; when=monday, 9:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm leaving from Ely, and I should be in Cambridge no later than 9:00, on Monday.\nChunk 2: I have a meeting in town.\nChunk 3: I would prefer TR0755.\nChunk 4: Yes, that would be great.\nChunk 5: Thank you very much.\nChunk 6: I would like two tickets please.\nChunk 7: I just need to know the id.\nChunk 8: I do not need to book it.\nChunk 9: No, that's all Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=9:00; day+=monday. C2 intent=context_update. C3 intent=context_update. C4 acceptance=selected_option. C5 [SKIP: thanks_only]. C6 intent=context_update. C7 goal=search; destination+=know the id. C8 goal=booking. C9 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search, booking; destination=know the id; when=monday, 9:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm leaving from Ely, and I should be in Cambridge no later than 9:00, on Monday.\nChunk 2: I have a meeting in town.\nChunk 3: I would prefer TR0755.\nChunk 4: Yes, that would be great.\nChunk 5: Thank you very much.\nChunk 6: I would like two tickets please.\nChunk 7: I just need to know the id.\nChunk 8: I do not need to book it.\nChunk 9: No, that's all Thank you.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 9:00; day: monday. Next, intent: context_update. Next, intent: context_update. Next, acceptance: selected_option. Next, intent: context_update. Next, the goal is search; destination: know the id. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is booking.. time: 9:00; day: monday.; intent: context_update.; acceptance: selected_option.; destination: know the id..", "trace": "C1 time+=9:00; day+=monday. C2 intent=context_update. C3 intent=context_update. C4 acceptance=selected_option. C5 [SKIP: thanks_only]. C6 intent=context_update. C7 goal=search; destination+=know the id. C8 goal=booking. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm leaving from Ely, and I should be in Cambridge no later than 9:00, on Monday.", "streaming_reasoning": "Initially, time: 9:00; day: monday..", "trace": "time+=9:00; day+=monday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I have a meeting in town.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would prefer TR0755.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, that would be great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I would like two tickets please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I just need to know the id.", "streaming_reasoning": "As more information arrives, the goal is search; destination: know the id..", "trace": "goal=search; destination+=know the id."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I do not need to book it.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No, that's all Thank you.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search, booking; destination=know the id; when=monday, 9:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001850", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I was able to save a blind lady from falling down an escalator.\nChunk 2: I was able to save a blind lady from falling down an escalator Is she ok?\nChunk 3: Im glad you were close by!\nChunk 4: She was very alarmed and rightfully so.\nChunk 5: I'm usually not a nice person, but I'm glad I did the right thing that time!", "streaming_reasoning": "C1 need=validation. C2 [SKIP: repeated_information]. C3 emotion=happy; need=celebration. C4 support_signal=received. C5 emotion=happy; event=usually not a nice person, but I'm glad I did the right.", "deep_reasoning": "User feels happy because usually not a nice person, but I'm glad I did the right and needs celebration.", "answer": "That is worth celebrating, especially because usually not a nice person, but I'm glad I did the right. Take a moment to enjoy it and share the good news with someone who will be happy for you.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I was able to save a blind lady from falling down an escalator.\nChunk 2: I was able to save a blind lady from falling down an escalator Is she ok?\nChunk 3: Im glad you were close by!\nChunk 4: She was very alarmed and rightfully so.\nChunk 5: I'm usually not a nice person, but I'm glad I did the right thing that time!"}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 [SKIP: repeated_information]. C3 emotion=happy; need=celebration. C4 support_signal=received. C5 emotion=happy; event=usually not a nice person, but I'm glad I did the right.\n\nDeep reasoning: User feels happy because usually not a nice person, but I'm glad I did the right and needs celebration.\n\nAnswer: That is worth celebrating, especially because usually not a nice person, but I'm glad I did the right. Take a moment to enjoy it and share the good news with someone who will be happy for you."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I was able to save a blind lady from falling down an escalator.\nChunk 2: I was able to save a blind lady from falling down an escalator Is she ok?\nChunk 3: Im glad you were close by!\nChunk 4: She was very alarmed and rightfully so.\nChunk 5: I'm usually not a nice person, but I'm glad I did the right thing that time!", "input_token_count": 68, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user expresses happy; the user needs celebration. Next, the user signals support or acknowledgment. Finally, the user expresses happy; event: usually not a nice person.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 need=validation. C2 [SKIP: repeated_information]. C3 emotion=happy; need=celebration. C4 support_signal=received. C5 emotion=happy; event=usually not a nice person, but I'm glad I did the right.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I was able to save a blind lady from falling down an escalator.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I was able to save a blind lady from falling down an escalator Is she ok?", "streaming_reasoning": "The content at C2 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Im glad you were close by!", "streaming_reasoning": "As more information arrives, the user expresses happy; the user needs celebration..", "trace": "emotion=happy; need=celebration."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "She was very alarmed and rightfully so.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm usually not a nice person, but I'm glad I did the right thing that time!", "streaming_reasoning": "Finally, the user expresses happy; event: usually not a nice person.", "trace": "emotion=happy; event=usually not a nice person, but I'm glad I did the right."}]}, "output": {"deep_reasoning": "User feels happy because usually not a nice person, but I'm glad I did the right and needs celebration.", "answer": "That is worth celebrating, especially because usually not a nice person, but I'm glad I did the right. Take a moment to enjoy it and share the good news with someone who will be happy for you."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002764", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to travel on Tuesday and leave sometime after 11:15 Not really.\nChunk 2: Can I also please have the travel time of the train.\nChunk 3: What time will the train arrive?\nChunk 4: Also, I am looking to stay at the Gonville Hotel.\nChunk 5: What availability is there for that hotel?\nChunk 6: Oh, I just wanted information.\nChunk 7: Does that hotel have free parking Excellent.\nChunk 8: Thanks for the help.\nChunk 9: No, that is all I need for today.", "streaming_reasoning": "C1 time+=11:15; day+=tuesday; destination+=travel on tuesday and leave sometime afte. C2 domain=train; goal=request_info; requested_info+=travel_time. C3 goal=request_info. C4 domain=hotel; hotel_type+=hotel; destination+=stay at the gonville hotel. C5 goal=request_info. C6 intent=context_update. C7 amenities+=parking, free parking. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, hotel; goal=request_info; amenities=parking, free parking; destination=travel on tuesday and leave sometime afte, stay at the gonville hotel; requested_info=travel_time; when=tuesday, 11:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to travel on Tuesday and leave sometime after 11:15 Not really.\nChunk 2: Can I also please have the travel time of the train.\nChunk 3: What time will the train arrive?\nChunk 4: Also, I am looking to stay at the Gonville Hotel.\nChunk 5: What availability is there for that hotel?\nChunk 6: Oh, I just wanted information.\nChunk 7: Does that hotel have free parking Excellent.\nChunk 8: Thanks for the help.\nChunk 9: No, that is all I need for today."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=11:15; day+=tuesday; destination+=travel on tuesday and leave sometime afte. C2 domain=train; goal=request_info; requested_info+=travel_time. C3 goal=request_info. C4 domain=hotel; hotel_type+=hotel; destination+=stay at the gonville hotel. C5 goal=request_info. C6 intent=context_update. C7 amenities+=parking, free parking. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, hotel; goal=request_info; amenities=parking, free parking; destination=travel on tuesday and leave sometime afte, stay at the gonville hotel; requested_info=travel_time; when=tuesday, 11:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to travel on Tuesday and leave sometime after 11:15 Not really.\nChunk 2: Can I also please have the travel time of the train.\nChunk 3: What time will the train arrive?\nChunk 4: Also, I am looking to stay at the Gonville Hotel.\nChunk 5: What availability is there for that hotel?\nChunk 6: Oh, I just wanted information.\nChunk 7: Does that hotel have free parking Excellent.\nChunk 8: Thanks for the help.\nChunk 9: No, that is all I need for today.", "input_token_count": 91, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 11:15; day: tuesday; destination: travel on tuesday and leave sometime afte. Next, the topic is train; the goal is request info; requested information: travel_time. Next, the goal is request info. Next, the topic is hotel; hotel type: hotel; destination: stay at the gonville hotel. Next, the goal is request info. Next, intent: context_update. Finally, amenities: parking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is request info.. time: 11:15; day: tuesday; destination: travel on tuesday and leave sometime afte., stay at the gonville hotel.; requested information: travel_time.; hotel type: hotel; intent: context_update.; amenities: parking.", "trace": "C1 time+=11:15; day+=tuesday; destination+=travel on tuesday and leave sometime afte. C2 domain=train; goal=request_info; requested_info+=travel_time. C3 goal=request_info. C4 domain=hotel; hotel_type+=hotel; destination+=stay at the gonville hotel. C5 goal=request_info. C6 intent=context_update. C7 amenities+=parking, free parking. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to travel on Tuesday and leave sometime after 11:15 Not really.", "streaming_reasoning": "Initially, time: 11:15; day: tuesday; destination: travel on tuesday and leave sometime afte..", "trace": "time+=11:15; day+=tuesday; destination+=travel on tuesday and leave sometime afte."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I also please have the travel time of the train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is request info; requested information: travel_time..", "trace": "domain=train; goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What time will the train arrive?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Also, I am looking to stay at the Gonville Hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: stay at the gonville hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=stay at the gonville hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What availability is there for that hotel?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Oh, I just wanted information.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Does that hotel have free parking Excellent.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks for the help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No, that is all I need for today.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: amenities is parking; destination is travel on tuesday and leave sometime afte; requested information is travel_time; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=request_info; amenities=parking, free parking; destination=travel on tuesday and leave sometime afte, stay at the gonville hotel; requested_info=travel_time; when=tuesday, 11:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002765", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok that will have to do then.\nChunk 2: Please give me the reference number and have the taxi commute between both places, car type and contact info please.\nChunk 3: I would only require arriving to the restaurant by the booked time.\nChunk 4: I want British food at a moderate price.\nChunk 5: I want to find a restaurant.\nChunk 6: It should be in the north part of town.\nChunk 7: The time is friday, 7, 19:30.\nChunk 8: Please make a booking.\nChunk 9: I just need to arrive at the restaurant by the booked time Thank you.\nChunk 10: That is all I need.", "streaming_reasoning": "C1 destination+=do then. C2 domain=taxi; goal=request_info; requested_info+=reference_number. C3 domain=restaurant. C4 goal=search; cuisine+=british; price+=moderate. C5 destination+=find a restaurant. C6 area+=north. C7 time+=7, 19:30; day+=friday. C8 goal=booking. C9 intent=context_update. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi, restaurant; goal=request_info, search, booking; area=north; food=british; price=moderate; destination=do then, find a restaurant; requested_info=reference_number; when=friday, 7, 19:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Ok that will have to do then.\nChunk 2: Please give me the reference number and have the taxi commute between both places, car type and contact info please.\nChunk 3: I would only require arriving to the restaurant by the booked time.\nChunk 4: I want British food at a moderate price.\nChunk 5: I want to find a restaurant.\nChunk 6: It should be in the north part of town.\nChunk 7: The time is friday, 7, 19:30.\nChunk 8: Please make a booking.\nChunk 9: I just need to arrive at the restaurant by the booked time Thank you.\nChunk 10: That is all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 destination+=do then. C2 domain=taxi; goal=request_info; requested_info+=reference_number. C3 domain=restaurant. C4 goal=search; cuisine+=british; price+=moderate. C5 destination+=find a restaurant. C6 area+=north. C7 time+=7, 19:30; day+=friday. C8 goal=booking. C9 intent=context_update. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi, restaurant; goal=request_info, search, booking; area=north; food=british; price=moderate; destination=do then, find a restaurant; requested_info=reference_number; when=friday, 7, 19:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok that will have to do then.\nChunk 2: Please give me the reference number and have the taxi commute between both places, car type and contact info please.\nChunk 3: I would only require arriving to the restaurant by the booked time.\nChunk 4: I want British food at a moderate price.\nChunk 5: I want to find a restaurant.\nChunk 6: It should be in the north part of town.\nChunk 7: The time is friday, 7, 19:30.\nChunk 8: Please make a booking.\nChunk 9: I just need to arrive at the restaurant by the booked time Thank you.\nChunk 10: That is all I need.", "input_token_count": 112, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, destination: do then. Next, the topic is taxi; the goal is request info; requested information: reference_number. Next, the topic is restaurant. Next, the goal is search; cuisine: british; price: moderate. Next, destination: find a restaurant. Next, area: north. Next, time: 7; day: friday. Next, the goal is booking. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant.. the goal is booking.. destination: do then., find a restaurant.; requested information: reference_number.; cuisine: british; price: moderate.; area: north.; time: 7; day: friday.; intent: context_update..", "trace": "C1 destination+=do then. C2 domain=taxi; goal=request_info; requested_info+=reference_number. C3 domain=restaurant. C4 goal=search; cuisine+=british; price+=moderate. C5 destination+=find a restaurant. C6 area+=north. C7 time+=7, 19:30; day+=friday. C8 goal=booking. C9 intent=context_update. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Ok that will have to do then.", "streaming_reasoning": "Initially, destination: do then..", "trace": "destination+=do then."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Please give me the reference number and have the taxi commute between both places, car type and contact info please.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is request info; requested information: reference_number..", "trace": "domain=taxi; goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would only require arriving to the restaurant by the booked time.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want British food at a moderate price.", "streaming_reasoning": "As more information arrives, the goal is search; cuisine: british; price: moderate..", "trace": "goal=search; cuisine+=british; price+=moderate."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, destination: find a restaurant..", "trace": "destination+=find a restaurant."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is friday, 7, 19:30.", "streaming_reasoning": "As more information arrives, time: 7; day: friday..", "trace": "time+=7, 19:30; day+=friday."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I just need to arrive at the restaurant by the booked time Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That is all I need.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of request info. Key information: area is north; cuisine is british; price is moderate; destination is do then; requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, restaurant; goal=request_info, search, booking; area=north; food=british; price=moderate; destination=do then, find a restaurant; requested_info=reference_number; when=friday, 7, 19:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002766", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What is the entrance fee?\nChunk 2: Thanks!\nChunk 3: I also need a train to Cambridge on Wednesday.\nChunk 4: I am leaving ely after 20:15.\nChunk 5: Can you provide more information for that train?\nChunk 6: I'd like to book a seat on that train Please provide confirmation.\nChunk 7: That's all i need for today.\nChunk 8: Thanks very much for your help.", "streaming_reasoning": "C1 goal=request_info; requested_info+=entrance_fee. C2 [SKIP: thanks_only]. C3 domain=train; goal=search; day+=wednesday; destination+=cambridge on wednesday. C4 time+=20:15. C5 goal=request_info. C6 goal=booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=request_info, search, booking; destination=cambridge on wednesday; requested_info=entrance_fee; when=wednesday, 20:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What is the entrance fee?\nChunk 2: Thanks!\nChunk 3: I also need a train to Cambridge on Wednesday.\nChunk 4: I am leaving ely after 20:15.\nChunk 5: Can you provide more information for that train?\nChunk 6: I'd like to book a seat on that train Please provide confirmation.\nChunk 7: That's all i need for today.\nChunk 8: Thanks very much for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=entrance_fee. C2 [SKIP: thanks_only]. C3 domain=train; goal=search; day+=wednesday; destination+=cambridge on wednesday. C4 time+=20:15. C5 goal=request_info. C6 goal=booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=request_info, search, booking; destination=cambridge on wednesday; requested_info=entrance_fee; when=wednesday, 20:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What is the entrance fee?\nChunk 2: Thanks!\nChunk 3: I also need a train to Cambridge on Wednesday.\nChunk 4: I am leaving ely after 20:15.\nChunk 5: Can you provide more information for that train?\nChunk 6: I'd like to book a seat on that train Please provide confirmation.\nChunk 7: That's all i need for today.\nChunk 8: Thanks very much for your help.", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: entrance_fee. Next, the topic is train; the goal is search; day: wednesday; destination: cambridge on wednesday. Next, time: 20:15. Next, the goal is request info. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is booking.. requested information: entrance_fee.; day: wednesday; destination: cambridge on wednesday.; time: 20:15..", "trace": "C1 goal=request_info; requested_info+=entrance_fee. C2 [SKIP: thanks_only]. C3 domain=train; goal=search; day+=wednesday; destination+=cambridge on wednesday. C4 time+=20:15. C5 goal=request_info. C6 goal=booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What is the entrance fee?", "streaming_reasoning": "Initially, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks!", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need a train to Cambridge on Wednesday.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: wednesday; destination: cambridge on wednesday..", "trace": "domain=train; goal=search; day+=wednesday; destination+=cambridge on wednesday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am leaving ely after 20:15.", "streaming_reasoning": "As more information arrives, time: 20:15..", "trace": "time+=20:15."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you provide more information for that train?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'd like to book a seat on that train Please provide confirmation.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's all i need for today.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks very much for your help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: destination is cambridge on wednesday; requested information is entrance_fee; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search, booking; destination=cambridge on wednesday; requested_info=entrance_fee; when=wednesday, 20:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002767", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I am looking for a restaurant in any area that serves danish food.\nChunk 2: what about international food?\nChunk 3: I do not have a preference.\nChunk 4: Can I get the phone number and postcode, please?\nChunk 5: Thank you bye bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=any; cuisine+=danish. C2 goal=recommendation. C3 goal=modify_constraint. C4 goal=request_info; requested_info+=phone, postcode. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, request_info; area=any; food=danish; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, I am looking for a restaurant in any area that serves danish food.\nChunk 2: what about international food?\nChunk 3: I do not have a preference.\nChunk 4: Can I get the phone number and postcode, please?\nChunk 5: Thank you bye bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=any; cuisine+=danish. C2 goal=recommendation. C3 goal=modify_constraint. C4 goal=request_info; requested_info+=phone, postcode. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, request_info; area=any; food=danish; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I am looking for a restaurant in any area that serves danish food.\nChunk 2: what about international food?\nChunk 3: I do not have a preference.\nChunk 4: Can I get the phone number and postcode, please?\nChunk 5: Thank you bye bye.", "input_token_count": 47, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: any; cuisine: danish. Next, the goal is recommendation. Next, the goal is modify constraint. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: any; cuisine: danish.; requested information: phone.", "trace": "C1 domain=restaurant; goal=search; area+=any; cuisine+=danish. C2 goal=recommendation. C3 goal=modify_constraint. C4 goal=request_info; requested_info+=phone, postcode. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, I am looking for a restaurant in any area that serves danish food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: any; cuisine: danish..", "trace": "domain=restaurant; goal=search; area+=any; cuisine+=danish."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "what about international food?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I do not have a preference.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I get the phone number and postcode, please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you bye bye.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is any; cuisine is danish; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, request_info; area=any; food=danish; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002768", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a hotel called huntingdon marriott hotel Thank you.\nChunk 2: Can you book it for 5 people and 4 nights starting on Thursday?\nChunk 3: I'm also looking for a train departing Cambridge and arriving at 8:30.\nChunk 4: Can you help out?\nChunk 5: We would like to go to peterborough on Friday.\nChunk 6: Yes, please book it for 5 people.\nChunk 7: Thank you for all your help.\nChunk 8: Have a great day.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 goal=booking; time+=5, 4; day+=thursday; party_size+=5 people; stay_length+=4 nights. C3 domain=train; time+=8:30. C4 goal=request_info. C5 day+=friday; destination+=go to peterborough on friday. C6 [SKIP: repeated_information]. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, train; goal=search, booking; party_size=5 people; stay_length=4 nights; destination=go to peterborough on friday; when=thursday, friday, 5, 4, 8:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a hotel called huntingdon marriott hotel Thank you.\nChunk 2: Can you book it for 5 people and 4 nights starting on Thursday?\nChunk 3: I'm also looking for a train departing Cambridge and arriving at 8:30.\nChunk 4: Can you help out?\nChunk 5: We would like to go to peterborough on Friday.\nChunk 6: Yes, please book it for 5 people.\nChunk 7: Thank you for all your help.\nChunk 8: Have a great day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel. C2 goal=booking; time+=5, 4; day+=thursday; party_size+=5 people; stay_length+=4 nights. C3 domain=train; time+=8:30. C4 goal=request_info. C5 day+=friday; destination+=go to peterborough on friday. C6 [SKIP: repeated_information]. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, train; goal=search, booking; party_size=5 people; stay_length=4 nights; destination=go to peterborough on friday; when=thursday, friday, 5, 4, 8:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a hotel called huntingdon marriott hotel Thank you.\nChunk 2: Can you book it for 5 people and 4 nights starting on Thursday?\nChunk 3: I'm also looking for a train departing Cambridge and arriving at 8:30.\nChunk 4: Can you help out?\nChunk 5: We would like to go to peterborough on Friday.\nChunk 6: Yes, please book it for 5 people.\nChunk 7: Thank you for all your help.\nChunk 8: Have a great day.", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel. Next, the goal is booking; time: 5; day: thursday; party size: 5 people; stay length: 4 nights. Next, the topic is train; time: 8:30. Next, the goal is request info. Finally, day: friday; destination: go to peterborough on friday.  Some chunks were skipped because they contained closing_only or repeated_information or thanks_only. In summary, The overall topic is train. the goal is request info.. hotel type: hotel.; time: 5, 8:30.; day: thursday, friday; party size: 5 people; stay length: 4 nights.; destination: go to peterborough on friday..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 goal=booking; time+=5, 4; day+=thursday; party_size+=5 people; stay_length+=4 nights. C3 domain=train; time+=8:30. C4 goal=request_info. C5 day+=friday; destination+=go to peterborough on friday. C6 [SKIP: repeated_information]. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a hotel called huntingdon marriott hotel Thank you.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you book it for 5 people and 4 nights starting on Thursday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 5; day: thursday; party size: 5 people; stay length: 4 nights..", "trace": "goal=booking; time+=5, 4; day+=thursday; party_size+=5 people; stay_length+=4 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm also looking for a train departing Cambridge and arriving at 8:30.", "streaming_reasoning": "As more information arrives, the topic is train; time: 8:30..", "trace": "domain=train; time+=8:30."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you help out?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "We would like to go to peterborough on Friday.", "streaming_reasoning": "As more information arrives, day: friday; destination: go to peterborough on friday..", "trace": "day+=friday; destination+=go to peterborough on friday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, please book it for 5 people.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 5 people; stay length is 4 nights; destination is go to peterborough on friday; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, train; goal=search, booking; party_size=5 people; stay_length=4 nights; destination=go to peterborough on friday; when=thursday, friday, 5, 4, 8:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002769", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can I please get the reference number?\nChunk 2: I need help with train.\nChunk 3: The time is thursday, 9:15.\nChunk 4: I will be departing from broxbourne.\nChunk 5: No, I only need the train's departure time and travel time.\nChunk 6: Can you verify that the train is departing on Thursday?\nChunk 7: No thanks That does it.\nChunk 8: Have a nice night Goodbye.", "streaming_reasoning": "C1 goal=request_info; requested_info+=reference_number. C2 domain=train; goal=search. C3 time+=9:15; day+=thursday. C4 departure+=broxbourne. C5 requested_info+=travel_time. C6 goal=request_info. C7 [SKIP: thanks_only]. C8 intent=context_update.", "deep_reasoning": "Need domain=train; goal=request_info, search; departure=broxbourne; requested_info=reference_number, travel_time; when=thursday, 9:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can I please get the reference number?\nChunk 2: I need help with train.\nChunk 3: The time is thursday, 9:15.\nChunk 4: I will be departing from broxbourne.\nChunk 5: No, I only need the train's departure time and travel time.\nChunk 6: Can you verify that the train is departing on Thursday?\nChunk 7: No thanks That does it.\nChunk 8: Have a nice night Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=reference_number. C2 domain=train; goal=search. C3 time+=9:15; day+=thursday. C4 departure+=broxbourne. C5 requested_info+=travel_time. C6 goal=request_info. C7 [SKIP: thanks_only]. C8 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=request_info, search; departure=broxbourne; requested_info=reference_number, travel_time; when=thursday, 9:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can I please get the reference number?\nChunk 2: I need help with train.\nChunk 3: The time is thursday, 9:15.\nChunk 4: I will be departing from broxbourne.\nChunk 5: No, I only need the train's departure time and travel time.\nChunk 6: Can you verify that the train is departing on Thursday?\nChunk 7: No thanks That does it.\nChunk 8: Have a nice night Goodbye.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: reference_number. Next, the topic is train; the goal is search. Next, time: 9:15; day: thursday. Next, departure point: broxbourne. Next, requested information: travel_time. Next, the goal is request info. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is request info.. requested information: reference_number., travel_time.; time: 9:15; day: thursday.; departure point: broxbourne.; intent: context_update..", "trace": "C1 goal=request_info; requested_info+=reference_number. C2 domain=train; goal=search. C3 time+=9:15; day+=thursday. C4 departure+=broxbourne. C5 requested_info+=travel_time. C6 goal=request_info. C7 [SKIP: thanks_only]. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can I please get the reference number?", "streaming_reasoning": "Initially, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is thursday, 9:15.", "streaming_reasoning": "As more information arrives, time: 9:15; day: thursday..", "trace": "time+=9:15; day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I will be departing from broxbourne.", "streaming_reasoning": "As more information arrives, departure point: broxbourne..", "trace": "departure+=broxbourne."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, I only need the train's departure time and travel time.", "streaming_reasoning": "As more information arrives, requested information: travel_time..", "trace": "requested_info+=travel_time."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you verify that the train is departing on Thursday?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No thanks That does it.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Have a nice night Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: departure point is broxbourne; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search; departure=broxbourne; requested_info=reference_number, travel_time; when=thursday, 9:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002770", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like an expensive 3-star hotel.\nChunk 2: What do you recommend?\nChunk 3: It is for 6 people.\nChunk 4: The time is thursday, 6, 3.\nChunk 5: Please make a booking.\nChunk 6: Yes, can you please book a room with the details I already provided.\nChunk 7: Thank you so much.\nChunk 8: I appreciate your help with this.\nChunk 9: That is all, thank you for all your help.", "streaming_reasoning": "C1 domain=hotel; price+=expensive; hotel_type+=hotel. C2 goal=recommendation. C3 party_size+=6 people. C4 time+=6, 3; day+=thursday. C5 goal=booking. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: thanks_only]. C8 goal=search. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=recommendation, booking, confirm_booking, search; price=expensive; party_size=6 people; when=thursday, 6, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like an expensive 3-star hotel.\nChunk 2: What do you recommend?\nChunk 3: It is for 6 people.\nChunk 4: The time is thursday, 6, 3.\nChunk 5: Please make a booking.\nChunk 6: Yes, can you please book a room with the details I already provided.\nChunk 7: Thank you so much.\nChunk 8: I appreciate your help with this.\nChunk 9: That is all, thank you for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; price+=expensive; hotel_type+=hotel. C2 goal=recommendation. C3 party_size+=6 people. C4 time+=6, 3; day+=thursday. C5 goal=booking. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: thanks_only]. C8 goal=search. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=recommendation, booking, confirm_booking, search; price=expensive; party_size=6 people; when=thursday, 6, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like an expensive 3-star hotel.\nChunk 2: What do you recommend?\nChunk 3: It is for 6 people.\nChunk 4: The time is thursday, 6, 3.\nChunk 5: Please make a booking.\nChunk 6: Yes, can you please book a room with the details I already provided.\nChunk 7: Thank you so much.\nChunk 8: I appreciate your help with this.\nChunk 9: That is all, thank you for all your help.", "input_token_count": 76, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; price: expensive; hotel type: hotel. Next, the goal is recommendation. Next, party size: 6 people. Next, time: 6; day: thursday. Next, the goal is booking. Next, the goal is confirm booking. Finally, the goal is search.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is search.. price: expensive; hotel type: hotel.; party size: 6 people.; time: 6; day: thursday..", "trace": "C1 domain=hotel; price+=expensive; hotel_type+=hotel. C2 goal=recommendation. C3 party_size+=6 people. C4 time+=6, 3; day+=thursday. C5 goal=booking. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: thanks_only]. C8 goal=search. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like an expensive 3-star hotel.", "streaming_reasoning": "Initially, the topic is hotel; price: expensive; hotel type: hotel..", "trace": "domain=hotel; price+=expensive; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What do you recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 6 people.", "streaming_reasoning": "As more information arrives, party size: 6 people..", "trace": "party_size+=6 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is thursday, 6, 3.", "streaming_reasoning": "As more information arrives, time: 6; day: thursday..", "trace": "time+=6, 3; day+=thursday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, can you please book a room with the details I already provided.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you so much.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I appreciate your help with this.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That is all, thank you for all your help.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of recommendation. Key information: price is expensive; party size is 6 people; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=recommendation, booking, confirm_booking, search; price=expensive; party_size=6 people; when=thursday, 6, 3; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002771", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Great, thanks.\nChunk 2: I am also looking to book a train for this Friday.\nChunk 3: I am hoping to leave after 08:45.\nChunk 4: I'm headed to London Liverpool Street from Cambridge.\nChunk 5: Possibly, what time does it arrive at London Liverpool Street?\nChunk 6: What's the travel time on that trip?\nChunk 7: Thank you for your help, I'll pick up tickets at the station.\nChunk 8: Thank you, I think that is it, enjoy your day!", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 domain=train; goal=booking; day+=friday. C3 time+=08:45; destination+=leave after 08:45. C4 amenities+=pool. C5 destination+=london liverpool street. C6 goal=request_info; requested_info+=travel_time. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=booking, request_info; amenities=pool; destination=leave after 08:45, london liverpool street; requested_info=travel_time; when=friday, 08:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Great, thanks.\nChunk 2: I am also looking to book a train for this Friday.\nChunk 3: I am hoping to leave after 08:45.\nChunk 4: I'm headed to London Liverpool Street from Cambridge.\nChunk 5: Possibly, what time does it arrive at London Liverpool Street?\nChunk 6: What's the travel time on that trip?\nChunk 7: Thank you for your help, I'll pick up tickets at the station.\nChunk 8: Thank you, I think that is it, enjoy your day!"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 domain=train; goal=booking; day+=friday. C3 time+=08:45; destination+=leave after 08:45. C4 amenities+=pool. C5 destination+=london liverpool street. C6 goal=request_info; requested_info+=travel_time. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=booking, request_info; amenities=pool; destination=leave after 08:45, london liverpool street; requested_info=travel_time; when=friday, 08:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Great, thanks.\nChunk 2: I am also looking to book a train for this Friday.\nChunk 3: I am hoping to leave after 08:45.\nChunk 4: I'm headed to London Liverpool Street from Cambridge.\nChunk 5: Possibly, what time does it arrive at London Liverpool Street?\nChunk 6: What's the travel time on that trip?\nChunk 7: Thank you for your help, I'll pick up tickets at the station.\nChunk 8: Thank you, I think that is it, enjoy your day!", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is booking; day: friday. Next, time: 08:45; destination: leave after 08:45. Next, amenities: pool. Next, destination: london liverpool street. Finally, the goal is request info; requested information: travel_time.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is request info. day: friday.; time: 08:45; destination: leave after 08:45., london liverpool street.; amenities: pool.; requested information: travel_time..", "trace": "C1 [SKIP: thanks_only]. C2 domain=train; goal=booking; day+=friday. C3 time+=08:45; destination+=leave after 08:45. C4 amenities+=pool. C5 destination+=london liverpool street. C6 goal=request_info; requested_info+=travel_time. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Great, thanks.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also looking to book a train for this Friday.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is booking; day: friday..", "trace": "domain=train; goal=booking; day+=friday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am hoping to leave after 08:45.", "streaming_reasoning": "As more information arrives, time: 08:45; destination: leave after 08:45..", "trace": "time+=08:45; destination+=leave after 08:45."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm headed to London Liverpool Street from Cambridge.", "streaming_reasoning": "As more information arrives, amenities: pool..", "trace": "amenities+=pool."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Possibly, what time does it arrive at London Liverpool Street?", "streaming_reasoning": "As more information arrives, destination: london liverpool street..", "trace": "destination+=london liverpool street."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What's the travel time on that trip?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your help, I'll pick up tickets at the station.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you, I think that is it, enjoy your day!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: amenities is pool; destination is leave after 08:45; requested information is travel_time; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, request_info; amenities=pool; destination=leave after 08:45, london liverpool street; requested_info=travel_time; when=friday, 08:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002772", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure!\nChunk 2: Can I have the address and the area it's located in Okay great.\nChunk 3: Thank you so much.\nChunk 4: I am also looking for a park to visit, can I get the postcode of one Free is perfect.\nChunk 5: That will leave me extra to book a taxi from my hotel.\nChunk 6: I want to find a hotel.\nChunk 7: The time is 14:00 Great!\nChunk 8: Thank you so very much!", "streaming_reasoning": "C1 [SKIP: backchannel_only]. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 domain=attraction; goal=confirm_booking; destination+=visit; requested_info+=postcode; type+=park; acceptance=selected_option. C5 domain=taxi; goal=booking; hotel_type+=hotel. C6 destination+=find a hotel. C7 time+=14:00. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, hotel, taxi; goal=request_info, search, confirm_booking, booking; destination=visit, find a hotel; requested_info=address, postcode; when=14:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sure!\nChunk 2: Can I have the address and the area it's located in Okay great.\nChunk 3: Thank you so much.\nChunk 4: I am also looking for a park to visit, can I get the postcode of one Free is perfect.\nChunk 5: That will leave me extra to book a taxi from my hotel.\nChunk 6: I want to find a hotel.\nChunk 7: The time is 14:00 Great!\nChunk 8: Thank you so very much!"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: backchannel_only]. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 domain=attraction; goal=confirm_booking; destination+=visit; requested_info+=postcode; type+=park; acceptance=selected_option. C5 domain=taxi; goal=booking; hotel_type+=hotel. C6 destination+=find a hotel. C7 time+=14:00. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, hotel, taxi; goal=request_info, search, confirm_booking, booking; destination=visit, find a hotel; requested_info=address, postcode; when=14:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sure!\nChunk 2: Can I have the address and the area it's located in Okay great.\nChunk 3: Thank you so much.\nChunk 4: I am also looking for a park to visit, can I get the postcode of one Free is perfect.\nChunk 5: That will leave me extra to book a taxi from my hotel.\nChunk 6: I want to find a hotel.\nChunk 7: The time is 14:00 Great!\nChunk 8: Thank you so very much!", "input_token_count": 82, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the topic is attraction; the goal is confirm booking; destination: visit; requested information: postcode; type: park; acceptance: selected_option. Next, the topic is taxi; the goal is booking; hotel type: hotel. Next, destination: find a hotel. Finally, time: 14:00.  Some chunks were skipped because they contained backchannel_only or thanks_only. In summary, The overall topic is taxi. the goal is booking. requested information: address., postcode; destination: visit, find a hotel.; type: park; acceptance: selected_option.; hotel type: hotel.; time: 14:00..", "trace": "C1 [SKIP: backchannel_only]. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 domain=attraction; goal=confirm_booking; destination+=visit; requested_info+=postcode; type+=park; acceptance=selected_option. C5 domain=taxi; goal=booking; hotel_type+=hotel. C6 destination+=find a hotel. C7 time+=14:00. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sure!", "streaming_reasoning": "The content at C1 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I have the address and the area it's located in Okay great.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you so much.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am also looking for a park to visit, can I get the postcode of one Free is perfect.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is confirm booking; destination: visit; requested information: postcode; type: park; acceptance: selected_option..", "trace": "domain=attraction; goal=confirm_booking; destination+=visit; requested_info+=postcode; type+=park; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That will leave me extra to book a taxi from my hotel.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is booking; hotel type: hotel..", "trace": "domain=taxi; goal=booking; hotel_type+=hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, destination: find a hotel..", "trace": "destination+=find a hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 14:00 Great!", "streaming_reasoning": "As more information arrives, time: 14:00..", "trace": "time+=14:00."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you so very much!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: destination is visit; requested information is address; timing is 14:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, hotel, taxi; goal=request_info, search, confirm_booking, booking; destination=visit, find a hotel; requested_info=address, postcode; when=14:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002773", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need the phone.\nChunk 2: I also need the postcode.\nChunk 3: I also need the entrance fee sweet, brah.\nChunk 4: i'm also looking to book a train.\nChunk 5: I will be leaving after 8:15 from london kings cross.\nChunk 6: I will travel in Tuesday.\nChunk 7: Arrival is not important Thank you.\nChunk 8: Yes I would really love for you to book the train for 2 people.\nChunk 9: Great, thanks so much!\nChunk 10: That's all I'll be needing Bye bye!", "streaming_reasoning": "C1 goal=request_info; requested_info+=phone. C2 requested_info+=postcode. C3 requested_info+=entrance_fee. C4 domain=train; goal=booking. C5 time+=8:15. C6 day+=tuesday. C7 goal=modify_constraint. C8 goal=confirm_booking; party_size+=2 people; goal=confirm_booking. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info, booking, confirm_booking; party_size=2 people; requested_info=phone, postcode, entrance_fee; when=tuesday, 8:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also need the phone.\nChunk 2: I also need the postcode.\nChunk 3: I also need the entrance fee sweet, brah.\nChunk 4: i'm also looking to book a train.\nChunk 5: I will be leaving after 8:15 from london kings cross.\nChunk 6: I will travel in Tuesday.\nChunk 7: Arrival is not important Thank you.\nChunk 8: Yes I would really love for you to book the train for 2 people.\nChunk 9: Great, thanks so much!\nChunk 10: That's all I'll be needing Bye bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=phone. C2 requested_info+=postcode. C3 requested_info+=entrance_fee. C4 domain=train; goal=booking. C5 time+=8:15. C6 day+=tuesday. C7 goal=modify_constraint. C8 goal=confirm_booking; party_size+=2 people; goal=confirm_booking. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking, confirm_booking; party_size=2 people; requested_info=phone, postcode, entrance_fee; when=tuesday, 8:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need the phone.\nChunk 2: I also need the postcode.\nChunk 3: I also need the entrance fee sweet, brah.\nChunk 4: i'm also looking to book a train.\nChunk 5: I will be leaving after 8:15 from london kings cross.\nChunk 6: I will travel in Tuesday.\nChunk 7: Arrival is not important Thank you.\nChunk 8: Yes I would really love for you to book the train for 2 people.\nChunk 9: Great, thanks so much!\nChunk 10: That's all I'll be needing Bye bye!", "input_token_count": 92, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: phone. Next, requested information: postcode. Next, requested information: entrance_fee. Next, the topic is train; the goal is booking. Next, time: 8:15. Next, day: tuesday. Next, the goal is modify constraint. Finally, the goal is confirm booking.; party size: 2 people.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is confirm booking.. requested information: phone., postcode., entrance_fee.; time: 8:15.; day: tuesday.; party size: 2 people.", "trace": "C1 goal=request_info; requested_info+=phone. C2 requested_info+=postcode. C3 requested_info+=entrance_fee. C4 domain=train; goal=booking. C5 time+=8:15. C6 day+=tuesday. C7 goal=modify_constraint. C8 goal=confirm_booking; party_size+=2 people; goal=confirm_booking. C9 [SKIP: thanks_only]. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also need the phone.", "streaming_reasoning": "Initially, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need the postcode.", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the entrance fee sweet, brah.", "streaming_reasoning": "As more information arrives, requested information: entrance_fee..", "trace": "requested_info+=entrance_fee."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "i'm also looking to book a train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is booking..", "trace": "domain=train; goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will be leaving after 8:15 from london kings cross.", "streaming_reasoning": "As more information arrives, time: 8:15..", "trace": "time+=8:15."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I will travel in Tuesday.", "streaming_reasoning": "As more information arrives, day: tuesday..", "trace": "day+=tuesday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Arrival is not important Thank you.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Yes I would really love for you to book the train for 2 people.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; party size: 2 people.", "trace": "goal=confirm_booking; party_size+=2 people; goal=confirm_booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Great, thanks so much!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That's all I'll be needing Bye bye!", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 2 people; requested information is phone; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking, confirm_booking; party_size=2 people; requested_info=phone, postcode, entrance_fee; when=tuesday, 8:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002774", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a cheap restaurant.\nChunk 2: It should be in the north part of town.\nChunk 3: I also need the address Thank You.", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=cheap; destination+=find a cheap restaurant. C2 area+=north. C3 goal=request_info; requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=north; price=cheap; destination=find a cheap restaurant; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a cheap restaurant.\nChunk 2: It should be in the north part of town.\nChunk 3: I also need the address Thank You."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=cheap; destination+=find a cheap restaurant. C2 area+=north. C3 goal=request_info; requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=north; price=cheap; destination=find a cheap restaurant; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a cheap restaurant.\nChunk 2: It should be in the north part of town.\nChunk 3: I also need the address Thank You.", "input_token_count": 29, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: cheap; destination: find a cheap restaurant. Next, area: north. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. price: cheap; destination: find a cheap restaurant.; area: north.; requested information: address..", "trace": "C1 domain=restaurant; goal=search; price+=cheap; destination+=find a cheap restaurant. C2 area+=north. C3 goal=request_info; requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a cheap restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: cheap; destination: find a cheap restaurant..", "trace": "domain=restaurant; goal=search; price+=cheap; destination+=find a cheap restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the address Thank You.", "streaming_reasoning": "Finally, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; price is cheap; destination is find a cheap restaurant; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=north; price=cheap; destination=find a cheap restaurant; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003444", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: You didn't ring me last night.You said you would.\nChunk 2: I'm sorry to have made you disappointed That's all right.\nChunk 3: But why were you so rude to me at lunch Was I?\nChunk 4: Sorry, I didn'y mean to be I do apologize.\nChunk 5: And why are you yarning now Are you bored?", "streaming_reasoning": "C1 casual_comment=didn't, ring. C2 [SKIP: closing_only]. C3 question=true. C4 casual_comment=sorry, didn'y. C5 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: You didn't ring me last night.You said you would.\nChunk 2: I'm sorry to have made you disappointed That's all right.\nChunk 3: But why were you so rude to me at lunch Was I?\nChunk 4: Sorry, I didn'y mean to be I do apologize.\nChunk 5: And why are you yarning now Are you bored?"}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=didn't, ring. C2 [SKIP: closing_only]. C3 question=true. C4 casual_comment=sorry, didn'y. C5 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: You didn't ring me last night.You said you would.\nChunk 2: I'm sorry to have made you disappointed That's all right.\nChunk 3: But why were you so rude to me at lunch Was I?\nChunk 4: Sorry, I didn'y mean to be I do apologize.\nChunk 5: And why are you yarning now Are you bored?", "input_token_count": 60, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on didn't. Next, the input provides additional context about question=true. Next, the user comments on sorry. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained closing_only.", "trace": "C1 casual_comment=didn't, ring. C2 [SKIP: closing_only]. C3 question=true. C4 casual_comment=sorry, didn'y. C5 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "You didn't ring me last night.You said you would.", "streaming_reasoning": "Initially, the user comments on didn't.", "trace": "casual_comment=didn't, ring."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm sorry to have made you disappointed That's all right.", "streaming_reasoning": "The content at C2 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "But why were you so rude to me at lunch Was I?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Sorry, I didn'y mean to be I do apologize.", "streaming_reasoning": "As more information arrives, the user comments on sorry.", "trace": "casual_comment=sorry, didn'y."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "And why are you yarning now Are you bored?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002776", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to leave after 09:45.\nChunk 2: What time does it arrive by?\nChunk 3: Thanks, can I also find a college to go to.\nChunk 4: If you could recommend one that would be great!\nChunk 5: Could you give me the postcode, address and the area of the one you choose?\nChunk 6: That's all I need for now.\nChunk 7: Thanks!\nChunk 8: Thanks very much, take care!", "streaming_reasoning": "C1 goal=search; time+=09:45; destination+=leave after 09:45. C2 goal=request_info. C3 domain=attraction; goal=request_info; destination+=go to. C4 goal=recommendation. C5 requested_info+=address, postcode. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction; goal=search, request_info, recommendation; destination=leave after 09:45, go to; requested_info=address, postcode; when=09:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to leave after 09:45.\nChunk 2: What time does it arrive by?\nChunk 3: Thanks, can I also find a college to go to.\nChunk 4: If you could recommend one that would be great!\nChunk 5: Could you give me the postcode, address and the area of the one you choose?\nChunk 6: That's all I need for now.\nChunk 7: Thanks!\nChunk 8: Thanks very much, take care!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; time+=09:45; destination+=leave after 09:45. C2 goal=request_info. C3 domain=attraction; goal=request_info; destination+=go to. C4 goal=recommendation. C5 requested_info+=address, postcode. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction; goal=search, request_info, recommendation; destination=leave after 09:45, go to; requested_info=address, postcode; when=09:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to leave after 09:45.\nChunk 2: What time does it arrive by?\nChunk 3: Thanks, can I also find a college to go to.\nChunk 4: If you could recommend one that would be great!\nChunk 5: Could you give me the postcode, address and the area of the one you choose?\nChunk 6: That's all I need for now.\nChunk 7: Thanks!\nChunk 8: Thanks very much, take care!", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; time: 09:45; destination: leave after 09:45. Next, the goal is request info. Next, the topic is attraction; the goal is request info; destination: go to. Next, the goal is recommendation. Finally, requested information: address.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction. the goal is recommendation.. time: 09:45; destination: leave after 09:45., go to.; requested information: address.", "trace": "C1 goal=search; time+=09:45; destination+=leave after 09:45. C2 goal=request_info. C3 domain=attraction; goal=request_info; destination+=go to. C4 goal=recommendation. C5 requested_info+=address, postcode. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to leave after 09:45.", "streaming_reasoning": "Initially, the goal is search; time: 09:45; destination: leave after 09:45..", "trace": "goal=search; time+=09:45; destination+=leave after 09:45."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What time does it arrive by?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks, can I also find a college to go to.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is request info; destination: go to..", "trace": "domain=attraction; goal=request_info; destination+=go to."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "If you could recommend one that would be great!", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Could you give me the postcode, address and the area of the one you choose?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all I need for now.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks very much, take care!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: destination is leave after 09:45; requested information is address; timing is 09:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info, recommendation; destination=leave after 09:45, go to; requested_info=address, postcode; when=09:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000575", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Watch YouTube Videos with Friends During a Google+ Hangouts Video Call.\nChunk 2: Join or start a meeting in Google Meet.\nChunk 3: Open another browser tab.\nChunk 4: Open the YouTube video.\nChunk 5: Return to Google Meet and select Present now.\nChunk 6: Select the YouTube tap and click Share.", "streaming_reasoning": "C1 task=watch_youtube_videos_with. C2 step=join_or_start_a. C3 step=open_another_browser_tab. C4 step=open_the_youtube_video. C5 step=return_to_google_meet. C6 step=select_the_youtube_tap.", "deep_reasoning": "Procedure for Watch YouTube Videos with Friends During a Google+: Join or start a meeting in Google Meet, Open another browser tab, Open the YouTube video, Return to Google Meet and select Present now, Select the YouTube tap and click Share.", "answer": "For Watch YouTube Videos with Friends During a Google+, follow the steps in order: Join or start a meeting in Google Meet, Open another browser tab, Open the YouTube video, Return to Google Meet and select Present now.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Watch YouTube Videos with Friends During a Google+ Hangouts Video Call.\nChunk 2: Join or start a meeting in Google Meet.\nChunk 3: Open another browser tab.\nChunk 4: Open the YouTube video.\nChunk 5: Return to Google Meet and select Present now.\nChunk 6: Select the YouTube tap and click Share."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=watch_youtube_videos_with. C2 step=join_or_start_a. C3 step=open_another_browser_tab. C4 step=open_the_youtube_video. C5 step=return_to_google_meet. C6 step=select_the_youtube_tap.\n\nDeep reasoning: Procedure for Watch YouTube Videos with Friends During a Google+: Join or start a meeting in Google Meet, Open another browser tab, Open the YouTube video, Return to Google Meet and select Present now, Select the YouTube tap and click Share.\n\nAnswer: For Watch YouTube Videos with Friends During a Google+, follow the steps in order: Join or start a meeting in Google Meet, Open another browser tab, Open the YouTube video, Return to Google Meet and select Present now."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Watch YouTube Videos with Friends During a Google+ Hangouts Video Call.\nChunk 2: Join or start a meeting in Google Meet.\nChunk 3: Open another browser tab.\nChunk 4: Open the YouTube video.\nChunk 5: Return to Google Meet and select Present now.\nChunk 6: Select the YouTube tap and click Share.", "input_token_count": 55, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, task: watch_youtube_videos_with. Next, step: join_or_start_a. Next, step: open_another_browser_tab. Next, step: open_the_youtube_video. Next, step: return_to_google_meet. Finally, step: select_the_youtube_tap. In summary, task: watch_youtube_videos_with.; step: join_or_start_a., open_another_browser_tab., open_the_youtube_video., return_to_google_meet., select_the_youtube_tap..", "trace": "C1 task=watch_youtube_videos_with. C2 step=join_or_start_a. C3 step=open_another_browser_tab. C4 step=open_the_youtube_video. C5 step=return_to_google_meet. C6 step=select_the_youtube_tap.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Watch YouTube Videos with Friends During a Google+ Hangouts Video Call.", "streaming_reasoning": "Initially, task: watch_youtube_videos_with..", "trace": "task=watch_youtube_videos_with."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Join or start a meeting in Google Meet.", "streaming_reasoning": "As more information arrives, step: join_or_start_a..", "trace": "step=join_or_start_a."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Open another browser tab.", "streaming_reasoning": "As more information arrives, step: open_another_browser_tab..", "trace": "step=open_another_browser_tab."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Open the YouTube video.", "streaming_reasoning": "As more information arrives, step: open_the_youtube_video..", "trace": "step=open_the_youtube_video."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Return to Google Meet and select Present now.", "streaming_reasoning": "As more information arrives, step: return_to_google_meet..", "trace": "step=return_to_google_meet."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Select the YouTube tap and click Share.", "streaming_reasoning": "Finally, step: select_the_youtube_tap..", "trace": "step=select_the_youtube_tap."}]}, "output": {"deep_reasoning": "Procedure for Watch YouTube Videos with Friends During a Google+: Join or start a meeting in Google Meet, Open another browser tab, Open the YouTube video, Return to Google Meet and select Present now, Select the YouTube tap and click Share.", "answer": "For Watch YouTube Videos with Friends During a Google+, follow the steps in order: Join or start a meeting in Google Meet, Open another browser tab, Open the YouTube video, Return to Google Meet and select Present now."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002777", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks!\nChunk 2: I also need help finding a train.\nChunk 3: I'm leaving from Norwich.\nChunk 4: I'll need to arrive at Cambridge on Monday by 08:15.\nChunk 5: grab me 8 tickets please and I need the conf # too Great, thank you.\nChunk 6: Thank you, thats all I need today.\nChunk 7: have a good day.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 domain=train; goal=search. C3 intent=context_update. C4 time+=08:15; day+=monday; destination+=arrive at cambridge on monday by 08:15. C5 intent=context_update. C6 [SKIP: closing_only]. C7 intent=context_update.", "deep_reasoning": "Need domain=train; goal=search; destination=arrive at cambridge on monday by 08:15; when=monday, 08:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thanks!\nChunk 2: I also need help finding a train.\nChunk 3: I'm leaving from Norwich.\nChunk 4: I'll need to arrive at Cambridge on Monday by 08:15.\nChunk 5: grab me 8 tickets please and I need the conf # too Great, thank you.\nChunk 6: Thank you, thats all I need today.\nChunk 7: have a good day."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 domain=train; goal=search. C3 intent=context_update. C4 time+=08:15; day+=monday; destination+=arrive at cambridge on monday by 08:15. C5 intent=context_update. C6 [SKIP: closing_only]. C7 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=search; destination=arrive at cambridge on monday by 08:15; when=monday, 08:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks!\nChunk 2: I also need help finding a train.\nChunk 3: I'm leaving from Norwich.\nChunk 4: I'll need to arrive at Cambridge on Monday by 08:15.\nChunk 5: grab me 8 tickets please and I need the conf # too Great, thank you.\nChunk 6: Thank you, thats all I need today.\nChunk 7: have a good day.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, intent: context_update. Next, time: 08:15; day: monday; destination: arrive at cambridge on monday by 08:15. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is search.. intent: context_update.; time: 08:15; day: monday; destination: arrive at cambridge on monday by 08:15..", "trace": "C1 [SKIP: thanks_only]. C2 domain=train; goal=search. C3 intent=context_update. C4 time+=08:15; day+=monday; destination+=arrive at cambridge on monday by 08:15. C5 intent=context_update. C6 [SKIP: closing_only]. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thanks!", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need help finding a train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm leaving from Norwich.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll need to arrive at Cambridge on Monday by 08:15.", "streaming_reasoning": "As more information arrives, time: 08:15; day: monday; destination: arrive at cambridge on monday by 08:15..", "trace": "time+=08:15; day+=monday; destination+=arrive at cambridge on monday by 08:15."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "grab me 8 tickets please and I need the conf # too Great, thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you, thats all I need today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "have a good day.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is arrive at cambridge on monday by 08:15; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search; destination=arrive at cambridge on monday by 08:15; when=monday, 08:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003448", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Well, if spicy local dishes are what you are looking for, In Hua Restaurant is the best place to go.\nChunk 2: The restaurant serves very good and spicy local dishes.\nChunk 3: You might want to try there.\nChunk 4: How far is it from here?\nChunk 5: It is near the university.\nChunk 6: Five minutes ' walk from your flat, I think Great.\nChunk 7: We'll go and have a try.\nChunk 8: Thank you very much You're welcome.\nChunk 9: May you have a good time.\nChunk 10: Please give my regards to your wife.\nChunk 11: I wish her a happy birthday tomorrow.", "streaming_reasoning": "C1 casual_comment=spicy, local. C2 casual_comment=restaurant, serves. C3 casual_comment=might, try. C4 question=true. C5 casual_comment=near, university. C6 casual_comment=five, minutes. C7 casual_comment=we'll, try. C8 [SKIP: thanks_only]. C9 casual_comment=may. C10 casual_comment=give, regards. C11 casual_comment=wish, her.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Well, if spicy local dishes are what you are looking for, In Hua Restaurant is the best place to go.\nChunk 2: The restaurant serves very good and spicy local dishes.\nChunk 3: You might want to try there.\nChunk 4: How far is it from here?\nChunk 5: It is near the university.\nChunk 6: Five minutes ' walk from your flat, I think Great.\nChunk 7: We'll go and have a try.\nChunk 8: Thank you very much You're welcome.\nChunk 9: May you have a good time.\nChunk 10: Please give my regards to your wife.\nChunk 11: I wish her a happy birthday tomorrow."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=spicy, local. C2 casual_comment=restaurant, serves. C3 casual_comment=might, try. C4 question=true. C5 casual_comment=near, university. C6 casual_comment=five, minutes. C7 casual_comment=we'll, try. C8 [SKIP: thanks_only]. C9 casual_comment=may. C10 casual_comment=give, regards. C11 casual_comment=wish, her.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Well, if spicy local dishes are what you are looking for, In Hua Restaurant is the best place to go.\nChunk 2: The restaurant serves very good and spicy local dishes.\nChunk 3: You might want to try there.\nChunk 4: How far is it from here?\nChunk 5: It is near the university.\nChunk 6: Five minutes ' walk from your flat, I think Great.\nChunk 7: We'll go and have a try.\nChunk 8: Thank you very much You're welcome.\nChunk 9: May you have a good time.\nChunk 10: Please give my regards to your wife.\nChunk 11: I wish her a happy birthday tomorrow.", "input_token_count": 109, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the user comments on spicy. Next, the user comments on restaurant. Next, the user comments on might. Next, the input provides additional context about question=true. Next, the user comments on near. Next, the user comments on five. Next, the user comments on we'll. Next, the user comments on may. Next, the user comments on give. Finally, the user comments on wish.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=spicy, local. C2 casual_comment=restaurant, serves. C3 casual_comment=might, try. C4 question=true. C5 casual_comment=near, university. C6 casual_comment=five, minutes. C7 casual_comment=we'll, try. C8 [SKIP: thanks_only]. C9 casual_comment=may. C10 casual_comment=give, regards. C11 casual_comment=wish, her.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Well, if spicy local dishes are what you are looking for, In Hua Restaurant is the best place to go.", "streaming_reasoning": "Initially, the user comments on spicy.", "trace": "casual_comment=spicy, local."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The restaurant serves very good and spicy local dishes.", "streaming_reasoning": "As more information arrives, the user comments on restaurant.", "trace": "casual_comment=restaurant, serves."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "You might want to try there.", "streaming_reasoning": "As more information arrives, the user comments on might.", "trace": "casual_comment=might, try."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "How far is it from here?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It is near the university.", "streaming_reasoning": "As more information arrives, the user comments on near.", "trace": "casual_comment=near, university."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Five minutes ' walk from your flat, I think Great.", "streaming_reasoning": "As more information arrives, the user comments on five.", "trace": "casual_comment=five, minutes."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "We'll go and have a try.", "streaming_reasoning": "As more information arrives, the user comments on we'll.", "trace": "casual_comment=we'll, try."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you very much You're welcome.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "May you have a good time.", "streaming_reasoning": "As more information arrives, the user comments on may..", "trace": "casual_comment=may."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Please give my regards to your wife.", "streaming_reasoning": "As more information arrives, the user comments on give.", "trace": "casual_comment=give, regards."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "I wish her a happy birthday tomorrow.", "streaming_reasoning": "Finally, the user comments on wish.", "trace": "casual_comment=wish, her."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002778", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please try 10:45.\nChunk 2: I will need a taxi to go between the two places please.\nChunk 3: I would like to arrive at 10:45.\nChunk 4: Cambridge Artworks please and going to Saffron Brasserie.\nChunk 5: No, thats it thanks!\nChunk 6: Thank you for your help Goodbye!", "streaming_reasoning": "C1 time+=10:45. C2 domain=taxi; goal=search; destination+=go between the two places please. C3 destination+=arrive at 10:45. C4 destination+=saffron brasserie. C5 goal=modify_constraint. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi; goal=search; destination=go between the two places please, arrive at 10:45, saffron brasserie; when=10:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Please try 10:45.\nChunk 2: I will need a taxi to go between the two places please.\nChunk 3: I would like to arrive at 10:45.\nChunk 4: Cambridge Artworks please and going to Saffron Brasserie.\nChunk 5: No, thats it thanks!\nChunk 6: Thank you for your help Goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=10:45. C2 domain=taxi; goal=search; destination+=go between the two places please. C3 destination+=arrive at 10:45. C4 destination+=saffron brasserie. C5 goal=modify_constraint. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi; goal=search; destination=go between the two places please, arrive at 10:45, saffron brasserie; when=10:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please try 10:45.\nChunk 2: I will need a taxi to go between the two places please.\nChunk 3: I would like to arrive at 10:45.\nChunk 4: Cambridge Artworks please and going to Saffron Brasserie.\nChunk 5: No, thats it thanks!\nChunk 6: Thank you for your help Goodbye!", "input_token_count": 54, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 10:45. Next, the topic is taxi; the goal is search; destination: go between the two places please. Next, destination: arrive at 10:45. Next, destination: saffron brasserie. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is taxi. the goal is modify constraint.. time: 10:45.; destination: go between the two places please., arrive at 10:45., saffron brasserie..", "trace": "C1 time+=10:45. C2 domain=taxi; goal=search; destination+=go between the two places please. C3 destination+=arrive at 10:45. C4 destination+=saffron brasserie. C5 goal=modify_constraint. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Please try 10:45.", "streaming_reasoning": "Initially, time: 10:45..", "trace": "time+=10:45."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will need a taxi to go between the two places please.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is search; destination: go between the two places please..", "trace": "domain=taxi; goal=search; destination+=go between the two places please."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to arrive at 10:45.", "streaming_reasoning": "As more information arrives, destination: arrive at 10:45..", "trace": "destination+=arrive at 10:45."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Cambridge Artworks please and going to Saffron Brasserie.", "streaming_reasoning": "As more information arrives, destination: saffron brasserie..", "trace": "destination+=saffron brasserie."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, thats it thanks!", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for your help Goodbye!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is go between the two places please; timing is 10:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search; destination=go between the two places please, arrive at 10:45, saffron brasserie; when=10:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002779", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i would like to arrive in cambridge by 08:00.\nChunk 2: that is right, please get me the booking.\nChunk 3: Can i get the reference number please?\nChunk 4: I need 7 tickets please.\nChunk 5: Thank you so much No, that's it.\nChunk 6: Thank you so much for your help.", "streaming_reasoning": "C1 time+=08:00; destination+=arrive in cambridge by 08:00. C2 goal=request_info. C3 requested_info+=reference_number. C4 intent=context_update. C5 [SKIP: thanks_only]. C6 [SKIP: thanks_only].", "deep_reasoning": "Need goal=search, booking, request_info; destination=arrive in cambridge by 08:00; requested_info=reference_number; when=08:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i would like to arrive in cambridge by 08:00.\nChunk 2: that is right, please get me the booking.\nChunk 3: Can i get the reference number please?\nChunk 4: I need 7 tickets please.\nChunk 5: Thank you so much No, that's it.\nChunk 6: Thank you so much for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=08:00; destination+=arrive in cambridge by 08:00. C2 goal=request_info. C3 requested_info+=reference_number. C4 intent=context_update. C5 [SKIP: thanks_only]. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need goal=search, booking, request_info; destination=arrive in cambridge by 08:00; requested_info=reference_number; when=08:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i would like to arrive in cambridge by 08:00.\nChunk 2: that is right, please get me the booking.\nChunk 3: Can i get the reference number please?\nChunk 4: I need 7 tickets please.\nChunk 5: Thank you so much No, that's it.\nChunk 6: Thank you so much for your help.", "input_token_count": 56, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 08:00; destination: arrive in cambridge by 08:00. Next, the goal is request info. Next, requested information: reference_number. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, the goal is request info.. time: 08:00; destination: arrive in cambridge by 08:00.; requested information: reference_number.; intent: context_update..", "trace": "C1 time+=08:00; destination+=arrive in cambridge by 08:00. C2 goal=request_info. C3 requested_info+=reference_number. C4 intent=context_update. C5 [SKIP: thanks_only]. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i would like to arrive in cambridge by 08:00.", "streaming_reasoning": "Initially, time: 08:00; destination: arrive in cambridge by 08:00..", "trace": "time+=08:00; destination+=arrive in cambridge by 08:00."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "that is right, please get me the booking.", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can i get the reference number please?", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need 7 tickets please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you so much No, that's it.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you so much for your help.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need goal=search, booking, request_info; destination=arrive in cambridge by 08:00; requested_info=reference_number; when=08:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002780", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, nothing specific.\nChunk 2: I'd like to book a table for 5 on Monday at 15:45, so if one of them can fit us in at that time I'd like to book it.\nChunk 3: How about 14:45?\nChunk 4: I need help with train.\nChunk 5: The time is tuesday, 16:30.\nChunk 6: Yes I'd like to book 5 tickets.\nChunk 7: And can I get the reference number?\nChunk 8: That is everything I needed Thank you!", "streaming_reasoning": "C1 goal=modify_constraint. C2 goal=booking; time+=5, 15:45; day+=monday. C3 goal=recommendation; time+=14:45. C4 domain=train; goal=search. C5 time+=16:30; day+=tuesday. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=booking, recommendation, search, confirm_booking, request_info; requested_info=reference_number; when=monday, tuesday, 5, 15:45, 14:45, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, nothing specific.\nChunk 2: I'd like to book a table for 5 on Monday at 15:45, so if one of them can fit us in at that time I'd like to book it.\nChunk 3: How about 14:45?\nChunk 4: I need help with train.\nChunk 5: The time is tuesday, 16:30.\nChunk 6: Yes I'd like to book 5 tickets.\nChunk 7: And can I get the reference number?\nChunk 8: That is everything I needed Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=modify_constraint. C2 goal=booking; time+=5, 15:45; day+=monday. C3 goal=recommendation; time+=14:45. C4 domain=train; goal=search. C5 time+=16:30; day+=tuesday. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=booking, recommendation, search, confirm_booking, request_info; requested_info=reference_number; when=monday, tuesday, 5, 15:45, 14:45, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, nothing specific.\nChunk 2: I'd like to book a table for 5 on Monday at 15:45, so if one of them can fit us in at that time I'd like to book it.\nChunk 3: How about 14:45?\nChunk 4: I need help with train.\nChunk 5: The time is tuesday, 16:30.\nChunk 6: Yes I'd like to book 5 tickets.\nChunk 7: And can I get the reference number?\nChunk 8: That is everything I needed Thank you!", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is modify constraint. Next, the goal is booking; time: 5; day: monday. Next, the goal is recommendation; time: 14:45. Next, the topic is train; the goal is search. Next, time: 16:30; day: tuesday. Next, the goal is confirm booking. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. time: 5, 14:45., 16:30; day: monday., tuesday.; requested information: reference_number..", "trace": "C1 goal=modify_constraint. C2 goal=booking; time+=5, 15:45; day+=monday. C3 goal=recommendation; time+=14:45. C4 domain=train; goal=search. C5 time+=16:30; day+=tuesday. C6 goal=confirm_booking; goal=confirm_booking. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, nothing specific.", "streaming_reasoning": "Initially, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to book a table for 5 on Monday at 15:45, so if one of them can fit us in at that time I'd like to book it.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 5; day: monday..", "trace": "goal=booking; time+=5, 15:45; day+=monday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about 14:45?", "streaming_reasoning": "As more information arrives, the goal is recommendation; time: 14:45..", "trace": "goal=recommendation; time+=14:45."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is tuesday, 16:30.", "streaming_reasoning": "As more information arrives, time: 16:30; day: tuesday..", "trace": "time+=16:30; day+=tuesday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes I'd like to book 5 tickets.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "And can I get the reference number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is everything I needed Thank you!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, recommendation, search, confirm_booking, request_info; requested_info=reference_number; when=monday, tuesday, 5, 15:45, 14:45, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002781", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Let's find me a place that serves expensive european food.\nChunk 2: Can I have their address and phone number?\nChunk 3: I'm also looking to book some train tickets for Thursday.\nChunk 4: I need to leave Cambridge and arrive in Leicaster by 09:15.\nChunk 5: I will need tickets for 2 people Yay, thank you!\nChunk 6: Thank you for your help.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=european; price+=expensive. C2 goal=request_info; requested_info+=address, phone. C3 domain=train; goal=booking; day+=thursday. C4 time+=09:15; destination+=leave cambridge and arrive in leicaster b. C5 party_size+=2 people. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, train; goal=search, request_info, booking; food=european; price=expensive; party_size=2 people; destination=leave cambridge and arrive in leicaster b; requested_info=address, phone; when=thursday, 09:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Let's find me a place that serves expensive european food.\nChunk 2: Can I have their address and phone number?\nChunk 3: I'm also looking to book some train tickets for Thursday.\nChunk 4: I need to leave Cambridge and arrive in Leicaster by 09:15.\nChunk 5: I will need tickets for 2 people Yay, thank you!\nChunk 6: Thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=european; price+=expensive. C2 goal=request_info; requested_info+=address, phone. C3 domain=train; goal=booking; day+=thursday. C4 time+=09:15; destination+=leave cambridge and arrive in leicaster b. C5 party_size+=2 people. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, train; goal=search, request_info, booking; food=european; price=expensive; party_size=2 people; destination=leave cambridge and arrive in leicaster b; requested_info=address, phone; when=thursday, 09:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Let's find me a place that serves expensive european food.\nChunk 2: Can I have their address and phone number?\nChunk 3: I'm also looking to book some train tickets for Thursday.\nChunk 4: I need to leave Cambridge and arrive in Leicaster by 09:15.\nChunk 5: I will need tickets for 2 people Yay, thank you!\nChunk 6: Thank you for your help.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: european; price: expensive. Next, the goal is request info; requested information: address. Next, the topic is train; the goal is booking; day: thursday. Next, time: 09:15; destination: leave cambridge and arrive in leicaster b. Finally, party size: 2 people.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is booking. cuisine: european; price: expensive.; requested information: address; day: thursday.; time: 09:15; destination: leave cambridge and arrive in leicaster b.; party size: 2 people..", "trace": "C1 domain=restaurant; goal=search; cuisine+=european; price+=expensive. C2 goal=request_info; requested_info+=address, phone. C3 domain=train; goal=booking; day+=thursday. C4 time+=09:15; destination+=leave cambridge and arrive in leicaster b. C5 party_size+=2 people. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Let's find me a place that serves expensive european food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: european; price: expensive..", "trace": "domain=restaurant; goal=search; cuisine+=european; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I have their address and phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm also looking to book some train tickets for Thursday.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is booking; day: thursday..", "trace": "domain=train; goal=booking; day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to leave Cambridge and arrive in Leicaster by 09:15.", "streaming_reasoning": "As more information arrives, time: 09:15; destination: leave cambridge and arrive in leicaster b..", "trace": "time+=09:15; destination+=leave cambridge and arrive in leicaster b."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will need tickets for 2 people Yay, thank you!", "streaming_reasoning": "As more information arrives, party size: 2 people..", "trace": "party_size+=2 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is european; price is expensive; party size is 2 people; destination is leave cambridge and arrive in leicaster b; requested information is address; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, train; goal=search, request_info, booking; food=european; price=expensive; party_size=2 people; destination=leave cambridge and arrive in leicaster b; requested_info=address, phone; when=thursday, 09:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002782", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should depart from india house and should arrive by 24:00.\nChunk 3: Whale of a time is where I want to get to.\nChunk 4: No, thank you for your help!", "streaming_reasoning": "C1 domain=taxi; goal=booking. C2 time+=24:00; departure+=india house and should arrive by 24:00. C3 goal=request_info. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi; goal=search, booking, request_info; departure=india house and should arrive by 24:00; when=24:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i want to book a taxi.\nChunk 2: The taxi should depart from india house and should arrive by 24:00.\nChunk 3: Whale of a time is where I want to get to.\nChunk 4: No, thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=booking. C2 time+=24:00; departure+=india house and should arrive by 24:00. C3 goal=request_info. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi; goal=search, booking, request_info; departure=india house and should arrive by 24:00; when=24:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should depart from india house and should arrive by 24:00.\nChunk 3: Whale of a time is where I want to get to.\nChunk 4: No, thank you for your help!", "input_token_count": 44, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is booking. Next, time: 24:00; departure point: india house and should arrive by 24:00. Finally, the goal is request info.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is taxi. the goal is request info.. time: 24:00; departure point: india house and should arrive by 24:00..", "trace": "C1 domain=taxi; goal=booking. C2 time+=24:00; departure+=india house and should arrive by 24:00. C3 goal=request_info. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i want to book a taxi.", "streaming_reasoning": "Initially, the topic is taxi; the goal is booking..", "trace": "domain=taxi; goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The taxi should depart from india house and should arrive by 24:00.", "streaming_reasoning": "As more information arrives, time: 24:00; departure point: india house and should arrive by 24:00..", "trace": "time+=24:00; departure+=india house and should arrive by 24:00."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Whale of a time is where I want to get to.", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, thank you for your help!", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: departure point is india house and should arrive by 24:00; timing is 24:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search, booking, request_info; departure=india house and should arrive by 24:00; when=24:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002783", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant in the north part of town that is in the cheap price range.\nChunk 2: can i have something else?\nChunk 3: What is the address?\nChunk 4: Thank you good bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=north; price+=cheap. C2 goal=request_info. C3 requested_info+=address. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, compare_alternative, request_info; area=north; price=cheap; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant in the north part of town that is in the cheap price range.\nChunk 2: can i have something else?\nChunk 3: What is the address?\nChunk 4: Thank you good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=north; price+=cheap. C2 goal=request_info. C3 requested_info+=address. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, compare_alternative, request_info; area=north; price=cheap; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant in the north part of town that is in the cheap price range.\nChunk 2: can i have something else?\nChunk 3: What is the address?\nChunk 4: Thank you good bye.", "input_token_count": 40, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: north; price: cheap. Next, the goal is request info. Finally, requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info.. area: north; price: cheap.; requested information: address..", "trace": "C1 domain=restaurant; goal=search; area+=north; price+=cheap. C2 goal=request_info. C3 requested_info+=address. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant in the north part of town that is in the cheap price range.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: north; price: cheap..", "trace": "domain=restaurant; goal=search; area+=north; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "can i have something else?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the address?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you good bye.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; price is cheap; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, compare_alternative, request_info; area=north; price=cheap; requested_info=address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002784", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Help me, please, I was just the victim of a robbery!\nChunk 2: I need help right away!\nChunk 3: How do I contact the Parkside, Cambridge police station?\nChunk 4: I'll need to address also No, thank you.", "streaming_reasoning": "C1 goal=search. C2 intent=context_update. C3 domain=train. C4 goal=request_info; destination+=address also no; requested_info+=address.", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=address also no; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Help me, please, I was just the victim of a robbery!\nChunk 2: I need help right away!\nChunk 3: How do I contact the Parkside, Cambridge police station?\nChunk 4: I'll need to address also No, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 intent=context_update. C3 domain=train. C4 goal=request_info; destination+=address also no; requested_info+=address.\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=address also no; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Help me, please, I was just the victim of a robbery!\nChunk 2: I need help right away!\nChunk 3: How do I contact the Parkside, Cambridge police station?\nChunk 4: I'll need to address also No, thank you.", "input_token_count": 41, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, intent: context_update. Next, the topic is train. Finally, the goal is request info; destination: address also no; requested information: address. In summary, The overall topic is train.. the goal is request info. intent: context_update.; destination: address also no; requested information: address..", "trace": "C1 goal=search. C2 intent=context_update. C3 domain=train. C4 goal=request_info; destination+=address also no; requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Help me, please, I was just the victim of a robbery!", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need help right away!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How do I contact the Parkside, Cambridge police station?", "streaming_reasoning": "As more information arrives, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll need to address also No, thank you.", "streaming_reasoning": "Finally, the goal is request info; destination: address also no; requested information: address..", "trace": "goal=request_info; destination+=address also no; requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is address also no; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=address also no; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002785", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes it is the carolina bed and breakfast.\nChunk 2: I am also looking to go to a concerthall.\nChunk 3: Oh, before I forget.\nChunk 4: Can I ask for the star rating on Carolina B&B?\nChunk 5: And yes, can I get both the address and phone number for the concert hall please?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 09:45.\nChunk 8: Please make a booking.\nChunk 9: Thanks, I think that is all I need.\nChunk 10: I certainly will Thank you, again Goodbye.", "streaming_reasoning": "C1 domain=restaurant; amenities+=breakfast; acceptance=selected_option. C2 destination+=go to a concerthall. C3 intent=context_update. C4 goal=request_info. C5 requested_info+=address, phone; acceptance=selected_option. C6 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C7 time+=09:45. C8 goal=booking. C9 [SKIP: closing_only]. C10 intent=context_update.", "deep_reasoning": "Need domain=restaurant, hotel; goal=request_info, search, booking; amenities=breakfast; destination=go to a concerthall, find a hotel; requested_info=address, phone; when=09:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes it is the carolina bed and breakfast.\nChunk 2: I am also looking to go to a concerthall.\nChunk 3: Oh, before I forget.\nChunk 4: Can I ask for the star rating on Carolina B&B?\nChunk 5: And yes, can I get both the address and phone number for the concert hall please?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 09:45.\nChunk 8: Please make a booking.\nChunk 9: Thanks, I think that is all I need.\nChunk 10: I certainly will Thank you, again Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; amenities+=breakfast; acceptance=selected_option. C2 destination+=go to a concerthall. C3 intent=context_update. C4 goal=request_info. C5 requested_info+=address, phone; acceptance=selected_option. C6 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C7 time+=09:45. C8 goal=booking. C9 [SKIP: closing_only]. C10 intent=context_update.\n\nDeep reasoning: Need domain=restaurant, hotel; goal=request_info, search, booking; amenities=breakfast; destination=go to a concerthall, find a hotel; requested_info=address, phone; when=09:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes it is the carolina bed and breakfast.\nChunk 2: I am also looking to go to a concerthall.\nChunk 3: Oh, before I forget.\nChunk 4: Can I ask for the star rating on Carolina B&B?\nChunk 5: And yes, can I get both the address and phone number for the concert hall please?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 09:45.\nChunk 8: Please make a booking.\nChunk 9: Thanks, I think that is all I need.\nChunk 10: I certainly will Thank you, again Goodbye.", "input_token_count": 98, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; amenities: breakfast; acceptance: selected_option. Next, destination: go to a concerthall. Next, intent: context_update. Next, the goal is request info. Next, requested information: address; acceptance: selected_option. Next, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, time: 09:45. Next, the goal is booking. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking.. amenities: breakfast; acceptance: selected_option.; destination: go to a concerthall., find a hotel.; intent: context_update.; requested information: address; hotel type: hotel; time: 09:45..", "trace": "C1 domain=restaurant; amenities+=breakfast; acceptance=selected_option. C2 destination+=go to a concerthall. C3 intent=context_update. C4 goal=request_info. C5 requested_info+=address, phone; acceptance=selected_option. C6 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C7 time+=09:45. C8 goal=booking. C9 [SKIP: closing_only]. C10 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes it is the carolina bed and breakfast.", "streaming_reasoning": "Initially, the topic is restaurant; amenities: breakfast; acceptance: selected_option..", "trace": "domain=restaurant; amenities+=breakfast; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also looking to go to a concerthall.", "streaming_reasoning": "As more information arrives, destination: go to a concerthall..", "trace": "destination+=go to a concerthall."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Oh, before I forget.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I ask for the star rating on Carolina B&B?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "And yes, can I get both the address and phone number for the concert hall please?", "streaming_reasoning": "As more information arrives, requested information: address; acceptance: selected_option..", "trace": "requested_info+=address, phone; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 09:45.", "streaming_reasoning": "As more information arrives, time: 09:45..", "trace": "time+=09:45."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks, I think that is all I need.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "I certainly will Thank you, again Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: amenities is breakfast; destination is go to a concerthall; requested information is address; timing is 09:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=request_info, search, booking; amenities=breakfast; destination=go to a concerthall, find a hotel; requested_info=address, phone; when=09:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002786", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a restaurant in the cheap price range.\nChunk 2: How about one that serves Asian Oriental food?\nChunk 3: Could I have the phone number?\nChunk 4: Can you book it for me and get a reference number?\nChunk 5: Whenever is fine, just for me.\nChunk 6: i did not have any in mind.\nChunk 7: Thank you for such great customer service.\nChunk 8: I am set for now Goodbye.", "streaming_reasoning": "C1 domain=restaurant; price+=cheap. C2 goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 goal=booking; requested_info+=reference_number. C5 intent=context_update. C6 goal=modify_constraint. C7 [SKIP: thanks_only]. C8 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=recommendation, request_info, booking; price=cheap; requested_info=phone, reference_number; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a restaurant in the cheap price range.\nChunk 2: How about one that serves Asian Oriental food?\nChunk 3: Could I have the phone number?\nChunk 4: Can you book it for me and get a reference number?\nChunk 5: Whenever is fine, just for me.\nChunk 6: i did not have any in mind.\nChunk 7: Thank you for such great customer service.\nChunk 8: I am set for now Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; price+=cheap. C2 goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 goal=booking; requested_info+=reference_number. C5 intent=context_update. C6 goal=modify_constraint. C7 [SKIP: thanks_only]. C8 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=recommendation, request_info, booking; price=cheap; requested_info=phone, reference_number; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a restaurant in the cheap price range.\nChunk 2: How about one that serves Asian Oriental food?\nChunk 3: Could I have the phone number?\nChunk 4: Can you book it for me and get a reference number?\nChunk 5: Whenever is fine, just for me.\nChunk 6: i did not have any in mind.\nChunk 7: Thank you for such great customer service.\nChunk 8: I am set for now Goodbye.", "input_token_count": 77, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; price: cheap. Next, the goal is recommendation. Next, the goal is request info; requested information: phone. Next, the goal is booking; requested information: reference_number. Next, intent: context_update. Next, the goal is modify constraint. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is modify constraint.. price: cheap.; requested information: phone., reference_number.; intent: context_update..", "trace": "C1 domain=restaurant; price+=cheap. C2 goal=recommendation. C3 goal=request_info; requested_info+=phone. C4 goal=booking; requested_info+=reference_number. C5 intent=context_update. C6 goal=modify_constraint. C7 [SKIP: thanks_only]. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a restaurant in the cheap price range.", "streaming_reasoning": "Initially, the topic is restaurant; price: cheap..", "trace": "domain=restaurant; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How about one that serves Asian Oriental food?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Could I have the phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you book it for me and get a reference number?", "streaming_reasoning": "As more information arrives, the goal is booking; requested information: reference_number..", "trace": "goal=booking; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Whenever is fine, just for me.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "i did not have any in mind.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for such great customer service.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I am set for now Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: price is cheap; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=recommendation, request_info, booking; price=cheap; requested_info=phone, reference_number; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002788", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to leave on Tuesday.\nChunk 2: I am leaving ely and need to arrive by 09:30.\nChunk 3: I think I will buy my ticket at the station.\nChunk 4: So that is only a 17 minute trip?\nChunk 5: I would like to see a college in the west That is perfect.\nChunk 6: Can I get the address for Magdalene College, please?\nChunk 7: No, I think that is all Thank you!", "streaming_reasoning": "C1 day+=tuesday; destination+=leave on tuesday. C2 goal=search; time+=09:30; destination+=arrive by 09:30. C3 domain=train. C4 goal=request_info. C5 domain=attraction; area+=west; acceptance=selected_option. C6 goal=request_info; requested_info+=address. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, attraction; goal=search, request_info; area=west; destination=leave on tuesday, arrive by 09:30; requested_info=address; when=tuesday, 09:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to leave on Tuesday.\nChunk 2: I am leaving ely and need to arrive by 09:30.\nChunk 3: I think I will buy my ticket at the station.\nChunk 4: So that is only a 17 minute trip?\nChunk 5: I would like to see a college in the west That is perfect.\nChunk 6: Can I get the address for Magdalene College, please?\nChunk 7: No, I think that is all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=tuesday; destination+=leave on tuesday. C2 goal=search; time+=09:30; destination+=arrive by 09:30. C3 domain=train. C4 goal=request_info. C5 domain=attraction; area+=west; acceptance=selected_option. C6 goal=request_info; requested_info+=address. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, attraction; goal=search, request_info; area=west; destination=leave on tuesday, arrive by 09:30; requested_info=address; when=tuesday, 09:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to leave on Tuesday.\nChunk 2: I am leaving ely and need to arrive by 09:30.\nChunk 3: I think I will buy my ticket at the station.\nChunk 4: So that is only a 17 minute trip?\nChunk 5: I would like to see a college in the west That is perfect.\nChunk 6: Can I get the address for Magdalene College, please?\nChunk 7: No, I think that is all Thank you!", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, day: tuesday; destination: leave on tuesday. Next, the goal is search; time: 09:30; destination: arrive by 09:30. Next, the topic is train. Next, the goal is request info. Next, the topic is attraction; area: west; acceptance: selected_option. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is request info. day: tuesday; destination: leave on tuesday., arrive by 09:30.; time: 09:30; area: west; acceptance: selected_option.; requested information: address..", "trace": "C1 day+=tuesday; destination+=leave on tuesday. C2 goal=search; time+=09:30; destination+=arrive by 09:30. C3 domain=train. C4 goal=request_info. C5 domain=attraction; area+=west; acceptance=selected_option. C6 goal=request_info; requested_info+=address. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to leave on Tuesday.", "streaming_reasoning": "Initially, day: tuesday; destination: leave on tuesday..", "trace": "day+=tuesday; destination+=leave on tuesday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am leaving ely and need to arrive by 09:30.", "streaming_reasoning": "As more information arrives, the goal is search; time: 09:30; destination: arrive by 09:30..", "trace": "goal=search; time+=09:30; destination+=arrive by 09:30."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I think I will buy my ticket at the station.", "streaming_reasoning": "As more information arrives, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "So that is only a 17 minute trip?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like to see a college in the west That is perfect.", "streaming_reasoning": "As more information arrives, the topic is attraction; area: west; acceptance: selected_option..", "trace": "domain=attraction; area+=west; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I get the address for Magdalene College, please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, I think that is all Thank you!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is west; destination is leave on tuesday; requested information is address; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=search, request_info; area=west; destination=leave on tuesday, arrive by 09:30; requested_info=address; when=tuesday, 09:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003464", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Did you have the room checked before we move in?\nChunk 2: Which room are you in 1808.\nChunk 3: The toilet doesn ' t work properly.\nChunk 4: The water doesn ' t run in the shower.\nChunk 5: I'm awfully sorry to hear that.\nChunk 6: ( After checking ) I'll turn to it right away I do apologize.\nChunk 7: We ' ll change your room to 2002.\nChunk 8: That ' s not bad.\nChunk 9: Thanks for your help.", "streaming_reasoning": "C1 question=true. C2 [SKIP: repeated_information]. C3 casual_comment=toilet, doesn. C4 casual_comment=water, doesn. C5 casual_comment=i'm, awfully. C6 casual_comment=checking, i'll. C7 casual_comment=change, room. C8 casual_comment=not, bad. C9 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Did you have the room checked before we move in?\nChunk 2: Which room are you in 1808.\nChunk 3: The toilet doesn ' t work properly.\nChunk 4: The water doesn ' t run in the shower.\nChunk 5: I'm awfully sorry to hear that.\nChunk 6: ( After checking ) I'll turn to it right away I do apologize.\nChunk 7: We ' ll change your room to 2002.\nChunk 8: That ' s not bad.\nChunk 9: Thanks for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 [SKIP: repeated_information]. C3 casual_comment=toilet, doesn. C4 casual_comment=water, doesn. C5 casual_comment=i'm, awfully. C6 casual_comment=checking, i'll. C7 casual_comment=change, room. C8 casual_comment=not, bad. C9 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Did you have the room checked before we move in?\nChunk 2: Which room are you in 1808.\nChunk 3: The toilet doesn ' t work properly.\nChunk 4: The water doesn ' t run in the shower.\nChunk 5: I'm awfully sorry to hear that.\nChunk 6: ( After checking ) I'll turn to it right away I do apologize.\nChunk 7: We ' ll change your room to 2002.\nChunk 8: That ' s not bad.\nChunk 9: Thanks for your help.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on toilet. Next, the user comments on water. Next, the user comments on i'm. Next, the user comments on checking. Next, the user comments on change. Finally, the user comments on not.  Some chunks were skipped because they contained repeated_information or thanks_only.", "trace": "C1 question=true. C2 [SKIP: repeated_information]. C3 casual_comment=toilet, doesn. C4 casual_comment=water, doesn. C5 casual_comment=i'm, awfully. C6 casual_comment=checking, i'll. C7 casual_comment=change, room. C8 casual_comment=not, bad. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Did you have the room checked before we move in?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Which room are you in 1808.", "streaming_reasoning": "The content at C2 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The toilet doesn ' t work properly.", "streaming_reasoning": "As more information arrives, the user comments on toilet.", "trace": "casual_comment=toilet, doesn."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The water doesn ' t run in the shower.", "streaming_reasoning": "As more information arrives, the user comments on water.", "trace": "casual_comment=water, doesn."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm awfully sorry to hear that.", "streaming_reasoning": "As more information arrives, the user comments on i'm.", "trace": "casual_comment=i'm, awfully."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "( After checking ) I'll turn to it right away I do apologize.", "streaming_reasoning": "As more information arrives, the user comments on checking.", "trace": "casual_comment=checking, i'll."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "We ' ll change your room to 2002.", "streaming_reasoning": "As more information arrives, the user comments on change.", "trace": "casual_comment=change, room."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That ' s not bad.", "streaming_reasoning": "As more information arrives, the user comments on not.", "trace": "casual_comment=not, bad."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks for your help.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002789", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It is for 4 people.\nChunk 2: The time is sunday, 4, 13:30.\nChunk 3: Please make a booking.\nChunk 4: Thanks!\nChunk 5: I also need a train from Cambridge to Ely, please.\nChunk 6: I want to leave after 10:30 on Monday.\nChunk 7: Yes, what time do I need to be at the station?\nChunk 8: I just need the arrival time and price.\nChunk 9: That was everything Thanks very much!", "streaming_reasoning": "C1 party_size+=4 people. C2 time+=4, 13:30; day+=sunday. C3 goal=booking. C4 [SKIP: thanks_only]. C5 domain=train; goal=search; destination+=ely; departure+=cambridge. C6 time+=10:30; day+=monday; destination+=leave after 10:30 on monday. C7 destination+=be at the station; goal=confirm_booking. C8 requested_info+=price. C9 intent=context_update.", "deep_reasoning": "Need domain=train; goal=booking, search; party_size=4 people; destination=ely, leave after 10:30 on monday, be at the station; departure=cambridge; requested_info=price; when=sunday, monday, 4, 13:30, 10:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: It is for 4 people.\nChunk 2: The time is sunday, 4, 13:30.\nChunk 3: Please make a booking.\nChunk 4: Thanks!\nChunk 5: I also need a train from Cambridge to Ely, please.\nChunk 6: I want to leave after 10:30 on Monday.\nChunk 7: Yes, what time do I need to be at the station?\nChunk 8: I just need the arrival time and price.\nChunk 9: That was everything Thanks very much!"}, {"role": "assistant", "content": "Streaming reasoning: C1 party_size+=4 people. C2 time+=4, 13:30; day+=sunday. C3 goal=booking. C4 [SKIP: thanks_only]. C5 domain=train; goal=search; destination+=ely; departure+=cambridge. C6 time+=10:30; day+=monday; destination+=leave after 10:30 on monday. C7 destination+=be at the station; goal=confirm_booking. C8 requested_info+=price. C9 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=booking, search; party_size=4 people; destination=ely, leave after 10:30 on monday, be at the station; departure=cambridge; requested_info=price; when=sunday, monday, 4, 13:30, 10:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It is for 4 people.\nChunk 2: The time is sunday, 4, 13:30.\nChunk 3: Please make a booking.\nChunk 4: Thanks!\nChunk 5: I also need a train from Cambridge to Ely, please.\nChunk 6: I want to leave after 10:30 on Monday.\nChunk 7: Yes, what time do I need to be at the station?\nChunk 8: I just need the arrival time and price.\nChunk 9: That was everything Thanks very much!", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, party size: 4 people. Next, time: 4; day: sunday. Next, the goal is booking. Next, the topic is train; the goal is search; destination: ely; departure point: cambridge. Next, time: 10:30; day: monday; destination: leave after 10:30 on monday. Next, the goal is confirm booking.; destination: be at the station. Next, requested information: price. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is confirm booking.. party size: 4 people.; time: 4, 10:30; day: sunday., monday; destination: ely, leave after 10:30 on monday., be at the station; departure point: cambridge.; requested information: price.; intent: context_update..", "trace": "C1 party_size+=4 people. C2 time+=4, 13:30; day+=sunday. C3 goal=booking. C4 [SKIP: thanks_only]. C5 domain=train; goal=search; destination+=ely; departure+=cambridge. C6 time+=10:30; day+=monday; destination+=leave after 10:30 on monday. C7 destination+=be at the station; goal=confirm_booking. C8 requested_info+=price. C9 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "It is for 4 people.", "streaming_reasoning": "Initially, party size: 4 people..", "trace": "party_size+=4 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is sunday, 4, 13:30.", "streaming_reasoning": "As more information arrives, time: 4; day: sunday..", "trace": "time+=4, 13:30; day+=sunday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks!", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need a train from Cambridge to Ely, please.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; destination: ely; departure point: cambridge..", "trace": "domain=train; goal=search; destination+=ely; departure+=cambridge."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to leave after 10:30 on Monday.", "streaming_reasoning": "As more information arrives, time: 10:30; day: monday; destination: leave after 10:30 on monday..", "trace": "time+=10:30; day+=monday; destination+=leave after 10:30 on monday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, what time do I need to be at the station?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; destination: be at the station.", "trace": "destination+=be at the station; goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I just need the arrival time and price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That was everything Thanks very much!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: party size is 4 people; destination is ely; departure point is cambridge; requested information is price; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=booking, search; party_size=4 people; destination=ely, leave after 10:30 on monday, be at the station; departure=cambridge; requested_info=price; when=sunday, monday, 4, 13:30, 10:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002790", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: May I have information for an italian restaurant in the east part of town?\nChunk 2: What is their address please Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; area+=east; cuisine+=italian. C2 goal=request_info; requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=request_info; area=east; food=italian; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: May I have information for an italian restaurant in the east part of town?\nChunk 2: What is their address please Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=east; cuisine+=italian. C2 goal=request_info; requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=request_info; area=east; food=italian; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: May I have information for an italian restaurant in the east part of town?\nChunk 2: What is their address please Thank you, goodbye.", "input_token_count": 26, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: east; cuisine: italian. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. area: east; cuisine: italian.; requested information: address..", "trace": "C1 domain=restaurant; area+=east; cuisine+=italian. C2 goal=request_info; requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "May I have information for an italian restaurant in the east part of town?", "streaming_reasoning": "Initially, the topic is restaurant; area: east; cuisine: italian..", "trace": "domain=restaurant; area+=east; cuisine+=italian."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is their address please Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is east; cuisine is italian; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info; area=east; food=italian; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002791", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: How about a theatre?\nChunk 2: I think we would enjoy seeing a show!\nChunk 3: That would be great.\nChunk 4: Can I have the postcode, address, and entrance fee please?\nChunk 5: Ok.\nChunk 6: I also need info on the restaurant Darrys cookhouse and wine shop.\nChunk 7: Yes, that would be great.\nChunk 8: I'll need a table for 7 on Friday at 18:00.\nChunk 9: I don't think so.\nChunk 10: Thanks for all your help.\nChunk 11: That was so nice of you to say thanks so much.", "streaming_reasoning": "C1 domain=attraction; goal=recommendation. C2 intent=context_update. C3 intent=context_update. C4 goal=request_info; requested_info+=address, postcode, entrance_fee. C5 [SKIP: backchannel_only]. C6 domain=restaurant; goal=search. C7 acceptance=selected_option. C8 time+=7, 18:00; day+=friday. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 destination+=say thanks so much.", "deep_reasoning": "Need domain=attraction, restaurant; goal=recommendation, request_info, search; destination=say thanks so much; requested_info=address, postcode, entrance_fee; when=friday, 7, 18:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: How about a theatre?\nChunk 2: I think we would enjoy seeing a show!\nChunk 3: That would be great.\nChunk 4: Can I have the postcode, address, and entrance fee please?\nChunk 5: Ok.\nChunk 6: I also need info on the restaurant Darrys cookhouse and wine shop.\nChunk 7: Yes, that would be great.\nChunk 8: I'll need a table for 7 on Friday at 18:00.\nChunk 9: I don't think so.\nChunk 10: Thanks for all your help.\nChunk 11: That was so nice of you to say thanks so much."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=recommendation. C2 intent=context_update. C3 intent=context_update. C4 goal=request_info; requested_info+=address, postcode, entrance_fee. C5 [SKIP: backchannel_only]. C6 domain=restaurant; goal=search. C7 acceptance=selected_option. C8 time+=7, 18:00; day+=friday. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 destination+=say thanks so much.\n\nDeep reasoning: Need domain=attraction, restaurant; goal=recommendation, request_info, search; destination=say thanks so much; requested_info=address, postcode, entrance_fee; when=friday, 7, 18:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: How about a theatre?\nChunk 2: I think we would enjoy seeing a show!\nChunk 3: That would be great.\nChunk 4: Can I have the postcode, address, and entrance fee please?\nChunk 5: Ok.\nChunk 6: I also need info on the restaurant Darrys cookhouse and wine shop.\nChunk 7: Yes, that would be great.\nChunk 8: I'll need a table for 7 on Friday at 18:00.\nChunk 9: I don't think so.\nChunk 10: Thanks for all your help.\nChunk 11: That was so nice of you to say thanks so much.", "input_token_count": 97, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is recommendation. Next, intent: context_update. Next, intent: context_update. Next, the goal is request info; requested information: address. Next, the topic is restaurant; the goal is search. Next, acceptance: selected_option. Next, time: 7; day: friday. Next, intent: context_update. Finally, destination: say thanks so much.  Some chunks were skipped because they contained backchannel_only or thanks_only. In summary, The overall topic is restaurant. the goal is search.. intent: context_update.; requested information: address; acceptance: selected_option.; time: 7; day: friday.; destination: say thanks so much..", "trace": "C1 domain=attraction; goal=recommendation. C2 intent=context_update. C3 intent=context_update. C4 goal=request_info; requested_info+=address, postcode, entrance_fee. C5 [SKIP: backchannel_only]. C6 domain=restaurant; goal=search. C7 acceptance=selected_option. C8 time+=7, 18:00; day+=friday. C9 intent=context_update. C10 [SKIP: thanks_only]. C11 destination+=say thanks so much.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "How about a theatre?", "streaming_reasoning": "Initially, the topic is attraction; the goal is recommendation..", "trace": "domain=attraction; goal=recommendation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I think we would enjoy seeing a show!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That would be great.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I have the postcode, address, and entrance fee please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode, entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Ok.", "streaming_reasoning": "The content at C5 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need info on the restaurant Darrys cookhouse and wine shop.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, that would be great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'll need a table for 7 on Friday at 18:00.", "streaming_reasoning": "As more information arrives, time: 7; day: friday..", "trace": "time+=7, 18:00; day+=friday."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I don't think so.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thanks for all your help.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "That was so nice of you to say thanks so much.", "streaming_reasoning": "Finally, destination: say thanks so much..", "trace": "destination+=say thanks so much."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of recommendation. Key information: destination is say thanks so much; requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=recommendation, request_info, search; destination=say thanks so much; requested_info=address, postcode, entrance_fee; when=friday, 7, 18:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002792", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I just need one that is moderately priced.\nChunk 2: Can you just recommend one and give me the phone number please?\nChunk 3: Could you recommend me some places to go that is in the centre?\nChunk 4: Oh anything would do really, just needs to be in the centre.\nChunk 5: Yes could I get the postcode of the nightclub Okay thanks!\nChunk 6: That's all I needed to know!\nChunk 7: That is all I needed, thank you Good bye.", "streaming_reasoning": "C1 goal=search; price+=moderate. C2 goal=request_info; requested_info+=phone. C3 area+=centre; destination+=go that is in the centre. C4 destination+=be in the centre. C5 requested_info+=postcode; acceptance=selected_option. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need goal=search, recommendation, request_info; area=centre; price=moderate; destination=go that is in the centre, be in the centre; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I just need one that is moderately priced.\nChunk 2: Can you just recommend one and give me the phone number please?\nChunk 3: Could you recommend me some places to go that is in the centre?\nChunk 4: Oh anything would do really, just needs to be in the centre.\nChunk 5: Yes could I get the postcode of the nightclub Okay thanks!\nChunk 6: That's all I needed to know!\nChunk 7: That is all I needed, thank you Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; price+=moderate. C2 goal=request_info; requested_info+=phone. C3 area+=centre; destination+=go that is in the centre. C4 destination+=be in the centre. C5 requested_info+=postcode; acceptance=selected_option. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search, recommendation, request_info; area=centre; price=moderate; destination=go that is in the centre, be in the centre; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I just need one that is moderately priced.\nChunk 2: Can you just recommend one and give me the phone number please?\nChunk 3: Could you recommend me some places to go that is in the centre?\nChunk 4: Oh anything would do really, just needs to be in the centre.\nChunk 5: Yes could I get the postcode of the nightclub Okay thanks!\nChunk 6: That's all I needed to know!\nChunk 7: That is all I needed, thank you Good bye.", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; price: moderate. Next, the goal is request info; requested information: phone. Next, area: centre; destination: go that is in the centre. Next, destination: be in the centre. Finally, requested information: postcode; acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, the goal is request info. price: moderate.; requested information: phone., postcode; area: centre; destination: go that is in the centre., be in the centre.; acceptance: selected_option..", "trace": "C1 goal=search; price+=moderate. C2 goal=request_info; requested_info+=phone. C3 area+=centre; destination+=go that is in the centre. C4 destination+=be in the centre. C5 requested_info+=postcode; acceptance=selected_option. C6 [SKIP: closing_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I just need one that is moderately priced.", "streaming_reasoning": "Initially, the goal is search; price: moderate..", "trace": "goal=search; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you just recommend one and give me the phone number please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Could you recommend me some places to go that is in the centre?", "streaming_reasoning": "As more information arrives, area: centre; destination: go that is in the centre..", "trace": "area+=centre; destination+=go that is in the centre."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Oh anything would do really, just needs to be in the centre.", "streaming_reasoning": "As more information arrives, destination: be in the centre..", "trace": "destination+=be in the centre."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes could I get the postcode of the nightclub Okay thanks!", "streaming_reasoning": "As more information arrives, requested information: postcode; acceptance: selected_option..", "trace": "requested_info+=postcode; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all I needed to know!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I needed, thank you Good bye.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search, recommendation, request_info; area=centre; price=moderate; destination=go that is in the centre, be in the centre; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002794", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want a restaurant in the north part of town.\nChunk 2: I want a restaurant that is moderately priced.\nChunk 3: What is their address and phone number Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=north. C2 price+=moderate. C3 goal=request_info; requested_info+=address, phone.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=north; price=moderate; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want a restaurant in the north part of town.\nChunk 2: I want a restaurant that is moderately priced.\nChunk 3: What is their address and phone number Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=north. C2 price+=moderate. C3 goal=request_info; requested_info+=address, phone.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=north; price=moderate; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want a restaurant in the north part of town.\nChunk 2: I want a restaurant that is moderately priced.\nChunk 3: What is their address and phone number Thank you, goodbye.", "input_token_count": 34, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: north. Next, price: moderate. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. area: north.; price: moderate.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; area+=north. C2 price+=moderate. C3 goal=request_info; requested_info+=address, phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want a restaurant in the north part of town.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: north..", "trace": "domain=restaurant; goal=search; area+=north."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want a restaurant that is moderately priced.", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is their address and phone number Thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; price is moderate; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=north; price=moderate; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002795", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Great can I get the address of one and whether or not they have free parking Thank you.\nChunk 2: Can you tell me if there is a train going to Norwich on Friday?\nChunk 3: Yes, after 19:45 and departing from cambridge please.\nChunk 4: Yes, I think that will work.\nChunk 5: Can you tell me the price, travel time and confirm the arrival time please?\nChunk 6: Okay, thank you for your help Nope, that's everything.\nChunk 7: You've been very helpful.", "streaming_reasoning": "C1 goal=request_info; amenities+=parking, free parking; requested_info+=address. C2 domain=train; day+=friday; destination+=norwich on friday. C3 time+=19:45; departure+=cambridge please; acceptance=selected_option. C4 acceptance=selected_option. C5 requested_info+=travel_time, price. C6 goal=search. C7 intent=context_update.", "deep_reasoning": "Need domain=train; goal=request_info, search; amenities=parking, free parking; destination=norwich on friday; departure=cambridge please; requested_info=address, travel_time, price; when=friday, 19:45.", "answer": "I can help with that and include the address, travel time, price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Great can I get the address of one and whether or not they have free parking Thank you.\nChunk 2: Can you tell me if there is a train going to Norwich on Friday?\nChunk 3: Yes, after 19:45 and departing from cambridge please.\nChunk 4: Yes, I think that will work.\nChunk 5: Can you tell me the price, travel time and confirm the arrival time please?\nChunk 6: Okay, thank you for your help Nope, that's everything.\nChunk 7: You've been very helpful."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; amenities+=parking, free parking; requested_info+=address. C2 domain=train; day+=friday; destination+=norwich on friday. C3 time+=19:45; departure+=cambridge please; acceptance=selected_option. C4 acceptance=selected_option. C5 requested_info+=travel_time, price. C6 goal=search. C7 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=request_info, search; amenities=parking, free parking; destination=norwich on friday; departure=cambridge please; requested_info=address, travel_time, price; when=friday, 19:45.\n\nAnswer: I can help with that and include the address, travel time, price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Great can I get the address of one and whether or not they have free parking Thank you.\nChunk 2: Can you tell me if there is a train going to Norwich on Friday?\nChunk 3: Yes, after 19:45 and departing from cambridge please.\nChunk 4: Yes, I think that will work.\nChunk 5: Can you tell me the price, travel time and confirm the arrival time please?\nChunk 6: Okay, thank you for your help Nope, that's everything.\nChunk 7: You've been very helpful.", "input_token_count": 88, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; amenities: parking; requested information: address. Next, the topic is train; day: friday; destination: norwich on friday. Next, time: 19:45; departure point: cambridge please; acceptance: selected_option. Next, acceptance: selected_option. Next, requested information: travel_time. Next, the goal is search. Finally, intent: context_update. In summary, The overall topic is train. the goal is search.. amenities: parking; requested information: address., travel_time; day: friday; destination: norwich on friday.; time: 19:45; departure point: cambridge please; acceptance: selected_option.; intent: context_update..", "trace": "C1 goal=request_info; amenities+=parking, free parking; requested_info+=address. C2 domain=train; day+=friday; destination+=norwich on friday. C3 time+=19:45; departure+=cambridge please; acceptance=selected_option. C4 acceptance=selected_option. C5 requested_info+=travel_time, price. C6 goal=search. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Great can I get the address of one and whether or not they have free parking Thank you.", "streaming_reasoning": "Initially, the goal is request info; amenities: parking; requested information: address..", "trace": "goal=request_info; amenities+=parking, free parking; requested_info+=address."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you tell me if there is a train going to Norwich on Friday?", "streaming_reasoning": "As more information arrives, the topic is train; day: friday; destination: norwich on friday..", "trace": "domain=train; day+=friday; destination+=norwich on friday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, after 19:45 and departing from cambridge please.", "streaming_reasoning": "As more information arrives, time: 19:45; departure point: cambridge please; acceptance: selected_option..", "trace": "time+=19:45; departure+=cambridge please; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I think that will work.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you tell me the price, travel time and confirm the arrival time please?", "streaming_reasoning": "As more information arrives, requested information: travel_time.", "trace": "requested_info+=travel_time, price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Okay, thank you for your help Nope, that's everything.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "You've been very helpful.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: amenities is parking; destination is norwich on friday; departure point is cambridge please; requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, travel time, price once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search; amenities=parking, free parking; destination=norwich on friday; departure=cambridge please; requested_info=address, travel_time, price; when=friday, 19:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002797", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: where else could ypou suppose i get american food.\nChunk 2: How about italian I love pasta.\nChunk 3: It is for 5 people.\nChunk 4: The time is wednesday, 5, 18:15.\nChunk 5: Please make a booking.\nChunk 6: No thank you, that was all I needed.\nChunk 7: Have a great day.\nChunk 8: There seems to be an error.\nChunk 9: Thanks for booking the Italian restaurant.\nChunk 10: That is all I needed.\nChunk 11: No that was everything.\nChunk 12: Thanks.", "streaming_reasoning": "C1 domain=restaurant; goal=request_info. C2 goal=recommendation; cuisine+=italian. C3 party_size+=5 people. C4 time+=5, 18:15; day+=wednesday. C5 goal=booking. C6 [SKIP: closing_only]. C7 [SKIP: closing_only]. C8 destination+=be an error. C9 intent=context_update. C10 [SKIP: closing_only]. C11 goal=modify_constraint. C12 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=compare_alternative, request_info, recommendation, booking; food=italian; party_size=5 people; destination=be an error; when=wednesday, 5, 18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: where else could ypou suppose i get american food.\nChunk 2: How about italian I love pasta.\nChunk 3: It is for 5 people.\nChunk 4: The time is wednesday, 5, 18:15.\nChunk 5: Please make a booking.\nChunk 6: No thank you, that was all I needed.\nChunk 7: Have a great day.\nChunk 8: There seems to be an error.\nChunk 9: Thanks for booking the Italian restaurant.\nChunk 10: That is all I needed.\nChunk 11: No that was everything.\nChunk 12: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=request_info. C2 goal=recommendation; cuisine+=italian. C3 party_size+=5 people. C4 time+=5, 18:15; day+=wednesday. C5 goal=booking. C6 [SKIP: closing_only]. C7 [SKIP: closing_only]. C8 destination+=be an error. C9 intent=context_update. C10 [SKIP: closing_only]. C11 goal=modify_constraint. C12 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=compare_alternative, request_info, recommendation, booking; food=italian; party_size=5 people; destination=be an error; when=wednesday, 5, 18:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: where else could ypou suppose i get american food.\nChunk 2: How about italian I love pasta.\nChunk 3: It is for 5 people.\nChunk 4: The time is wednesday, 5, 18:15.\nChunk 5: Please make a booking.\nChunk 6: No thank you, that was all I needed.\nChunk 7: Have a great day.\nChunk 8: There seems to be an error.\nChunk 9: Thanks for booking the Italian restaurant.\nChunk 10: That is all I needed.\nChunk 11: No that was everything.\nChunk 12: Thanks.", "input_token_count": 89, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is request info. Next, the goal is recommendation; cuisine: italian. Next, party size: 5 people. Next, time: 5; day: wednesday. Next, the goal is booking. Next, destination: be an error. Next, intent: context_update. Finally, the goal is modify constraint.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is modify constraint.. cuisine: italian.; party size: 5 people.; time: 5; day: wednesday.; destination: be an error.; intent: context_update..", "trace": "C1 domain=restaurant; goal=request_info. C2 goal=recommendation; cuisine+=italian. C3 party_size+=5 people. C4 time+=5, 18:15; day+=wednesday. C5 goal=booking. C6 [SKIP: closing_only]. C7 [SKIP: closing_only]. C8 destination+=be an error. C9 intent=context_update. C10 [SKIP: closing_only]. C11 goal=modify_constraint. C12 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "where else could ypou suppose i get american food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is request info..", "trace": "domain=restaurant; goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How about italian I love pasta.", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: italian..", "trace": "goal=recommendation; cuisine+=italian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 5 people.", "streaming_reasoning": "As more information arrives, party size: 5 people..", "trace": "party_size+=5 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is wednesday, 5, 18:15.", "streaming_reasoning": "As more information arrives, time: 5; day: wednesday..", "trace": "time+=5, 18:15; day+=wednesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No thank you, that was all I needed.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "There seems to be an error.", "streaming_reasoning": "As more information arrives, destination: be an error..", "trace": "destination+=be an error."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks for booking the Italian restaurant.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That is all I needed.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "No that was everything.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C12", "chunk_index": 11, "observed_text": "Thanks.", "streaming_reasoning": "The content at C12 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of compare alternative. Key information: cuisine is italian; party size is 5 people; destination is be an error; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=compare_alternative, request_info, recommendation, booking; food=italian; party_size=5 people; destination=be an error; when=wednesday, 5, 18:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002799", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Okay, what about a college?\nChunk 2: No, it doesn't matter.\nChunk 3: Sure, can I have their phone number please?\nChunk 4: I need to book a taxi for the commute between the two places.\nChunk 5: can you book one for me so I arrive on time?\nChunk 6: No, that's all the information I need Thank you.\nChunk 7: I am good to go.\nChunk 8: Thanks!", "streaming_reasoning": "C1 domain=attraction; goal=recommendation. C2 goal=modify_constraint. C3 goal=request_info; requested_info+=phone. C4 domain=taxi; goal=booking. C5 goal=request_info. C6 [SKIP: closing_only]. C7 intent=context_update. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, taxi; goal=recommendation, request_info, search, booking; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Okay, what about a college?\nChunk 2: No, it doesn't matter.\nChunk 3: Sure, can I have their phone number please?\nChunk 4: I need to book a taxi for the commute between the two places.\nChunk 5: can you book one for me so I arrive on time?\nChunk 6: No, that's all the information I need Thank you.\nChunk 7: I am good to go.\nChunk 8: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=recommendation. C2 goal=modify_constraint. C3 goal=request_info; requested_info+=phone. C4 domain=taxi; goal=booking. C5 goal=request_info. C6 [SKIP: closing_only]. C7 intent=context_update. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, taxi; goal=recommendation, request_info, search, booking; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Okay, what about a college?\nChunk 2: No, it doesn't matter.\nChunk 3: Sure, can I have their phone number please?\nChunk 4: I need to book a taxi for the commute between the two places.\nChunk 5: can you book one for me so I arrive on time?\nChunk 6: No, that's all the information I need Thank you.\nChunk 7: I am good to go.\nChunk 8: Thanks!", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is recommendation. Next, the goal is modify constraint. Next, the goal is request info; requested information: phone. Next, the topic is taxi; the goal is booking. Next, the goal is request info. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is request info.. requested information: phone.; intent: context_update..", "trace": "C1 domain=attraction; goal=recommendation. C2 goal=modify_constraint. C3 goal=request_info; requested_info+=phone. C4 domain=taxi; goal=booking. C5 goal=request_info. C6 [SKIP: closing_only]. C7 intent=context_update. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Okay, what about a college?", "streaming_reasoning": "Initially, the topic is attraction; the goal is recommendation..", "trace": "domain=attraction; goal=recommendation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, it doesn't matter.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Sure, can I have their phone number please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to book a taxi for the commute between the two places.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is booking..", "trace": "domain=taxi; goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "can you book one for me so I arrive on time?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, that's all the information I need Thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am good to go.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of recommendation. Key information: requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, taxi; goal=recommendation, request_info, search, booking; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001867", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My son failed his physics exam yesterday So disappointed.\nChunk 2: My son failed his physics exam yesterday.\nChunk 3: Ouch, was it an unfair test or did he not study?\nChunk 4: Naw, he's somewhat lazy like myself when I was a young lad, but still, it was rather disappointing.", "streaming_reasoning": "C1 emotion=disappointed; cause=My son failed his physics exam yesterday So; need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 need=encouragement.", "deep_reasoning": "User feels disappointed after My son failed his physics exam yesterday So and needs encouragement.", "answer": "It makes sense to feel disappointed after My son failed his physics exam yesterday So. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: My son failed his physics exam yesterday So disappointed.\nChunk 2: My son failed his physics exam yesterday.\nChunk 3: Ouch, was it an unfair test or did he not study?\nChunk 4: Naw, he's somewhat lazy like myself when I was a young lad, but still, it was rather disappointing."}, {"role": "assistant", "content": "Streaming reasoning: C1 emotion=disappointed; cause=My son failed his physics exam yesterday So; need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 need=encouragement.\n\nDeep reasoning: User feels disappointed after My son failed his physics exam yesterday So and needs encouragement.\n\nAnswer: It makes sense to feel disappointed after My son failed his physics exam yesterday So. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My son failed his physics exam yesterday So disappointed.\nChunk 2: My son failed his physics exam yesterday.\nChunk 3: Ouch, was it an unfair test or did he not study?\nChunk 4: Naw, he's somewhat lazy like myself when I was a young lad, but still, it was rather disappointing.", "input_token_count": 53, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user expresses disappointed about My son failed his physics exam yesterday So; the user needs validation. Next, the user signals support or acknowledgment. Finally, the user needs encouragement.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 emotion=disappointed; cause=My son failed his physics exam yesterday So; need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 need=encouragement.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "My son failed his physics exam yesterday So disappointed.", "streaming_reasoning": "Initially, the user expresses disappointed about My son failed his physics exam yesterday So; the user needs validation..", "trace": "emotion=disappointed; cause=My son failed his physics exam yesterday So; need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "My son failed his physics exam yesterday.", "streaming_reasoning": "The content at C2 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Ouch, was it an unfair test or did he not study?", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Naw, he's somewhat lazy like myself when I was a young lad, but still, it was rather disappointing.", "streaming_reasoning": "Finally, the user needs encouragement..", "trace": "need=encouragement."}]}, "output": {"deep_reasoning": "User feels disappointed after My son failed his physics exam yesterday So and needs encouragement.", "answer": "It makes sense to feel disappointed after My son failed his physics exam yesterday So. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002800", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for Milton Country Park.\nChunk 2: Can I get the attraction type, entrance fee, and postcode please?\nChunk 3: I'm also looking for a great Italian restaurant on the east side of town that you would recommend.\nChunk 4: What are their prices like?\nChunk 5: What is the address and phone number to Pizza Hut Fen Ditton Great Thank you!\nChunk 6: That's all I needed.", "streaming_reasoning": "C1 domain=attraction; goal=search; type+=park. C2 goal=request_info; requested_info+=postcode, entrance_fee. C3 domain=restaurant; goal=recommendation; area+=east; cuisine+=italian. C4 goal=request_info. C5 destination+=pizza hut fen ditton great thank you!; requested_info+=address, phone. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, restaurant; goal=search, request_info, recommendation; area=east; food=italian; destination=pizza hut fen ditton great thank you!; requested_info=postcode, entrance_fee, address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for Milton Country Park.\nChunk 2: Can I get the attraction type, entrance fee, and postcode please?\nChunk 3: I'm also looking for a great Italian restaurant on the east side of town that you would recommend.\nChunk 4: What are their prices like?\nChunk 5: What is the address and phone number to Pizza Hut Fen Ditton Great Thank you!\nChunk 6: That's all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search; type+=park. C2 goal=request_info; requested_info+=postcode, entrance_fee. C3 domain=restaurant; goal=recommendation; area+=east; cuisine+=italian. C4 goal=request_info. C5 destination+=pizza hut fen ditton great thank you!; requested_info+=address, phone. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, restaurant; goal=search, request_info, recommendation; area=east; food=italian; destination=pizza hut fen ditton great thank you!; requested_info=postcode, entrance_fee, address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for Milton Country Park.\nChunk 2: Can I get the attraction type, entrance fee, and postcode please?\nChunk 3: I'm also looking for a great Italian restaurant on the east side of town that you would recommend.\nChunk 4: What are their prices like?\nChunk 5: What is the address and phone number to Pizza Hut Fen Ditton Great Thank you!\nChunk 6: That's all I needed.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; type: park. Next, the goal is request info; requested information: postcode. Next, the topic is restaurant; the goal is recommendation; area: east; cuisine: italian. Next, the goal is request info. Finally, destination: pizza hut fen ditton great thank you!; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info.. type: park.; requested information: postcode, address; area: east; cuisine: italian.; destination: pizza hut fen ditton great thank you!.", "trace": "C1 domain=attraction; goal=search; type+=park. C2 goal=request_info; requested_info+=postcode, entrance_fee. C3 domain=restaurant; goal=recommendation; area+=east; cuisine+=italian. C4 goal=request_info. C5 destination+=pizza hut fen ditton great thank you!; requested_info+=address, phone. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for Milton Country Park.", "streaming_reasoning": "Initially, the topic is attraction; the goal is search; type: park..", "trace": "domain=attraction; goal=search; type+=park."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I get the attraction type, entrance fee, and postcode please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode.", "trace": "goal=request_info; requested_info+=postcode, entrance_fee."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm also looking for a great Italian restaurant on the east side of town that you would recommend.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is recommendation; area: east; cuisine: italian..", "trace": "domain=restaurant; goal=recommendation; area+=east; cuisine+=italian."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What are their prices like?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What is the address and phone number to Pizza Hut Fen Ditton Great Thank you!", "streaming_reasoning": "As more information arrives, destination: pizza hut fen ditton great thank you!; requested information: address.", "trace": "destination+=pizza hut fen ditton great thank you!; requested_info+=address, phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all I needed.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is east; cuisine is italian; destination is pizza hut fen ditton great thank you!; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=search, request_info, recommendation; area=east; food=italian; destination=pizza hut fen ditton great thank you!; requested_info=postcode, entrance_fee, address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002801", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, can you tell me the star rating of that hotel?\nChunk 2: I want to find a same price european restaurant.\nChunk 3: It should be in the centre part of town.\nChunk 4: I also need the price Sounds good.\nChunk 5: I would like to make a reservation for Friday at 17:15 for 4 people.\nChunk 6: Could you also book me a taxi that arrives at the restaurant by the time of my reservation From the hotel.\nChunk 7: I would like to get a contact number for the taxi also, just in case something changes.\nChunk 8: No that will be all thank you goodbye.", "streaming_reasoning": "C1 domain=hotel; goal=request_info; hotel_type+=hotel; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; cuisine+=european; price+=same price; destination+=find a same price european restaurant. C3 area+=centre. C4 requested_info+=price; acceptance=selected_option. C5 goal=booking; time+=17:15, 4; day+=friday; party_size+=4 people; destination+=make a reservation for friday at 17:15 fo. C6 domain=taxi. C7 intent=context_update. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant, taxi; goal=request_info, search, modify_constraint, booking; area=centre; food=european; price=same price; party_size=4 people; destination=find a same price european restaurant, make a reservation for friday at 17:15 fo; requested_info=price; when=friday, 17:15, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, can you tell me the star rating of that hotel?\nChunk 2: I want to find a same price european restaurant.\nChunk 3: It should be in the centre part of town.\nChunk 4: I also need the price Sounds good.\nChunk 5: I would like to make a reservation for Friday at 17:15 for 4 people.\nChunk 6: Could you also book me a taxi that arrives at the restaurant by the time of my reservation From the hotel.\nChunk 7: I would like to get a contact number for the taxi also, just in case something changes.\nChunk 8: No that will be all thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=request_info; hotel_type+=hotel; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; cuisine+=european; price+=same price; destination+=find a same price european restaurant. C3 area+=centre. C4 requested_info+=price; acceptance=selected_option. C5 goal=booking; time+=17:15, 4; day+=friday; party_size+=4 people; destination+=make a reservation for friday at 17:15 fo. C6 domain=taxi. C7 intent=context_update. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant, taxi; goal=request_info, search, modify_constraint, booking; area=centre; food=european; price=same price; party_size=4 people; destination=find a same price european restaurant, make a reservation for friday at 17:15 fo; requested_info=price; when=friday, 17:15, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, can you tell me the star rating of that hotel?\nChunk 2: I want to find a same price european restaurant.\nChunk 3: It should be in the centre part of town.\nChunk 4: I also need the price Sounds good.\nChunk 5: I would like to make a reservation for Friday at 17:15 for 4 people.\nChunk 6: Could you also book me a taxi that arrives at the restaurant by the time of my reservation From the hotel.\nChunk 7: I would like to get a contact number for the taxi also, just in case something changes.\nChunk 8: No that will be all thank you goodbye.", "input_token_count": 113, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is request info; hotel type: hotel; acceptance: selected_option. Next, the topic is restaurant; the goal is modify constraint; cuisine: european; price: same price; destination: find a same price european restaurant. Next, area: centre. Next, requested information: price; acceptance: selected_option. Next, the goal is booking; time: 17:15; day: friday; party size: 4 people; destination: make a reservation for friday at 17:15 fo. Next, the topic is taxi. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi.. the goal is booking. hotel type: hotel; acceptance: selected_option.; cuisine: european; price: same price; destination: find a same price european restaurant., make a reservation for friday at 17:15 fo.; area: centre.; requested information: price; time: 17:15; day: friday; party size: 4 people; intent: context_update..", "trace": "C1 domain=hotel; goal=request_info; hotel_type+=hotel; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; cuisine+=european; price+=same price; destination+=find a same price european restaurant. C3 area+=centre. C4 requested_info+=price; acceptance=selected_option. C5 goal=booking; time+=17:15, 4; day+=friday; party_size+=4 people; destination+=make a reservation for friday at 17:15 fo. C6 domain=taxi. C7 intent=context_update. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, can you tell me the star rating of that hotel?", "streaming_reasoning": "Initially, the topic is hotel; the goal is request info; hotel type: hotel; acceptance: selected_option..", "trace": "domain=hotel; goal=request_info; hotel_type+=hotel; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to find a same price european restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint; cuisine: european; price: same price; destination: find a same price european restaurant..", "trace": "domain=restaurant; goal=modify_constraint; cuisine+=european; price+=same price; destination+=find a same price european restaurant."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the price Sounds good.", "streaming_reasoning": "As more information arrives, requested information: price; acceptance: selected_option..", "trace": "requested_info+=price; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like to make a reservation for Friday at 17:15 for 4 people.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 17:15; day: friday; party size: 4 people; destination: make a reservation for friday at 17:15 fo..", "trace": "goal=booking; time+=17:15, 4; day+=friday; party_size+=4 people; destination+=make a reservation for friday at 17:15 fo."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could you also book me a taxi that arrives at the restaurant by the time of my reservation From the hotel.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I would like to get a contact number for the taxi also, just in case something changes.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No that will be all thank you goodbye.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: area is centre; cuisine is european; price is same price; party size is 4 people; destination is find a same price european restaurant; requested information is price; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant, taxi; goal=request_info, search, modify_constraint, booking; area=centre; food=european; price=same price; party_size=4 people; destination=find a same price european restaurant, make a reservation for friday at 17:15 fo; requested_info=price; when=friday, 17:15, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002802", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to dine at a restaurant in the west part of town.\nChunk 2: Can you help me find one Moderately priced.\nChunk 3: yes please give me the phone number and address of it.\nChunk 4: No, thank you goodbye.\nChunk 5: Bye!", "streaming_reasoning": "C1 domain=restaurant; area+=west; destination+=dine at a restaurant in the west part of. C2 goal=search; price+=moderate. C3 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=west; price=moderate; destination=dine at a restaurant in the west part of; requested_info=address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like to dine at a restaurant in the west part of town.\nChunk 2: Can you help me find one Moderately priced.\nChunk 3: yes please give me the phone number and address of it.\nChunk 4: No, thank you goodbye.\nChunk 5: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=west; destination+=dine at a restaurant in the west part of. C2 goal=search; price+=moderate. C3 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=west; price=moderate; destination=dine at a restaurant in the west part of; requested_info=address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to dine at a restaurant in the west part of town.\nChunk 2: Can you help me find one Moderately priced.\nChunk 3: yes please give me the phone number and address of it.\nChunk 4: No, thank you goodbye.\nChunk 5: Bye!", "input_token_count": 47, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: west; destination: dine at a restaurant in the west part of. Next, the goal is search; price: moderate. Finally, the goal is request info; requested information: address; acceptance: selected_option.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: west; destination: dine at a restaurant in the west part of.; price: moderate.; requested information: address; acceptance: selected_option..", "trace": "C1 domain=restaurant; area+=west; destination+=dine at a restaurant in the west part of. C2 goal=search; price+=moderate. C3 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C4 [SKIP: thanks_only]. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like to dine at a restaurant in the west part of town.", "streaming_reasoning": "Initially, the topic is restaurant; area: west; destination: dine at a restaurant in the west part of..", "trace": "domain=restaurant; area+=west; destination+=dine at a restaurant in the west part of."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you help me find one Moderately priced.", "streaming_reasoning": "As more information arrives, the goal is search; price: moderate..", "trace": "goal=search; price+=moderate."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "yes please give me the phone number and address of it.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=address, phone; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, thank you goodbye.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Bye!", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is west; price is moderate; destination is dine at a restaurant in the west part of; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=west; price=moderate; destination=dine at a restaurant in the west part of; requested_info=address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001869", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My nephew told me once of something really stupid that he would do if the situation arose.\nChunk 2: My nephew told me once of something really stupid that he would do if the situation arose What situation?\nChunk 3: He would drink bleach.\nChunk 4: That really made my blood boil.", "streaming_reasoning": "C1 need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 emotion=frustrated; cause=That really made my blood boil.", "deep_reasoning": "User feels frustrated after That really made my blood boil and needs validation.", "answer": "It makes sense to feel frustrated after That really made my blood boil. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: My nephew told me once of something really stupid that he would do if the situation arose.\nChunk 2: My nephew told me once of something really stupid that he would do if the situation arose What situation?\nChunk 3: He would drink bleach.\nChunk 4: That really made my blood boil."}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 emotion=frustrated; cause=That really made my blood boil.\n\nDeep reasoning: User feels frustrated after That really made my blood boil and needs validation.\n\nAnswer: It makes sense to feel frustrated after That really made my blood boil. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My nephew told me once of something really stupid that he would do if the situation arose.\nChunk 2: My nephew told me once of something really stupid that he would do if the situation arose What situation?\nChunk 3: He would drink bleach.\nChunk 4: That really made my blood boil.", "input_token_count": 54, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user signals support or acknowledgment. Finally, the user expresses frustrated about That really made my blood boil.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 emotion=frustrated; cause=That really made my blood boil.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "My nephew told me once of something really stupid that he would do if the situation arose.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "My nephew told me once of something really stupid that he would do if the situation arose What situation?", "streaming_reasoning": "The content at C2 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "He would drink bleach.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That really made my blood boil.", "streaming_reasoning": "Finally, the user expresses frustrated about That really made my blood boil..", "trace": "emotion=frustrated; cause=That really made my blood boil."}]}, "output": {"deep_reasoning": "User feels frustrated after That really made my blood boil and needs validation.", "answer": "It makes sense to feel frustrated after That really made my blood boil. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002804", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please.\nChunk 2: I did state that I wanted the phone number.\nChunk 3: Can you give me some information on a hotel called holiday inn Cambridge, please Yes, please!\nChunk 4: I'll be traveling solo, and I need 3 nights starting Monday.\nChunk 5: Can I get a taxi that will take me to the hotel from the restaurant?\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 09:15.\nChunk 8: No, thank you That is all Goodbye.", "streaming_reasoning": "C1 acceptance=selected_option. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; hotel_type+=hotel; acceptance=selected_option. C4 goal=search; time+=3; day+=monday; stay_length+=3 nights. C5 domain=taxi. C6 destination+=find a restaurant. C7 time+=09:15. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant, taxi; goal=request_info, search; stay_length=3 nights; destination=find a restaurant; requested_info=phone; when=monday, 3, 09:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please.\nChunk 2: I did state that I wanted the phone number.\nChunk 3: Can you give me some information on a hotel called holiday inn Cambridge, please Yes, please!\nChunk 4: I'll be traveling solo, and I need 3 nights starting Monday.\nChunk 5: Can I get a taxi that will take me to the hotel from the restaurant?\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 09:15.\nChunk 8: No, thank you That is all Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 acceptance=selected_option. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; hotel_type+=hotel; acceptance=selected_option. C4 goal=search; time+=3; day+=monday; stay_length+=3 nights. C5 domain=taxi. C6 destination+=find a restaurant. C7 time+=09:15. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant, taxi; goal=request_info, search; stay_length=3 nights; destination=find a restaurant; requested_info=phone; when=monday, 3, 09:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please.\nChunk 2: I did state that I wanted the phone number.\nChunk 3: Can you give me some information on a hotel called holiday inn Cambridge, please Yes, please!\nChunk 4: I'll be traveling solo, and I need 3 nights starting Monday.\nChunk 5: Can I get a taxi that will take me to the hotel from the restaurant?\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 09:15.\nChunk 8: No, thank you That is all Goodbye.", "input_token_count": 87, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, acceptance: selected_option. Next, the goal is request info; requested information: phone. Next, the topic is hotel; hotel type: hotel; acceptance: selected_option. Next, the goal is search; time: 3; day: monday; stay length: 3 nights. Next, the topic is taxi. Next, destination: find a restaurant. Finally, time: 09:15.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi.. the goal is search. acceptance: selected_option.; requested information: phone.; hotel type: hotel; time: 3, 09:15.; day: monday; stay length: 3 nights.; destination: find a restaurant..", "trace": "C1 acceptance=selected_option. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; hotel_type+=hotel; acceptance=selected_option. C4 goal=search; time+=3; day+=monday; stay_length+=3 nights. C5 domain=taxi. C6 destination+=find a restaurant. C7 time+=09:15. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please.", "streaming_reasoning": "Initially, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I did state that I wanted the phone number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you give me some information on a hotel called holiday inn Cambridge, please Yes, please!", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; acceptance: selected_option..", "trace": "domain=hotel; hotel_type+=hotel; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll be traveling solo, and I need 3 nights starting Monday.", "streaming_reasoning": "As more information arrives, the goal is search; time: 3; day: monday; stay length: 3 nights..", "trace": "goal=search; time+=3; day+=monday; stay_length+=3 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get a taxi that will take me to the hotel from the restaurant?", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, destination: find a restaurant..", "trace": "destination+=find a restaurant."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 09:15.", "streaming_reasoning": "As more information arrives, time: 09:15..", "trace": "time+=09:15."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, thank you That is all Goodbye.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: stay length is 3 nights; destination is find a restaurant; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant, taxi; goal=request_info, search; stay_length=3 nights; destination=find a restaurant; requested_info=phone; when=monday, 3, 09:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000582", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Install Windows XP on an ASUS Eee PC Using a USB Drive.\nChunk 2: • A desktop computer (not your ASUS EeePc) • A legal copy of Windows XP Service Pack 2 CD with proper serial key • A USB memory flash drive (you can also use a USB Hard Drive).\nChunk 3: 4GB and up recommended for later Windows versions (i.e.\nChunk 4: Windows Vista or Windows 7), which use up to 2.7/2.8GB of space • USB multi-boot software from the internet • Asus EeePc (Asus Eee Pc 701 4G is used in example, but it should work for any Asus netbook).", "streaming_reasoning": "C1 task=install_windows_xp_on. C2 step=a_desktop_computer_not. C3 step=4gb_and_up_recommended. C4 step=windows_vista_or_windows.", "deep_reasoning": "Procedure for Install Windows XP on an ASUS Eee PC: A desktop computer A legal copy of Windows XP Service, 4GB and up recommended for later Windows versions (i.e, Windows Vista or Windows 7), which use up to 2.7/2.8GB.", "answer": "For Install Windows XP on an ASUS Eee PC, follow the steps in order: A desktop computer A legal copy of Windows XP Service, 4GB and up recommended for later Windows versions (i.e, Windows Vista or Windows 7), which use up to 2.7/2.8GB.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Install Windows XP on an ASUS Eee PC Using a USB Drive.\nChunk 2: • A desktop computer (not your ASUS EeePc) • A legal copy of Windows XP Service Pack 2 CD with proper serial key • A USB memory flash drive (you can also use a USB Hard Drive).\nChunk 3: 4GB and up recommended for later Windows versions (i.e.\nChunk 4: Windows Vista or Windows 7), which use up to 2.7/2.8GB of space • USB multi-boot software from the internet • Asus EeePc (Asus Eee Pc 701 4G is used in example, but it should work for any Asus netbook)."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=install_windows_xp_on. C2 step=a_desktop_computer_not. C3 step=4gb_and_up_recommended. C4 step=windows_vista_or_windows.\n\nDeep reasoning: Procedure for Install Windows XP on an ASUS Eee PC: A desktop computer A legal copy of Windows XP Service, 4GB and up recommended for later Windows versions (i.e, Windows Vista or Windows 7), which use up to 2.7/2.8GB.\n\nAnswer: For Install Windows XP on an ASUS Eee PC, follow the steps in order: A desktop computer A legal copy of Windows XP Service, 4GB and up recommended for later Windows versions (i.e, Windows Vista or Windows 7), which use up to 2.7/2.8GB."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Install Windows XP on an ASUS Eee PC Using a USB Drive.\nChunk 2: • A desktop computer (not your ASUS EeePc) • A legal copy of Windows XP Service Pack 2 CD with proper serial key • A USB memory flash drive (you can also use a USB Hard Drive).\nChunk 3: 4GB and up recommended for later Windows versions (i.e.\nChunk 4: Windows Vista or Windows 7), which use up to 2.7/2.8GB of space • USB multi-boot software from the internet • Asus EeePc (Asus Eee Pc 701 4G is used in example, but it should work for any Asus netbook).", "input_token_count": 105, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, task: install_windows_xp_on. Next, step: a_desktop_computer_not. Next, step: 4gb_and_up_recommended. Finally, step: windows_vista_or_windows. In summary, task: install_windows_xp_on.; step: a_desktop_computer_not., 4gb_and_up_recommended., windows_vista_or_windows..", "trace": "C1 task=install_windows_xp_on. C2 step=a_desktop_computer_not. C3 step=4gb_and_up_recommended. C4 step=windows_vista_or_windows.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Install Windows XP on an ASUS Eee PC Using a USB Drive.", "streaming_reasoning": "Initially, task: install_windows_xp_on..", "trace": "task=install_windows_xp_on."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "• A desktop computer (not your ASUS EeePc) • A legal copy of Windows XP Service Pack 2 CD with proper serial key • A USB memory flash drive (you can also use a USB Hard Drive).", "streaming_reasoning": "As more information arrives, step: a_desktop_computer_not..", "trace": "step=a_desktop_computer_not."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "4GB and up recommended for later Windows versions (i.e.", "streaming_reasoning": "As more information arrives, step: 4gb_and_up_recommended..", "trace": "step=4gb_and_up_recommended."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Windows Vista or Windows 7), which use up to 2.7/2.8GB of space • USB multi-boot software from the internet • Asus EeePc (Asus Eee Pc 701 4G is used in example, but it should work for any Asus netbook).", "streaming_reasoning": "Finally, step: windows_vista_or_windows..", "trace": "step=windows_vista_or_windows."}]}, "output": {"deep_reasoning": "Procedure for Install Windows XP on an ASUS Eee PC: A desktop computer A legal copy of Windows XP Service, 4GB and up recommended for later Windows versions (i.e, Windows Vista or Windows 7), which use up to 2.7/2.8GB.", "answer": "For Install Windows XP on an ASUS Eee PC, follow the steps in order: A desktop computer A legal copy of Windows XP Service, 4GB and up recommended for later Windows versions (i.e, Windows Vista or Windows 7), which use up to 2.7/2.8GB."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002805", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It should be a guesthouse and very expensive.\nChunk 2: yeah, check hotels instead of guesthouses Awesome.\nChunk 3: Thanks.\nChunk 4: Can you book that for me?\nChunk 5: Three people starting on saturday for four nights please.\nChunk 6: I also need a reference number.\nChunk 7: That sounds great, thank you!\nChunk 8: Thank you for booking that hotel stay for me.\nChunk 9: That will be all for today.", "streaming_reasoning": "C1 domain=hotel; price+=expensive; hotel_type+=guesthouse. C2 goal=compare_alternative; hotel_type+=hotel. C3 [SKIP: thanks_only]. C4 goal=booking. C5 day+=saturday; party_size+=3 people. C6 goal=request_info; requested_info+=reference_number. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=compare_alternative, booking, search, request_info; price=expensive; party_size=3 people; requested_info=reference_number; when=saturday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: It should be a guesthouse and very expensive.\nChunk 2: yeah, check hotels instead of guesthouses Awesome.\nChunk 3: Thanks.\nChunk 4: Can you book that for me?\nChunk 5: Three people starting on saturday for four nights please.\nChunk 6: I also need a reference number.\nChunk 7: That sounds great, thank you!\nChunk 8: Thank you for booking that hotel stay for me.\nChunk 9: That will be all for today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; price+=expensive; hotel_type+=guesthouse. C2 goal=compare_alternative; hotel_type+=hotel. C3 [SKIP: thanks_only]. C4 goal=booking. C5 day+=saturday; party_size+=3 people. C6 goal=request_info; requested_info+=reference_number. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=compare_alternative, booking, search, request_info; price=expensive; party_size=3 people; requested_info=reference_number; when=saturday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It should be a guesthouse and very expensive.\nChunk 2: yeah, check hotels instead of guesthouses Awesome.\nChunk 3: Thanks.\nChunk 4: Can you book that for me?\nChunk 5: Three people starting on saturday for four nights please.\nChunk 6: I also need a reference number.\nChunk 7: That sounds great, thank you!\nChunk 8: Thank you for booking that hotel stay for me.\nChunk 9: That will be all for today.", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; price: expensive; hotel type: guesthouse. Next, the goal is compare alternative; hotel type: hotel. Next, the goal is booking. Next, day: saturday; party size: 3 people. Next, the goal is request info; requested information: reference_number. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is request info. price: expensive; hotel type: guesthouse., hotel.; day: saturday; party size: 3 people.; requested information: reference_number.; intent: context_update..", "trace": "C1 domain=hotel; price+=expensive; hotel_type+=guesthouse. C2 goal=compare_alternative; hotel_type+=hotel. C3 [SKIP: thanks_only]. C4 goal=booking. C5 day+=saturday; party_size+=3 people. C6 goal=request_info; requested_info+=reference_number. C7 intent=context_update. C8 intent=context_update. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "It should be a guesthouse and very expensive.", "streaming_reasoning": "Initially, the topic is hotel; price: expensive; hotel type: guesthouse..", "trace": "domain=hotel; price+=expensive; hotel_type+=guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "yeah, check hotels instead of guesthouses Awesome.", "streaming_reasoning": "As more information arrives, the goal is compare alternative; hotel type: hotel..", "trace": "goal=compare_alternative; hotel_type+=hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you book that for me?", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Three people starting on saturday for four nights please.", "streaming_reasoning": "As more information arrives, day: saturday; party size: 3 people..", "trace": "day+=saturday; party_size+=3 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need a reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That sounds great, thank you!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for booking that hotel stay for me.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That will be all for today.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of compare alternative. Key information: price is expensive; party size is 3 people; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=compare_alternative, booking, search, request_info; price=expensive; party_size=3 people; requested_info=reference_number; when=saturday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002807", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I need a train to cambridge.\nChunk 2: I need to depart from kings lynn on the same day as the hotel booking.\nChunk 3: I need to depart from kings lynn on Wednesday and arrive by 9:15.\nChunk 4: Can you tell me when that departs and the total travel time?\nChunk 5: Also, how much is it?\nChunk 6: I actually won't need a reservation, just the information you provided is enough Thank you.\nChunk 7: Have a good day.\nChunk 8: Bye.\nChunk 9: Thank you for all your help.", "streaming_reasoning": "C1 domain=train; goal=search; destination+=cambridge; acceptance=selected_option. C2 domain=hotel; goal=booking; hotel_type+=hotel; departure+=kings lynn on the same day as the hotel booking. C3 time+=9:15; day+=wednesday; departure+=kings lynn on wednesday and arrive by 9:15. C4 goal=request_info; requested_info+=travel_time. C5 goal=request_info. C6 intent=context_update. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, hotel; goal=search, booking, request_info; destination=cambridge; departure=kings lynn on the same day as the hotel booking, kings lynn on wednesday and arrive by 9:15; requested_info=travel_time; when=wednesday, 9:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I need a train to cambridge.\nChunk 2: I need to depart from kings lynn on the same day as the hotel booking.\nChunk 3: I need to depart from kings lynn on Wednesday and arrive by 9:15.\nChunk 4: Can you tell me when that departs and the total travel time?\nChunk 5: Also, how much is it?\nChunk 6: I actually won't need a reservation, just the information you provided is enough Thank you.\nChunk 7: Have a good day.\nChunk 8: Bye.\nChunk 9: Thank you for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=cambridge; acceptance=selected_option. C2 domain=hotel; goal=booking; hotel_type+=hotel; departure+=kings lynn on the same day as the hotel booking. C3 time+=9:15; day+=wednesday; departure+=kings lynn on wednesday and arrive by 9:15. C4 goal=request_info; requested_info+=travel_time. C5 goal=request_info. C6 intent=context_update. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, hotel; goal=search, booking, request_info; destination=cambridge; departure=kings lynn on the same day as the hotel booking, kings lynn on wednesday and arrive by 9:15; requested_info=travel_time; when=wednesday, 9:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I need a train to cambridge.\nChunk 2: I need to depart from kings lynn on the same day as the hotel booking.\nChunk 3: I need to depart from kings lynn on Wednesday and arrive by 9:15.\nChunk 4: Can you tell me when that departs and the total travel time?\nChunk 5: Also, how much is it?\nChunk 6: I actually won't need a reservation, just the information you provided is enough Thank you.\nChunk 7: Have a good day.\nChunk 8: Bye.\nChunk 9: Thank you for all your help.", "input_token_count": 97, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge; acceptance: selected_option. Next, the topic is hotel; the goal is booking; hotel type: hotel; departure point: kings lynn on the same day as the hotel booking. Next, time: 9:15; day: wednesday; departure point: kings lynn on wednesday and arrive by 9:15. Next, the goal is request info; requested information: travel_time. Next, the goal is request info. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or repeated_information or thanks_only. In summary, The overall topic is hotel. the goal is request info.. destination: cambridge; acceptance: selected_option.; hotel type: hotel; departure point: kings lynn on the same day as the hotel booking., kings lynn on wednesday and arrive by 9:15.; time: 9:15; day: wednesday; requested information: travel_time.; intent: context_update..", "trace": "C1 domain=train; goal=search; destination+=cambridge; acceptance=selected_option. C2 domain=hotel; goal=booking; hotel_type+=hotel; departure+=kings lynn on the same day as the hotel booking. C3 time+=9:15; day+=wednesday; departure+=kings lynn on wednesday and arrive by 9:15. C4 goal=request_info; requested_info+=travel_time. C5 goal=request_info. C6 intent=context_update. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I need a train to cambridge.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge; acceptance: selected_option..", "trace": "domain=train; goal=search; destination+=cambridge; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to depart from kings lynn on the same day as the hotel booking.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is booking; hotel type: hotel; departure point: kings lynn on the same day as the hotel booking..", "trace": "domain=hotel; goal=booking; hotel_type+=hotel; departure+=kings lynn on the same day as the hotel booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to depart from kings lynn on Wednesday and arrive by 9:15.", "streaming_reasoning": "As more information arrives, time: 9:15; day: wednesday; departure point: kings lynn on wednesday and arrive by 9:15..", "trace": "time+=9:15; day+=wednesday; departure+=kings lynn on wednesday and arrive by 9:15."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you tell me when that departs and the total travel time?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Also, how much is it?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I actually won't need a reservation, just the information you provided is enough Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a good day.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Bye.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge; departure point is kings lynn on the same day as the hotel booking; requested information is travel_time; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, booking, request_info; destination=cambridge; departure=kings lynn on the same day as the hotel booking, kings lynn on wednesday and arrive by 9:15; requested_info=travel_time; when=wednesday, 9:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002808", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to get a train ticket for friday please.\nChunk 2: I need to get to Cambridge from Broxbourne and I'd like to leave after 13:15.\nChunk 3: Yes.\nChunk 4: Please book for 1 person.\nChunk 5: Yes, if I could please get the reference number.\nChunk 6: I want to find a hotel.\nChunk 7: The time is friday, 4.\nChunk 8: Please make a booking That's it!\nChunk 9: Thank you for your help!", "streaming_reasoning": "C1 domain=train; goal=request_info; day+=friday. C2 time+=13:15; destination+=leave; departure+=broxbourne and i'd like. C3 [SKIP: acknowledgement_only]. C4 goal=booking. C5 requested_info+=reference_number; goal=confirm_booking. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, hotel; goal=search, request_info, booking; destination=leave, find a hotel; departure=broxbourne and i'd like; requested_info=reference_number; when=friday, 13:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to get a train ticket for friday please.\nChunk 2: I need to get to Cambridge from Broxbourne and I'd like to leave after 13:15.\nChunk 3: Yes.\nChunk 4: Please book for 1 person.\nChunk 5: Yes, if I could please get the reference number.\nChunk 6: I want to find a hotel.\nChunk 7: The time is friday, 4.\nChunk 8: Please make a booking That's it!\nChunk 9: Thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=request_info; day+=friday. C2 time+=13:15; destination+=leave; departure+=broxbourne and i'd like. C3 [SKIP: acknowledgement_only]. C4 goal=booking. C5 requested_info+=reference_number; goal=confirm_booking. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, hotel; goal=search, request_info, booking; destination=leave, find a hotel; departure=broxbourne and i'd like; requested_info=reference_number; when=friday, 13:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to get a train ticket for friday please.\nChunk 2: I need to get to Cambridge from Broxbourne and I'd like to leave after 13:15.\nChunk 3: Yes.\nChunk 4: Please book for 1 person.\nChunk 5: Yes, if I could please get the reference number.\nChunk 6: I want to find a hotel.\nChunk 7: The time is friday, 4.\nChunk 8: Please make a booking That's it!\nChunk 9: Thank you for your help!", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is request info; day: friday. Next, time: 13:15; destination: leave; departure point: broxbourne and i'd like. Next, the goal is booking. Next, the goal is confirm booking.; requested information: reference_number. Next, the topic is hotel; hotel type: hotel; destination: find a hotel. Finally, intent: context_update.  Some chunks were skipped because they contained acknowledgement_only or repeated_information or thanks_only. In summary, The overall topic is hotel. the goal is confirm booking.. day: friday.; time: 13:15; destination: leave, find a hotel.; departure point: broxbourne and i'd like.; requested information: reference_number; hotel type: hotel; intent: context_update..", "trace": "C1 domain=train; goal=request_info; day+=friday. C2 time+=13:15; destination+=leave; departure+=broxbourne and i'd like. C3 [SKIP: acknowledgement_only]. C4 goal=booking. C5 requested_info+=reference_number; goal=confirm_booking. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to get a train ticket for friday please.", "streaming_reasoning": "Initially, the topic is train; the goal is request info; day: friday..", "trace": "domain=train; goal=request_info; day+=friday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to get to Cambridge from Broxbourne and I'd like to leave after 13:15.", "streaming_reasoning": "As more information arrives, time: 13:15; destination: leave; departure point: broxbourne and i'd like..", "trace": "time+=13:15; destination+=leave; departure+=broxbourne and i'd like."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes.", "streaming_reasoning": "The content at C3 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please book for 1 person.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, if I could please get the reference number.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: reference_number.", "trace": "requested_info+=reference_number; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is friday, 4.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking That's it!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you for your help!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is leave; departure point is broxbourne and i'd like; requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, request_info, booking; destination=leave, find a hotel; departure=broxbourne and i'd like; requested_info=reference_number; when=friday, 13:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002809", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need the type of place it is, the number and full adress please.\nChunk 2: Great thank you I also will need some info on a restaurant called The Copper Kettle.\nChunk 3: Yes, I would like to book a table for 2 people at 15:30 on Monday, please.\nChunk 4: Yes, I would also like a taxi to get me from the guesthouse to the restaurant.\nChunk 5: Thank you very much for the service.\nChunk 6: Thats all thank you for your help,goodbye.", "streaming_reasoning": "C1 goal=search. C2 domain=restaurant. C3 goal=confirm_booking; time+=2, 15:30; day+=monday; party_size+=2 people; goal=confirm_booking. C4 domain=taxi; goal=request_info; hotel_type+=guesthouse; destination+=the restaurant; departure+=the guesthouse; goal=confirm_booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel, taxi; goal=search, booking, confirm_booking, request_info; party_size=2 people; destination=the restaurant; departure=the guesthouse; when=monday, 2, 15:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need the type of place it is, the number and full adress please.\nChunk 2: Great thank you I also will need some info on a restaurant called The Copper Kettle.\nChunk 3: Yes, I would like to book a table for 2 people at 15:30 on Monday, please.\nChunk 4: Yes, I would also like a taxi to get me from the guesthouse to the restaurant.\nChunk 5: Thank you very much for the service.\nChunk 6: Thats all thank you for your help,goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 domain=restaurant. C3 goal=confirm_booking; time+=2, 15:30; day+=monday; party_size+=2 people; goal=confirm_booking. C4 domain=taxi; goal=request_info; hotel_type+=guesthouse; destination+=the restaurant; departure+=the guesthouse; goal=confirm_booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel, taxi; goal=search, booking, confirm_booking, request_info; party_size=2 people; destination=the restaurant; departure=the guesthouse; when=monday, 2, 15:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need the type of place it is, the number and full adress please.\nChunk 2: Great thank you I also will need some info on a restaurant called The Copper Kettle.\nChunk 3: Yes, I would like to book a table for 2 people at 15:30 on Monday, please.\nChunk 4: Yes, I would also like a taxi to get me from the guesthouse to the restaurant.\nChunk 5: Thank you very much for the service.\nChunk 6: Thats all thank you for your help,goodbye.", "input_token_count": 90, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, the topic is restaurant. Next, the goal is confirm booking.; time: 2; day: monday; party size: 2 people. Finally, the topic is taxi; the goal is confirm booking.; hotel type: guesthouse; destination: the restaurant; departure point: the guesthouse.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is confirm booking.. time: 2; day: monday; party size: 2 people; hotel type: guesthouse; destination: the restaurant; departure point: the guesthouse.", "trace": "C1 goal=search. C2 domain=restaurant. C3 goal=confirm_booking; time+=2, 15:30; day+=monday; party_size+=2 people; goal=confirm_booking. C4 domain=taxi; goal=request_info; hotel_type+=guesthouse; destination+=the restaurant; departure+=the guesthouse; goal=confirm_booking. C5 [SKIP: thanks_only]. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need the type of place it is, the number and full adress please.", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Great thank you I also will need some info on a restaurant called The Copper Kettle.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I would like to book a table for 2 people at 15:30 on Monday, please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 2; day: monday; party size: 2 people.", "trace": "goal=confirm_booking; time+=2, 15:30; day+=monday; party_size+=2 people; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I would also like a taxi to get me from the guesthouse to the restaurant.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is confirm booking.; hotel type: guesthouse; destination: the restaurant; departure point: the guesthouse.", "trace": "domain=taxi; goal=request_info; hotel_type+=guesthouse; destination+=the restaurant; departure+=the guesthouse; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you very much for the service.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thats all thank you for your help,goodbye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 2 people; destination is the restaurant; departure point is the guesthouse; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel, taxi; goal=search, booking, confirm_booking, request_info; party_size=2 people; destination=the restaurant; departure=the guesthouse; when=monday, 2, 15:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002810", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need the name and number for an expensive restaurant in the city center.\nChunk 2: Yes expensive Korean food.\nChunk 3: Yes, please book a table.\nChunk 4: for 2 peopl at 18:15 on sunday.\nChunk 5: No.\nChunk 6: That is all for today Thank you.\nChunk 7: I've got to run so I'm not late for work Thanks Goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; price+=expensive. C2 cuisine+=korean; acceptance=selected_option. C3 goal=confirm_booking; goal=confirm_booking. C4 time+=2, 18:15; day+=sunday. C5 goal=modify_constraint. C6 [SKIP: closing_only]. C7 destination+=run so i'm not late for work thanks goodb.", "deep_reasoning": "Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; food=korean; price=expensive; destination=run so i'm not late for work thanks goodb; when=sunday, 2, 18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also need the name and number for an expensive restaurant in the city center.\nChunk 2: Yes expensive Korean food.\nChunk 3: Yes, please book a table.\nChunk 4: for 2 peopl at 18:15 on sunday.\nChunk 5: No.\nChunk 6: That is all for today Thank you.\nChunk 7: I've got to run so I'm not late for work Thanks Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; price+=expensive. C2 cuisine+=korean; acceptance=selected_option. C3 goal=confirm_booking; goal=confirm_booking. C4 time+=2, 18:15; day+=sunday. C5 goal=modify_constraint. C6 [SKIP: closing_only]. C7 destination+=run so i'm not late for work thanks goodb.\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; food=korean; price=expensive; destination=run so i'm not late for work thanks goodb; when=sunday, 2, 18:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need the name and number for an expensive restaurant in the city center.\nChunk 2: Yes expensive Korean food.\nChunk 3: Yes, please book a table.\nChunk 4: for 2 peopl at 18:15 on sunday.\nChunk 5: No.\nChunk 6: That is all for today Thank you.\nChunk 7: I've got to run so I'm not late for work Thanks Goodbye.", "input_token_count": 66, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: expensive. Next, cuisine: korean; acceptance: selected_option. Next, the goal is confirm booking. Next, time: 2; day: sunday. Next, the goal is modify constraint. Finally, destination: run so i'm not late for work thanks goodb.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is modify constraint.. area: centre; price: expensive.; cuisine: korean; acceptance: selected_option.; time: 2; day: sunday.; destination: run so i'm not late for work thanks goodb..", "trace": "C1 domain=restaurant; goal=search; area+=centre; price+=expensive. C2 cuisine+=korean; acceptance=selected_option. C3 goal=confirm_booking; goal=confirm_booking. C4 time+=2, 18:15; day+=sunday. C5 goal=modify_constraint. C6 [SKIP: closing_only]. C7 destination+=run so i'm not late for work thanks goodb.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also need the name and number for an expensive restaurant in the city center.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; price: expensive..", "trace": "domain=restaurant; goal=search; area+=centre; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes expensive Korean food.", "streaming_reasoning": "As more information arrives, cuisine: korean; acceptance: selected_option..", "trace": "cuisine+=korean; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, please book a table.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "for 2 peopl at 18:15 on sunday.", "streaming_reasoning": "As more information arrives, time: 2; day: sunday..", "trace": "time+=2, 18:15; day+=sunday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all for today Thank you.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I've got to run so I'm not late for work Thanks Goodbye.", "streaming_reasoning": "Finally, destination: run so i'm not late for work thanks goodb..", "trace": "destination+=run so i'm not late for work thanks goodb."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is korean; price is expensive; destination is run so i'm not late for work thanks goodb; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; food=korean; price=expensive; destination=run so i'm not late for work thanks goodb; when=sunday, 2, 18:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002811", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm departing from Stevenage on Thursday.\nChunk 2: I don't think so but how much does that one cost?\nChunk 3: I need the train ID.\nChunk 4: No, but I do need to know when the train TR 3330 arrives, please.\nChunk 5: That looks to be all, thank you for your help Thank you, goodbye.", "streaming_reasoning": "C1 day+=thursday; departure+=stevenage on thursday. C2 goal=request_info; requested_info+=price. C3 domain=train; goal=search. C4 destination+=know when the train tr 3330 arrives. C5 destination+=be all.", "deep_reasoning": "Need domain=train; goal=request_info, search; destination=know when the train tr 3330 arrives, be all; departure=stevenage on thursday; requested_info=price; when=thursday.", "answer": "I can help with that and include the price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm departing from Stevenage on Thursday.\nChunk 2: I don't think so but how much does that one cost?\nChunk 3: I need the train ID.\nChunk 4: No, but I do need to know when the train TR 3330 arrives, please.\nChunk 5: That looks to be all, thank you for your help Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=thursday; departure+=stevenage on thursday. C2 goal=request_info; requested_info+=price. C3 domain=train; goal=search. C4 destination+=know when the train tr 3330 arrives. C5 destination+=be all.\n\nDeep reasoning: Need domain=train; goal=request_info, search; destination=know when the train tr 3330 arrives, be all; departure=stevenage on thursday; requested_info=price; when=thursday.\n\nAnswer: I can help with that and include the price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm departing from Stevenage on Thursday.\nChunk 2: I don't think so but how much does that one cost?\nChunk 3: I need the train ID.\nChunk 4: No, but I do need to know when the train TR 3330 arrives, please.\nChunk 5: That looks to be all, thank you for your help Thank you, goodbye.", "input_token_count": 59, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, day: thursday; departure point: stevenage on thursday. Next, the goal is request info; requested information: price. Next, the topic is train; the goal is search. Next, destination: know when the train tr 3330 arrives. Finally, destination: be all. In summary, The overall topic is train. the goal is search.. day: thursday; departure point: stevenage on thursday.; requested information: price.; destination: know when the train tr 3330 arrives., be all..", "trace": "C1 day+=thursday; departure+=stevenage on thursday. C2 goal=request_info; requested_info+=price. C3 domain=train; goal=search. C4 destination+=know when the train tr 3330 arrives. C5 destination+=be all.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm departing from Stevenage on Thursday.", "streaming_reasoning": "Initially, day: thursday; departure point: stevenage on thursday..", "trace": "day+=thursday; departure+=stevenage on thursday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I don't think so but how much does that one cost?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need the train ID.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, but I do need to know when the train TR 3330 arrives, please.", "streaming_reasoning": "As more information arrives, destination: know when the train tr 3330 arrives..", "trace": "destination+=know when the train tr 3330 arrives."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That looks to be all, thank you for your help Thank you, goodbye.", "streaming_reasoning": "Finally, destination: be all..", "trace": "destination+=be all."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: destination is know when the train tr 3330 arrives; departure point is stevenage on thursday; requested information is price; timing is thursday.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the price once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=request_info, search; destination=know when the train tr 3330 arrives, be all; departure=stevenage on thursday; requested_info=price; when=thursday."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003494", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can I have an aisle seat, PLS No problem.\nChunk 2: I'll give you an aisle seat in the center row.\nChunk 3: And here is your ticket, passport and boarding pass.\nChunk 4: Please board the plane at Gate 15 Thank you.\nChunk 5: And when is the latest time for me to board the plane?\nChunk 6: 15mins before the plane takes off.\nChunk 7: The plane is scheduled to leave on time.\nChunk 8: Thank you very much!", "streaming_reasoning": "C1 casual_comment=aisle, seat. C2 casual_comment=i'll, give. C3 casual_comment=here, ticket. C4 casual_comment=board, plane. C5 question=true. C6 casual_comment=mins, plane. C7 casual_comment=plane, scheduled. C8 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can I have an aisle seat, PLS No problem.\nChunk 2: I'll give you an aisle seat in the center row.\nChunk 3: And here is your ticket, passport and boarding pass.\nChunk 4: Please board the plane at Gate 15 Thank you.\nChunk 5: And when is the latest time for me to board the plane?\nChunk 6: 15mins before the plane takes off.\nChunk 7: The plane is scheduled to leave on time.\nChunk 8: Thank you very much!"}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=aisle, seat. C2 casual_comment=i'll, give. C3 casual_comment=here, ticket. C4 casual_comment=board, plane. C5 question=true. C6 casual_comment=mins, plane. C7 casual_comment=plane, scheduled. C8 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can I have an aisle seat, PLS No problem.\nChunk 2: I'll give you an aisle seat in the center row.\nChunk 3: And here is your ticket, passport and boarding pass.\nChunk 4: Please board the plane at Gate 15 Thank you.\nChunk 5: And when is the latest time for me to board the plane?\nChunk 6: 15mins before the plane takes off.\nChunk 7: The plane is scheduled to leave on time.\nChunk 8: Thank you very much!", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on aisle. Next, the user comments on i'll. Next, the user comments on here. Next, the user comments on board. Next, the input provides additional context about question=true. Next, the user comments on mins. Finally, the user comments on plane.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=aisle, seat. C2 casual_comment=i'll, give. C3 casual_comment=here, ticket. C4 casual_comment=board, plane. C5 question=true. C6 casual_comment=mins, plane. C7 casual_comment=plane, scheduled. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can I have an aisle seat, PLS No problem.", "streaming_reasoning": "Initially, the user comments on aisle.", "trace": "casual_comment=aisle, seat."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'll give you an aisle seat in the center row.", "streaming_reasoning": "As more information arrives, the user comments on i'll.", "trace": "casual_comment=i'll, give."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "And here is your ticket, passport and boarding pass.", "streaming_reasoning": "As more information arrives, the user comments on here.", "trace": "casual_comment=here, ticket."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please board the plane at Gate 15 Thank you.", "streaming_reasoning": "As more information arrives, the user comments on board.", "trace": "casual_comment=board, plane."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "And when is the latest time for me to board the plane?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "15mins before the plane takes off.", "streaming_reasoning": "As more information arrives, the user comments on mins.", "trace": "casual_comment=mins, plane."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The plane is scheduled to leave on time.", "streaming_reasoning": "As more information arrives, the user comments on plane.", "trace": "casual_comment=plane, scheduled."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you very much!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002815", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a museum in east area.\nChunk 2: Can you give me the address and phone number of the free museum?\nChunk 3: That will do thank you.\nChunk 4: I also need a restaurant in the moderate price range.\nChunk 5: In the same area as Cambridge Artworks.\nChunk 6: Yes.\nChunk 7: I need to book it for Saturday at 17:30 Just for me.\nChunk 8: thanks.\nChunk 9: thats it for today thanks again goodbye.", "streaming_reasoning": "C1 domain=attraction; goal=search; area+=east. C2 goal=request_info; requested_info+=address, phone. C3 intent=context_update. C4 domain=restaurant; price+=moderate; requested_info+=price. C5 goal=modify_constraint. C6 [SKIP: acknowledgement_only]. C7 goal=booking; time+=17:30; day+=saturday. C8 [SKIP: thanks_only]. C9 day+=today.", "deep_reasoning": "Need domain=attraction, restaurant; goal=search, request_info, modify_constraint, booking; area=east; price=moderate; requested_info=address, phone, price; when=saturday, today, 17:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a museum in east area.\nChunk 2: Can you give me the address and phone number of the free museum?\nChunk 3: That will do thank you.\nChunk 4: I also need a restaurant in the moderate price range.\nChunk 5: In the same area as Cambridge Artworks.\nChunk 6: Yes.\nChunk 7: I need to book it for Saturday at 17:30 Just for me.\nChunk 8: thanks.\nChunk 9: thats it for today thanks again goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search; area+=east. C2 goal=request_info; requested_info+=address, phone. C3 intent=context_update. C4 domain=restaurant; price+=moderate; requested_info+=price. C5 goal=modify_constraint. C6 [SKIP: acknowledgement_only]. C7 goal=booking; time+=17:30; day+=saturday. C8 [SKIP: thanks_only]. C9 day+=today.\n\nDeep reasoning: Need domain=attraction, restaurant; goal=search, request_info, modify_constraint, booking; area=east; price=moderate; requested_info=address, phone, price; when=saturday, today, 17:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a museum in east area.\nChunk 2: Can you give me the address and phone number of the free museum?\nChunk 3: That will do thank you.\nChunk 4: I also need a restaurant in the moderate price range.\nChunk 5: In the same area as Cambridge Artworks.\nChunk 6: Yes.\nChunk 7: I need to book it for Saturday at 17:30 Just for me.\nChunk 8: thanks.\nChunk 9: thats it for today thanks again goodbye.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; area: east. Next, the goal is request info; requested information: address. Next, intent: context_update. Next, the topic is restaurant; price: moderate; requested information: price. Next, the goal is modify constraint. Next, the goal is booking; time: 17:30; day: saturday. Finally, day: today.  Some chunks were skipped because they contained acknowledgement_only or thanks_only. In summary, The overall topic is restaurant. the goal is booking. area: east.; requested information: address, price.; intent: context_update.; price: moderate; time: 17:30; day: saturday., today..", "trace": "C1 domain=attraction; goal=search; area+=east. C2 goal=request_info; requested_info+=address, phone. C3 intent=context_update. C4 domain=restaurant; price+=moderate; requested_info+=price. C5 goal=modify_constraint. C6 [SKIP: acknowledgement_only]. C7 goal=booking; time+=17:30; day+=saturday. C8 [SKIP: thanks_only]. C9 day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a museum in east area.", "streaming_reasoning": "Initially, the topic is attraction; the goal is search; area: east..", "trace": "domain=attraction; goal=search; area+=east."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you give me the address and phone number of the free museum?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That will do thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need a restaurant in the moderate price range.", "streaming_reasoning": "As more information arrives, the topic is restaurant; price: moderate; requested information: price..", "trace": "domain=restaurant; price+=moderate; requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "In the same area as Cambridge Artworks.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes.", "streaming_reasoning": "The content at C6 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I need to book it for Saturday at 17:30 Just for me.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 17:30; day: saturday..", "trace": "goal=booking; time+=17:30; day+=saturday."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "thanks.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "thats it for today thanks again goodbye.", "streaming_reasoning": "Finally, day: today..", "trace": "day+=today."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is east; price is moderate; requested information is address; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=search, request_info, modify_constraint, booking; area=east; price=moderate; requested_info=address, phone, price; when=saturday, today, 17:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003497", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: We hope you'll be able to join us.\nChunk 3: Thank you for the invitation.\nChunk 4: I'll be very happy to go Good!\nChunk 5: What time should I arrive?\nChunk 6: How about 6:00?", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 casual_comment=hope, you'll. C3 [SKIP: thanks_only]. C4 casual_comment=i'll, very. C5 question=true. C6 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: We hope you'll be able to join us.\nChunk 3: Thank you for the invitation.\nChunk 4: I'll be very happy to go Good!\nChunk 5: What time should I arrive?\nChunk 6: How about 6:00?"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 casual_comment=hope, you'll. C3 [SKIP: thanks_only]. C4 casual_comment=i'll, very. C5 question=true. C6 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: We hope you'll be able to join us.\nChunk 3: Thank you for the invitation.\nChunk 4: I'll be very happy to go Good!\nChunk 5: What time should I arrive?\nChunk 6: How about 6:00?", "input_token_count": 42, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on hope. Next, the user comments on i'll. Next, the input provides additional context about question=true. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained acknowledgement_only or thanks_only.", "trace": "C1 [SKIP: acknowledgement_only]. C2 casual_comment=hope, you'll. C3 [SKIP: thanks_only]. C4 casual_comment=i'll, very. C5 question=true. C6 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "We hope you'll be able to join us.", "streaming_reasoning": "As more information arrives, the user comments on hope.", "trace": "casual_comment=hope, you'll."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you for the invitation.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll be very happy to go Good!", "streaming_reasoning": "As more information arrives, the user comments on i'll.", "trace": "casual_comment=i'll, very."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What time should I arrive?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "How about 6:00?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002816", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Does it include free wifi?\nChunk 2: I want to find a hotel.\nChunk 3: It is for 6 people.\nChunk 4: The time is friday, 6.\nChunk 5: Please make a booking.\nChunk 6: Can you check for a different hotel in the same pricerange?\nChunk 7: It does not need to be a guesthouse.\nChunk 8: Can't you find anything that is east, 4 star with free wifi.\nChunk 9: That is all I require Please, its important.\nChunk 10: Yes, one of those will be fine Great!\nChunk 11: Nothing else at the moment, but thank you and goodbye.", "streaming_reasoning": "C1 amenities+=wifi. C2 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C3 party_size+=6 people. C4 time+=6; day+=friday. C5 goal=booking. C6 goal=modify_constraint; price+=same price range, same price. C7 hotel_type+=guesthouse; destination+=be a guesthouse. C8 area+=east; stars+=4 stars. C9 [SKIP: closing_only]. C10 goal=confirm_booking; goal=confirm_booking. C11 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=search, booking, compare_alternative, modify_constraint, confirm_booking; area=east; price=same price range, same price; party_size=6 people; stars=4 stars; amenities=wifi; destination=find a hotel, be a guesthouse; when=friday, 6; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Does it include free wifi?\nChunk 2: I want to find a hotel.\nChunk 3: It is for 6 people.\nChunk 4: The time is friday, 6.\nChunk 5: Please make a booking.\nChunk 6: Can you check for a different hotel in the same pricerange?\nChunk 7: It does not need to be a guesthouse.\nChunk 8: Can't you find anything that is east, 4 star with free wifi.\nChunk 9: That is all I require Please, its important.\nChunk 10: Yes, one of those will be fine Great!\nChunk 11: Nothing else at the moment, but thank you and goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 amenities+=wifi. C2 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C3 party_size+=6 people. C4 time+=6; day+=friday. C5 goal=booking. C6 goal=modify_constraint; price+=same price range, same price. C7 hotel_type+=guesthouse; destination+=be a guesthouse. C8 area+=east; stars+=4 stars. C9 [SKIP: closing_only]. C10 goal=confirm_booking; goal=confirm_booking. C11 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=search, booking, compare_alternative, modify_constraint, confirm_booking; area=east; price=same price range, same price; party_size=6 people; stars=4 stars; amenities=wifi; destination=find a hotel, be a guesthouse; when=friday, 6; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Does it include free wifi?\nChunk 2: I want to find a hotel.\nChunk 3: It is for 6 people.\nChunk 4: The time is friday, 6.\nChunk 5: Please make a booking.\nChunk 6: Can you check for a different hotel in the same pricerange?\nChunk 7: It does not need to be a guesthouse.\nChunk 8: Can't you find anything that is east, 4 star with free wifi.\nChunk 9: That is all I require Please, its important.\nChunk 10: Yes, one of those will be fine Great!\nChunk 11: Nothing else at the moment, but thank you and goodbye.", "input_token_count": 104, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, amenities: wifi. Next, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, party size: 6 people. Next, time: 6; day: friday. Next, the goal is booking. Next, the goal is modify constraint; price: same price range. Next, hotel type: guesthouse; destination: be a guesthouse. Next, area: east; star rating: 4 stars. Next, the goal is confirm booking. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is confirm booking.. amenities: wifi.; hotel type: hotel, guesthouse; destination: find a hotel., be a guesthouse.; party size: 6 people.; time: 6; day: friday.; price: same price range; area: east; star rating: 4 stars.; intent: context_update..", "trace": "C1 amenities+=wifi. C2 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C3 party_size+=6 people. C4 time+=6; day+=friday. C5 goal=booking. C6 goal=modify_constraint; price+=same price range, same price. C7 hotel_type+=guesthouse; destination+=be a guesthouse. C8 area+=east; stars+=4 stars. C9 [SKIP: closing_only]. C10 goal=confirm_booking; goal=confirm_booking. C11 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Does it include free wifi?", "streaming_reasoning": "Initially, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 6 people.", "streaming_reasoning": "As more information arrives, party size: 6 people..", "trace": "party_size+=6 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is friday, 6.", "streaming_reasoning": "As more information arrives, time: 6; day: friday..", "trace": "time+=6; day+=friday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you check for a different hotel in the same pricerange?", "streaming_reasoning": "As more information arrives, the goal is modify constraint; price: same price range.", "trace": "goal=modify_constraint; price+=same price range, same price."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "It does not need to be a guesthouse.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse; destination: be a guesthouse..", "trace": "hotel_type+=guesthouse; destination+=be a guesthouse."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Can't you find anything that is east, 4 star with free wifi.", "streaming_reasoning": "As more information arrives, area: east; star rating: 4 stars..", "trace": "area+=east; stars+=4 stars."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That is all I require Please, its important.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Yes, one of those will be fine Great!", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Nothing else at the moment, but thank you and goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is east; price is same price range; party size is 6 people; star rating is 4 stars; amenities is wifi; destination is find a hotel; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, compare_alternative, modify_constraint, confirm_booking; area=east; price=same price range, same price; party_size=6 people; stars=4 stars; amenities=wifi; destination=find a hotel, be a guesthouse; when=friday, 6; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002818", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to visit Clare College.\nChunk 2: Can you give me more information on it?\nChunk 3: You've told me everything I need to know.\nChunk 4: Thanks!\nChunk 5: Im looking for a expensive restaurant in the centre Can you assist?\nChunk 6: What an interesting name!\nChunk 7: Hmm, what do you have in the way of seafood restaurants?\nChunk 8: No thanks that's all I needed thank you for your help.", "streaming_reasoning": "C1 domain=attraction; destination+=visit clare college. C2 goal=request_info. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only]. C5 domain=restaurant; goal=search; area+=centre; price+=expensive. C6 intent=context_update. C7 cuisine+=seafood. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, restaurant; goal=request_info, search; area=centre; food=seafood; price=expensive; destination=visit clare college; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to visit Clare College.\nChunk 2: Can you give me more information on it?\nChunk 3: You've told me everything I need to know.\nChunk 4: Thanks!\nChunk 5: Im looking for a expensive restaurant in the centre Can you assist?\nChunk 6: What an interesting name!\nChunk 7: Hmm, what do you have in the way of seafood restaurants?\nChunk 8: No thanks that's all I needed thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; destination+=visit clare college. C2 goal=request_info. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only]. C5 domain=restaurant; goal=search; area+=centre; price+=expensive. C6 intent=context_update. C7 cuisine+=seafood. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, restaurant; goal=request_info, search; area=centre; food=seafood; price=expensive; destination=visit clare college; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to visit Clare College.\nChunk 2: Can you give me more information on it?\nChunk 3: You've told me everything I need to know.\nChunk 4: Thanks!\nChunk 5: Im looking for a expensive restaurant in the centre Can you assist?\nChunk 6: What an interesting name!\nChunk 7: Hmm, what do you have in the way of seafood restaurants?\nChunk 8: No thanks that's all I needed thank you for your help.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; destination: visit clare college. Next, the goal is request info. Next, the topic is restaurant; the goal is search; area: centre; price: expensive. Next, intent: context_update. Finally, cuisine: seafood.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is search. destination: visit clare college.; area: centre; price: expensive.; intent: context_update.; cuisine: seafood..", "trace": "C1 domain=attraction; destination+=visit clare college. C2 goal=request_info. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only]. C5 domain=restaurant; goal=search; area+=centre; price+=expensive. C6 intent=context_update. C7 cuisine+=seafood. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to visit Clare College.", "streaming_reasoning": "Initially, the topic is attraction; destination: visit clare college..", "trace": "domain=attraction; destination+=visit clare college."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you give me more information on it?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "You've told me everything I need to know.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks!", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Im looking for a expensive restaurant in the centre Can you assist?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; area: centre; price: expensive..", "trace": "domain=restaurant; goal=search; area+=centre; price+=expensive."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What an interesting name!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Hmm, what do you have in the way of seafood restaurants?", "streaming_reasoning": "As more information arrives, cuisine: seafood..", "trace": "cuisine+=seafood."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No thanks that's all I needed thank you for your help.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: area is centre; cuisine is seafood; price is expensive; destination is visit clare college. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=request_info, search; area=centre; food=seafood; price=expensive; destination=visit clare college; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002819", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.Let`s please try for shorter number of days.\nChunk 2: Thanks.\nChunk 3: Sorry, I did not want to book a room until I was sure of the price could you give that to me first?\nChunk 4: That's fine, thank you.\nChunk 5: I also need help with a train leaving Cambridge and going to London kings cross.\nChunk 6: I just want to leave after 16:45 going from cambridge to london kings cross on thursday.\nChunk 7: Not at this time.\nChunk 8: I just need the price.\nChunk 9: No, you've been a great help, thanks for your time.", "streaming_reasoning": "C1 acceptance=selected_option. C2 [SKIP: thanks_only]. C3 domain=hotel; goal=booking; requested_info+=price. C4 intent=context_update. C5 domain=train; destination+=london kings cross. C6 time+=16:45; day+=thursday; departure+=cambridge. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 goal=modify_constraint.", "deep_reasoning": "Need domain=hotel, train; goal=search, booking; destination=london kings cross; departure=cambridge; requested_info=price; when=thursday, 16:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.Let`s please try for shorter number of days.\nChunk 2: Thanks.\nChunk 3: Sorry, I did not want to book a room until I was sure of the price could you give that to me first?\nChunk 4: That's fine, thank you.\nChunk 5: I also need help with a train leaving Cambridge and going to London kings cross.\nChunk 6: I just want to leave after 16:45 going from cambridge to london kings cross on thursday.\nChunk 7: Not at this time.\nChunk 8: I just need the price.\nChunk 9: No, you've been a great help, thanks for your time."}, {"role": "assistant", "content": "Streaming reasoning: C1 acceptance=selected_option. C2 [SKIP: thanks_only]. C3 domain=hotel; goal=booking; requested_info+=price. C4 intent=context_update. C5 domain=train; destination+=london kings cross. C6 time+=16:45; day+=thursday; departure+=cambridge. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 goal=modify_constraint.\n\nDeep reasoning: Need domain=hotel, train; goal=search, booking; destination=london kings cross; departure=cambridge; requested_info=price; when=thursday, 16:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.Let`s please try for shorter number of days.\nChunk 2: Thanks.\nChunk 3: Sorry, I did not want to book a room until I was sure of the price could you give that to me first?\nChunk 4: That's fine, thank you.\nChunk 5: I also need help with a train leaving Cambridge and going to London kings cross.\nChunk 6: I just want to leave after 16:45 going from cambridge to london kings cross on thursday.\nChunk 7: Not at this time.\nChunk 8: I just need the price.\nChunk 9: No, you've been a great help, thanks for your time.", "input_token_count": 107, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, acceptance: selected_option. Next, the topic is hotel; the goal is booking; requested information: price. Next, intent: context_update. Next, the topic is train; destination: london kings cross. Next, time: 16:45; day: thursday; departure point: cambridge. Next, intent: context_update. Finally, the goal is modify constraint.  Some chunks were skipped because they contained repeated_information or thanks_only. In summary, The overall topic is train. the goal is modify constraint.. acceptance: selected_option.; requested information: price.; intent: context_update.; destination: london kings cross.; time: 16:45; day: thursday; departure point: cambridge..", "trace": "C1 acceptance=selected_option. C2 [SKIP: thanks_only]. C3 domain=hotel; goal=booking; requested_info+=price. C4 intent=context_update. C5 domain=train; destination+=london kings cross. C6 time+=16:45; day+=thursday; departure+=cambridge. C7 [SKIP: repeated_information]. C8 intent=context_update. C9 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.Let`s please try for shorter number of days.", "streaming_reasoning": "Initially, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Sorry, I did not want to book a room until I was sure of the price could you give that to me first?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is booking; requested information: price..", "trace": "domain=hotel; goal=booking; requested_info+=price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That's fine, thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need help with a train leaving Cambridge and going to London kings cross.", "streaming_reasoning": "As more information arrives, the topic is train; destination: london kings cross..", "trace": "domain=train; destination+=london kings cross."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I just want to leave after 16:45 going from cambridge to london kings cross on thursday.", "streaming_reasoning": "As more information arrives, time: 16:45; day: thursday; departure point: cambridge..", "trace": "time+=16:45; day+=thursday; departure+=cambridge."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Not at this time.", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I just need the price.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No, you've been a great help, thanks for your time.", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: destination is london kings cross; departure point is cambridge; requested information is price; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, train; goal=search, booking; destination=london kings cross; departure=cambridge; requested_info=price; when=thursday, 16:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003503", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: You're right--Italian Ha Ha!\nChunk 2: I was trying to trick you, but you didn't fall for it I almost did!\nChunk 3: Actually, I don't know that much about coffee, even though I sell it.\nChunk 4: I could give you a few pointers if you want.\nChunk 5: I know a lot about coffee.\nChunk 6: Thanks.\nChunk 7: Maybe if things slow down later I'll stop by your table.\nChunk 8: I'm Robert, at your service.", "streaming_reasoning": "C1 casual_comment=you're, right--italian. C2 casual_comment=trying, trick. C3 casual_comment=actually, don't. C4 casual_comment=give, few. C5 casual_comment=lot, coffee. C6 [SKIP: thanks_only]. C7 casual_comment=maybe, slow. C8 casual_comment=i'm, robert.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: You're right--Italian Ha Ha!\nChunk 2: I was trying to trick you, but you didn't fall for it I almost did!\nChunk 3: Actually, I don't know that much about coffee, even though I sell it.\nChunk 4: I could give you a few pointers if you want.\nChunk 5: I know a lot about coffee.\nChunk 6: Thanks.\nChunk 7: Maybe if things slow down later I'll stop by your table.\nChunk 8: I'm Robert, at your service."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=you're, right--italian. C2 casual_comment=trying, trick. C3 casual_comment=actually, don't. C4 casual_comment=give, few. C5 casual_comment=lot, coffee. C6 [SKIP: thanks_only]. C7 casual_comment=maybe, slow. C8 casual_comment=i'm, robert.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: You're right--Italian Ha Ha!\nChunk 2: I was trying to trick you, but you didn't fall for it I almost did!\nChunk 3: Actually, I don't know that much about coffee, even though I sell it.\nChunk 4: I could give you a few pointers if you want.\nChunk 5: I know a lot about coffee.\nChunk 6: Thanks.\nChunk 7: Maybe if things slow down later I'll stop by your table.\nChunk 8: I'm Robert, at your service.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on you're. Next, the user comments on trying. Next, the user comments on actually. Next, the user comments on give. Next, the user comments on lot. Next, the user comments on maybe. Finally, the user comments on i'm.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=you're, right--italian. C2 casual_comment=trying, trick. C3 casual_comment=actually, don't. C4 casual_comment=give, few. C5 casual_comment=lot, coffee. C6 [SKIP: thanks_only]. C7 casual_comment=maybe, slow. C8 casual_comment=i'm, robert.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "You're right--Italian Ha Ha!", "streaming_reasoning": "Initially, the user comments on you're.", "trace": "casual_comment=you're, right--italian."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I was trying to trick you, but you didn't fall for it I almost did!", "streaming_reasoning": "As more information arrives, the user comments on trying.", "trace": "casual_comment=trying, trick."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Actually, I don't know that much about coffee, even though I sell it.", "streaming_reasoning": "As more information arrives, the user comments on actually.", "trace": "casual_comment=actually, don't."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I could give you a few pointers if you want.", "streaming_reasoning": "As more information arrives, the user comments on give.", "trace": "casual_comment=give, few."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I know a lot about coffee.", "streaming_reasoning": "As more information arrives, the user comments on lot.", "trace": "casual_comment=lot, coffee."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Maybe if things slow down later I'll stop by your table.", "streaming_reasoning": "As more information arrives, the user comments on maybe.", "trace": "casual_comment=maybe, slow."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I'm Robert, at your service.", "streaming_reasoning": "Finally, the user comments on i'm.", "trace": "casual_comment=i'm, robert."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002820", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be leaving Cambridge.\nChunk 2: I will be leaving on saturday Great!\nChunk 3: Can you book 2 tickets on that train, please?\nChunk 4: Thanks!\nChunk 5: I'm also looking for a restaurant named efes restaurant.\nChunk 6: The time is 2, 15:01, 28, 64.\nChunk 7: I also need the reference number.\nChunk 8: No thank you, that is everything.", "streaming_reasoning": "C1 intent=context_update. C2 day+=saturday. C3 domain=train; goal=booking. C4 [SKIP: thanks_only]. C5 domain=restaurant; goal=search. C6 time+=2, 15:01, 28, 64. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, restaurant; goal=booking, search, request_info; requested_info=reference_number; when=saturday, 2, 15:01, 28, 64; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I will be leaving Cambridge.\nChunk 2: I will be leaving on saturday Great!\nChunk 3: Can you book 2 tickets on that train, please?\nChunk 4: Thanks!\nChunk 5: I'm also looking for a restaurant named efes restaurant.\nChunk 6: The time is 2, 15:01, 28, 64.\nChunk 7: I also need the reference number.\nChunk 8: No thank you, that is everything."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 day+=saturday. C3 domain=train; goal=booking. C4 [SKIP: thanks_only]. C5 domain=restaurant; goal=search. C6 time+=2, 15:01, 28, 64. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=booking, search, request_info; requested_info=reference_number; when=saturday, 2, 15:01, 28, 64; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be leaving Cambridge.\nChunk 2: I will be leaving on saturday Great!\nChunk 3: Can you book 2 tickets on that train, please?\nChunk 4: Thanks!\nChunk 5: I'm also looking for a restaurant named efes restaurant.\nChunk 6: The time is 2, 15:01, 28, 64.\nChunk 7: I also need the reference number.\nChunk 8: No thank you, that is everything.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, day: saturday. Next, the topic is train; the goal is booking. Next, the topic is restaurant; the goal is search. Next, time: 2. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info. intent: context_update.; day: saturday.; time: 2; requested information: reference_number..", "trace": "C1 intent=context_update. C2 day+=saturday. C3 domain=train; goal=booking. C4 [SKIP: thanks_only]. C5 domain=restaurant; goal=search. C6 time+=2, 15:01, 28, 64. C7 goal=request_info; requested_info+=reference_number. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I will be leaving Cambridge.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be leaving on saturday Great!", "streaming_reasoning": "As more information arrives, day: saturday..", "trace": "day+=saturday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you book 2 tickets on that train, please?", "streaming_reasoning": "As more information arrives, the topic is train; the goal is booking..", "trace": "domain=train; goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks!", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm also looking for a restaurant named efes restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 2, 15:01, 28, 64.", "streaming_reasoning": "As more information arrives, time: 2.", "trace": "time+=2, 15:01, 28, 64."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No thank you, that is everything.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=booking, search, request_info; requested_info=reference_number; when=saturday, 2, 15:01, 28, 64; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002821", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a moderately priced place to dine in the centre please.\nChunk 2: Do you have any Lebanese restaurants?\nChunk 3: Okay.\nChunk 4: Could you book that for 3 people for Sunday at 15:00.\nChunk 5: That is all I need, thank you.", "streaming_reasoning": "C1 goal=search; area+=centre; price+=moderate; destination+=find a moderately priced place to dine in. C2 goal=request_info. C3 [SKIP: backchannel_only]. C4 goal=booking; time+=3, 15:00; day+=sunday; party_size+=3 people. C5 [SKIP: closing_only].", "deep_reasoning": "Need goal=search, booking; area=centre; price=moderate; party_size=3 people; destination=find a moderately priced place to dine in; when=sunday, 3, 15:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to find a moderately priced place to dine in the centre please.\nChunk 2: Do you have any Lebanese restaurants?\nChunk 3: Okay.\nChunk 4: Could you book that for 3 people for Sunday at 15:00.\nChunk 5: That is all I need, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre; price+=moderate; destination+=find a moderately priced place to dine in. C2 goal=request_info. C3 [SKIP: backchannel_only]. C4 goal=booking; time+=3, 15:00; day+=sunday; party_size+=3 people. C5 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search, booking; area=centre; price=moderate; party_size=3 people; destination=find a moderately priced place to dine in; when=sunday, 3, 15:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a moderately priced place to dine in the centre please.\nChunk 2: Do you have any Lebanese restaurants?\nChunk 3: Okay.\nChunk 4: Could you book that for 3 people for Sunday at 15:00.\nChunk 5: That is all I need, thank you.", "input_token_count": 50, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre; price: moderate; destination: find a moderately priced place to dine in. Next, the goal is request info. Finally, the goal is booking; time: 3; day: sunday; party size: 3 people.  Some chunks were skipped because they contained backchannel_only or closing_only. In summary, the goal is booking. area: centre; price: moderate; destination: find a moderately priced place to dine in.; time: 3; day: sunday; party size: 3 people..", "trace": "C1 goal=search; area+=centre; price+=moderate; destination+=find a moderately priced place to dine in. C2 goal=request_info. C3 [SKIP: backchannel_only]. C4 goal=booking; time+=3, 15:00; day+=sunday; party_size+=3 people. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to find a moderately priced place to dine in the centre please.", "streaming_reasoning": "Initially, the goal is search; area: centre; price: moderate; destination: find a moderately priced place to dine in..", "trace": "goal=search; area+=centre; price+=moderate; destination+=find a moderately priced place to dine in."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Do you have any Lebanese restaurants?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Okay.", "streaming_reasoning": "The content at C3 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you book that for 3 people for Sunday at 15:00.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 3; day: sunday; party size: 3 people..", "trace": "goal=booking; time+=3, 15:00; day+=sunday; party_size+=3 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That is all I need, thank you.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search, booking; area=centre; price=moderate; party_size=3 people; destination=find a moderately priced place to dine in; when=sunday, 3, 15:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003508", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you so much You're welcome.\nChunk 2: Don ' t you agree that all the thieves should be punished by cutting off their fingers?\nChunk 3: I'm afraid many people would turn thumbs down on it.\nChunk 4: Don ' t you think in that case, there wouldn ' t be so much stealing?", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=i'm, afraid. C4 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you so much You're welcome.\nChunk 2: Don ' t you agree that all the thieves should be punished by cutting off their fingers?\nChunk 3: I'm afraid many people would turn thumbs down on it.\nChunk 4: Don ' t you think in that case, there wouldn ' t be so much stealing?"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=i'm, afraid. C4 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you so much You're welcome.\nChunk 2: Don ' t you agree that all the thieves should be punished by cutting off their fingers?\nChunk 3: I'm afraid many people would turn thumbs down on it.\nChunk 4: Don ' t you think in that case, there wouldn ' t be so much stealing?", "input_token_count": 54, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on i'm. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 [SKIP: thanks_only]. C2 question=true. C3 casual_comment=i'm, afraid. C4 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you so much You're welcome.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Don ' t you agree that all the thieves should be punished by cutting off their fingers?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm afraid many people would turn thumbs down on it.", "streaming_reasoning": "As more information arrives, the user comments on i'm.", "trace": "casual_comment=i'm, afraid."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Don ' t you think in that case, there wouldn ' t be so much stealing?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002822", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for an Eastern restaurant, medium price Yes, please.\nChunk 2: What is the address, postcode, and phone number Okay thank you.\nChunk 3: Can you tell me their hours of operation?\nChunk 4: OK, then that's all I need.\nChunk 5: Thank you for your help.", "streaming_reasoning": "C1 domain=restaurant; goal=search; acceptance=selected_option. C2 goal=request_info; requested_info+=address, phone, postcode. C3 goal=request_info. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; requested_info=address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for an Eastern restaurant, medium price Yes, please.\nChunk 2: What is the address, postcode, and phone number Okay thank you.\nChunk 3: Can you tell me their hours of operation?\nChunk 4: OK, then that's all I need.\nChunk 5: Thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; acceptance=selected_option. C2 goal=request_info; requested_info+=address, phone, postcode. C3 goal=request_info. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; requested_info=address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for an Eastern restaurant, medium price Yes, please.\nChunk 2: What is the address, postcode, and phone number Okay thank you.\nChunk 3: Can you tell me their hours of operation?\nChunk 4: OK, then that's all I need.\nChunk 5: Thank you for your help.", "input_token_count": 51, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; acceptance: selected_option. Next, the goal is request info; requested information: address. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is request info.. acceptance: selected_option.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; acceptance=selected_option. C2 goal=request_info; requested_info+=address, phone, postcode. C3 goal=request_info. C4 [SKIP: closing_only]. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for an Eastern restaurant, medium price Yes, please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; acceptance: selected_option..", "trace": "domain=restaurant; goal=search; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the address, postcode, and phone number Okay thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you tell me their hours of operation?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "OK, then that's all I need.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; requested_info=address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002823", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hospital in town.\nChunk 2: The hospital should have the neurology neurosurgery department.\nChunk 3: That would be fine.\nChunk 4: I just need the phone number and postcode.\nChunk 5: Thanks No, thank you.\nChunk 6: I got what I needed Goodbye.", "streaming_reasoning": "C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 intent=context_update. C3 intent=context_update. C4 goal=request_info; requested_info+=phone, postcode. C5 [SKIP: thanks_only]. C6 intent=context_update.", "deep_reasoning": "Need domain=hospital; goal=search, request_info; destination=find a hospital in town; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a hospital in town.\nChunk 2: The hospital should have the neurology neurosurgery department.\nChunk 3: That would be fine.\nChunk 4: I just need the phone number and postcode.\nChunk 5: Thanks No, thank you.\nChunk 6: I got what I needed Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 intent=context_update. C3 intent=context_update. C4 goal=request_info; requested_info+=phone, postcode. C5 [SKIP: thanks_only]. C6 intent=context_update.\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; destination=find a hospital in town; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hospital in town.\nChunk 2: The hospital should have the neurology neurosurgery department.\nChunk 3: That would be fine.\nChunk 4: I just need the phone number and postcode.\nChunk 5: Thanks No, thank you.\nChunk 6: I got what I needed Goodbye.", "input_token_count": 50, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital in town. Next, intent: context_update. Next, intent: context_update. Next, the goal is request info; requested information: phone. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hospital. the goal is request info. destination: find a hospital in town.; intent: context_update.; requested information: phone.", "trace": "C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 intent=context_update. C3 intent=context_update. C4 goal=request_info; requested_info+=phone, postcode. C5 [SKIP: thanks_only]. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a hospital in town.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital in town..", "trace": "domain=hospital; goal=search; destination+=find a hospital in town."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The hospital should have the neurology neurosurgery department.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That would be fine.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I just need the phone number and postcode.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks No, thank you.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I got what I needed Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: destination is find a hospital in town; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; destination=find a hospital in town; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002824", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I don't have a preference for side of town.\nChunk 2: Can you book it for me and get a reference number?\nChunk 3: Great I also need a train please.\nChunk 4: I'm going from cambridge to broxbourne after 20:00 on monday.\nChunk 5: Yes, two tickets please No thanks.\nChunk 6: You've been very helpful Take care Goodbye.", "streaming_reasoning": "C1 intent=context_update. C2 goal=request_info; requested_info+=reference_number. C3 domain=train; goal=search. C4 time+=20:00; day+=monday; destination+=broxbourne; departure+=cambridge. C5 goal=confirm_booking. C6 intent=context_update.", "deep_reasoning": "Need domain=train; goal=booking, request_info, search; destination=broxbourne; departure=cambridge; requested_info=reference_number; when=monday, 20:00.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I don't have a preference for side of town.\nChunk 2: Can you book it for me and get a reference number?\nChunk 3: Great I also need a train please.\nChunk 4: I'm going from cambridge to broxbourne after 20:00 on monday.\nChunk 5: Yes, two tickets please No thanks.\nChunk 6: You've been very helpful Take care Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=request_info; requested_info+=reference_number. C3 domain=train; goal=search. C4 time+=20:00; day+=monday; destination+=broxbourne; departure+=cambridge. C5 goal=confirm_booking. C6 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=booking, request_info, search; destination=broxbourne; departure=cambridge; requested_info=reference_number; when=monday, 20:00.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I don't have a preference for side of town.\nChunk 2: Can you book it for me and get a reference number?\nChunk 3: Great I also need a train please.\nChunk 4: I'm going from cambridge to broxbourne after 20:00 on monday.\nChunk 5: Yes, two tickets please No thanks.\nChunk 6: You've been very helpful Take care Goodbye.", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is request info; requested information: reference_number. Next, the topic is train; the goal is search. Next, time: 20:00; day: monday; destination: broxbourne; departure point: cambridge. Next, the goal is confirm booking. Finally, intent: context_update. In summary, The overall topic is train. the goal is confirm booking.. intent: context_update.; requested information: reference_number.; time: 20:00; day: monday; destination: broxbourne; departure point: cambridge..", "trace": "C1 intent=context_update. C2 goal=request_info; requested_info+=reference_number. C3 domain=train; goal=search. C4 time+=20:00; day+=monday; destination+=broxbourne; departure+=cambridge. C5 goal=confirm_booking. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I don't have a preference for side of town.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you book it for me and get a reference number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Great I also need a train please.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm going from cambridge to broxbourne after 20:00 on monday.", "streaming_reasoning": "As more information arrives, time: 20:00; day: monday; destination: broxbourne; departure point: cambridge..", "trace": "time+=20:00; day+=monday; destination+=broxbourne; departure+=cambridge."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, two tickets please No thanks.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "You've been very helpful Take care Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: destination is broxbourne; departure point is cambridge; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=booking, request_info, search; destination=broxbourne; departure=cambridge; requested_info=reference_number; when=monday, 20:00."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002825", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am in the centre of town and am looking for a restaurant.\nChunk 2: Ideally it would be in the expensive price range.\nChunk 3: Chinese food is okay are there any tables available for 7 people on Sunday at 17:45?\nChunk 4: I am also looking for a place to go.\nChunk 5: I would like to go to a college in the same area of town as the restaurant Thank you.\nChunk 6: That was all I needed.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre. C2 price+=expensive. C3 cuisine+=chinese; time+=7, 17:45; day+=sunday; party_size+=7 people. C4 intent=context_update. C5 domain=attraction; goal=modify_constraint; destination+=go to a college in the same area of town. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, attraction; goal=search, modify_constraint; area=centre; food=chinese; price=expensive; party_size=7 people; destination=go to a college in the same area of town; when=sunday, 7, 17:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am in the centre of town and am looking for a restaurant.\nChunk 2: Ideally it would be in the expensive price range.\nChunk 3: Chinese food is okay are there any tables available for 7 people on Sunday at 17:45?\nChunk 4: I am also looking for a place to go.\nChunk 5: I would like to go to a college in the same area of town as the restaurant Thank you.\nChunk 6: That was all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre. C2 price+=expensive. C3 cuisine+=chinese; time+=7, 17:45; day+=sunday; party_size+=7 people. C4 intent=context_update. C5 domain=attraction; goal=modify_constraint; destination+=go to a college in the same area of town. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, attraction; goal=search, modify_constraint; area=centre; food=chinese; price=expensive; party_size=7 people; destination=go to a college in the same area of town; when=sunday, 7, 17:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am in the centre of town and am looking for a restaurant.\nChunk 2: Ideally it would be in the expensive price range.\nChunk 3: Chinese food is okay are there any tables available for 7 people on Sunday at 17:45?\nChunk 4: I am also looking for a place to go.\nChunk 5: I would like to go to a college in the same area of town as the restaurant Thank you.\nChunk 6: That was all I needed.", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre. Next, price: expensive. Next, cuisine: chinese; time: 7; day: sunday; party size: 7 people. Next, intent: context_update. Finally, the topic is attraction; the goal is modify constraint; destination: go to a college in the same area of town.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is modify constraint. area: centre.; price: expensive.; cuisine: chinese; time: 7; day: sunday; party size: 7 people.; intent: context_update.; destination: go to a college in the same area of town..", "trace": "C1 domain=restaurant; goal=search; area+=centre. C2 price+=expensive. C3 cuisine+=chinese; time+=7, 17:45; day+=sunday; party_size+=7 people. C4 intent=context_update. C5 domain=attraction; goal=modify_constraint; destination+=go to a college in the same area of town. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am in the centre of town and am looking for a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre..", "trace": "domain=restaurant; goal=search; area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Ideally it would be in the expensive price range.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Chinese food is okay are there any tables available for 7 people on Sunday at 17:45?", "streaming_reasoning": "As more information arrives, cuisine: chinese; time: 7; day: sunday; party size: 7 people..", "trace": "cuisine+=chinese; time+=7, 17:45; day+=sunday; party_size+=7 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am also looking for a place to go.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like to go to a college in the same area of town as the restaurant Thank you.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is modify constraint; destination: go to a college in the same area of town..", "trace": "domain=attraction; goal=modify_constraint; destination+=go to a college in the same area of town."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That was all I needed.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; price is expensive; party size is 7 people; destination is go to a college in the same area of town; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction; goal=search, modify_constraint; area=centre; food=chinese; price=expensive; party_size=7 people; destination=go to a college in the same area of town; when=sunday, 7, 17:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001889", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Once i stole from my mother purse.\nChunk 2: i wanted to buy a video game.\nChunk 3: felt so bad after she got mad at me.\nChunk 4: When i was younger i would steal 20 bucks from my mothers purse at times.\nChunk 5: oh no, did you ever get caught.\nChunk 6: I did and i felt really bad because she got mad at me.", "streaming_reasoning": "C1 need=validation. C2 support_signal=received. C3 emotion=frustrated; cause=she got mad at me. C4 need=encouragement. C5 support_signal=received. C6 [SKIP: repeated_information].", "deep_reasoning": "User feels frustrated after she got mad at me and needs encouragement.", "answer": "It makes sense to feel frustrated after she got mad at me. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Once i stole from my mother purse.\nChunk 2: i wanted to buy a video game.\nChunk 3: felt so bad after she got mad at me.\nChunk 4: When i was younger i would steal 20 bucks from my mothers purse at times.\nChunk 5: oh no, did you ever get caught.\nChunk 6: I did and i felt really bad because she got mad at me."}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 support_signal=received. C3 emotion=frustrated; cause=she got mad at me. C4 need=encouragement. C5 support_signal=received. C6 [SKIP: repeated_information].\n\nDeep reasoning: User feels frustrated after she got mad at me and needs encouragement.\n\nAnswer: It makes sense to feel frustrated after she got mad at me. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Once i stole from my mother purse.\nChunk 2: i wanted to buy a video game.\nChunk 3: felt so bad after she got mad at me.\nChunk 4: When i was younger i would steal 20 bucks from my mothers purse at times.\nChunk 5: oh no, did you ever get caught.\nChunk 6: I did and i felt really bad because she got mad at me.", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user signals support or acknowledgment. Next, the user expresses frustrated about she got mad at me. Next, the user needs encouragement. Finally, the user signals support or acknowledgment.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 need=validation. C2 support_signal=received. C3 emotion=frustrated; cause=she got mad at me. C4 need=encouragement. C5 support_signal=received. C6 [SKIP: repeated_information].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Once i stole from my mother purse.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "i wanted to buy a video game.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "felt so bad after she got mad at me.", "streaming_reasoning": "As more information arrives, the user expresses frustrated about she got mad at me..", "trace": "emotion=frustrated; cause=she got mad at me."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "When i was younger i would steal 20 bucks from my mothers purse at times.", "streaming_reasoning": "As more information arrives, the user needs encouragement..", "trace": "need=encouragement."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "oh no, did you ever get caught.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I did and i felt really bad because she got mad at me.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}]}, "output": {"deep_reasoning": "User feels frustrated after she got mad at me and needs encouragement.", "answer": "It makes sense to feel frustrated after she got mad at me. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002826", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: How much does it cost to take the bus in Cambridge?\nChunk 2: I will be traveling to london.\nChunk 3: I am also looking for a hotel in the west side of Cambridge.\nChunk 4: Can you help me?\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the west part of town.\nChunk 7: Are you sure that there are no hotels on the west side of town?\nChunk 8: With or without internet?", "streaming_reasoning": "C1 goal=request_info; destination+=take the bus in cambridge; requested_info+=price. C2 destination+=london. C3 domain=hotel; goal=search; area+=west; hotel_type+=hotel. C4 goal=request_info. C5 destination+=find a hotel. C6 intent=context_update. C7 goal=request_info. C8 amenities+=internet.", "deep_reasoning": "Need domain=hotel; goal=request_info, search; area=west; amenities=internet; destination=take the bus in cambridge, london, find a hotel; requested_info=price.", "answer": "I can help with that and include the price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: How much does it cost to take the bus in Cambridge?\nChunk 2: I will be traveling to london.\nChunk 3: I am also looking for a hotel in the west side of Cambridge.\nChunk 4: Can you help me?\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the west part of town.\nChunk 7: Are you sure that there are no hotels on the west side of town?\nChunk 8: With or without internet?"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; destination+=take the bus in cambridge; requested_info+=price. C2 destination+=london. C3 domain=hotel; goal=search; area+=west; hotel_type+=hotel. C4 goal=request_info. C5 destination+=find a hotel. C6 intent=context_update. C7 goal=request_info. C8 amenities+=internet.\n\nDeep reasoning: Need domain=hotel; goal=request_info, search; area=west; amenities=internet; destination=take the bus in cambridge, london, find a hotel; requested_info=price.\n\nAnswer: I can help with that and include the price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: How much does it cost to take the bus in Cambridge?\nChunk 2: I will be traveling to london.\nChunk 3: I am also looking for a hotel in the west side of Cambridge.\nChunk 4: Can you help me?\nChunk 5: I want to find a hotel.\nChunk 6: It should be in the west part of town.\nChunk 7: Are you sure that there are no hotels on the west side of town?\nChunk 8: With or without internet?", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; destination: take the bus in cambridge; requested information: price. Next, destination: london. Next, the topic is hotel; the goal is search; area: west; hotel type: hotel. Next, the goal is request info. Next, destination: find a hotel. Next, intent: context_update. Next, the goal is request info. Finally, amenities: internet. In summary, The overall topic is hotel. the goal is request info.. destination: take the bus in cambridge, london., find a hotel.; requested information: price.; area: west; hotel type: hotel.; intent: context_update.; amenities: internet..", "trace": "C1 goal=request_info; destination+=take the bus in cambridge; requested_info+=price. C2 destination+=london. C3 domain=hotel; goal=search; area+=west; hotel_type+=hotel. C4 goal=request_info. C5 destination+=find a hotel. C6 intent=context_update. C7 goal=request_info. C8 amenities+=internet.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "How much does it cost to take the bus in Cambridge?", "streaming_reasoning": "Initially, the goal is request info; destination: take the bus in cambridge; requested information: price..", "trace": "goal=request_info; destination+=take the bus in cambridge; requested_info+=price."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be traveling to london.", "streaming_reasoning": "As more information arrives, destination: london..", "trace": "destination+=london."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am also looking for a hotel in the west side of Cambridge.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; area: west; hotel type: hotel..", "trace": "domain=hotel; goal=search; area+=west; hotel_type+=hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you help me?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, destination: find a hotel..", "trace": "destination+=find a hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It should be in the west part of town.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Are you sure that there are no hotels on the west side of town?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "With or without internet?", "streaming_reasoning": "Finally, amenities: internet..", "trace": "amenities+=internet."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: area is west; amenities is internet; destination is take the bus in cambridge; requested information is price.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the price once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search; area=west; amenities=internet; destination=take the bus in cambridge, london, find a hotel; requested_info=price."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002827", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What restaurants are on the east part of town expensive.\nChunk 2: What is the address?\nChunk 3: Great, thanks for your help.\nChunk 4: That's all I need.", "streaming_reasoning": "C1 area+=east; price+=expensive. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].", "deep_reasoning": "Need goal=request_info; area=east; price=expensive; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What restaurants are on the east part of town expensive.\nChunk 2: What is the address?\nChunk 3: Great, thanks for your help.\nChunk 4: That's all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=east; price+=expensive. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].\n\nDeep reasoning: Need goal=request_info; area=east; price=expensive; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What restaurants are on the east part of town expensive.\nChunk 2: What is the address?\nChunk 3: Great, thanks for your help.\nChunk 4: That's all I need.", "input_token_count": 31, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, area: east; price: expensive. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is request info. area: east; price: expensive.; requested information: address..", "trace": "C1 area+=east; price+=expensive. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What restaurants are on the east part of town expensive.", "streaming_reasoning": "Initially, area: east; price: expensive..", "trace": "area+=east; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the address?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Great, thanks for your help.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That's all I need.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=request_info; area=east; price=expensive; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002829", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is it a guesthouse?\nChunk 2: Yes please, 3 people for 5 nights starting on wednesday.\nChunk 3: I am looking to get train tickets as well.\nChunk 4: I will travel to cambridge from stansted airport on wednesday and need to arrive by 14:15.\nChunk 5: Yes, I will need tickets for the group Thank you.\nChunk 6: That is all for now Thank You.", "streaming_reasoning": "C1 domain=hotel; hotel_type+=guesthouse. C2 time+=3, 5; day+=wednesday; party_size+=3 people; stay_length+=5 nights; acceptance=selected_option. C3 domain=train; goal=request_info. C4 goal=search; time+=14:15; destination+=arrive by 14:15; departure+=stansted airport. C5 acceptance=selected_option. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, train; goal=request_info, search; party_size=3 people; stay_length=5 nights; destination=arrive by 14:15; departure=stansted airport; when=wednesday, 3, 5, 14:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Is it a guesthouse?\nChunk 2: Yes please, 3 people for 5 nights starting on wednesday.\nChunk 3: I am looking to get train tickets as well.\nChunk 4: I will travel to cambridge from stansted airport on wednesday and need to arrive by 14:15.\nChunk 5: Yes, I will need tickets for the group Thank you.\nChunk 6: That is all for now Thank You."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=guesthouse. C2 time+=3, 5; day+=wednesday; party_size+=3 people; stay_length+=5 nights; acceptance=selected_option. C3 domain=train; goal=request_info. C4 goal=search; time+=14:15; destination+=arrive by 14:15; departure+=stansted airport. C5 acceptance=selected_option. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, train; goal=request_info, search; party_size=3 people; stay_length=5 nights; destination=arrive by 14:15; departure=stansted airport; when=wednesday, 3, 5, 14:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Is it a guesthouse?\nChunk 2: Yes please, 3 people for 5 nights starting on wednesday.\nChunk 3: I am looking to get train tickets as well.\nChunk 4: I will travel to cambridge from stansted airport on wednesday and need to arrive by 14:15.\nChunk 5: Yes, I will need tickets for the group Thank you.\nChunk 6: That is all for now Thank You.", "input_token_count": 69, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse. Next, time: 3; day: wednesday; party size: 3 people; stay length: 5 nights; acceptance: selected_option. Next, the topic is train; the goal is request info. Next, the goal is search; time: 14:15; destination: arrive by 14:15; departure point: stansted airport. Finally, acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is search. hotel type: guesthouse.; time: 3, 14:15; day: wednesday; party size: 3 people; stay length: 5 nights; acceptance: selected_option.; destination: arrive by 14:15; departure point: stansted airport..", "trace": "C1 domain=hotel; hotel_type+=guesthouse. C2 time+=3, 5; day+=wednesday; party_size+=3 people; stay_length+=5 nights; acceptance=selected_option. C3 domain=train; goal=request_info. C4 goal=search; time+=14:15; destination+=arrive by 14:15; departure+=stansted airport. C5 acceptance=selected_option. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Is it a guesthouse?", "streaming_reasoning": "Initially, the topic is hotel; hotel type: guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes please, 3 people for 5 nights starting on wednesday.", "streaming_reasoning": "As more information arrives, time: 3; day: wednesday; party size: 3 people; stay length: 5 nights; acceptance: selected_option..", "trace": "time+=3, 5; day+=wednesday; party_size+=3 people; stay_length+=5 nights; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am looking to get train tickets as well.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is request info..", "trace": "domain=train; goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I will travel to cambridge from stansted airport on wednesday and need to arrive by 14:15.", "streaming_reasoning": "As more information arrives, the goal is search; time: 14:15; destination: arrive by 14:15; departure point: stansted airport..", "trace": "goal=search; time+=14:15; destination+=arrive by 14:15; departure+=stansted airport."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, I will need tickets for the group Thank you.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all for now Thank You.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: party size is 3 people; stay length is 5 nights; destination is arrive by 14:15; departure point is stansted airport; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, train; goal=request_info, search; party_size=3 people; stay_length=5 nights; destination=arrive by 14:15; departure=stansted airport; when=wednesday, 3, 5, 14:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002831", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a guesthouse in the east please.\nChunk 2: Yes, I would like free wifi and a 4 star rating Not particularly.\nChunk 3: Do you have one you would recommend?\nChunk 4: please, For 2 people for 5 nights starting on Wednesday.\nChunk 5: Can you try 4 nights instead?\nChunk 6: Great, could I also find someplace near the hotel to go for fun?", "streaming_reasoning": "C1 domain=hotel; goal=search; area+=east; hotel_type+=guesthouse. C2 stars+=4 stars; amenities+=wifi; acceptance=selected_option. C3 goal=recommendation. C4 time+=2, 5; day+=wednesday; party_size+=2 people; stay_length+=5 nights. C5 goal=compare_alternative; stay_length+=4 nights. C6 hotel_type+=hotel; destination+=go for fun.", "deep_reasoning": "Need domain=hotel; goal=search, recommendation, compare_alternative; area=east; party_size=2 people; stay_length=5 nights, 4 nights; stars=4 stars; amenities=wifi; destination=go for fun; when=wednesday, 2, 5.", "answer": "What price range should I use for the search?", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a guesthouse in the east please.\nChunk 2: Yes, I would like free wifi and a 4 star rating Not particularly.\nChunk 3: Do you have one you would recommend?\nChunk 4: please, For 2 people for 5 nights starting on Wednesday.\nChunk 5: Can you try 4 nights instead?\nChunk 6: Great, could I also find someplace near the hotel to go for fun?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; area+=east; hotel_type+=guesthouse. C2 stars+=4 stars; amenities+=wifi; acceptance=selected_option. C3 goal=recommendation. C4 time+=2, 5; day+=wednesday; party_size+=2 people; stay_length+=5 nights. C5 goal=compare_alternative; stay_length+=4 nights. C6 hotel_type+=hotel; destination+=go for fun.\n\nDeep reasoning: Need domain=hotel; goal=search, recommendation, compare_alternative; area=east; party_size=2 people; stay_length=5 nights, 4 nights; stars=4 stars; amenities=wifi; destination=go for fun; when=wednesday, 2, 5.\n\nAnswer: What price range should I use for the search?"}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a guesthouse in the east please.\nChunk 2: Yes, I would like free wifi and a 4 star rating Not particularly.\nChunk 3: Do you have one you would recommend?\nChunk 4: please, For 2 people for 5 nights starting on Wednesday.\nChunk 5: Can you try 4 nights instead?\nChunk 6: Great, could I also find someplace near the hotel to go for fun?", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: east; hotel type: guesthouse. Next, star rating: 4 stars; amenities: wifi; acceptance: selected_option. Next, the goal is recommendation. Next, time: 2; day: wednesday; party size: 2 people; stay length: 5 nights. Next, the goal is compare alternative; stay length: 4 nights. Finally, hotel type: hotel; destination: go for fun. In summary, The overall topic is hotel. the goal is compare alternative. area: east; hotel type: guesthouse., hotel; star rating: 4 stars; amenities: wifi; acceptance: selected_option.; time: 2; day: wednesday; party size: 2 people; stay length: 5 nights., 4 nights.; destination: go for fun..", "trace": "C1 domain=hotel; goal=search; area+=east; hotel_type+=guesthouse. C2 stars+=4 stars; amenities+=wifi; acceptance=selected_option. C3 goal=recommendation. C4 time+=2, 5; day+=wednesday; party_size+=2 people; stay_length+=5 nights. C5 goal=compare_alternative; stay_length+=4 nights. C6 hotel_type+=hotel; destination+=go for fun.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a guesthouse in the east please.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: east; hotel type: guesthouse..", "trace": "domain=hotel; goal=search; area+=east; hotel_type+=guesthouse."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I would like free wifi and a 4 star rating Not particularly.", "streaming_reasoning": "As more information arrives, star rating: 4 stars; amenities: wifi; acceptance: selected_option..", "trace": "stars+=4 stars; amenities+=wifi; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Do you have one you would recommend?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "please, For 2 people for 5 nights starting on Wednesday.", "streaming_reasoning": "As more information arrives, time: 2; day: wednesday; party size: 2 people; stay length: 5 nights..", "trace": "time+=2, 5; day+=wednesday; party_size+=2 people; stay_length+=5 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you try 4 nights instead?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; stay length: 4 nights..", "trace": "goal=compare_alternative; stay_length+=4 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Great, could I also find someplace near the hotel to go for fun?", "streaming_reasoning": "Finally, hotel type: hotel; destination: go for fun..", "trace": "hotel_type+=hotel; destination+=go for fun."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is east; party size is 2 people; stay length is 5 nights; star rating is 4 stars; amenities is wifi; destination is go for fun; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "What price range should I use for the search?", "deep_reasoning_trace": "Need domain=hotel; goal=search, recommendation, compare_alternative; area=east; party_size=2 people; stay_length=5 nights, 4 nights; stars=4 stars; amenities=wifi; destination=go for fun; when=wednesday, 2, 5."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003526", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I want to go to Beijing Hotel I'm sorry.\nChunk 3: You are going in the wrong direction Oh no!\nChunk 4: What shall I do Don't worry.\nChunk 5: You can get off at the next stop and go across the street through the overpass.\nChunk 6: The bus stop is right there.\nChunk 7: Thank you very much.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 casual_comment=beijing, hotel. C3 casual_comment=going, wrong. C4 casual_comment=shall, don't. C5 casual_comment=off, next. C6 casual_comment=bus, stop. C7 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I want to go to Beijing Hotel I'm sorry.\nChunk 3: You are going in the wrong direction Oh no!\nChunk 4: What shall I do Don't worry.\nChunk 5: You can get off at the next stop and go across the street through the overpass.\nChunk 6: The bus stop is right there.\nChunk 7: Thank you very much."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 casual_comment=beijing, hotel. C3 casual_comment=going, wrong. C4 casual_comment=shall, don't. C5 casual_comment=off, next. C6 casual_comment=bus, stop. C7 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I want to go to Beijing Hotel I'm sorry.\nChunk 3: You are going in the wrong direction Oh no!\nChunk 4: What shall I do Don't worry.\nChunk 5: You can get off at the next stop and go across the street through the overpass.\nChunk 6: The bus stop is right there.\nChunk 7: Thank you very much.", "input_token_count": 65, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on beijing. Next, the user comments on going. Next, the user comments on shall. Next, the user comments on off. Finally, the user comments on bus.  Some chunks were skipped because they contained acknowledgement_only or thanks_only.", "trace": "C1 [SKIP: acknowledgement_only]. C2 casual_comment=beijing, hotel. C3 casual_comment=going, wrong. C4 casual_comment=shall, don't. C5 casual_comment=off, next. C6 casual_comment=bus, stop. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to go to Beijing Hotel I'm sorry.", "streaming_reasoning": "As more information arrives, the user comments on beijing.", "trace": "casual_comment=beijing, hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "You are going in the wrong direction Oh no!", "streaming_reasoning": "As more information arrives, the user comments on going.", "trace": "casual_comment=going, wrong."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What shall I do Don't worry.", "streaming_reasoning": "As more information arrives, the user comments on shall.", "trace": "casual_comment=shall, don't."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "You can get off at the next stop and go across the street through the overpass.", "streaming_reasoning": "As more information arrives, the user comments on off.", "trace": "casual_comment=off, next."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The bus stop is right there.", "streaming_reasoning": "As more information arrives, the user comments on bus.", "trace": "casual_comment=bus, stop."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you very much.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002832", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to book a taxi to the place, please.\nChunk 2: I need help with taxi.\nChunk 3: It should be in the north part of town.\nChunk 4: The time is 8:00.\nChunk 5: That is it, Thank you.\nChunk 6: Thank you once again for all of your assistance.\nChunk 7: Have a great day.", "streaming_reasoning": "C1 domain=taxi; goal=booking. C2 intent=context_update. C3 area+=north. C4 time+=8:00. C5 intent=context_update. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi; goal=search, booking; area=north; when=8:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to book a taxi to the place, please.\nChunk 2: I need help with taxi.\nChunk 3: It should be in the north part of town.\nChunk 4: The time is 8:00.\nChunk 5: That is it, Thank you.\nChunk 6: Thank you once again for all of your assistance.\nChunk 7: Have a great day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=booking. C2 intent=context_update. C3 area+=north. C4 time+=8:00. C5 intent=context_update. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi; goal=search, booking; area=north; when=8:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to book a taxi to the place, please.\nChunk 2: I need help with taxi.\nChunk 3: It should be in the north part of town.\nChunk 4: The time is 8:00.\nChunk 5: That is it, Thank you.\nChunk 6: Thank you once again for all of your assistance.\nChunk 7: Have a great day.", "input_token_count": 61, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is booking. Next, intent: context_update. Next, area: north. Next, time: 8:00. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is booking.. intent: context_update.; area: north.; time: 8:00..", "trace": "C1 domain=taxi; goal=booking. C2 intent=context_update. C3 area+=north. C4 time+=8:00. C5 intent=context_update. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to book a taxi to the place, please.", "streaming_reasoning": "Initially, the topic is taxi; the goal is booking..", "trace": "domain=taxi; goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need help with taxi.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is 8:00.", "streaming_reasoning": "As more information arrives, time: 8:00..", "trace": "time+=8:00."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That is it, Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you once again for all of your assistance.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: area is north; timing is 8:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search, booking; area=north; when=8:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002833", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Monday at 19:30 would be perfect.\nChunk 2: I'm also looking for some entertainment in the same area as the restaurant Sounds good.\nChunk 3: I need the address and phone number for them too.\nChunk 4: Thank you so much for your help.\nChunk 5: Can we also look at 4 star hotels in the same area Forget the hotels.\nChunk 6: That's all the information I need today.\nChunk 7: Thanks for all your help.\nChunk 8: I don't need anything other than the restaurant and the attractions.\nChunk 9: Thank you for your assistance Goodbye.", "streaming_reasoning": "C1 time+=19:30; day+=monday; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; acceptance=selected_option. C3 goal=request_info; requested_info+=address, phone. C4 [SKIP: thanks_only]. C5 time+=4; hotel_type+=hotel; stars+=4 stars. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 intent=context_update. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, modify_constraint, request_info; stars=4 stars; requested_info=address, phone; when=monday, 19:30, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Monday at 19:30 would be perfect.\nChunk 2: I'm also looking for some entertainment in the same area as the restaurant Sounds good.\nChunk 3: I need the address and phone number for them too.\nChunk 4: Thank you so much for your help.\nChunk 5: Can we also look at 4 star hotels in the same area Forget the hotels.\nChunk 6: That's all the information I need today.\nChunk 7: Thanks for all your help.\nChunk 8: I don't need anything other than the restaurant and the attractions.\nChunk 9: Thank you for your assistance Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=19:30; day+=monday; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; acceptance=selected_option. C3 goal=request_info; requested_info+=address, phone. C4 [SKIP: thanks_only]. C5 time+=4; hotel_type+=hotel; stars+=4 stars. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 intent=context_update. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, modify_constraint, request_info; stars=4 stars; requested_info=address, phone; when=monday, 19:30, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Monday at 19:30 would be perfect.\nChunk 2: I'm also looking for some entertainment in the same area as the restaurant Sounds good.\nChunk 3: I need the address and phone number for them too.\nChunk 4: Thank you so much for your help.\nChunk 5: Can we also look at 4 star hotels in the same area Forget the hotels.\nChunk 6: That's all the information I need today.\nChunk 7: Thanks for all your help.\nChunk 8: I don't need anything other than the restaurant and the attractions.\nChunk 9: Thank you for your assistance Goodbye.", "input_token_count": 101, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, time: 19:30; day: monday; acceptance: selected_option. Next, the topic is restaurant; the goal is modify constraint; acceptance: selected_option. Next, the goal is request info; requested information: address. Next, time: 4; hotel type: hotel; star rating: 4 stars. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is request info. time: 19:30, 4; day: monday; acceptance: selected_option.; requested information: address; hotel type: hotel; star rating: 4 stars.; intent: context_update..", "trace": "C1 time+=19:30; day+=monday; acceptance=selected_option. C2 domain=restaurant; goal=modify_constraint; acceptance=selected_option. C3 goal=request_info; requested_info+=address, phone. C4 [SKIP: thanks_only]. C5 time+=4; hotel_type+=hotel; stars+=4 stars. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only]. C8 intent=context_update. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Monday at 19:30 would be perfect.", "streaming_reasoning": "Initially, time: 19:30; day: monday; acceptance: selected_option..", "trace": "time+=19:30; day+=monday; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm also looking for some entertainment in the same area as the restaurant Sounds good.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint; acceptance: selected_option..", "trace": "domain=restaurant; goal=modify_constraint; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need the address and phone number for them too.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you so much for your help.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can we also look at 4 star hotels in the same area Forget the hotels.", "streaming_reasoning": "As more information arrives, time: 4; hotel type: hotel; star rating: 4 stars..", "trace": "time+=4; hotel_type+=hotel; stars+=4 stars."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all the information I need today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks for all your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I don't need anything other than the restaurant and the attractions.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you for your assistance Goodbye.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: star rating is 4 stars; requested information is address; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, modify_constraint, request_info; stars=4 stars; requested_info=address, phone; when=monday, 19:30, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002834", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place to stay.\nChunk 2: I want to stay in a hotel that includes free wifi.\nChunk 3: Any area in Cambridge is fine, but I want the hotel to have a 2 star rating.\nChunk 4: Something moderately priced would be ideal, please.\nChunk 5: Yes, that would be great.\nChunk 6: For 4 nights on Tuesday for 7 people please.", "streaming_reasoning": "C1 domain=hotel; goal=search; destination+=stay. C2 hotel_type+=hotel; amenities+=wifi; destination+=stay in a hotel that includes free wifi. C3 area+=any; stars+=2 stars; destination+=have a 2 star rating. C4 price+=moderate. C5 acceptance=selected_option. C6 day+=tuesday; party_size+=7 people; stay_length+=4 nights.", "deep_reasoning": "Need domain=hotel; goal=search; area=any; price=moderate; party_size=7 people; stay_length=4 nights; stars=2 stars; amenities=wifi; destination=stay, stay in a hotel that includes free wifi, have a 2 star rating; when=tuesday.", "answer": "Got it. I will use hotel, any, moderate, 7 people, tuesday and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a place to stay.\nChunk 2: I want to stay in a hotel that includes free wifi.\nChunk 3: Any area in Cambridge is fine, but I want the hotel to have a 2 star rating.\nChunk 4: Something moderately priced would be ideal, please.\nChunk 5: Yes, that would be great.\nChunk 6: For 4 nights on Tuesday for 7 people please."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; destination+=stay. C2 hotel_type+=hotel; amenities+=wifi; destination+=stay in a hotel that includes free wifi. C3 area+=any; stars+=2 stars; destination+=have a 2 star rating. C4 price+=moderate. C5 acceptance=selected_option. C6 day+=tuesday; party_size+=7 people; stay_length+=4 nights.\n\nDeep reasoning: Need domain=hotel; goal=search; area=any; price=moderate; party_size=7 people; stay_length=4 nights; stars=2 stars; amenities=wifi; destination=stay, stay in a hotel that includes free wifi, have a 2 star rating; when=tuesday.\n\nAnswer: Got it. I will use hotel, any, moderate, 7 people, tuesday and move the task forward."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place to stay.\nChunk 2: I want to stay in a hotel that includes free wifi.\nChunk 3: Any area in Cambridge is fine, but I want the hotel to have a 2 star rating.\nChunk 4: Something moderately priced would be ideal, please.\nChunk 5: Yes, that would be great.\nChunk 6: For 4 nights on Tuesday for 7 people please.", "input_token_count": 69, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay. Next, hotel type: hotel; amenities: wifi; destination: stay in a hotel that includes free wifi. Next, area: any; star rating: 2 stars; destination: have a 2 star rating. Next, price: moderate. Next, acceptance: selected_option. Finally, day: tuesday; party size: 7 people; stay length: 4 nights. In summary, The overall topic is hotel. the goal is search. destination: stay., stay in a hotel that includes free wifi., have a 2 star rating.; hotel type: hotel; amenities: wifi; area: any; star rating: 2 stars; price: moderate.; acceptance: selected_option.; day: tuesday; party size: 7 people; stay length: 4 nights..", "trace": "C1 domain=hotel; goal=search; destination+=stay. C2 hotel_type+=hotel; amenities+=wifi; destination+=stay in a hotel that includes free wifi. C3 area+=any; stars+=2 stars; destination+=have a 2 star rating. C4 price+=moderate. C5 acceptance=selected_option. C6 day+=tuesday; party_size+=7 people; stay_length+=4 nights.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a place to stay.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to stay in a hotel that includes free wifi.", "streaming_reasoning": "As more information arrives, hotel type: hotel; amenities: wifi; destination: stay in a hotel that includes free wifi..", "trace": "hotel_type+=hotel; amenities+=wifi; destination+=stay in a hotel that includes free wifi."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Any area in Cambridge is fine, but I want the hotel to have a 2 star rating.", "streaming_reasoning": "As more information arrives, area: any; star rating: 2 stars; destination: have a 2 star rating..", "trace": "area+=any; stars+=2 stars; destination+=have a 2 star rating."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Something moderately priced would be ideal, please.", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, that would be great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "For 4 nights on Tuesday for 7 people please.", "streaming_reasoning": "Finally, day: tuesday; party size: 7 people; stay length: 4 nights..", "trace": "day+=tuesday; party_size+=7 people; stay_length+=4 nights."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is any; price is moderate; party size is 7 people; stay length is 4 nights; star rating is 2 stars; amenities is wifi; destination is stay; timing is tuesday.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use hotel, any, moderate, 7 people, tuesday and move the task forward.", "deep_reasoning_trace": "Need domain=hotel; goal=search; area=any; price=moderate; party_size=7 people; stay_length=4 nights; stars=2 stars; amenities=wifi; destination=stay, stay in a hotel that includes free wifi, have a 2 star rating; when=tuesday."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003527", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: You are a good wife, Julia.\nChunk 2: But you must take care of yourself.\nChunk 3: Give me some time to think about it.\nChunk 4: I'm dreadfully sorry for you.\nChunk 5: Thank you very much for your kindness.\nChunk 6: Is there any clue?", "streaming_reasoning": "C1 casual_comment=wife, julia. C2 casual_comment=must, take. C3 casual_comment=give, think. C4 casual_comment=i'm, dreadfully. C5 [SKIP: thanks_only]. C6 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: You are a good wife, Julia.\nChunk 2: But you must take care of yourself.\nChunk 3: Give me some time to think about it.\nChunk 4: I'm dreadfully sorry for you.\nChunk 5: Thank you very much for your kindness.\nChunk 6: Is there any clue?"}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=wife, julia. C2 casual_comment=must, take. C3 casual_comment=give, think. C4 casual_comment=i'm, dreadfully. C5 [SKIP: thanks_only]. C6 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: You are a good wife, Julia.\nChunk 2: But you must take care of yourself.\nChunk 3: Give me some time to think about it.\nChunk 4: I'm dreadfully sorry for you.\nChunk 5: Thank you very much for your kindness.\nChunk 6: Is there any clue?", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on wife. Next, the user comments on must. Next, the user comments on give. Next, the user comments on i'm. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=wife, julia. C2 casual_comment=must, take. C3 casual_comment=give, think. C4 casual_comment=i'm, dreadfully. C5 [SKIP: thanks_only]. C6 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "You are a good wife, Julia.", "streaming_reasoning": "Initially, the user comments on wife.", "trace": "casual_comment=wife, julia."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "But you must take care of yourself.", "streaming_reasoning": "As more information arrives, the user comments on must.", "trace": "casual_comment=must, take."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Give me some time to think about it.", "streaming_reasoning": "As more information arrives, the user comments on give.", "trace": "casual_comment=give, think."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm dreadfully sorry for you.", "streaming_reasoning": "As more information arrives, the user comments on i'm.", "trace": "casual_comment=i'm, dreadfully."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you very much for your kindness.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Is there any clue?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003531", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you and goodbye.\nChunk 2: Today I want to invite you to talk about insurance you ' re interested in Thank you.\nChunk 3: I wonder whether I can enjoy the life insurance and health insurance Of course.\nChunk 4: A two-week paid vacation a year, a five-day workweek Good Anything else?", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 invitation=true. C3 casual_comment=wonder, whether. C4 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you and goodbye.\nChunk 2: Today I want to invite you to talk about insurance you ' re interested in Thank you.\nChunk 3: I wonder whether I can enjoy the life insurance and health insurance Of course.\nChunk 4: A two-week paid vacation a year, a five-day workweek Good Anything else?"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 invitation=true. C3 casual_comment=wonder, whether. C4 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you and goodbye.\nChunk 2: Today I want to invite you to talk about insurance you ' re interested in Thank you.\nChunk 3: I wonder whether I can enjoy the life insurance and health insurance Of course.\nChunk 4: A two-week paid vacation a year, a five-day workweek Good Anything else?", "input_token_count": 54, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, invitation: true. Next, the user comments on wonder. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained thanks_only. In summary, invitation: true..", "trace": "C1 [SKIP: thanks_only]. C2 invitation=true. C3 casual_comment=wonder, whether. C4 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you and goodbye.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Today I want to invite you to talk about insurance you ' re interested in Thank you.", "streaming_reasoning": "As more information arrives, invitation: true..", "trace": "invitation=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I wonder whether I can enjoy the life insurance and health insurance Of course.", "streaming_reasoning": "As more information arrives, the user comments on wonder.", "trace": "casual_comment=wonder, whether."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "A two-week paid vacation a year, a five-day workweek Good Anything else?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002835", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I could use a recommendation on a nightclub in the centre of town.\nChunk 2: I'd like to stay around the restaurant Cheap price please.\nChunk 3: I don't need a hotel.\nChunk 4: I'd just like a recommendation for a nightclub near the restaurant.\nChunk 5: Do you know what the entrance fee is?\nChunk 6: Great that is everything, I apologize for being so high maintenance, thanks for the help.", "streaming_reasoning": "C1 area+=centre. C2 domain=hotel; price+=cheap; destination+=stay around the restaurant cheap price pl. C3 goal=search; hotel_type+=hotel. C4 intent=context_update. C5 goal=request_info; requested_info+=entrance_fee. C6 intent=context_update.", "deep_reasoning": "Need domain=restaurant, hotel; goal=search, request_info; area=centre; price=cheap; destination=stay around the restaurant cheap price pl; requested_info=entrance_fee.", "answer": "I can help with that and include the entrance fee once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I could use a recommendation on a nightclub in the centre of town.\nChunk 2: I'd like to stay around the restaurant Cheap price please.\nChunk 3: I don't need a hotel.\nChunk 4: I'd just like a recommendation for a nightclub near the restaurant.\nChunk 5: Do you know what the entrance fee is?\nChunk 6: Great that is everything, I apologize for being so high maintenance, thanks for the help."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre. C2 domain=hotel; price+=cheap; destination+=stay around the restaurant cheap price pl. C3 goal=search; hotel_type+=hotel. C4 intent=context_update. C5 goal=request_info; requested_info+=entrance_fee. C6 intent=context_update.\n\nDeep reasoning: Need domain=restaurant, hotel; goal=search, request_info; area=centre; price=cheap; destination=stay around the restaurant cheap price pl; requested_info=entrance_fee.\n\nAnswer: I can help with that and include the entrance fee once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I could use a recommendation on a nightclub in the centre of town.\nChunk 2: I'd like to stay around the restaurant Cheap price please.\nChunk 3: I don't need a hotel.\nChunk 4: I'd just like a recommendation for a nightclub near the restaurant.\nChunk 5: Do you know what the entrance fee is?\nChunk 6: Great that is everything, I apologize for being so high maintenance, thanks for the help.", "input_token_count": 74, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: centre. Next, the topic is hotel; price: cheap; destination: stay around the restaurant cheap price pl. Next, the goal is search; hotel type: hotel. Next, intent: context_update. Next, the goal is request info; requested information: entrance_fee. Finally, intent: context_update. In summary, The overall topic is hotel. the goal is request info. area: centre.; price: cheap; destination: stay around the restaurant cheap price pl.; hotel type: hotel.; intent: context_update.; requested information: entrance_fee..", "trace": "C1 area+=centre. C2 domain=hotel; price+=cheap; destination+=stay around the restaurant cheap price pl. C3 goal=search; hotel_type+=hotel. C4 intent=context_update. C5 goal=request_info; requested_info+=entrance_fee. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I could use a recommendation on a nightclub in the centre of town.", "streaming_reasoning": "Initially, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to stay around the restaurant Cheap price please.", "streaming_reasoning": "As more information arrives, the topic is hotel; price: cheap; destination: stay around the restaurant cheap price pl..", "trace": "domain=hotel; price+=cheap; destination+=stay around the restaurant cheap price pl."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I don't need a hotel.", "streaming_reasoning": "As more information arrives, the goal is search; hotel type: hotel..", "trace": "goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd just like a recommendation for a nightclub near the restaurant.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Do you know what the entrance fee is?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: entrance_fee..", "trace": "goal=request_info; requested_info+=entrance_fee."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Great that is everything, I apologize for being so high maintenance, thanks for the help.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is cheap; destination is stay around the restaurant cheap price pl; requested information is entrance_fee.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the entrance fee once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=search, request_info; area=centre; price=cheap; destination=stay around the restaurant cheap price pl; requested_info=entrance_fee."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002836", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Book for 8 people on Friday at 17:15.\nChunk 2: Yes, I'd also like to check out a cool place in the centre area.\nChunk 3: How about multiple sports?\nChunk 4: What about a museum That sounds great.\nChunk 5: Can you tell me a phone number I can reach them at, and also the entrance fee?\nChunk 6: That is everything, thank you so much for your assistance.", "streaming_reasoning": "C1 goal=booking; time+=8, 17:15; day+=friday; party_size+=8 people. C2 area+=centre; destination+=check out a cool place in the centre area; goal=confirm_booking. C3 goal=recommendation; type+=sports. C4 domain=attraction. C5 goal=request_info; requested_info+=phone, entrance_fee. C6 intent=context_update.", "deep_reasoning": "Need domain=attraction; goal=booking, recommendation, request_info; area=centre; party_size=8 people; destination=check out a cool place in the centre area; requested_info=phone, entrance_fee; when=friday, 8, 17:15.", "answer": "I can help with that and include the phone, entrance fee once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Book for 8 people on Friday at 17:15.\nChunk 2: Yes, I'd also like to check out a cool place in the centre area.\nChunk 3: How about multiple sports?\nChunk 4: What about a museum That sounds great.\nChunk 5: Can you tell me a phone number I can reach them at, and also the entrance fee?\nChunk 6: That is everything, thank you so much for your assistance."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=8, 17:15; day+=friday; party_size+=8 people. C2 area+=centre; destination+=check out a cool place in the centre area; goal=confirm_booking. C3 goal=recommendation; type+=sports. C4 domain=attraction. C5 goal=request_info; requested_info+=phone, entrance_fee. C6 intent=context_update.\n\nDeep reasoning: Need domain=attraction; goal=booking, recommendation, request_info; area=centre; party_size=8 people; destination=check out a cool place in the centre area; requested_info=phone, entrance_fee; when=friday, 8, 17:15.\n\nAnswer: I can help with that and include the phone, entrance fee once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Book for 8 people on Friday at 17:15.\nChunk 2: Yes, I'd also like to check out a cool place in the centre area.\nChunk 3: How about multiple sports?\nChunk 4: What about a museum That sounds great.\nChunk 5: Can you tell me a phone number I can reach them at, and also the entrance fee?\nChunk 6: That is everything, thank you so much for your assistance.", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 8; day: friday; party size: 8 people. Next, the goal is confirm booking.; area: centre; destination: check out a cool place in the centre area. Next, the goal is recommendation; type: sports. Next, the topic is attraction. Next, the goal is request info; requested information: phone. Finally, intent: context_update. In summary, The overall topic is attraction.. the goal is request info. time: 8; day: friday; party size: 8 people.; area: centre; destination: check out a cool place in the centre area; type: sports.; requested information: phone; intent: context_update..", "trace": "C1 goal=booking; time+=8, 17:15; day+=friday; party_size+=8 people. C2 area+=centre; destination+=check out a cool place in the centre area; goal=confirm_booking. C3 goal=recommendation; type+=sports. C4 domain=attraction. C5 goal=request_info; requested_info+=phone, entrance_fee. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Book for 8 people on Friday at 17:15.", "streaming_reasoning": "Initially, the goal is booking; time: 8; day: friday; party size: 8 people..", "trace": "goal=booking; time+=8, 17:15; day+=friday; party_size+=8 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I'd also like to check out a cool place in the centre area.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; area: centre; destination: check out a cool place in the centre area.", "trace": "area+=centre; destination+=check out a cool place in the centre area; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about multiple sports?", "streaming_reasoning": "As more information arrives, the goal is recommendation; type: sports..", "trace": "goal=recommendation; type+=sports."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What about a museum That sounds great.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you tell me a phone number I can reach them at, and also the entrance fee?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, entrance_fee."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is everything, thank you so much for your assistance.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of booking. Key information: area is centre; party size is 8 people; destination is check out a cool place in the centre area; requested information is phone; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, entrance fee once I find the matching option.", "deep_reasoning_trace": "Need domain=attraction; goal=booking, recommendation, request_info; area=centre; party_size=8 people; destination=check out a cool place in the centre area; requested_info=phone, entrance_fee; when=friday, 8, 17:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002837", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yeah Moderate price range.\nChunk 2: Internet and parking are not a priority for me.\nChunk 3: No star preference, just as long as it's moderately priced Thank you.\nChunk 4: I prefer hotels Moderately priced.\nChunk 5: I'd like one with free wifi, and could you give me the star rating Not right now.\nChunk 6: Thank you for the information Nope!\nChunk 7: That will do it, thanks!", "streaming_reasoning": "C1 price+=moderate. C2 amenities+=parking, internet. C3 goal=modify_constraint. C4 hotel_type+=hotel. C5 goal=request_info; amenities+=wifi. C6 [SKIP: thanks_only]. C7 intent=context_update.", "deep_reasoning": "Need goal=request_info; price=moderate; amenities=parking, internet, wifi; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yeah Moderate price range.\nChunk 2: Internet and parking are not a priority for me.\nChunk 3: No star preference, just as long as it's moderately priced Thank you.\nChunk 4: I prefer hotels Moderately priced.\nChunk 5: I'd like one with free wifi, and could you give me the star rating Not right now.\nChunk 6: Thank you for the information Nope!\nChunk 7: That will do it, thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 price+=moderate. C2 amenities+=parking, internet. C3 goal=modify_constraint. C4 hotel_type+=hotel. C5 goal=request_info; amenities+=wifi. C6 [SKIP: thanks_only]. C7 intent=context_update.\n\nDeep reasoning: Need goal=request_info; price=moderate; amenities=parking, internet, wifi; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yeah Moderate price range.\nChunk 2: Internet and parking are not a priority for me.\nChunk 3: No star preference, just as long as it's moderately priced Thank you.\nChunk 4: I prefer hotels Moderately priced.\nChunk 5: I'd like one with free wifi, and could you give me the star rating Not right now.\nChunk 6: Thank you for the information Nope!\nChunk 7: That will do it, thanks!", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, price: moderate. Next, amenities: parking. Next, the goal is modify constraint. Next, hotel type: hotel. Next, the goal is request info; amenities: wifi. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, the goal is request info. price: moderate.; amenities: parking, wifi.; hotel type: hotel.; intent: context_update..", "trace": "C1 price+=moderate. C2 amenities+=parking, internet. C3 goal=modify_constraint. C4 hotel_type+=hotel. C5 goal=request_info; amenities+=wifi. C6 [SKIP: thanks_only]. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yeah Moderate price range.", "streaming_reasoning": "Initially, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Internet and parking are not a priority for me.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, internet."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No star preference, just as long as it's moderately priced Thank you.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I prefer hotels Moderately priced.", "streaming_reasoning": "As more information arrives, hotel type: hotel..", "trace": "hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'd like one with free wifi, and could you give me the star rating Not right now.", "streaming_reasoning": "As more information arrives, the goal is request info; amenities: wifi..", "trace": "goal=request_info; amenities+=wifi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for the information Nope!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That will do it, thanks!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "Need goal=request_info; price=moderate; amenities=parking, internet, wifi; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002838", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to visit something like a museum, no specific part of town That sounds great.\nChunk 2: Can I please have the phone number?\nChunk 3: Yes I need to find a guesthouse, prefer with a 4 star rating.\nChunk 4: If you could just pick one, it does not have to have free parking.\nChunk 5: Maybe close to the Broughton House Gallery That sounds great!\nChunk 6: Could I get the area and phone number of the Bed and Breakfast?\nChunk 7: Nope that'll be it.\nChunk 8: Thanks.", "streaming_reasoning": "C1 domain=attraction; destination+=visit something like a museum. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars; destination+=find a guesthouse; acceptance=selected_option. C4 amenities+=parking, free parking; destination+=have free parking. C5 destination+=the broughton house gallery that sounds g. C6 domain=restaurant; amenities+=breakfast. C7 intent=context_update. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, hotel, restaurant; goal=request_info, search; stars=4 stars; amenities=parking, free parking, breakfast; destination=visit something like a museum, find a guesthouse, have free parking, the broughton house gallery that sounds g; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to visit something like a museum, no specific part of town That sounds great.\nChunk 2: Can I please have the phone number?\nChunk 3: Yes I need to find a guesthouse, prefer with a 4 star rating.\nChunk 4: If you could just pick one, it does not have to have free parking.\nChunk 5: Maybe close to the Broughton House Gallery That sounds great!\nChunk 6: Could I get the area and phone number of the Bed and Breakfast?\nChunk 7: Nope that'll be it.\nChunk 8: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; destination+=visit something like a museum. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars; destination+=find a guesthouse; acceptance=selected_option. C4 amenities+=parking, free parking; destination+=have free parking. C5 destination+=the broughton house gallery that sounds g. C6 domain=restaurant; amenities+=breakfast. C7 intent=context_update. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, hotel, restaurant; goal=request_info, search; stars=4 stars; amenities=parking, free parking, breakfast; destination=visit something like a museum, find a guesthouse, have free parking, the broughton house gallery that sounds g; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to visit something like a museum, no specific part of town That sounds great.\nChunk 2: Can I please have the phone number?\nChunk 3: Yes I need to find a guesthouse, prefer with a 4 star rating.\nChunk 4: If you could just pick one, it does not have to have free parking.\nChunk 5: Maybe close to the Broughton House Gallery That sounds great!\nChunk 6: Could I get the area and phone number of the Bed and Breakfast?\nChunk 7: Nope that'll be it.\nChunk 8: Thanks.", "input_token_count": 95, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; destination: visit something like a museum. Next, the goal is request info; requested information: phone. Next, the topic is hotel; the goal is search; hotel type: guesthouse; star rating: 4 stars; destination: find a guesthouse; acceptance: selected_option. Next, amenities: parking; destination: have free parking. Next, destination: the broughton house gallery that sounds g. Next, the topic is restaurant; amenities: breakfast. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is search. destination: visit something like a museum., find a guesthouse, have free parking., the broughton house gallery that sounds g.; requested information: phone.; hotel type: guesthouse; star rating: 4 stars; acceptance: selected_option.; amenities: parking, breakfast.; intent: context_update..", "trace": "C1 domain=attraction; destination+=visit something like a museum. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars; destination+=find a guesthouse; acceptance=selected_option. C4 amenities+=parking, free parking; destination+=have free parking. C5 destination+=the broughton house gallery that sounds g. C6 domain=restaurant; amenities+=breakfast. C7 intent=context_update. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to visit something like a museum, no specific part of town That sounds great.", "streaming_reasoning": "Initially, the topic is attraction; destination: visit something like a museum..", "trace": "domain=attraction; destination+=visit something like a museum."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I please have the phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes I need to find a guesthouse, prefer with a 4 star rating.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: guesthouse; star rating: 4 stars; destination: find a guesthouse; acceptance: selected_option..", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; stars+=4 stars; destination+=find a guesthouse; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "If you could just pick one, it does not have to have free parking.", "streaming_reasoning": "As more information arrives, amenities: parking; destination: have free parking..", "trace": "amenities+=parking, free parking; destination+=have free parking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Maybe close to the Broughton House Gallery That sounds great!", "streaming_reasoning": "As more information arrives, destination: the broughton house gallery that sounds g..", "trace": "destination+=the broughton house gallery that sounds g."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could I get the area and phone number of the Bed and Breakfast?", "streaming_reasoning": "As more information arrives, the topic is restaurant; amenities: breakfast..", "trace": "domain=restaurant; amenities+=breakfast."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Nope that'll be it.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: star rating is 4 stars; amenities is parking; destination is visit something like a museum; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, hotel, restaurant; goal=request_info, search; stars=4 stars; amenities=parking, free parking, breakfast; destination=visit something like a museum, find a guesthouse, have free parking, the broughton house gallery that sounds g; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000594", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Make Your Computer Run Faster.\nChunk 2: Back up your computer.\nChunk 3: Prevent programs from starting automatically.\nChunk 4: Switch your power plan to High Performance (Windows).\nChunk 5: Run anti-virus and anti-malware scans.\nChunk 6: Disable visual effects and animations.", "streaming_reasoning": "C1 task=make_your_computer_run. C2 step=back_up_your_computer. C3 step=prevent_programs_from_starting. C4 step=switch_your_power_plan. C5 step=run_antivirus_and_antimalware. C6 step=disable_visual_effects_and.", "deep_reasoning": "Procedure for Make Your Computer Run Faster: Back up your computer, Prevent programs from starting automatically, Switch your power plan to High Performance, Run anti-virus and anti-malware scans, Disable visual effects and animations.", "answer": "For Make Your Computer Run Faster, follow the steps in order: Back up your computer, Prevent programs from starting automatically, Switch your power plan to High Performance, Run anti-virus and anti-malware scans.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Make Your Computer Run Faster.\nChunk 2: Back up your computer.\nChunk 3: Prevent programs from starting automatically.\nChunk 4: Switch your power plan to High Performance (Windows).\nChunk 5: Run anti-virus and anti-malware scans.\nChunk 6: Disable visual effects and animations."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=make_your_computer_run. C2 step=back_up_your_computer. C3 step=prevent_programs_from_starting. C4 step=switch_your_power_plan. C5 step=run_antivirus_and_antimalware. C6 step=disable_visual_effects_and.\n\nDeep reasoning: Procedure for Make Your Computer Run Faster: Back up your computer, Prevent programs from starting automatically, Switch your power plan to High Performance, Run anti-virus and anti-malware scans, Disable visual effects and animations.\n\nAnswer: For Make Your Computer Run Faster, follow the steps in order: Back up your computer, Prevent programs from starting automatically, Switch your power plan to High Performance, Run anti-virus and anti-malware scans."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Make Your Computer Run Faster.\nChunk 2: Back up your computer.\nChunk 3: Prevent programs from starting automatically.\nChunk 4: Switch your power plan to High Performance (Windows).\nChunk 5: Run anti-virus and anti-malware scans.\nChunk 6: Disable visual effects and animations.", "input_token_count": 45, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, task: make_your_computer_run. Next, step: back_up_your_computer. Next, step: prevent_programs_from_starting. Next, step: switch_your_power_plan. Next, step: run_antivirus_and_antimalware. Finally, step: disable_visual_effects_and. In summary, task: make_your_computer_run.; step: back_up_your_computer., prevent_programs_from_starting., switch_your_power_plan., run_antivirus_and_antimalware., disable_visual_effects_and..", "trace": "C1 task=make_your_computer_run. C2 step=back_up_your_computer. C3 step=prevent_programs_from_starting. C4 step=switch_your_power_plan. C5 step=run_antivirus_and_antimalware. C6 step=disable_visual_effects_and.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Make Your Computer Run Faster.", "streaming_reasoning": "Initially, task: make_your_computer_run..", "trace": "task=make_your_computer_run."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Back up your computer.", "streaming_reasoning": "As more information arrives, step: back_up_your_computer..", "trace": "step=back_up_your_computer."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Prevent programs from starting automatically.", "streaming_reasoning": "As more information arrives, step: prevent_programs_from_starting..", "trace": "step=prevent_programs_from_starting."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Switch your power plan to High Performance (Windows).", "streaming_reasoning": "As more information arrives, step: switch_your_power_plan..", "trace": "step=switch_your_power_plan."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Run anti-virus and anti-malware scans.", "streaming_reasoning": "As more information arrives, step: run_antivirus_and_antimalware..", "trace": "step=run_antivirus_and_antimalware."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Disable visual effects and animations.", "streaming_reasoning": "Finally, step: disable_visual_effects_and..", "trace": "step=disable_visual_effects_and."}]}, "output": {"deep_reasoning": "Procedure for Make Your Computer Run Faster: Back up your computer, Prevent programs from starting automatically, Switch your power plan to High Performance, Run anti-virus and anti-malware scans, Disable visual effects and animations.", "answer": "For Make Your Computer Run Faster, follow the steps in order: Back up your computer, Prevent programs from starting automatically, Switch your power plan to High Performance, Run anti-virus and anti-malware scans."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002839", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: need a restaurant serving turkish style venue.\nChunk 2: Any area would be fine!\nChunk 3: Could I please get the address and postcode of a Turkish restaurant Thank you goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=turkish. C2 area+=any. C3 goal=request_info; requested_info+=address, postcode.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=any; food=turkish; requested_info=address, postcode.", "answer": "I can help with that and include the address, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: need a restaurant serving turkish style venue.\nChunk 2: Any area would be fine!\nChunk 3: Could I please get the address and postcode of a Turkish restaurant Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=turkish. C2 area+=any. C3 goal=request_info; requested_info+=address, postcode.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=any; food=turkish; requested_info=address, postcode.\n\nAnswer: I can help with that and include the address, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: need a restaurant serving turkish style venue.\nChunk 2: Any area would be fine!\nChunk 3: Could I please get the address and postcode of a Turkish restaurant Thank you goodbye.", "input_token_count": 33, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: turkish. Next, area: any. Finally, the goal is request info; requested information: address. In summary, The overall topic is restaurant. the goal is request info. cuisine: turkish.; area: any.; requested information: address.", "trace": "C1 domain=restaurant; goal=search; cuisine+=turkish. C2 area+=any. C3 goal=request_info; requested_info+=address, postcode.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "need a restaurant serving turkish style venue.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: turkish..", "trace": "domain=restaurant; goal=search; cuisine+=turkish."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Any area would be fine!", "streaming_reasoning": "As more information arrives, area: any..", "trace": "area+=any."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Could I please get the address and postcode of a Turkish restaurant Thank you goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is any; cuisine is turkish; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=any; food=turkish; requested_info=address, postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002840", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Not interested in the price, but I would like it to be a 4-star hotel I'm sorry.\nChunk 2: I needed a hotel, not a guesthouse Yes please.\nChunk 3: I need it to be for 1 person for 2 nights starting on Friday.\nChunk 4: Great, can you also find me a Japanese food restaurant in the expensive price range?\nChunk 5: Yes.\nChunk 6: Can you please book a table for one at 12:45 on Friday?\nChunk 7: Thanks so so much!\nChunk 8: That's all now, bye!", "streaming_reasoning": "C1 domain=hotel; hotel_type+=hotel; destination+=be a 4-star hotel i'm sorry. C2 hotel_type+=guesthouse; acceptance=selected_option. C3 goal=search; time+=1, 2; day+=friday; stay_length+=2 nights; destination+=be for 1 person for 2 nights starting on. C4 domain=restaurant; cuisine+=japanese; price+=expensive; requested_info+=price. C5 [SKIP: acknowledgement_only]. C6 goal=booking; time+=12:45. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, booking; food=japanese; price=expensive; stay_length=2 nights; destination=be a 4-star hotel i'm sorry, be for 1 person for 2 nights starting on; requested_info=price; when=friday, 1, 2, 12:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Not interested in the price, but I would like it to be a 4-star hotel I'm sorry.\nChunk 2: I needed a hotel, not a guesthouse Yes please.\nChunk 3: I need it to be for 1 person for 2 nights starting on Friday.\nChunk 4: Great, can you also find me a Japanese food restaurant in the expensive price range?\nChunk 5: Yes.\nChunk 6: Can you please book a table for one at 12:45 on Friday?\nChunk 7: Thanks so so much!\nChunk 8: That's all now, bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=hotel; destination+=be a 4-star hotel i'm sorry. C2 hotel_type+=guesthouse; acceptance=selected_option. C3 goal=search; time+=1, 2; day+=friday; stay_length+=2 nights; destination+=be for 1 person for 2 nights starting on. C4 domain=restaurant; cuisine+=japanese; price+=expensive; requested_info+=price. C5 [SKIP: acknowledgement_only]. C6 goal=booking; time+=12:45. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, booking; food=japanese; price=expensive; stay_length=2 nights; destination=be a 4-star hotel i'm sorry, be for 1 person for 2 nights starting on; requested_info=price; when=friday, 1, 2, 12:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Not interested in the price, but I would like it to be a 4-star hotel I'm sorry.\nChunk 2: I needed a hotel, not a guesthouse Yes please.\nChunk 3: I need it to be for 1 person for 2 nights starting on Friday.\nChunk 4: Great, can you also find me a Japanese food restaurant in the expensive price range?\nChunk 5: Yes.\nChunk 6: Can you please book a table for one at 12:45 on Friday?\nChunk 7: Thanks so so much!\nChunk 8: That's all now, bye!", "input_token_count": 93, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: hotel; destination: be a 4-star hotel i'm sorry. Next, hotel type: guesthouse; acceptance: selected_option. Next, the goal is search; time: 1; day: friday; stay length: 2 nights; destination: be for 1 person for 2 nights starting on. Next, the topic is restaurant; cuisine: japanese; price: expensive; requested information: price. Finally, the goal is booking; time: 12:45.  Some chunks were skipped because they contained acknowledgement_only or closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is booking. hotel type: hotel, guesthouse; destination: be a 4-star hotel i'm sorry., be for 1 person for 2 nights starting on.; acceptance: selected_option.; time: 1, 12:45.; day: friday; stay length: 2 nights; cuisine: japanese; price: expensive; requested information: price..", "trace": "C1 domain=hotel; hotel_type+=hotel; destination+=be a 4-star hotel i'm sorry. C2 hotel_type+=guesthouse; acceptance=selected_option. C3 goal=search; time+=1, 2; day+=friday; stay_length+=2 nights; destination+=be for 1 person for 2 nights starting on. C4 domain=restaurant; cuisine+=japanese; price+=expensive; requested_info+=price. C5 [SKIP: acknowledgement_only]. C6 goal=booking; time+=12:45. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Not interested in the price, but I would like it to be a 4-star hotel I'm sorry.", "streaming_reasoning": "Initially, the topic is hotel; hotel type: hotel; destination: be a 4-star hotel i'm sorry..", "trace": "domain=hotel; hotel_type+=hotel; destination+=be a 4-star hotel i'm sorry."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I needed a hotel, not a guesthouse Yes please.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse; acceptance: selected_option..", "trace": "hotel_type+=guesthouse; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need it to be for 1 person for 2 nights starting on Friday.", "streaming_reasoning": "As more information arrives, the goal is search; time: 1; day: friday; stay length: 2 nights; destination: be for 1 person for 2 nights starting on..", "trace": "goal=search; time+=1, 2; day+=friday; stay_length+=2 nights; destination+=be for 1 person for 2 nights starting on."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Great, can you also find me a Japanese food restaurant in the expensive price range?", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: japanese; price: expensive; requested information: price..", "trace": "domain=restaurant; cuisine+=japanese; price+=expensive; requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes.", "streaming_reasoning": "The content at C5 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you please book a table for one at 12:45 on Friday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 12:45..", "trace": "goal=booking; time+=12:45."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks so so much!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's all now, bye!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: cuisine is japanese; price is expensive; stay length is 2 nights; destination is be a 4-star hotel i'm sorry; requested information is price; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, booking; food=japanese; price=expensive; stay_length=2 nights; destination=be a 4-star hotel i'm sorry, be for 1 person for 2 nights starting on; requested_info=price; when=friday, 1, 2, 12:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002841", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place with free wifi, doesn't need parking, and expensive price range No particular area.\nChunk 2: I would definitely want a moderate priced room though.\nChunk 3: Yes.\nChunk 4: I need it for 6 people for 5 nights starting on Friday.\nChunk 5: Can I get it for 1 night, then?\nChunk 6: May I have the booking reference number, please?\nChunk 7: No, that is just what I needed.\nChunk 8: Thanks for your help.\nChunk 9: Bye.", "streaming_reasoning": "C1 goal=search; price+=expensive; amenities+=parking, wifi; requested_info+=price. C2 domain=hotel; price+=moderate. C3 [SKIP: acknowledgement_only]. C4 time+=6, 5; day+=friday; party_size+=6 people; stay_length+=5 nights. C5 goal=request_info; stay_length+=1 nights. C6 goal=booking; requested_info+=reference_number. C7 goal=modify_constraint. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info, booking; price=expensive, moderate; party_size=6 people; stay_length=5 nights, 1 nights; amenities=parking, wifi; requested_info=price, reference_number; when=friday, 6, 5; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a place with free wifi, doesn't need parking, and expensive price range No particular area.\nChunk 2: I would definitely want a moderate priced room though.\nChunk 3: Yes.\nChunk 4: I need it for 6 people for 5 nights starting on Friday.\nChunk 5: Can I get it for 1 night, then?\nChunk 6: May I have the booking reference number, please?\nChunk 7: No, that is just what I needed.\nChunk 8: Thanks for your help.\nChunk 9: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; price+=expensive; amenities+=parking, wifi; requested_info+=price. C2 domain=hotel; price+=moderate. C3 [SKIP: acknowledgement_only]. C4 time+=6, 5; day+=friday; party_size+=6 people; stay_length+=5 nights. C5 goal=request_info; stay_length+=1 nights. C6 goal=booking; requested_info+=reference_number. C7 goal=modify_constraint. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info, booking; price=expensive, moderate; party_size=6 people; stay_length=5 nights, 1 nights; amenities=parking, wifi; requested_info=price, reference_number; when=friday, 6, 5; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place with free wifi, doesn't need parking, and expensive price range No particular area.\nChunk 2: I would definitely want a moderate priced room though.\nChunk 3: Yes.\nChunk 4: I need it for 6 people for 5 nights starting on Friday.\nChunk 5: Can I get it for 1 night, then?\nChunk 6: May I have the booking reference number, please?\nChunk 7: No, that is just what I needed.\nChunk 8: Thanks for your help.\nChunk 9: Bye.", "input_token_count": 87, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; price: expensive; amenities: parking; requested information: price. Next, the topic is hotel; price: moderate. Next, time: 6; day: friday; party size: 6 people; stay length: 5 nights. Next, the goal is request info; stay length: 1 nights. Next, the goal is booking; requested information: reference_number. Finally, the goal is modify constraint.  Some chunks were skipped because they contained acknowledgement_only or closing_only or thanks_only. In summary, The overall topic is hotel. the goal is modify constraint.. price: expensive, moderate.; amenities: parking; requested information: price., reference_number.; time: 6; day: friday; party size: 6 people; stay length: 5 nights., 1 nights..", "trace": "C1 goal=search; price+=expensive; amenities+=parking, wifi; requested_info+=price. C2 domain=hotel; price+=moderate. C3 [SKIP: acknowledgement_only]. C4 time+=6, 5; day+=friday; party_size+=6 people; stay_length+=5 nights. C5 goal=request_info; stay_length+=1 nights. C6 goal=booking; requested_info+=reference_number. C7 goal=modify_constraint. C8 [SKIP: thanks_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a place with free wifi, doesn't need parking, and expensive price range No particular area.", "streaming_reasoning": "Initially, the goal is search; price: expensive; amenities: parking; requested information: price..", "trace": "goal=search; price+=expensive; amenities+=parking, wifi; requested_info+=price."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would definitely want a moderate priced room though.", "streaming_reasoning": "As more information arrives, the topic is hotel; price: moderate..", "trace": "domain=hotel; price+=moderate."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes.", "streaming_reasoning": "The content at C3 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need it for 6 people for 5 nights starting on Friday.", "streaming_reasoning": "As more information arrives, time: 6; day: friday; party size: 6 people; stay length: 5 nights..", "trace": "time+=6, 5; day+=friday; party_size+=6 people; stay_length+=5 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get it for 1 night, then?", "streaming_reasoning": "As more information arrives, the goal is request info; stay length: 1 nights..", "trace": "goal=request_info; stay_length+=1 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "May I have the booking reference number, please?", "streaming_reasoning": "As more information arrives, the goal is booking; requested information: reference_number..", "trace": "goal=booking; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that is just what I needed.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thanks for your help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Bye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is expensive; party size is 6 people; stay length is 5 nights; amenities is parking; requested information is price; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info, booking; price=expensive, moderate; party_size=6 people; stay_length=5 nights, 1 nights; amenities=parking, wifi; requested_info=price, reference_number; when=friday, 6, 5; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002842", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a train for Saturday.\nChunk 2: I will be departing from Ely and traveling to Cambridge.\nChunk 3: I need to arrive by 11:45 Yes please.\nChunk 4: I need it to be booked for 8 people.\nChunk 5: Thank you, that is all I need.", "streaming_reasoning": "C1 domain=train; goal=search; day+=saturday; destination+=find a train for saturday. C2 destination+=cambridge; departure+=ely and traveling, ely and traveling to cambridge. C3 time+=11:45; destination+=arrive by 11:45 yes please; acceptance=selected_option. C4 party_size+=8 people. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search; party_size=8 people; destination=find a train for saturday, cambridge, arrive by 11:45 yes please; departure=ely and traveling, ely and traveling to cambridge; when=saturday, 11:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to find a train for Saturday.\nChunk 2: I will be departing from Ely and traveling to Cambridge.\nChunk 3: I need to arrive by 11:45 Yes please.\nChunk 4: I need it to be booked for 8 people.\nChunk 5: Thank you, that is all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=saturday; destination+=find a train for saturday. C2 destination+=cambridge; departure+=ely and traveling, ely and traveling to cambridge. C3 time+=11:45; destination+=arrive by 11:45 yes please; acceptance=selected_option. C4 party_size+=8 people. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search; party_size=8 people; destination=find a train for saturday, cambridge, arrive by 11:45 yes please; departure=ely and traveling, ely and traveling to cambridge; when=saturday, 11:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to find a train for Saturday.\nChunk 2: I will be departing from Ely and traveling to Cambridge.\nChunk 3: I need to arrive by 11:45 Yes please.\nChunk 4: I need it to be booked for 8 people.\nChunk 5: Thank you, that is all I need.", "input_token_count": 53, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: saturday; destination: find a train for saturday. Next, destination: cambridge; departure point: ely and traveling. Next, time: 11:45; destination: arrive by 11:45 yes please; acceptance: selected_option. Finally, party size: 8 people.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is search. day: saturday; destination: find a train for saturday., cambridge, arrive by 11:45 yes please; departure point: ely and traveling; time: 11:45; acceptance: selected_option.; party size: 8 people..", "trace": "C1 domain=train; goal=search; day+=saturday; destination+=find a train for saturday. C2 destination+=cambridge; departure+=ely and traveling, ely and traveling to cambridge. C3 time+=11:45; destination+=arrive by 11:45 yes please; acceptance=selected_option. C4 party_size+=8 people. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to find a train for Saturday.", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: saturday; destination: find a train for saturday..", "trace": "domain=train; goal=search; day+=saturday; destination+=find a train for saturday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will be departing from Ely and traveling to Cambridge.", "streaming_reasoning": "As more information arrives, destination: cambridge; departure point: ely and traveling.", "trace": "destination+=cambridge; departure+=ely and traveling, ely and traveling to cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to arrive by 11:45 Yes please.", "streaming_reasoning": "As more information arrives, time: 11:45; destination: arrive by 11:45 yes please; acceptance: selected_option..", "trace": "time+=11:45; destination+=arrive by 11:45 yes please; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need it to be booked for 8 people.", "streaming_reasoning": "As more information arrives, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you, that is all I need.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 8 people; destination is find a train for saturday; departure point is ely and traveling; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search; party_size=8 people; destination=find a train for saturday, cambridge, arrive by 11:45 yes please; departure=ely and traveling, ely and traveling to cambridge; when=saturday, 11:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002843", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That would need helpful yes, however I need the hotel to also offer free parking!\nChunk 2: Yes, please tell me the star ratings.\nChunk 3: I want to find a expensive restaurant.\nChunk 4: It should be in the north part of town.\nChunk 5: I also need the phone.\nChunk 6: I am actually looking to eat lebanese food.\nChunk 7: How about Chinese then?\nChunk 8: Yes please, can I get a phone number, address, and reference number?", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking; destination+=also offer free parking!; acceptance=selected_option. C2 goal=request_info; acceptance=selected_option. C3 domain=restaurant; price+=expensive; destination+=find a expensive restaurant. C4 area+=north. C5 requested_info+=phone. C6 destination+=eat lebanese food. C7 goal=recommendation; cuisine+=chinese. C8 requested_info+=address, reference_number; acceptance=selected_option.", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, request_info, recommendation; area=north; food=chinese; price=expensive; amenities=parking, free parking; destination=also offer free parking!, find a expensive restaurant, eat lebanese food; requested_info=phone, address, reference_number.", "answer": "I can help with that and include the phone, address, reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: That would need helpful yes, however I need the hotel to also offer free parking!\nChunk 2: Yes, please tell me the star ratings.\nChunk 3: I want to find a expensive restaurant.\nChunk 4: It should be in the north part of town.\nChunk 5: I also need the phone.\nChunk 6: I am actually looking to eat lebanese food.\nChunk 7: How about Chinese then?\nChunk 8: Yes please, can I get a phone number, address, and reference number?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking; destination+=also offer free parking!; acceptance=selected_option. C2 goal=request_info; acceptance=selected_option. C3 domain=restaurant; price+=expensive; destination+=find a expensive restaurant. C4 area+=north. C5 requested_info+=phone. C6 destination+=eat lebanese food. C7 goal=recommendation; cuisine+=chinese. C8 requested_info+=address, reference_number; acceptance=selected_option.\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, request_info, recommendation; area=north; food=chinese; price=expensive; amenities=parking, free parking; destination=also offer free parking!, find a expensive restaurant, eat lebanese food; requested_info=phone, address, reference_number.\n\nAnswer: I can help with that and include the phone, address, reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That would need helpful yes, however I need the hotel to also offer free parking!\nChunk 2: Yes, please tell me the star ratings.\nChunk 3: I want to find a expensive restaurant.\nChunk 4: It should be in the north part of town.\nChunk 5: I also need the phone.\nChunk 6: I am actually looking to eat lebanese food.\nChunk 7: How about Chinese then?\nChunk 8: Yes please, can I get a phone number, address, and reference number?", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; amenities: parking; destination: also offer free parking!; acceptance: selected_option. Next, the goal is request info; acceptance: selected_option. Next, the topic is restaurant; price: expensive; destination: find a expensive restaurant. Next, area: north. Next, requested information: phone. Next, destination: eat lebanese food. Next, the goal is recommendation; cuisine: chinese. Finally, requested information: address; acceptance: selected_option. In summary, The overall topic is restaurant. the goal is recommendation. hotel type: hotel; amenities: parking; destination: also offer free parking!, find a expensive restaurant., eat lebanese food.; acceptance: selected_option.; price: expensive; area: north.; requested information: phone., address; cuisine: chinese..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking; destination+=also offer free parking!; acceptance=selected_option. C2 goal=request_info; acceptance=selected_option. C3 domain=restaurant; price+=expensive; destination+=find a expensive restaurant. C4 area+=north. C5 requested_info+=phone. C6 destination+=eat lebanese food. C7 goal=recommendation; cuisine+=chinese. C8 requested_info+=address, reference_number; acceptance=selected_option.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "That would need helpful yes, however I need the hotel to also offer free parking!", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; amenities: parking; destination: also offer free parking!; acceptance: selected_option..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; amenities+=parking, free parking; destination+=also offer free parking!; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, please tell me the star ratings.", "streaming_reasoning": "As more information arrives, the goal is request info; acceptance: selected_option..", "trace": "goal=request_info; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a expensive restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; price: expensive; destination: find a expensive restaurant..", "trace": "domain=restaurant; price+=expensive; destination+=find a expensive restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It should be in the north part of town.", "streaming_reasoning": "As more information arrives, area: north..", "trace": "area+=north."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I am actually looking to eat lebanese food.", "streaming_reasoning": "As more information arrives, destination: eat lebanese food..", "trace": "destination+=eat lebanese food."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "How about Chinese then?", "streaming_reasoning": "As more information arrives, the goal is recommendation; cuisine: chinese..", "trace": "goal=recommendation; cuisine+=chinese."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Yes please, can I get a phone number, address, and reference number?", "streaming_reasoning": "Finally, requested information: address; acceptance: selected_option..", "trace": "requested_info+=address, reference_number; acceptance=selected_option."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is north; cuisine is chinese; price is expensive; amenities is parking; destination is also offer free parking!; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, address, reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, request_info, recommendation; area=north; food=chinese; price=expensive; amenities=parking, free parking; destination=also offer free parking!, find a expensive restaurant, eat lebanese food; requested_info=phone, address, reference_number."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002844", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: I am looking to find information about the Cambridge University Botanic gardens Thank you.\nChunk 3: What area is that in, and what type of attraction is it Thank you.\nChunk 4: Do you have any good korean restaurants listed?\nChunk 5: How about Thai food instead?\nChunk 6: It is for 2 people.\nChunk 7: The time is saturday, 2, 12:30.\nChunk 8: Please make a booking Thank you.\nChunk 9: That's all I need for today.", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 goal=search; destination+=find information about the cambridge univ. C3 domain=attraction. C4 cuisine+=korean. C5 domain=restaurant; goal=compare_alternative; cuisine+=thai. C6 party_size+=2 people. C7 time+=2, 12:30; day+=saturday. C8 goal=booking. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, restaurant; goal=search, recommendation, compare_alternative, booking; food=korean, thai; party_size=2 people; destination=find information about the cambridge univ; when=saturday, 2, 12:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi!\nChunk 2: I am looking to find information about the Cambridge University Botanic gardens Thank you.\nChunk 3: What area is that in, and what type of attraction is it Thank you.\nChunk 4: Do you have any good korean restaurants listed?\nChunk 5: How about Thai food instead?\nChunk 6: It is for 2 people.\nChunk 7: The time is saturday, 2, 12:30.\nChunk 8: Please make a booking Thank you.\nChunk 9: That's all I need for today."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 goal=search; destination+=find information about the cambridge univ. C3 domain=attraction. C4 cuisine+=korean. C5 domain=restaurant; goal=compare_alternative; cuisine+=thai. C6 party_size+=2 people. C7 time+=2, 12:30; day+=saturday. C8 goal=booking. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, restaurant; goal=search, recommendation, compare_alternative, booking; food=korean, thai; party_size=2 people; destination=find information about the cambridge univ; when=saturday, 2, 12:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: I am looking to find information about the Cambridge University Botanic gardens Thank you.\nChunk 3: What area is that in, and what type of attraction is it Thank you.\nChunk 4: Do you have any good korean restaurants listed?\nChunk 5: How about Thai food instead?\nChunk 6: It is for 2 people.\nChunk 7: The time is saturday, 2, 12:30.\nChunk 8: Please make a booking Thank you.\nChunk 9: That's all I need for today.", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; destination: find information about the cambridge univ. Next, the topic is attraction. Next, cuisine: korean. Next, the topic is restaurant; the goal is compare alternative; cuisine: thai. Next, party size: 2 people. Next, time: 2; day: saturday. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only or greeting_only. In summary, The overall topic is restaurant. the goal is booking.. destination: find information about the cambridge univ.; cuisine: korean., thai.; party size: 2 people.; time: 2; day: saturday..", "trace": "C1 [SKIP: greeting_only]. C2 goal=search; destination+=find information about the cambridge univ. C3 domain=attraction. C4 cuisine+=korean. C5 domain=restaurant; goal=compare_alternative; cuisine+=thai. C6 party_size+=2 people. C7 time+=2, 12:30; day+=saturday. C8 goal=booking. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi!", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am looking to find information about the Cambridge University Botanic gardens Thank you.", "streaming_reasoning": "As more information arrives, the goal is search; destination: find information about the cambridge univ..", "trace": "goal=search; destination+=find information about the cambridge univ."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What area is that in, and what type of attraction is it Thank you.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Do you have any good korean restaurants listed?", "streaming_reasoning": "As more information arrives, cuisine: korean..", "trace": "cuisine+=korean."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "How about Thai food instead?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is compare alternative; cuisine: thai..", "trace": "domain=restaurant; goal=compare_alternative; cuisine+=thai."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It is for 2 people.", "streaming_reasoning": "As more information arrives, party size: 2 people..", "trace": "party_size+=2 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is saturday, 2, 12:30.", "streaming_reasoning": "As more information arrives, time: 2; day: saturday..", "trace": "time+=2, 12:30; day+=saturday."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking Thank you.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That's all I need for today.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: cuisine is korean; party size is 2 people; destination is find information about the cambridge univ; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=search, recommendation, compare_alternative, booking; food=korean, thai; party_size=2 people; destination=find information about the cambridge univ; when=saturday, 2, 12:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002845", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a taxi from nusha to thanh binh at 6:15, please.\nChunk 2: That is all I needed, thanks.\nChunk 3: Thank you, you too.", "streaming_reasoning": "C1 domain=taxi; goal=search; time+=6:15; destination+=thanh binh; departure+=nusha. C2 [SKIP: closing_only]. C3 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi; goal=search; destination=thanh binh; departure=nusha; when=6:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a taxi from nusha to thanh binh at 6:15, please.\nChunk 2: That is all I needed, thanks.\nChunk 3: Thank you, you too."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search; time+=6:15; destination+=thanh binh; departure+=nusha. C2 [SKIP: closing_only]. C3 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi; goal=search; destination=thanh binh; departure=nusha; when=6:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a taxi from nusha to thanh binh at 6:15, please.\nChunk 2: That is all I needed, thanks.\nChunk 3: Thank you, you too.", "input_token_count": 29, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search; time: 6:15; destination: thanh binh; departure point: nusha.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi. the goal is search. time: 6:15; destination: thanh binh; departure point: nusha..", "trace": "C1 domain=taxi; goal=search; time+=6:15; destination+=thanh binh; departure+=nusha. C2 [SKIP: closing_only]. C3 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a taxi from nusha to thanh binh at 6:15, please.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search; time: 6:15; destination: thanh binh; departure point: nusha..", "trace": "domain=taxi; goal=search; time+=6:15; destination+=thanh binh; departure+=nusha."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "That is all I needed, thanks.", "streaming_reasoning": "The content at C2 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you, you too.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is thanh binh; departure point is nusha; timing is 6:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search; destination=thanh binh; departure=nusha; when=6:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002846", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a caribbean restaurant in the centre of the city.\nChunk 2: Are there any caribbean restaurants in any other part of town?\nChunk 3: Sure, a turkish restaurant in the moderate price range would be great.\nChunk 4: Yes, book me The Anatolia for 8 people at 12:00 on Friday.\nChunk 5: Yes please try booking that Great!\nChunk 6: Thank you so much for your help.\nChunk 7: That will be all.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre. C2 goal=request_info. C3 cuisine+=turkish; price+=moderate. C4 goal=confirm_booking; time+=8, 12:00; day+=friday; party_size+=8 people; goal=confirm_booking. C5 goal=confirm_booking. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; food=turkish; price=moderate; party_size=8 people; when=friday, 8, 12:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a caribbean restaurant in the centre of the city.\nChunk 2: Are there any caribbean restaurants in any other part of town?\nChunk 3: Sure, a turkish restaurant in the moderate price range would be great.\nChunk 4: Yes, book me The Anatolia for 8 people at 12:00 on Friday.\nChunk 5: Yes please try booking that Great!\nChunk 6: Thank you so much for your help.\nChunk 7: That will be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre. C2 goal=request_info. C3 cuisine+=turkish; price+=moderate. C4 goal=confirm_booking; time+=8, 12:00; day+=friday; party_size+=8 people; goal=confirm_booking. C5 goal=confirm_booking. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; food=turkish; price=moderate; party_size=8 people; when=friday, 8, 12:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a caribbean restaurant in the centre of the city.\nChunk 2: Are there any caribbean restaurants in any other part of town?\nChunk 3: Sure, a turkish restaurant in the moderate price range would be great.\nChunk 4: Yes, book me The Anatolia for 8 people at 12:00 on Friday.\nChunk 5: Yes please try booking that Great!\nChunk 6: Thank you so much for your help.\nChunk 7: That will be all.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre. Next, the goal is request info. Next, cuisine: turkish; price: moderate. Next, the goal is confirm booking.; time: 8; day: friday; party size: 8 people. Finally, the goal is confirm booking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is confirm booking.. area: centre.; cuisine: turkish; price: moderate.; time: 8; day: friday; party size: 8 people.", "trace": "C1 domain=restaurant; goal=search; area+=centre. C2 goal=request_info. C3 cuisine+=turkish; price+=moderate. C4 goal=confirm_booking; time+=8, 12:00; day+=friday; party_size+=8 people; goal=confirm_booking. C5 goal=confirm_booking. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a caribbean restaurant in the centre of the city.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre..", "trace": "domain=restaurant; goal=search; area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Are there any caribbean restaurants in any other part of town?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Sure, a turkish restaurant in the moderate price range would be great.", "streaming_reasoning": "As more information arrives, cuisine: turkish; price: moderate..", "trace": "cuisine+=turkish; price+=moderate."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, book me The Anatolia for 8 people at 12:00 on Friday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 8; day: friday; party size: 8 people.", "trace": "goal=confirm_booking; time+=8, 12:00; day+=friday; party_size+=8 people; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes please try booking that Great!", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you so much for your help.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That will be all.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is turkish; price is moderate; party size is 8 people; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, confirm_booking; area=centre; food=turkish; price=moderate; party_size=8 people; when=friday, 8, 12:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002847", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want some welsh food Moderately priced please.\nChunk 2: I'd like a Chinese restaurant instead then I don't care.\nChunk 3: I would like their phone number, please.\nChunk 4: Is there any thing else i can help you with Thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=moderate. C2 goal=compare_alternative; cuisine+=chinese. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, compare_alternative, request_info; food=chinese; price=moderate; requested_info=phone.", "answer": "I can help with that and include the phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want some welsh food Moderately priced please.\nChunk 2: I'd like a Chinese restaurant instead then I don't care.\nChunk 3: I would like their phone number, please.\nChunk 4: Is there any thing else i can help you with Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=moderate. C2 goal=compare_alternative; cuisine+=chinese. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, compare_alternative, request_info; food=chinese; price=moderate; requested_info=phone.\n\nAnswer: I can help with that and include the phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want some welsh food Moderately priced please.\nChunk 2: I'd like a Chinese restaurant instead then I don't care.\nChunk 3: I would like their phone number, please.\nChunk 4: Is there any thing else i can help you with Thank you, goodbye.", "input_token_count": 46, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate. Next, the goal is compare alternative; cuisine: chinese. Next, the goal is request info; requested information: phone. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is request info. price: moderate.; cuisine: chinese.; requested information: phone.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; price+=moderate. C2 goal=compare_alternative; cuisine+=chinese. C3 goal=request_info; requested_info+=phone. C4 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want some welsh food Moderately priced please.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate..", "trace": "domain=restaurant; goal=search; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like a Chinese restaurant instead then I don't care.", "streaming_reasoning": "As more information arrives, the goal is compare alternative; cuisine: chinese..", "trace": "goal=compare_alternative; cuisine+=chinese."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like their phone number, please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is there any thing else i can help you with Thank you, goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is chinese; price is moderate; requested information is phone.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, compare_alternative, request_info; food=chinese; price=moderate; requested_info=phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002848", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a expensive restraint om cambridge in the centre.\nChunk 2: My husband's family will be with us for a birthday dinner, so how about Italian.\nChunk 3: They are from an italian family.\nChunk 4: Please book a table for 2 on Monday at 18:15.", "streaming_reasoning": "C1 goal=search; area+=centre; price+=expensive. C2 domain=restaurant; goal=recommendation; cuisine+=italian. C3 intent=context_update. C4 goal=booking; time+=2, 18:15; day+=monday.", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, booking; area=centre; food=italian; price=expensive; when=monday, 2, 18:15.", "answer": "Got it. I will use restaurant, centre, italian, expensive, monday, 2, 18:15 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a expensive restraint om cambridge in the centre.\nChunk 2: My husband's family will be with us for a birthday dinner, so how about Italian.\nChunk 3: They are from an italian family.\nChunk 4: Please book a table for 2 on Monday at 18:15."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre; price+=expensive. C2 domain=restaurant; goal=recommendation; cuisine+=italian. C3 intent=context_update. C4 goal=booking; time+=2, 18:15; day+=monday.\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, booking; area=centre; food=italian; price=expensive; when=monday, 2, 18:15.\n\nAnswer: Got it. I will use restaurant, centre, italian, expensive, monday, 2, 18:15 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a expensive restraint om cambridge in the centre.\nChunk 2: My husband's family will be with us for a birthday dinner, so how about Italian.\nChunk 3: They are from an italian family.\nChunk 4: Please book a table for 2 on Monday at 18:15.", "input_token_count": 50, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre; price: expensive. Next, the topic is restaurant; the goal is recommendation; cuisine: italian. Next, intent: context_update. Finally, the goal is booking; time: 2; day: monday. In summary, The overall topic is restaurant. the goal is booking. area: centre; price: expensive.; cuisine: italian.; intent: context_update.; time: 2; day: monday..", "trace": "C1 goal=search; area+=centre; price+=expensive. C2 domain=restaurant; goal=recommendation; cuisine+=italian. C3 intent=context_update. C4 goal=booking; time+=2, 18:15; day+=monday.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a expensive restraint om cambridge in the centre.", "streaming_reasoning": "Initially, the goal is search; area: centre; price: expensive..", "trace": "goal=search; area+=centre; price+=expensive."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "My husband's family will be with us for a birthday dinner, so how about Italian.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is recommendation; cuisine: italian..", "trace": "domain=restaurant; goal=recommendation; cuisine+=italian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "They are from an italian family.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please book a table for 2 on Monday at 18:15.", "streaming_reasoning": "Finally, the goal is booking; time: 2; day: monday..", "trace": "goal=booking; time+=2, 18:15; day+=monday."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is italian; price is expensive; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use restaurant, centre, italian, expensive, monday, 2, 18:15 and move the task forward.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, booking; area=centre; food=italian; price=expensive; when=monday, 2, 18:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002849", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also am looking to dine out.\nChunk 2: Something European, and expensive.\nChunk 3: Nearest the hotel will be fine, I also need a cab after the restaurant.\nChunk 4: I would like to go back to the hotel after eating.\nChunk 5: I want to find a restaurant.\nChunk 6: It is for 4 people.\nChunk 7: The time is sunday, 4, 15:45.\nChunk 8: Please make a booking.\nChunk 9: I also need a taxi to commute between both places, and could you make sure it arrives at the restaurant by the booked time?\nChunk 10: That is all Thank you!\nChunk 11: You were so helpful!", "streaming_reasoning": "C1 destination+=dine out. C2 cuisine+=european; price+=expensive. C3 domain=taxi; goal=search; hotel_type+=hotel. C4 destination+=go back to the hotel after eating. C5 destination+=find a restaurant. C6 party_size+=4 people. C7 time+=4, 15:45; day+=sunday. C8 goal=booking. C9 destination+=commute between both places. C10 [SKIP: closing_only]. C11 intent=context_update.", "deep_reasoning": "Need domain=restaurant, hotel, taxi; goal=search, booking; food=european; price=expensive; party_size=4 people; destination=dine out, go back to the hotel after eating, find a restaurant, commute between both places; when=sunday, 4, 15:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also am looking to dine out.\nChunk 2: Something European, and expensive.\nChunk 3: Nearest the hotel will be fine, I also need a cab after the restaurant.\nChunk 4: I would like to go back to the hotel after eating.\nChunk 5: I want to find a restaurant.\nChunk 6: It is for 4 people.\nChunk 7: The time is sunday, 4, 15:45.\nChunk 8: Please make a booking.\nChunk 9: I also need a taxi to commute between both places, and could you make sure it arrives at the restaurant by the booked time?\nChunk 10: That is all Thank you!\nChunk 11: You were so helpful!"}, {"role": "assistant", "content": "Streaming reasoning: C1 destination+=dine out. C2 cuisine+=european; price+=expensive. C3 domain=taxi; goal=search; hotel_type+=hotel. C4 destination+=go back to the hotel after eating. C5 destination+=find a restaurant. C6 party_size+=4 people. C7 time+=4, 15:45; day+=sunday. C8 goal=booking. C9 destination+=commute between both places. C10 [SKIP: closing_only]. C11 intent=context_update.\n\nDeep reasoning: Need domain=restaurant, hotel, taxi; goal=search, booking; food=european; price=expensive; party_size=4 people; destination=dine out, go back to the hotel after eating, find a restaurant, commute between both places; when=sunday, 4, 15:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also am looking to dine out.\nChunk 2: Something European, and expensive.\nChunk 3: Nearest the hotel will be fine, I also need a cab after the restaurant.\nChunk 4: I would like to go back to the hotel after eating.\nChunk 5: I want to find a restaurant.\nChunk 6: It is for 4 people.\nChunk 7: The time is sunday, 4, 15:45.\nChunk 8: Please make a booking.\nChunk 9: I also need a taxi to commute between both places, and could you make sure it arrives at the restaurant by the booked time?\nChunk 10: That is all Thank you!\nChunk 11: You were so helpful!", "input_token_count": 113, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, destination: dine out. Next, cuisine: european; price: expensive. Next, the topic is taxi; the goal is search; hotel type: hotel. Next, destination: go back to the hotel after eating. Next, destination: find a restaurant. Next, party size: 4 people. Next, time: 4; day: sunday. Next, the goal is booking. Next, destination: commute between both places. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is booking.. destination: dine out., go back to the hotel after eating., find a restaurant., commute between both places.; cuisine: european; price: expensive.; hotel type: hotel.; party size: 4 people.; time: 4; day: sunday.; intent: context_update..", "trace": "C1 destination+=dine out. C2 cuisine+=european; price+=expensive. C3 domain=taxi; goal=search; hotel_type+=hotel. C4 destination+=go back to the hotel after eating. C5 destination+=find a restaurant. C6 party_size+=4 people. C7 time+=4, 15:45; day+=sunday. C8 goal=booking. C9 destination+=commute between both places. C10 [SKIP: closing_only]. C11 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also am looking to dine out.", "streaming_reasoning": "Initially, destination: dine out..", "trace": "destination+=dine out."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Something European, and expensive.", "streaming_reasoning": "As more information arrives, cuisine: european; price: expensive..", "trace": "cuisine+=european; price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Nearest the hotel will be fine, I also need a cab after the restaurant.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is search; hotel type: hotel..", "trace": "domain=taxi; goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like to go back to the hotel after eating.", "streaming_reasoning": "As more information arrives, destination: go back to the hotel after eating..", "trace": "destination+=go back to the hotel after eating."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, destination: find a restaurant..", "trace": "destination+=find a restaurant."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It is for 4 people.", "streaming_reasoning": "As more information arrives, party size: 4 people..", "trace": "party_size+=4 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is sunday, 4, 15:45.", "streaming_reasoning": "As more information arrives, time: 4; day: sunday..", "trace": "time+=4, 15:45; day+=sunday."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need a taxi to commute between both places, and could you make sure it arrives at the restaurant by the booked time?", "streaming_reasoning": "As more information arrives, destination: commute between both places..", "trace": "destination+=commute between both places."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That is all Thank you!", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "You were so helpful!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is european; price is expensive; party size is 4 people; destination is dine out; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel, taxi; goal=search, booking; food=european; price=expensive; party_size=4 people; destination=dine out, go back to the hotel after eating, find a restaurant, commute between both places; when=sunday, 4, 15:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002850", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with train.\nChunk 2: The time is tuesday.\nChunk 3: I need to leave by 17:30.\nChunk 4: No, but can I get a postcode and the entrance fee?\nChunk 5: I'm sorry my brain got jumbled there, no to booking a seat on the train.\nChunk 6: I do need to find some architecture to look at while visiting.\nChunk 7: That sounds amazing, what postcode are they in Thank you!\nChunk 8: I think that is all I need today.", "streaming_reasoning": "C1 domain=train; goal=search. C2 day+=tuesday. C3 time+=17:30; destination+=leave by 17:30. C4 goal=request_info; requested_info+=postcode, entrance_fee. C5 goal=booking. C6 destination+=find some architecture to look at while v. C7 intent=context_update. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info, booking; destination=leave by 17:30, find some architecture to look at while v; requested_info=postcode, entrance_fee; when=tuesday, 17:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need help with train.\nChunk 2: The time is tuesday.\nChunk 3: I need to leave by 17:30.\nChunk 4: No, but can I get a postcode and the entrance fee?\nChunk 5: I'm sorry my brain got jumbled there, no to booking a seat on the train.\nChunk 6: I do need to find some architecture to look at while visiting.\nChunk 7: That sounds amazing, what postcode are they in Thank you!\nChunk 8: I think that is all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 day+=tuesday. C3 time+=17:30; destination+=leave by 17:30. C4 goal=request_info; requested_info+=postcode, entrance_fee. C5 goal=booking. C6 destination+=find some architecture to look at while v. C7 intent=context_update. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking; destination=leave by 17:30, find some architecture to look at while v; requested_info=postcode, entrance_fee; when=tuesday, 17:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with train.\nChunk 2: The time is tuesday.\nChunk 3: I need to leave by 17:30.\nChunk 4: No, but can I get a postcode and the entrance fee?\nChunk 5: I'm sorry my brain got jumbled there, no to booking a seat on the train.\nChunk 6: I do need to find some architecture to look at while visiting.\nChunk 7: That sounds amazing, what postcode are they in Thank you!\nChunk 8: I think that is all I need today.", "input_token_count": 88, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, day: tuesday. Next, time: 17:30; destination: leave by 17:30. Next, the goal is request info; requested information: postcode. Next, the goal is booking. Next, destination: find some architecture to look at while v. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is booking.. day: tuesday.; time: 17:30; destination: leave by 17:30., find some architecture to look at while v.; requested information: postcode; intent: context_update..", "trace": "C1 domain=train; goal=search. C2 day+=tuesday. C3 time+=17:30; destination+=leave by 17:30. C4 goal=request_info; requested_info+=postcode, entrance_fee. C5 goal=booking. C6 destination+=find some architecture to look at while v. C7 intent=context_update. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need help with train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is tuesday.", "streaming_reasoning": "As more information arrives, day: tuesday..", "trace": "day+=tuesday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to leave by 17:30.", "streaming_reasoning": "As more information arrives, time: 17:30; destination: leave by 17:30..", "trace": "time+=17:30; destination+=leave by 17:30."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, but can I get a postcode and the entrance fee?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode.", "trace": "goal=request_info; requested_info+=postcode, entrance_fee."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm sorry my brain got jumbled there, no to booking a seat on the train.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I do need to find some architecture to look at while visiting.", "streaming_reasoning": "As more information arrives, destination: find some architecture to look at while v..", "trace": "destination+=find some architecture to look at while v."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That sounds amazing, what postcode are they in Thank you!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I think that is all I need today.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is leave by 17:30; requested information is postcode; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking; destination=leave by 17:30, find some architecture to look at while v; requested_info=postcode, entrance_fee; when=tuesday, 17:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002851", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a restaurant in a moderate price range.\nChunk 2: It should be in the centre part of town.\nChunk 3: The time is friday, 19:30, 2.\nChunk 4: Please make a booking.\nChunk 5: Why don't you choose one for me as long as I can get the tables booked.\nChunk 6: Just please book a table anywhere for 2 on friday for 19:30 please.\nChunk 7: And I'll need a reference number.\nChunk 8: No, thank you Good bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=moderate. C2 area+=centre. C3 time+=19:30, 2; day+=friday. C4 goal=booking. C5 goal=request_info. C6 intent=context_update. C7 requested_info+=reference_number. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, request_info; area=centre; price=moderate; requested_info=reference_number; when=friday, 19:30, 2; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a restaurant in a moderate price range.\nChunk 2: It should be in the centre part of town.\nChunk 3: The time is friday, 19:30, 2.\nChunk 4: Please make a booking.\nChunk 5: Why don't you choose one for me as long as I can get the tables booked.\nChunk 6: Just please book a table anywhere for 2 on friday for 19:30 please.\nChunk 7: And I'll need a reference number.\nChunk 8: No, thank you Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=moderate. C2 area+=centre. C3 time+=19:30, 2; day+=friday. C4 goal=booking. C5 goal=request_info. C6 intent=context_update. C7 requested_info+=reference_number. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, request_info; area=centre; price=moderate; requested_info=reference_number; when=friday, 19:30, 2; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a restaurant in a moderate price range.\nChunk 2: It should be in the centre part of town.\nChunk 3: The time is friday, 19:30, 2.\nChunk 4: Please make a booking.\nChunk 5: Why don't you choose one for me as long as I can get the tables booked.\nChunk 6: Just please book a table anywhere for 2 on friday for 19:30 please.\nChunk 7: And I'll need a reference number.\nChunk 8: No, thank you Good bye.", "input_token_count": 87, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate. Next, area: centre. Next, time: 19:30; day: friday. Next, the goal is booking. Next, the goal is request info. Next, intent: context_update. Finally, requested information: reference_number.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info.. price: moderate.; area: centre.; time: 19:30; day: friday.; intent: context_update.; requested information: reference_number..", "trace": "C1 domain=restaurant; goal=search; price+=moderate. C2 area+=centre. C3 time+=19:30, 2; day+=friday. C4 goal=booking. C5 goal=request_info. C6 intent=context_update. C7 requested_info+=reference_number. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a restaurant in a moderate price range.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: moderate..", "trace": "domain=restaurant; goal=search; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is friday, 19:30, 2.", "streaming_reasoning": "As more information arrives, time: 19:30; day: friday..", "trace": "time+=19:30, 2; day+=friday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Why don't you choose one for me as long as I can get the tables booked.", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Just please book a table anywhere for 2 on friday for 19:30 please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "And I'll need a reference number.", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, thank you Good bye.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is moderate; requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, request_info; area=centre; price=moderate; requested_info=reference_number; when=friday, 19:30, 2; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002852", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hey, I am looking for a train that leaves leicester to cambridge, where is it?\nChunk 2: I would like to leave on Thursday and arrive by 18:15.\nChunk 3: I don't need to book now.\nChunk 4: What is the total travel time for that train Yes you can.\nChunk 5: I'd like to see a few things while I'm in town so find me something nice to check out on the west side.\nChunk 6: Any attraction you recommend will be great.\nChunk 7: I just need the postcode and entrance fee Great, thanks!\nChunk 8: That'll be all that I need for today!", "streaming_reasoning": "C1 domain=train; goal=search; destination+=cambridge. C2 time+=18:15; day+=thursday; destination+=leave on thursday and arrive by 18:15. C3 goal=booking. C4 goal=request_info; requested_info+=travel_time; goal=confirm_booking. C5 area+=west. C6 domain=attraction; goal=recommendation. C7 requested_info+=postcode, entrance_fee. C8 day+=today.", "deep_reasoning": "Need domain=train, attraction; goal=search, booking, request_info, recommendation; area=west; destination=cambridge, leave on thursday and arrive by 18:15; requested_info=travel_time, postcode, entrance_fee; when=thursday, today, 18:15.", "answer": "I can help with that and include the travel time, postcode, entrance fee once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hey, I am looking for a train that leaves leicester to cambridge, where is it?\nChunk 2: I would like to leave on Thursday and arrive by 18:15.\nChunk 3: I don't need to book now.\nChunk 4: What is the total travel time for that train Yes you can.\nChunk 5: I'd like to see a few things while I'm in town so find me something nice to check out on the west side.\nChunk 6: Any attraction you recommend will be great.\nChunk 7: I just need the postcode and entrance fee Great, thanks!\nChunk 8: That'll be all that I need for today!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=cambridge. C2 time+=18:15; day+=thursday; destination+=leave on thursday and arrive by 18:15. C3 goal=booking. C4 goal=request_info; requested_info+=travel_time; goal=confirm_booking. C5 area+=west. C6 domain=attraction; goal=recommendation. C7 requested_info+=postcode, entrance_fee. C8 day+=today.\n\nDeep reasoning: Need domain=train, attraction; goal=search, booking, request_info, recommendation; area=west; destination=cambridge, leave on thursday and arrive by 18:15; requested_info=travel_time, postcode, entrance_fee; when=thursday, today, 18:15.\n\nAnswer: I can help with that and include the travel time, postcode, entrance fee once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hey, I am looking for a train that leaves leicester to cambridge, where is it?\nChunk 2: I would like to leave on Thursday and arrive by 18:15.\nChunk 3: I don't need to book now.\nChunk 4: What is the total travel time for that train Yes you can.\nChunk 5: I'd like to see a few things while I'm in town so find me something nice to check out on the west side.\nChunk 6: Any attraction you recommend will be great.\nChunk 7: I just need the postcode and entrance fee Great, thanks!\nChunk 8: That'll be all that I need for today!", "input_token_count": 109, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge. Next, time: 18:15; day: thursday; destination: leave on thursday and arrive by 18:15. Next, the goal is booking. Next, the goal is confirm booking.; requested information: travel_time. Next, area: west. Next, the topic is attraction; the goal is recommendation. Next, requested information: postcode. Finally, day: today. In summary, The overall topic is attraction. the goal is recommendation.. destination: cambridge., leave on thursday and arrive by 18:15.; time: 18:15; day: thursday, today.; requested information: travel_time, postcode; area: west..", "trace": "C1 domain=train; goal=search; destination+=cambridge. C2 time+=18:15; day+=thursday; destination+=leave on thursday and arrive by 18:15. C3 goal=booking. C4 goal=request_info; requested_info+=travel_time; goal=confirm_booking. C5 area+=west. C6 domain=attraction; goal=recommendation. C7 requested_info+=postcode, entrance_fee. C8 day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hey, I am looking for a train that leaves leicester to cambridge, where is it?", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge..", "trace": "domain=train; goal=search; destination+=cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to leave on Thursday and arrive by 18:15.", "streaming_reasoning": "As more information arrives, time: 18:15; day: thursday; destination: leave on thursday and arrive by 18:15..", "trace": "time+=18:15; day+=thursday; destination+=leave on thursday and arrive by 18:15."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I don't need to book now.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is the total travel time for that train Yes you can.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; requested information: travel_time.", "trace": "goal=request_info; requested_info+=travel_time; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'd like to see a few things while I'm in town so find me something nice to check out on the west side.", "streaming_reasoning": "As more information arrives, area: west..", "trace": "area+=west."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Any attraction you recommend will be great.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is recommendation..", "trace": "domain=attraction; goal=recommendation."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I just need the postcode and entrance fee Great, thanks!", "streaming_reasoning": "As more information arrives, requested information: postcode.", "trace": "requested_info+=postcode, entrance_fee."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That'll be all that I need for today!", "streaming_reasoning": "Finally, day: today..", "trace": "day+=today."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is west; destination is cambridge; requested information is travel_time; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the travel time, postcode, entrance fee once I find the matching option.", "deep_reasoning_trace": "Need domain=train, attraction; goal=search, booking, request_info, recommendation; area=west; destination=cambridge, leave on thursday and arrive by 18:15; requested_info=travel_time, postcode, entrance_fee; when=thursday, today, 18:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002853", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No reservation but can I get the price range, the post code and the address?\nChunk 2: Yes, I am also looking for a 4 star hotel.\nChunk 3: i would like it near the centre.\nChunk 4: Let's go for the guesthouse please.\nChunk 5: Can you tell me if it has free parking?\nChunk 6: Please give me their price range and postcode.", "streaming_reasoning": "C1 goal=request_info; requested_info+=address, postcode, price. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=4 stars; goal=confirm_booking. C3 area+=centre. C4 hotel_type+=guesthouse. C5 amenities+=parking, free parking. C6 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=booking, request_info, search; area=centre; stars=4 stars; amenities=parking, free parking; requested_info=address, postcode, price.", "answer": "I can help with that and include the address, postcode, price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No reservation but can I get the price range, the post code and the address?\nChunk 2: Yes, I am also looking for a 4 star hotel.\nChunk 3: i would like it near the centre.\nChunk 4: Let's go for the guesthouse please.\nChunk 5: Can you tell me if it has free parking?\nChunk 6: Please give me their price range and postcode."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address, postcode, price. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=4 stars; goal=confirm_booking. C3 area+=centre. C4 hotel_type+=guesthouse. C5 amenities+=parking, free parking. C6 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=booking, request_info, search; area=centre; stars=4 stars; amenities=parking, free parking; requested_info=address, postcode, price.\n\nAnswer: I can help with that and include the address, postcode, price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No reservation but can I get the price range, the post code and the address?\nChunk 2: Yes, I am also looking for a 4 star hotel.\nChunk 3: i would like it near the centre.\nChunk 4: Let's go for the guesthouse please.\nChunk 5: Can you tell me if it has free parking?\nChunk 6: Please give me their price range and postcode.", "input_token_count": 67, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the topic is hotel; the goal is confirm booking.; hotel type: hotel; star rating: 4 stars. Next, area: centre. Next, hotel type: guesthouse. Next, amenities: parking. Finally, intent: context_update. In summary, The overall topic is hotel. the goal is confirm booking.. requested information: address; hotel type: hotel, guesthouse.; star rating: 4 stars; area: centre.; amenities: parking; intent: context_update..", "trace": "C1 goal=request_info; requested_info+=address, postcode, price. C2 domain=hotel; goal=search; hotel_type+=hotel; stars+=4 stars; goal=confirm_booking. C3 area+=centre. C4 hotel_type+=guesthouse. C5 amenities+=parking, free parking. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No reservation but can I get the price range, the post code and the address?", "streaming_reasoning": "Initially, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode, price."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I am also looking for a 4 star hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is confirm booking.; hotel type: hotel; star rating: 4 stars.", "trace": "domain=hotel; goal=search; hotel_type+=hotel; stars+=4 stars; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "i would like it near the centre.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Let's go for the guesthouse please.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse..", "trace": "hotel_type+=guesthouse."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you tell me if it has free parking?", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please give me their price range and postcode.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: area is centre; star rating is 4 stars; amenities is parking; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, postcode, price once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, request_info, search; area=centre; stars=4 stars; amenities=parking, free parking; requested_info=address, postcode, price."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002854", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: The time is 6:45.\nChunk 3: I also need the phone.\nChunk 4: Can you book reservations for the restaurant at 7:30.\nChunk 5: 2 people on a Monday I think please No thank you.\nChunk 6: Yes, I wasn't planning to book but since I have I suppose I'll take that number.\nChunk 7: That will be all for today - thank you for your help!\nChunk 8: Thank you for your help!", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 time+=6:45. C3 goal=request_info; requested_info+=phone. C4 domain=restaurant; goal=booking; time+=7:30. C5 day+=monday; party_size+=2 people. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, request_info, booking, confirm_booking; party_size=2 people; destination=find a hotel; requested_info=phone; when=monday, 6:45, 7:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a hotel.\nChunk 2: The time is 6:45.\nChunk 3: I also need the phone.\nChunk 4: Can you book reservations for the restaurant at 7:30.\nChunk 5: 2 people on a Monday I think please No thank you.\nChunk 6: Yes, I wasn't planning to book but since I have I suppose I'll take that number.\nChunk 7: That will be all for today - thank you for your help!\nChunk 8: Thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 time+=6:45. C3 goal=request_info; requested_info+=phone. C4 domain=restaurant; goal=booking; time+=7:30. C5 day+=monday; party_size+=2 people. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, request_info, booking, confirm_booking; party_size=2 people; destination=find a hotel; requested_info=phone; when=monday, 6:45, 7:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hotel.\nChunk 2: The time is 6:45.\nChunk 3: I also need the phone.\nChunk 4: Can you book reservations for the restaurant at 7:30.\nChunk 5: 2 people on a Monday I think please No thank you.\nChunk 6: Yes, I wasn't planning to book but since I have I suppose I'll take that number.\nChunk 7: That will be all for today - thank you for your help!\nChunk 8: Thank you for your help!", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel. Next, time: 6:45. Next, the goal is request info; requested information: phone. Next, the topic is restaurant; the goal is booking; time: 7:30. Next, day: monday; party size: 2 people. Finally, the goal is confirm booking.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is confirm booking.. hotel type: hotel; destination: find a hotel.; time: 6:45., 7:30.; requested information: phone.; day: monday; party size: 2 people..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel. C2 time+=6:45. C3 goal=request_info; requested_info+=phone. C4 domain=restaurant; goal=booking; time+=7:30. C5 day+=monday; party_size+=2 people. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is 6:45.", "streaming_reasoning": "As more information arrives, time: 6:45..", "trace": "time+=6:45."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you book reservations for the restaurant at 7:30.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is booking; time: 7:30..", "trace": "domain=restaurant; goal=booking; time+=7:30."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "2 people on a Monday I think please No thank you.", "streaming_reasoning": "As more information arrives, day: monday; party size: 2 people..", "trace": "day+=monday; party_size+=2 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, I wasn't planning to book but since I have I suppose I'll take that number.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That will be all for today - thank you for your help!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for your help!", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 2 people; destination is find a hotel; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, request_info, booking, confirm_booking; party_size=2 people; destination=find a hotel; requested_info=phone; when=monday, 6:45, 7:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002855", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you give me information on a particular attraction, called kambar?\nChunk 2: Great, could you also provide me with the phone number?\nChunk 3: I want to also eat Indian food.\nChunk 4: What expensive restaurant do you have Great.\nChunk 5: Could you make a reservation for 7 people at 17:30 on Monday?\nChunk 6: No.\nChunk 7: That will be all.\nChunk 8: thank you for helping.", "streaming_reasoning": "C1 domain=attraction; goal=request_info. C2 requested_info+=phone. C3 domain=restaurant; goal=search; cuisine+=indian; destination+=also eat indian food. C4 price+=expensive. C5 goal=booking; time+=7, 17:30; day+=monday; party_size+=7 people. C6 goal=modify_constraint. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, restaurant; goal=request_info, search, booking; food=indian; price=expensive; party_size=7 people; destination=also eat indian food; requested_info=phone; when=monday, 7, 17:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you give me information on a particular attraction, called kambar?\nChunk 2: Great, could you also provide me with the phone number?\nChunk 3: I want to also eat Indian food.\nChunk 4: What expensive restaurant do you have Great.\nChunk 5: Could you make a reservation for 7 people at 17:30 on Monday?\nChunk 6: No.\nChunk 7: That will be all.\nChunk 8: thank you for helping."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=request_info. C2 requested_info+=phone. C3 domain=restaurant; goal=search; cuisine+=indian; destination+=also eat indian food. C4 price+=expensive. C5 goal=booking; time+=7, 17:30; day+=monday; party_size+=7 people. C6 goal=modify_constraint. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, restaurant; goal=request_info, search, booking; food=indian; price=expensive; party_size=7 people; destination=also eat indian food; requested_info=phone; when=monday, 7, 17:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you give me information on a particular attraction, called kambar?\nChunk 2: Great, could you also provide me with the phone number?\nChunk 3: I want to also eat Indian food.\nChunk 4: What expensive restaurant do you have Great.\nChunk 5: Could you make a reservation for 7 people at 17:30 on Monday?\nChunk 6: No.\nChunk 7: That will be all.\nChunk 8: thank you for helping.", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is request info. Next, requested information: phone. Next, the topic is restaurant; the goal is search; cuisine: indian; destination: also eat indian food. Next, price: expensive. Next, the goal is booking; time: 7; day: monday; party size: 7 people. Finally, the goal is modify constraint.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is modify constraint.. requested information: phone.; cuisine: indian; destination: also eat indian food.; price: expensive.; time: 7; day: monday; party size: 7 people..", "trace": "C1 domain=attraction; goal=request_info. C2 requested_info+=phone. C3 domain=restaurant; goal=search; cuisine+=indian; destination+=also eat indian food. C4 price+=expensive. C5 goal=booking; time+=7, 17:30; day+=monday; party_size+=7 people. C6 goal=modify_constraint. C7 [SKIP: closing_only]. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you give me information on a particular attraction, called kambar?", "streaming_reasoning": "Initially, the topic is attraction; the goal is request info..", "trace": "domain=attraction; goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Great, could you also provide me with the phone number?", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to also eat Indian food.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; cuisine: indian; destination: also eat indian food..", "trace": "domain=restaurant; goal=search; cuisine+=indian; destination+=also eat indian food."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What expensive restaurant do you have Great.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Could you make a reservation for 7 people at 17:30 on Monday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 7; day: monday; party size: 7 people..", "trace": "goal=booking; time+=7, 17:30; day+=monday; party_size+=7 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That will be all.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "thank you for helping.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: cuisine is indian; price is expensive; party size is 7 people; destination is also eat indian food; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=request_info, search, booking; food=indian; price=expensive; party_size=7 people; destination=also eat indian food; requested_info=phone; when=monday, 7, 17:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002856", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i'm also looking for a place in town in the centre.\nChunk 2: I'm looking for an entertainment place.\nChunk 3: centre and should be in the type of entertainment closeby as well Entertainment venues please.\nChunk 4: If they are not available then architecture venues.\nChunk 5: Can you please recommend one and provide me with their post code and phone number?\nChunk 6: Thank you for all your help.\nChunk 7: You have answered all my questions today Goodbye.", "streaming_reasoning": "C1 goal=search; area+=centre. C2 intent=context_update. C3 intent=context_update. C4 goal=modify_constraint. C5 goal=request_info; requested_info+=phone, postcode. C6 [SKIP: thanks_only]. C7 day+=today.", "deep_reasoning": "Need goal=search, recommendation, request_info; area=centre; requested_info=phone, postcode; when=today; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i'm also looking for a place in town in the centre.\nChunk 2: I'm looking for an entertainment place.\nChunk 3: centre and should be in the type of entertainment closeby as well Entertainment venues please.\nChunk 4: If they are not available then architecture venues.\nChunk 5: Can you please recommend one and provide me with their post code and phone number?\nChunk 6: Thank you for all your help.\nChunk 7: You have answered all my questions today Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre. C2 intent=context_update. C3 intent=context_update. C4 goal=modify_constraint. C5 goal=request_info; requested_info+=phone, postcode. C6 [SKIP: thanks_only]. C7 day+=today.\n\nDeep reasoning: Need goal=search, recommendation, request_info; area=centre; requested_info=phone, postcode; when=today; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i'm also looking for a place in town in the centre.\nChunk 2: I'm looking for an entertainment place.\nChunk 3: centre and should be in the type of entertainment closeby as well Entertainment venues please.\nChunk 4: If they are not available then architecture venues.\nChunk 5: Can you please recommend one and provide me with their post code and phone number?\nChunk 6: Thank you for all your help.\nChunk 7: You have answered all my questions today Goodbye.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre. Next, intent: context_update. Next, intent: context_update. Next, the goal is modify constraint. Next, the goal is request info; requested information: phone. Finally, day: today.  Some chunks were skipped because they contained thanks_only. In summary, the goal is request info. area: centre.; intent: context_update.; requested information: phone; day: today..", "trace": "C1 goal=search; area+=centre. C2 intent=context_update. C3 intent=context_update. C4 goal=modify_constraint. C5 goal=request_info; requested_info+=phone, postcode. C6 [SKIP: thanks_only]. C7 day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i'm also looking for a place in town in the centre.", "streaming_reasoning": "Initially, the goal is search; area: centre..", "trace": "goal=search; area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm looking for an entertainment place.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "centre and should be in the type of entertainment closeby as well Entertainment venues please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "If they are not available then architecture venues.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you please recommend one and provide me with their post code and phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "You have answered all my questions today Goodbye.", "streaming_reasoning": "Finally, day: today..", "trace": "day+=today."}]}, "output": {"deep_reasoning": "Need goal=search, recommendation, request_info; area=centre; requested_info=phone, postcode; when=today; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002857", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find a restaurant?\nChunk 2: I'm actually looking for a particular restaurant recommended to me by the name of royal spice.\nChunk 3: May I ask what type of food does Royal Spice serve?\nChunk 4: I'll also need the postcode and area please Great, thanks.\nChunk 5: That is all I need today.", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 destination+=me by the name of royal spice. C3 goal=request_info. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; destination=me by the name of royal spice; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you help me find a restaurant?\nChunk 2: I'm actually looking for a particular restaurant recommended to me by the name of royal spice.\nChunk 3: May I ask what type of food does Royal Spice serve?\nChunk 4: I'll also need the postcode and area please Great, thanks.\nChunk 5: That is all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 destination+=me by the name of royal spice. C3 goal=request_info. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; destination=me by the name of royal spice; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find a restaurant?\nChunk 2: I'm actually looking for a particular restaurant recommended to me by the name of royal spice.\nChunk 3: May I ask what type of food does Royal Spice serve?\nChunk 4: I'll also need the postcode and area please Great, thanks.\nChunk 5: That is all I need today.", "input_token_count": 60, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, destination: me by the name of royal spice. Next, the goal is request info. Finally, the goal is request info; requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. destination: me by the name of royal spice.; requested information: postcode..", "trace": "C1 domain=restaurant; goal=search. C2 destination+=me by the name of royal spice. C3 goal=request_info. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you help me find a restaurant?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm actually looking for a particular restaurant recommended to me by the name of royal spice.", "streaming_reasoning": "As more information arrives, destination: me by the name of royal spice..", "trace": "destination+=me by the name of royal spice."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "May I ask what type of food does Royal Spice serve?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll also need the postcode and area please Great, thanks.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That is all I need today.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: destination is me by the name of royal spice; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; destination=me by the name of royal spice; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001904", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I receive my blood test result yesterday and I am so grateful that I don't any immune system diseases.\nChunk 2: I receive my blood test result yesterday and I am so grateful that I don't any immune system diseases.\" That is great.\nChunk 3: The doctor made worry a lot.\nChunk 4: it seems that all the symptoms that I have matches an immune system disease.\nChunk 5: I am happy it is not.", "streaming_reasoning": "C1 need=validation. C2 [SKIP: repeated_information]. C3 emotion=worried; need=reassurance. C4 support_signal=received. C5 emotion=happy; event=it is not; need=celebration.", "deep_reasoning": "User feels happy because it is not and needs celebration.", "answer": "That is worth celebrating, especially because it is not. Take a moment to enjoy it and share the good news with someone who will be happy for you.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I receive my blood test result yesterday and I am so grateful that I don't any immune system diseases.\nChunk 2: I receive my blood test result yesterday and I am so grateful that I don't any immune system diseases.\" That is great.\nChunk 3: The doctor made worry a lot.\nChunk 4: it seems that all the symptoms that I have matches an immune system disease.\nChunk 5: I am happy it is not."}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 [SKIP: repeated_information]. C3 emotion=worried; need=reassurance. C4 support_signal=received. C5 emotion=happy; event=it is not; need=celebration.\n\nDeep reasoning: User feels happy because it is not and needs celebration.\n\nAnswer: That is worth celebrating, especially because it is not. Take a moment to enjoy it and share the good news with someone who will be happy for you."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I receive my blood test result yesterday and I am so grateful that I don't any immune system diseases.\nChunk 2: I receive my blood test result yesterday and I am so grateful that I don't any immune system diseases.\" That is great.\nChunk 3: The doctor made worry a lot.\nChunk 4: it seems that all the symptoms that I have matches an immune system disease.\nChunk 5: I am happy it is not.", "input_token_count": 77, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user expresses worried; the user needs reassurance. Next, the user signals support or acknowledgment. Finally, the user expresses happy; the user needs celebration.; event: it is not.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 need=validation. C2 [SKIP: repeated_information]. C3 emotion=worried; need=reassurance. C4 support_signal=received. C5 emotion=happy; event=it is not; need=celebration.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I receive my blood test result yesterday and I am so grateful that I don't any immune system diseases.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I receive my blood test result yesterday and I am so grateful that I don't any immune system diseases.\" That is great.", "streaming_reasoning": "The content at C2 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The doctor made worry a lot.", "streaming_reasoning": "As more information arrives, the user expresses worried; the user needs reassurance..", "trace": "emotion=worried; need=reassurance."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "it seems that all the symptoms that I have matches an immune system disease.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I am happy it is not.", "streaming_reasoning": "Finally, the user expresses happy; the user needs celebration.; event: it is not.", "trace": "emotion=happy; event=it is not; need=celebration."}]}, "output": {"deep_reasoning": "User feels happy because it is not and needs celebration.", "answer": "That is worth celebrating, especially because it is not. Take a moment to enjoy it and share the good news with someone who will be happy for you."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003552", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, Jack.Happy birthday My birthday?\nChunk 2: I forgot it, Thank you for remembering my birthday.\nChunk 3: I'd like to offer you my congratulations on your birthday and best wishes for your future happiness, good health and continued success.\nChunk 4: I've asked the Fairy Flowers to send you a bunch of flowers.\nChunk 5: I hope you'll like them.\nChunk 6: Thanks a lot I'm so touched.\nChunk 7: Now let me sing \" Happy birthday \" for you.", "streaming_reasoning": "C1 question=true. C2 casual_comment=forgot, thank. C3 preference=true. C4 casual_comment=i've, asked. C5 preference=true. C6 [SKIP: thanks_only]. C7 casual_comment=now, let.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, Jack.Happy birthday My birthday?\nChunk 2: I forgot it, Thank you for remembering my birthday.\nChunk 3: I'd like to offer you my congratulations on your birthday and best wishes for your future happiness, good health and continued success.\nChunk 4: I've asked the Fairy Flowers to send you a bunch of flowers.\nChunk 5: I hope you'll like them.\nChunk 6: Thanks a lot I'm so touched.\nChunk 7: Now let me sing \" Happy birthday \" for you."}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 casual_comment=forgot, thank. C3 preference=true. C4 casual_comment=i've, asked. C5 preference=true. C6 [SKIP: thanks_only]. C7 casual_comment=now, let.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, Jack.Happy birthday My birthday?\nChunk 2: I forgot it, Thank you for remembering my birthday.\nChunk 3: I'd like to offer you my congratulations on your birthday and best wishes for your future happiness, good health and continued success.\nChunk 4: I've asked the Fairy Flowers to send you a bunch of flowers.\nChunk 5: I hope you'll like them.\nChunk 6: Thanks a lot I'm so touched.\nChunk 7: Now let me sing \" Happy birthday \" for you.", "input_token_count": 82, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on forgot. Next, preference: true. Next, the user comments on i've. Next, preference: true. Finally, the user comments on now.  Some chunks were skipped because they contained thanks_only. In summary, preference: true..", "trace": "C1 question=true. C2 casual_comment=forgot, thank. C3 preference=true. C4 casual_comment=i've, asked. C5 preference=true. C6 [SKIP: thanks_only]. C7 casual_comment=now, let.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, Jack.Happy birthday My birthday?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I forgot it, Thank you for remembering my birthday.", "streaming_reasoning": "As more information arrives, the user comments on forgot.", "trace": "casual_comment=forgot, thank."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'd like to offer you my congratulations on your birthday and best wishes for your future happiness, good health and continued success.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I've asked the Fairy Flowers to send you a bunch of flowers.", "streaming_reasoning": "As more information arrives, the user comments on i've.", "trace": "casual_comment=i've, asked."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I hope you'll like them.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks a lot I'm so touched.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Now let me sing \" Happy birthday \" for you.", "streaming_reasoning": "Finally, the user comments on now.", "trace": "casual_comment=now, let."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002859", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please, can I have the address?\nChunk 2: Are there any moderately priced restaurants near the botanic gardens?\nChunk 3: I want to find a british restaurant.\nChunk 4: It should be in the centre part of town.\nChunk 5: I also need the price.\nChunk 6: I want to find a restaurant.\nChunk 7: Please make a booking.\nChunk 8: I would like to leave the restaurant by 14:45.\nChunk 9: Can I get a contact number for that taxi?", "streaming_reasoning": "C1 goal=request_info; requested_info+=address; acceptance=selected_option. C2 price+=moderate. C3 domain=restaurant; goal=search; cuisine+=british; destination+=find a british restaurant. C4 area+=centre. C5 requested_info+=price. C6 [SKIP: repeated_information]. C7 goal=booking. C8 time+=14:45; destination+=leave the restaurant by 14:45. C9 domain=taxi.", "deep_reasoning": "Need domain=restaurant, taxi; goal=request_info, search, booking; area=centre; food=british; price=moderate; destination=find a british restaurant, leave the restaurant by 14:45; requested_info=address, price; when=14:45.", "answer": "I can help with that and include the address, price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please, can I have the address?\nChunk 2: Are there any moderately priced restaurants near the botanic gardens?\nChunk 3: I want to find a british restaurant.\nChunk 4: It should be in the centre part of town.\nChunk 5: I also need the price.\nChunk 6: I want to find a restaurant.\nChunk 7: Please make a booking.\nChunk 8: I would like to leave the restaurant by 14:45.\nChunk 9: Can I get a contact number for that taxi?"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address; acceptance=selected_option. C2 price+=moderate. C3 domain=restaurant; goal=search; cuisine+=british; destination+=find a british restaurant. C4 area+=centre. C5 requested_info+=price. C6 [SKIP: repeated_information]. C7 goal=booking. C8 time+=14:45; destination+=leave the restaurant by 14:45. C9 domain=taxi.\n\nDeep reasoning: Need domain=restaurant, taxi; goal=request_info, search, booking; area=centre; food=british; price=moderate; destination=find a british restaurant, leave the restaurant by 14:45; requested_info=address, price; when=14:45.\n\nAnswer: I can help with that and include the address, price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please, can I have the address?\nChunk 2: Are there any moderately priced restaurants near the botanic gardens?\nChunk 3: I want to find a british restaurant.\nChunk 4: It should be in the centre part of town.\nChunk 5: I also need the price.\nChunk 6: I want to find a restaurant.\nChunk 7: Please make a booking.\nChunk 8: I would like to leave the restaurant by 14:45.\nChunk 9: Can I get a contact number for that taxi?", "input_token_count": 85, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address; acceptance: selected_option. Next, price: moderate. Next, the topic is restaurant; the goal is search; cuisine: british; destination: find a british restaurant. Next, area: centre. Next, requested information: price. Next, the goal is booking. Next, time: 14:45; destination: leave the restaurant by 14:45. Finally, the topic is taxi.  Some chunks were skipped because they contained repeated_information. In summary, The overall topic is taxi.. the goal is booking.. requested information: address, price.; acceptance: selected_option.; price: moderate.; cuisine: british; destination: find a british restaurant., leave the restaurant by 14:45.; area: centre.; time: 14:45.", "trace": "C1 goal=request_info; requested_info+=address; acceptance=selected_option. C2 price+=moderate. C3 domain=restaurant; goal=search; cuisine+=british; destination+=find a british restaurant. C4 area+=centre. C5 requested_info+=price. C6 [SKIP: repeated_information]. C7 goal=booking. C8 time+=14:45; destination+=leave the restaurant by 14:45. C9 domain=taxi.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please, can I have the address?", "streaming_reasoning": "Initially, the goal is request info; requested information: address; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=address; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Are there any moderately priced restaurants near the botanic gardens?", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a british restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; cuisine: british; destination: find a british restaurant..", "trace": "domain=restaurant; goal=search; cuisine+=british; destination+=find a british restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I would like to leave the restaurant by 14:45.", "streaming_reasoning": "As more information arrives, time: 14:45; destination: leave the restaurant by 14:45..", "trace": "time+=14:45; destination+=leave the restaurant by 14:45."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Can I get a contact number for that taxi?", "streaming_reasoning": "Finally, the topic is taxi..", "trace": "domain=taxi."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is centre; cuisine is british; price is moderate; destination is find a british restaurant; requested information is address; timing is 14:45.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, price once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant, taxi; goal=request_info, search, booking; area=centre; food=british; price=moderate; destination=find a british restaurant, leave the restaurant by 14:45; requested_info=address, price; when=14:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002860", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: am looking for a train,it should go to cambridge and should depart from norwich.\nChunk 2: Yes, I would like travel on Monday and I would need to arrive by 08:30.\nChunk 3: What is the price for the train?\nChunk 4: What time does the train leave?\nChunk 5: Thanks, that's all Good bye.", "streaming_reasoning": "C1 domain=train; goal=search; departure+=norwich. C2 time+=08:30; day+=monday; destination+=arrive by 08:30; acceptance=selected_option. C3 goal=request_info; requested_info+=price. C4 goal=request_info. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=arrive by 08:30; departure=norwich; requested_info=price; when=monday, 08:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: am looking for a train,it should go to cambridge and should depart from norwich.\nChunk 2: Yes, I would like travel on Monday and I would need to arrive by 08:30.\nChunk 3: What is the price for the train?\nChunk 4: What time does the train leave?\nChunk 5: Thanks, that's all Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; departure+=norwich. C2 time+=08:30; day+=monday; destination+=arrive by 08:30; acceptance=selected_option. C3 goal=request_info; requested_info+=price. C4 goal=request_info. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=arrive by 08:30; departure=norwich; requested_info=price; when=monday, 08:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: am looking for a train,it should go to cambridge and should depart from norwich.\nChunk 2: Yes, I would like travel on Monday and I would need to arrive by 08:30.\nChunk 3: What is the price for the train?\nChunk 4: What time does the train leave?\nChunk 5: Thanks, that's all Good bye.", "input_token_count": 59, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; departure point: norwich. Next, time: 08:30; day: monday; destination: arrive by 08:30; acceptance: selected_option. Next, the goal is request info; requested information: price. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info.. departure point: norwich.; time: 08:30; day: monday; destination: arrive by 08:30; acceptance: selected_option.; requested information: price..", "trace": "C1 domain=train; goal=search; departure+=norwich. C2 time+=08:30; day+=monday; destination+=arrive by 08:30; acceptance=selected_option. C3 goal=request_info; requested_info+=price. C4 goal=request_info. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "am looking for a train,it should go to cambridge and should depart from norwich.", "streaming_reasoning": "Initially, the topic is train; the goal is search; departure point: norwich..", "trace": "domain=train; goal=search; departure+=norwich."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I would like travel on Monday and I would need to arrive by 08:30.", "streaming_reasoning": "As more information arrives, time: 08:30; day: monday; destination: arrive by 08:30; acceptance: selected_option..", "trace": "time+=08:30; day+=monday; destination+=arrive by 08:30; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the price for the train?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What time does the train leave?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks, that's all Good bye.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is arrive by 08:30; departure point is norwich; requested information is price; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=arrive by 08:30; departure=norwich; requested_info=price; when=monday, 08:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002861", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with train.\nChunk 2: The time is 12:15.\nChunk 3: I also need the phone.\nChunk 4: I need it on Friday please.\nChunk 5: is there no one that leaves earlier?\nChunk 6: I can leave earlier, just not before 08:00.\nChunk 7: Yes that is great.\nChunk 8: Could you give me the price per ticket No thanks.\nChunk 9: That's all I need Thanks for everything!\nChunk 10: Bye!", "streaming_reasoning": "C1 domain=train; goal=search. C2 time+=12:15. C3 goal=request_info; requested_info+=phone. C4 day+=friday. C5 goal=request_info. C6 time+=08:00. C7 acceptance=selected_option. C8 requested_info+=price. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; requested_info=phone, price; when=friday, 12:15, 08:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need help with train.\nChunk 2: The time is 12:15.\nChunk 3: I also need the phone.\nChunk 4: I need it on Friday please.\nChunk 5: is there no one that leaves earlier?\nChunk 6: I can leave earlier, just not before 08:00.\nChunk 7: Yes that is great.\nChunk 8: Could you give me the price per ticket No thanks.\nChunk 9: That's all I need Thanks for everything!\nChunk 10: Bye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 time+=12:15. C3 goal=request_info; requested_info+=phone. C4 day+=friday. C5 goal=request_info. C6 time+=08:00. C7 acceptance=selected_option. C8 requested_info+=price. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; requested_info=phone, price; when=friday, 12:15, 08:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with train.\nChunk 2: The time is 12:15.\nChunk 3: I also need the phone.\nChunk 4: I need it on Friday please.\nChunk 5: is there no one that leaves earlier?\nChunk 6: I can leave earlier, just not before 08:00.\nChunk 7: Yes that is great.\nChunk 8: Could you give me the price per ticket No thanks.\nChunk 9: That's all I need Thanks for everything!\nChunk 10: Bye!", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, time: 12:15. Next, the goal is request info; requested information: phone. Next, day: friday. Next, the goal is request info. Next, time: 08:00. Next, acceptance: selected_option. Finally, requested information: price.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info.. time: 12:15., 08:00.; requested information: phone., price.; day: friday.; acceptance: selected_option..", "trace": "C1 domain=train; goal=search. C2 time+=12:15. C3 goal=request_info; requested_info+=phone. C4 day+=friday. C5 goal=request_info. C6 time+=08:00. C7 acceptance=selected_option. C8 requested_info+=price. C9 [SKIP: closing_only]. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need help with train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is 12:15.", "streaming_reasoning": "As more information arrives, time: 12:15..", "trace": "time+=12:15."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need it on Friday please.", "streaming_reasoning": "As more information arrives, day: friday..", "trace": "day+=friday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "is there no one that leaves earlier?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I can leave earlier, just not before 08:00.", "streaming_reasoning": "As more information arrives, time: 08:00..", "trace": "time+=08:00."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes that is great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Could you give me the price per ticket No thanks.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That's all I need Thanks for everything!", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Bye!", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: requested information is phone; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; requested_info=phone, price; when=friday, 12:15, 08:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002862", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i'm sorry, dude.\nChunk 2: i'm from florida so i'm not very smart.\nChunk 3: i'm trying to get from cambridge to stevenage.\nChunk 4: It is for 8 people.\nChunk 5: The time is sunday, 18:45.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: 8 tickets please, and I will need the reference number.\nChunk 9: I'd like somewhere to go in town.\nChunk 10: Something in the centre please Anything you recommend.\nChunk 11: I just need the entrance fee, attraction type and phone number.\nChunk 12: Thank you for all your help.", "streaming_reasoning": "C1 intent=context_update. C2 goal=modify_constraint. C3 goal=request_info; destination+=stevenage; departure+=cambridge. C4 party_size+=8 people. C5 time+=18:45; day+=sunday. C6 goal=booking. C7 goal=search; requested_info+=reference_number. C8 intent=context_update. C9 destination+=go in town. C10 goal=recommendation; area+=centre. C11 domain=attraction; requested_info+=phone, entrance_fee. C12 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction; goal=request_info, booking, search, recommendation; area=centre; party_size=8 people; destination=stevenage, go in town; departure=cambridge; requested_info=reference_number, phone, entrance_fee; when=sunday, 18:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i'm sorry, dude.\nChunk 2: i'm from florida so i'm not very smart.\nChunk 3: i'm trying to get from cambridge to stevenage.\nChunk 4: It is for 8 people.\nChunk 5: The time is sunday, 18:45.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: 8 tickets please, and I will need the reference number.\nChunk 9: I'd like somewhere to go in town.\nChunk 10: Something in the centre please Anything you recommend.\nChunk 11: I just need the entrance fee, attraction type and phone number.\nChunk 12: Thank you for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=modify_constraint. C3 goal=request_info; destination+=stevenage; departure+=cambridge. C4 party_size+=8 people. C5 time+=18:45; day+=sunday. C6 goal=booking. C7 goal=search; requested_info+=reference_number. C8 intent=context_update. C9 destination+=go in town. C10 goal=recommendation; area+=centre. C11 domain=attraction; requested_info+=phone, entrance_fee. C12 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction; goal=request_info, booking, search, recommendation; area=centre; party_size=8 people; destination=stevenage, go in town; departure=cambridge; requested_info=reference_number, phone, entrance_fee; when=sunday, 18:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i'm sorry, dude.\nChunk 2: i'm from florida so i'm not very smart.\nChunk 3: i'm trying to get from cambridge to stevenage.\nChunk 4: It is for 8 people.\nChunk 5: The time is sunday, 18:45.\nChunk 6: Please make a booking.\nChunk 7: I also need the reference number.\nChunk 8: 8 tickets please, and I will need the reference number.\nChunk 9: I'd like somewhere to go in town.\nChunk 10: Something in the centre please Anything you recommend.\nChunk 11: I just need the entrance fee, attraction type and phone number.\nChunk 12: Thank you for all your help.", "input_token_count": 106, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is modify constraint. Next, the goal is request info; destination: stevenage; departure point: cambridge. Next, party size: 8 people. Next, time: 18:45; day: sunday. Next, the goal is booking. Next, the goal is search; requested information: reference_number. Next, intent: context_update. Next, destination: go in town. Next, the goal is recommendation; area: centre. Finally, the topic is attraction; requested information: phone.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction. the goal is recommendation. intent: context_update.; destination: stevenage, go in town.; departure point: cambridge.; party size: 8 people.; time: 18:45; day: sunday.; requested information: reference_number., phone; area: centre..", "trace": "C1 intent=context_update. C2 goal=modify_constraint. C3 goal=request_info; destination+=stevenage; departure+=cambridge. C4 party_size+=8 people. C5 time+=18:45; day+=sunday. C6 goal=booking. C7 goal=search; requested_info+=reference_number. C8 intent=context_update. C9 destination+=go in town. C10 goal=recommendation; area+=centre. C11 domain=attraction; requested_info+=phone, entrance_fee. C12 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i'm sorry, dude.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "i'm from florida so i'm not very smart.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "i'm trying to get from cambridge to stevenage.", "streaming_reasoning": "As more information arrives, the goal is request info; destination: stevenage; departure point: cambridge..", "trace": "goal=request_info; destination+=stevenage; departure+=cambridge."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It is for 8 people.", "streaming_reasoning": "As more information arrives, party size: 8 people..", "trace": "party_size+=8 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is sunday, 18:45.", "streaming_reasoning": "As more information arrives, time: 18:45; day: sunday..", "trace": "time+=18:45; day+=sunday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is search; requested information: reference_number..", "trace": "goal=search; requested_info+=reference_number."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "8 tickets please, and I will need the reference number.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I'd like somewhere to go in town.", "streaming_reasoning": "As more information arrives, destination: go in town..", "trace": "destination+=go in town."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Something in the centre please Anything you recommend.", "streaming_reasoning": "As more information arrives, the goal is recommendation; area: centre..", "trace": "goal=recommendation; area+=centre."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "I just need the entrance fee, attraction type and phone number.", "streaming_reasoning": "As more information arrives, the topic is attraction; requested information: phone.", "trace": "domain=attraction; requested_info+=phone, entrance_fee."}, {"checkpoint_id": "C12", "chunk_index": 11, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C12 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: area is centre; party size is 8 people; destination is stevenage; departure point is cambridge; requested information is reference_number; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=request_info, booking, search, recommendation; area=centre; party_size=8 people; destination=stevenage, go in town; departure=cambridge; requested_info=reference_number, phone, entrance_fee; when=sunday, 18:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002863", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: Could you tell me the travel time and price for that train please?\nChunk 3: i'm also looking for a moderately priced hotel with free parking.\nChunk 4: Any area will do Definitely a hotel.\nChunk 5: Yes, 8 people, 3 nights starting Thursday.\nChunk 6: Please include reference number.\nChunk 7: Thank you for your help.\nChunk 8: No, that will be all.\nChunk 9: Thanks!", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=request_info; requested_info+=travel_time, price. C3 domain=hotel; goal=search; price+=moderate; hotel_type+=hotel; amenities+=parking, free parking. C4 area+=any. C5 time+=8, 3; day+=thursday; party_size+=8 people; stay_length+=3 nights; acceptance=selected_option. C6 requested_info+=reference_number. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, hotel; goal=request_info, search; area=any; price=moderate; party_size=8 people; stay_length=3 nights; amenities=parking, free parking; requested_info=travel_time, price, reference_number; when=thursday, 8, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: Could you tell me the travel time and price for that train please?\nChunk 3: i'm also looking for a moderately priced hotel with free parking.\nChunk 4: Any area will do Definitely a hotel.\nChunk 5: Yes, 8 people, 3 nights starting Thursday.\nChunk 6: Please include reference number.\nChunk 7: Thank you for your help.\nChunk 8: No, that will be all.\nChunk 9: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=request_info; requested_info+=travel_time, price. C3 domain=hotel; goal=search; price+=moderate; hotel_type+=hotel; amenities+=parking, free parking. C4 area+=any. C5 time+=8, 3; day+=thursday; party_size+=8 people; stay_length+=3 nights; acceptance=selected_option. C6 requested_info+=reference_number. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, hotel; goal=request_info, search; area=any; price=moderate; party_size=8 people; stay_length=3 nights; amenities=parking, free parking; requested_info=travel_time, price, reference_number; when=thursday, 8, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: Could you tell me the travel time and price for that train please?\nChunk 3: i'm also looking for a moderately priced hotel with free parking.\nChunk 4: Any area will do Definitely a hotel.\nChunk 5: Yes, 8 people, 3 nights starting Thursday.\nChunk 6: Please include reference number.\nChunk 7: Thank you for your help.\nChunk 8: No, that will be all.\nChunk 9: Thanks!", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is request info; requested information: travel_time. Next, the topic is hotel; the goal is search; price: moderate; hotel type: hotel; amenities: parking. Next, area: any. Next, time: 8; day: thursday; party size: 8 people; stay length: 3 nights; acceptance: selected_option. Finally, requested information: reference_number.  Some chunks were skipped because they contained acknowledgement_only or closing_only or thanks_only. In summary, The overall topic is hotel. the goal is search. requested information: travel_time, reference_number.; price: moderate; hotel type: hotel; amenities: parking; area: any.; time: 8; day: thursday; party size: 8 people; stay length: 3 nights; acceptance: selected_option..", "trace": "C1 [SKIP: acknowledgement_only]. C2 domain=train; goal=request_info; requested_info+=travel_time, price. C3 domain=hotel; goal=search; price+=moderate; hotel_type+=hotel; amenities+=parking, free parking. C4 area+=any. C5 time+=8, 3; day+=thursday; party_size+=8 people; stay_length+=3 nights; acceptance=selected_option. C6 requested_info+=reference_number. C7 [SKIP: thanks_only]. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Could you tell me the travel time and price for that train please?", "streaming_reasoning": "As more information arrives, the topic is train; the goal is request info; requested information: travel_time.", "trace": "domain=train; goal=request_info; requested_info+=travel_time, price."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "i'm also looking for a moderately priced hotel with free parking.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; price: moderate; hotel type: hotel; amenities: parking.", "trace": "domain=hotel; goal=search; price+=moderate; hotel_type+=hotel; amenities+=parking, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Any area will do Definitely a hotel.", "streaming_reasoning": "As more information arrives, area: any..", "trace": "area+=any."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, 8 people, 3 nights starting Thursday.", "streaming_reasoning": "As more information arrives, time: 8; day: thursday; party size: 8 people; stay length: 3 nights; acceptance: selected_option..", "trace": "time+=8, 3; day+=thursday; party_size+=8 people; stay_length+=3 nights; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please include reference number.", "streaming_reasoning": "As more information arrives, requested information: reference_number..", "trace": "requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, that will be all.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: area is any; price is moderate; party size is 8 people; stay length is 3 nights; amenities is parking; requested information is travel_time; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=request_info, search; area=any; price=moderate; party_size=8 people; stay_length=3 nights; amenities=parking, free parking; requested_info=travel_time, price, reference_number; when=thursday, 8, 3; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002864", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please, for 4 people at 17:45 on Saturday.\nChunk 2: Thank you, I am also looking for a train, I need it to depart from Cambridge on sunday Uh you alright?\nChunk 3: I guess I can do it myself...\nChunk 4: I'd like to leave after 09:30 on Sunday and go to kings lynn from cambridge.\nChunk 5: I need help with train.\nChunk 6: It is for 4 people.\nChunk 7: The time is 10:11.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number Alright, that's everything.\nChunk 10: Thank you for all of your help!", "streaming_reasoning": "C1 time+=4, 17:45; day+=saturday; party_size+=4 people; acceptance=selected_option. C2 domain=train; goal=search; day+=sunday; departure+=cambridge on sunday uh you alright. C3 intent=context_update. C4 time+=09:30. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 time+=10:11. C8 goal=booking. C9 goal=request_info; requested_info+=reference_number. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search, booking, request_info; party_size=4 people; departure=cambridge on sunday uh you alright; requested_info=reference_number; when=saturday, sunday, 4, 17:45, 09:30, 10:11; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes please, for 4 people at 17:45 on Saturday.\nChunk 2: Thank you, I am also looking for a train, I need it to depart from Cambridge on sunday Uh you alright?\nChunk 3: I guess I can do it myself...\nChunk 4: I'd like to leave after 09:30 on Sunday and go to kings lynn from cambridge.\nChunk 5: I need help with train.\nChunk 6: It is for 4 people.\nChunk 7: The time is 10:11.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number Alright, that's everything.\nChunk 10: Thank you for all of your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=4, 17:45; day+=saturday; party_size+=4 people; acceptance=selected_option. C2 domain=train; goal=search; day+=sunday; departure+=cambridge on sunday uh you alright. C3 intent=context_update. C4 time+=09:30. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 time+=10:11. C8 goal=booking. C9 goal=request_info; requested_info+=reference_number. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search, booking, request_info; party_size=4 people; departure=cambridge on sunday uh you alright; requested_info=reference_number; when=saturday, sunday, 4, 17:45, 09:30, 10:11; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes please, for 4 people at 17:45 on Saturday.\nChunk 2: Thank you, I am also looking for a train, I need it to depart from Cambridge on sunday Uh you alright?\nChunk 3: I guess I can do it myself...\nChunk 4: I'd like to leave after 09:30 on Sunday and go to kings lynn from cambridge.\nChunk 5: I need help with train.\nChunk 6: It is for 4 people.\nChunk 7: The time is 10:11.\nChunk 8: Please make a booking.\nChunk 9: I also need the reference number Alright, that's everything.\nChunk 10: Thank you for all of your help!", "input_token_count": 109, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, time: 4; day: saturday; party size: 4 people; acceptance: selected_option. Next, the topic is train; the goal is search; day: sunday; departure point: cambridge on sunday uh you alright. Next, intent: context_update. Next, time: 09:30. Next, intent: context_update. Next, time: 10:11. Next, the goal is booking. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained repeated_information or thanks_only. In summary, The overall topic is train. the goal is request info. time: 4, 09:30., 10:11.; day: saturday, sunday; party size: 4 people; acceptance: selected_option.; departure point: cambridge on sunday uh you alright.; intent: context_update.; requested information: reference_number..", "trace": "C1 time+=4, 17:45; day+=saturday; party_size+=4 people; acceptance=selected_option. C2 domain=train; goal=search; day+=sunday; departure+=cambridge on sunday uh you alright. C3 intent=context_update. C4 time+=09:30. C5 intent=context_update. C6 [SKIP: repeated_information]. C7 time+=10:11. C8 goal=booking. C9 goal=request_info; requested_info+=reference_number. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes please, for 4 people at 17:45 on Saturday.", "streaming_reasoning": "Initially, time: 4; day: saturday; party size: 4 people; acceptance: selected_option..", "trace": "time+=4, 17:45; day+=saturday; party_size+=4 people; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thank you, I am also looking for a train, I need it to depart from Cambridge on sunday Uh you alright?", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: sunday; departure point: cambridge on sunday uh you alright..", "trace": "domain=train; goal=search; day+=sunday; departure+=cambridge on sunday uh you alright."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I guess I can do it myself...", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd like to leave after 09:30 on Sunday and go to kings lynn from cambridge.", "streaming_reasoning": "As more information arrives, time: 09:30..", "trace": "time+=09:30."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It is for 4 people.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 10:11.", "streaming_reasoning": "As more information arrives, time: 10:11..", "trace": "time+=10:11."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need the reference number Alright, that's everything.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you for all of your help!", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 4 people; departure point is cambridge on sunday uh you alright; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, booking, request_info; party_size=4 people; departure=cambridge on sunday uh you alright; requested_info=reference_number; when=saturday, sunday, 4, 17:45, 09:30, 10:11; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002865", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I just need to leave after 08:45.\nChunk 2: yes, for 2 people.\nChunk 3: Please give me the reference number.\nChunk 4: I am looking for a restaurant.\nChunk 5: The restaurant should be in the centre and should be in the moderate price range.\nChunk 6: I don't have a food preference.\nChunk 7: Sure, that works for me.\nChunk 8: I need the phone number, postcode, and address for the restaurant Oh that's great.\nChunk 9: That would be all, thank you.", "streaming_reasoning": "C1 goal=search; time+=08:45; destination+=leave after 08:45. C2 party_size+=2 people; acceptance=selected_option. C3 goal=request_info; requested_info+=reference_number. C4 domain=restaurant. C5 area+=centre; price+=moderate. C6 intent=context_update. C7 acceptance=selected_option. C8 requested_info+=address, phone, postcode. C9 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=centre; price=moderate; party_size=2 people; destination=leave after 08:45; requested_info=reference_number, address, phone, postcode; when=08:45.", "answer": "I can help with that and include the reference number, address, phone, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I just need to leave after 08:45.\nChunk 2: yes, for 2 people.\nChunk 3: Please give me the reference number.\nChunk 4: I am looking for a restaurant.\nChunk 5: The restaurant should be in the centre and should be in the moderate price range.\nChunk 6: I don't have a food preference.\nChunk 7: Sure, that works for me.\nChunk 8: I need the phone number, postcode, and address for the restaurant Oh that's great.\nChunk 9: That would be all, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; time+=08:45; destination+=leave after 08:45. C2 party_size+=2 people; acceptance=selected_option. C3 goal=request_info; requested_info+=reference_number. C4 domain=restaurant. C5 area+=centre; price+=moderate. C6 intent=context_update. C7 acceptance=selected_option. C8 requested_info+=address, phone, postcode. C9 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=centre; price=moderate; party_size=2 people; destination=leave after 08:45; requested_info=reference_number, address, phone, postcode; when=08:45.\n\nAnswer: I can help with that and include the reference number, address, phone, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I just need to leave after 08:45.\nChunk 2: yes, for 2 people.\nChunk 3: Please give me the reference number.\nChunk 4: I am looking for a restaurant.\nChunk 5: The restaurant should be in the centre and should be in the moderate price range.\nChunk 6: I don't have a food preference.\nChunk 7: Sure, that works for me.\nChunk 8: I need the phone number, postcode, and address for the restaurant Oh that's great.\nChunk 9: That would be all, thank you.", "input_token_count": 88, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; time: 08:45; destination: leave after 08:45. Next, party size: 2 people; acceptance: selected_option. Next, the goal is request info; requested information: reference_number. Next, the topic is restaurant. Next, area: centre; price: moderate. Next, intent: context_update. Next, acceptance: selected_option. Next, requested information: address. Finally, intent: context_update. In summary, The overall topic is restaurant.. the goal is request info. time: 08:45; destination: leave after 08:45.; party size: 2 people; acceptance: selected_option.; requested information: reference_number., address; area: centre; price: moderate.; intent: context_update..", "trace": "C1 goal=search; time+=08:45; destination+=leave after 08:45. C2 party_size+=2 people; acceptance=selected_option. C3 goal=request_info; requested_info+=reference_number. C4 domain=restaurant. C5 area+=centre; price+=moderate. C6 intent=context_update. C7 acceptance=selected_option. C8 requested_info+=address, phone, postcode. C9 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I just need to leave after 08:45.", "streaming_reasoning": "Initially, the goal is search; time: 08:45; destination: leave after 08:45..", "trace": "goal=search; time+=08:45; destination+=leave after 08:45."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "yes, for 2 people.", "streaming_reasoning": "As more information arrives, party size: 2 people; acceptance: selected_option..", "trace": "party_size+=2 people; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Please give me the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am looking for a restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The restaurant should be in the centre and should be in the moderate price range.", "streaming_reasoning": "As more information arrives, area: centre; price: moderate..", "trace": "area+=centre; price+=moderate."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I don't have a food preference.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Sure, that works for me.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I need the phone number, postcode, and address for the restaurant Oh that's great.", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, phone, postcode."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "That would be all, thank you.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; price is moderate; party size is 2 people; destination is leave after 08:45; requested information is reference_number; timing is 08:45.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number, address, phone, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=centre; price=moderate; party_size=2 people; destination=leave after 08:45; requested_info=reference_number, address, phone, postcode; when=08:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002866", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a cheap restaurant.\nChunk 2: It should be in the west part of town.\nChunk 3: I also need the address.\nChunk 4: I also need the phone.\nChunk 5: Is there anything else, if so give me their address and phone number No thank you.\nChunk 6: No, that's fine Thank you!", "streaming_reasoning": "C1 domain=restaurant; goal=search; price+=cheap; destination+=find a cheap restaurant. C2 area+=west. C3 goal=request_info; requested_info+=address. C4 requested_info+=phone. C5 goal=compare_alternative. C6 goal=modify_constraint.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, compare_alternative; area=west; price=cheap; destination=find a cheap restaurant; requested_info=address, phone.", "answer": "I can help with that and include the address, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a cheap restaurant.\nChunk 2: It should be in the west part of town.\nChunk 3: I also need the address.\nChunk 4: I also need the phone.\nChunk 5: Is there anything else, if so give me their address and phone number No thank you.\nChunk 6: No, that's fine Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; price+=cheap; destination+=find a cheap restaurant. C2 area+=west. C3 goal=request_info; requested_info+=address. C4 requested_info+=phone. C5 goal=compare_alternative. C6 goal=modify_constraint.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, compare_alternative; area=west; price=cheap; destination=find a cheap restaurant; requested_info=address, phone.\n\nAnswer: I can help with that and include the address, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a cheap restaurant.\nChunk 2: It should be in the west part of town.\nChunk 3: I also need the address.\nChunk 4: I also need the phone.\nChunk 5: Is there anything else, if so give me their address and phone number No thank you.\nChunk 6: No, that's fine Thank you!", "input_token_count": 59, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: cheap; destination: find a cheap restaurant. Next, area: west. Next, the goal is request info; requested information: address. Next, requested information: phone. Next, the goal is compare alternative. Finally, the goal is modify constraint. In summary, The overall topic is restaurant. the goal is modify constraint.. price: cheap; destination: find a cheap restaurant.; area: west.; requested information: address., phone..", "trace": "C1 domain=restaurant; goal=search; price+=cheap; destination+=find a cheap restaurant. C2 area+=west. C3 goal=request_info; requested_info+=address. C4 requested_info+=phone. C5 goal=compare_alternative. C6 goal=modify_constraint.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a cheap restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; price: cheap; destination: find a cheap restaurant..", "trace": "domain=restaurant; goal=search; price+=cheap; destination+=find a cheap restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the west part of town.", "streaming_reasoning": "As more information arrives, area: west..", "trace": "area+=west."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the address.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Is there anything else, if so give me their address and phone number No thank you.", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, that's fine Thank you!", "streaming_reasoning": "Finally, the goal is modify constraint..", "trace": "goal=modify_constraint."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is west; price is cheap; destination is find a cheap restaurant; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, compare_alternative; area=west; price=cheap; destination=find a cheap restaurant; requested_info=address, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002867", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to go to a particular attraction called great saint mary's church Where is it?\nChunk 2: Please provide the address.\nChunk 3: I also need a train leaving from cambridge and should leave after 13:45.\nChunk 4: I'd like the train for Saturday and I'm headed to London Liverpool Street, please.\nChunk 5: I need to book that for 6 people.\nChunk 6: Please provide the reference number after booking is completed.", "streaming_reasoning": "C1 domain=attraction; goal=search; destination+=go to a particular attraction called grea. C2 goal=request_info; requested_info+=address. C3 domain=train; time+=13:45. C4 day+=saturday; amenities+=pool; destination+=london liverpool street. C5 goal=booking; party_size+=6 people. C6 requested_info+=reference_number.", "deep_reasoning": "Need domain=attraction, train; goal=search, request_info, booking; party_size=6 people; amenities=pool; destination=go to a particular attraction called grea, london liverpool street; requested_info=address, reference_number; when=saturday, 13:45.", "answer": "I can help with that and include the address, reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to go to a particular attraction called great saint mary's church Where is it?\nChunk 2: Please provide the address.\nChunk 3: I also need a train leaving from cambridge and should leave after 13:45.\nChunk 4: I'd like the train for Saturday and I'm headed to London Liverpool Street, please.\nChunk 5: I need to book that for 6 people.\nChunk 6: Please provide the reference number after booking is completed."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search; destination+=go to a particular attraction called grea. C2 goal=request_info; requested_info+=address. C3 domain=train; time+=13:45. C4 day+=saturday; amenities+=pool; destination+=london liverpool street. C5 goal=booking; party_size+=6 people. C6 requested_info+=reference_number.\n\nDeep reasoning: Need domain=attraction, train; goal=search, request_info, booking; party_size=6 people; amenities=pool; destination=go to a particular attraction called grea, london liverpool street; requested_info=address, reference_number; when=saturday, 13:45.\n\nAnswer: I can help with that and include the address, reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to go to a particular attraction called great saint mary's church Where is it?\nChunk 2: Please provide the address.\nChunk 3: I also need a train leaving from cambridge and should leave after 13:45.\nChunk 4: I'd like the train for Saturday and I'm headed to London Liverpool Street, please.\nChunk 5: I need to book that for 6 people.\nChunk 6: Please provide the reference number after booking is completed.", "input_token_count": 77, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; destination: go to a particular attraction called grea. Next, the goal is request info; requested information: address. Next, the topic is train; time: 13:45. Next, day: saturday; amenities: pool; destination: london liverpool street. Next, the goal is booking; party size: 6 people. Finally, requested information: reference_number. In summary, The overall topic is train. the goal is booking. destination: go to a particular attraction called grea., london liverpool street.; requested information: address., reference_number.; time: 13:45.; day: saturday; amenities: pool; party size: 6 people..", "trace": "C1 domain=attraction; goal=search; destination+=go to a particular attraction called grea. C2 goal=request_info; requested_info+=address. C3 domain=train; time+=13:45. C4 day+=saturday; amenities+=pool; destination+=london liverpool street. C5 goal=booking; party_size+=6 people. C6 requested_info+=reference_number.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to go to a particular attraction called great saint mary's church Where is it?", "streaming_reasoning": "Initially, the topic is attraction; the goal is search; destination: go to a particular attraction called grea..", "trace": "domain=attraction; goal=search; destination+=go to a particular attraction called grea."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Please provide the address.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need a train leaving from cambridge and should leave after 13:45.", "streaming_reasoning": "As more information arrives, the topic is train; time: 13:45..", "trace": "domain=train; time+=13:45."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd like the train for Saturday and I'm headed to London Liverpool Street, please.", "streaming_reasoning": "As more information arrives, day: saturday; amenities: pool; destination: london liverpool street..", "trace": "day+=saturday; amenities+=pool; destination+=london liverpool street."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need to book that for 6 people.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 6 people..", "trace": "goal=booking; party_size+=6 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please provide the reference number after booking is completed.", "streaming_reasoning": "Finally, requested information: reference_number..", "trace": "requested_info+=reference_number."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: party size is 6 people; amenities is pool; destination is go to a particular attraction called grea; requested information is address; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=attraction, train; goal=search, request_info, booking; party_size=6 people; amenities=pool; destination=go to a particular attraction called grea, london liverpool street; requested_info=address, reference_number; when=saturday, 13:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002868", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place to stay.\nChunk 2: The hotel should have a star of 4 and should include free parking.\nChunk 3: No, it just needs to be cheap Sounds good.\nChunk 4: Can I get it for 7 people and 4 nights from thursday please?\nChunk 5: Ok, try for 2 nights.\nChunk 6: Thank you so much for all of your help!\nChunk 7: No that was all I needed Thanks again.", "streaming_reasoning": "C1 domain=hotel; goal=search; destination+=stay. C2 hotel_type+=hotel; amenities+=parking, free parking. C3 price+=cheap; destination+=be cheap sounds good; acceptance=selected_option. C4 goal=request_info; day+=thursday; party_size+=7 people; stay_length+=4 nights. C5 stay_length+=2 nights. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info; price=cheap; party_size=7 people; stay_length=4 nights, 2 nights; amenities=parking, free parking; destination=stay, be cheap sounds good; when=thursday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a place to stay.\nChunk 2: The hotel should have a star of 4 and should include free parking.\nChunk 3: No, it just needs to be cheap Sounds good.\nChunk 4: Can I get it for 7 people and 4 nights from thursday please?\nChunk 5: Ok, try for 2 nights.\nChunk 6: Thank you so much for all of your help!\nChunk 7: No that was all I needed Thanks again."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; destination+=stay. C2 hotel_type+=hotel; amenities+=parking, free parking. C3 price+=cheap; destination+=be cheap sounds good; acceptance=selected_option. C4 goal=request_info; day+=thursday; party_size+=7 people; stay_length+=4 nights. C5 stay_length+=2 nights. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info; price=cheap; party_size=7 people; stay_length=4 nights, 2 nights; amenities=parking, free parking; destination=stay, be cheap sounds good; when=thursday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place to stay.\nChunk 2: The hotel should have a star of 4 and should include free parking.\nChunk 3: No, it just needs to be cheap Sounds good.\nChunk 4: Can I get it for 7 people and 4 nights from thursday please?\nChunk 5: Ok, try for 2 nights.\nChunk 6: Thank you so much for all of your help!\nChunk 7: No that was all I needed Thanks again.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay. Next, hotel type: hotel; amenities: parking. Next, price: cheap; destination: be cheap sounds good; acceptance: selected_option. Next, the goal is request info; day: thursday; party size: 7 people; stay length: 4 nights. Finally, stay length: 2 nights.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is request info. destination: stay., be cheap sounds good; hotel type: hotel; amenities: parking; price: cheap; acceptance: selected_option.; day: thursday; party size: 7 people; stay length: 4 nights., 2 nights..", "trace": "C1 domain=hotel; goal=search; destination+=stay. C2 hotel_type+=hotel; amenities+=parking, free parking. C3 price+=cheap; destination+=be cheap sounds good; acceptance=selected_option. C4 goal=request_info; day+=thursday; party_size+=7 people; stay_length+=4 nights. C5 stay_length+=2 nights. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a place to stay.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; destination: stay..", "trace": "domain=hotel; goal=search; destination+=stay."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The hotel should have a star of 4 and should include free parking.", "streaming_reasoning": "As more information arrives, hotel type: hotel; amenities: parking.", "trace": "hotel_type+=hotel; amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, it just needs to be cheap Sounds good.", "streaming_reasoning": "As more information arrives, price: cheap; destination: be cheap sounds good; acceptance: selected_option..", "trace": "price+=cheap; destination+=be cheap sounds good; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can I get it for 7 people and 4 nights from thursday please?", "streaming_reasoning": "As more information arrives, the goal is request info; day: thursday; party size: 7 people; stay length: 4 nights..", "trace": "goal=request_info; day+=thursday; party_size+=7 people; stay_length+=4 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Ok, try for 2 nights.", "streaming_reasoning": "As more information arrives, stay length: 2 nights..", "trace": "stay_length+=2 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you so much for all of your help!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No that was all I needed Thanks again.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is cheap; party size is 7 people; stay length is 4 nights; amenities is parking; destination is stay; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info; price=cheap; party_size=7 people; stay_length=4 nights, 2 nights; amenities=parking, free parking; destination=stay, be cheap sounds good; when=thursday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002869", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm at Kettle's Yard and need a taxi to pick me up by 19:30.\nChunk 2: I want to go to castle galleries.\nChunk 3: I need to leave after 19:30.\nChunk 4: Thank you, what is the contact number?\nChunk 5: No.\nChunk 6: Thank you for your assistance.", "streaming_reasoning": "C1 domain=taxi; goal=search; time+=19:30; destination+=pick me up by 19:30. C2 destination+=go to castle galleries. C3 destination+=leave after 19:30. C4 [SKIP: thanks_only]. C5 [SKIP: acknowledgement_only]. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi; goal=search; destination=pick me up by 19:30, go to castle galleries, leave after 19:30; when=19:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm at Kettle's Yard and need a taxi to pick me up by 19:30.\nChunk 2: I want to go to castle galleries.\nChunk 3: I need to leave after 19:30.\nChunk 4: Thank you, what is the contact number?\nChunk 5: No.\nChunk 6: Thank you for your assistance."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search; time+=19:30; destination+=pick me up by 19:30. C2 destination+=go to castle galleries. C3 destination+=leave after 19:30. C4 [SKIP: thanks_only]. C5 [SKIP: acknowledgement_only]. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi; goal=search; destination=pick me up by 19:30, go to castle galleries, leave after 19:30; when=19:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm at Kettle's Yard and need a taxi to pick me up by 19:30.\nChunk 2: I want to go to castle galleries.\nChunk 3: I need to leave after 19:30.\nChunk 4: Thank you, what is the contact number?\nChunk 5: No.\nChunk 6: Thank you for your assistance.", "input_token_count": 54, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search; time: 19:30; destination: pick me up by 19:30. Next, destination: go to castle galleries. Finally, destination: leave after 19:30.  Some chunks were skipped because they contained acknowledgement_only or thanks_only. In summary, The overall topic is taxi. the goal is search. time: 19:30; destination: pick me up by 19:30., go to castle galleries., leave after 19:30..", "trace": "C1 domain=taxi; goal=search; time+=19:30; destination+=pick me up by 19:30. C2 destination+=go to castle galleries. C3 destination+=leave after 19:30. C4 [SKIP: thanks_only]. C5 [SKIP: acknowledgement_only]. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm at Kettle's Yard and need a taxi to pick me up by 19:30.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search; time: 19:30; destination: pick me up by 19:30..", "trace": "domain=taxi; goal=search; time+=19:30; destination+=pick me up by 19:30."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want to go to castle galleries.", "streaming_reasoning": "As more information arrives, destination: go to castle galleries..", "trace": "destination+=go to castle galleries."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to leave after 19:30.", "streaming_reasoning": "As more information arrives, destination: leave after 19:30..", "trace": "destination+=leave after 19:30."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you, what is the contact number?", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No.", "streaming_reasoning": "The content at C5 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for your assistance.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is pick me up by 19:30; timing is 19:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search; destination=pick me up by 19:30, go to castle galleries, leave after 19:30; when=19:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002870", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a restaurant.\nChunk 2: The restaurant should serve italian food and should be in the expensive price range.\nChunk 3: I am looking in the centre of town.\nChunk 4: Yes, surprise me please!\nChunk 5: it's for 8 people at 16:30 on Tuesday.\nChunk 6: No, thank you so much!\nChunk 7: Have a nice day.", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 cuisine+=italian; price+=expensive. C3 area+=centre. C4 acceptance=selected_option. C5 time+=8, 16:30; day+=tuesday; party_size+=8 people. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search; area=centre; food=italian; price=expensive; party_size=8 people; when=tuesday, 8, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a restaurant.\nChunk 2: The restaurant should serve italian food and should be in the expensive price range.\nChunk 3: I am looking in the centre of town.\nChunk 4: Yes, surprise me please!\nChunk 5: it's for 8 people at 16:30 on Tuesday.\nChunk 6: No, thank you so much!\nChunk 7: Have a nice day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 cuisine+=italian; price+=expensive. C3 area+=centre. C4 acceptance=selected_option. C5 time+=8, 16:30; day+=tuesday; party_size+=8 people. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search; area=centre; food=italian; price=expensive; party_size=8 people; when=tuesday, 8, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a restaurant.\nChunk 2: The restaurant should serve italian food and should be in the expensive price range.\nChunk 3: I am looking in the centre of town.\nChunk 4: Yes, surprise me please!\nChunk 5: it's for 8 people at 16:30 on Tuesday.\nChunk 6: No, thank you so much!\nChunk 7: Have a nice day.", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, cuisine: italian; price: expensive. Next, area: centre. Next, acceptance: selected_option. Finally, time: 8; day: tuesday; party size: 8 people.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is search.. cuisine: italian; price: expensive.; area: centre.; acceptance: selected_option.; time: 8; day: tuesday; party size: 8 people..", "trace": "C1 domain=restaurant; goal=search. C2 cuisine+=italian; price+=expensive. C3 area+=centre. C4 acceptance=selected_option. C5 time+=8, 16:30; day+=tuesday; party_size+=8 people. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The restaurant should serve italian food and should be in the expensive price range.", "streaming_reasoning": "As more information arrives, cuisine: italian; price: expensive..", "trace": "cuisine+=italian; price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am looking in the centre of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, surprise me please!", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "it's for 8 people at 16:30 on Tuesday.", "streaming_reasoning": "As more information arrives, time: 8; day: tuesday; party size: 8 people..", "trace": "time+=8, 16:30; day+=tuesday; party_size+=8 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, thank you so much!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a nice day.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is italian; price is expensive; party size is 8 people; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search; area=centre; food=italian; price=expensive; party_size=8 people; when=tuesday, 8, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002871", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am traveling to Cambridge and looking forward to try local restaurants No, thank you!\nChunk 2: I am looking for a train that departs on Monday, though.\nChunk 3: Can you please help me with that?\nChunk 4: I want to leave from Cambridge traveling to Norwich, arriving by 18:30.\nChunk 5: Yes I am looking for a particular restaurant called Shanghai Family Restaurant.\nChunk 6: What's the food type?\nChunk 7: No, that is all the information i need Thank you.", "streaming_reasoning": "C1 destination+=cambridge and looking forward to try local. C2 domain=train; goal=search; day+=monday. C3 goal=request_info. C4 time+=18:30; destination+=norwich; departure+=cambridge traveling. C5 domain=restaurant; acceptance=selected_option. C6 goal=request_info. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, restaurant; goal=search, request_info; destination=cambridge and looking forward to try local, norwich; departure=cambridge traveling; when=monday, 18:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am traveling to Cambridge and looking forward to try local restaurants No, thank you!\nChunk 2: I am looking for a train that departs on Monday, though.\nChunk 3: Can you please help me with that?\nChunk 4: I want to leave from Cambridge traveling to Norwich, arriving by 18:30.\nChunk 5: Yes I am looking for a particular restaurant called Shanghai Family Restaurant.\nChunk 6: What's the food type?\nChunk 7: No, that is all the information i need Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 destination+=cambridge and looking forward to try local. C2 domain=train; goal=search; day+=monday. C3 goal=request_info. C4 time+=18:30; destination+=norwich; departure+=cambridge traveling. C5 domain=restaurant; acceptance=selected_option. C6 goal=request_info. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=search, request_info; destination=cambridge and looking forward to try local, norwich; departure=cambridge traveling; when=monday, 18:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am traveling to Cambridge and looking forward to try local restaurants No, thank you!\nChunk 2: I am looking for a train that departs on Monday, though.\nChunk 3: Can you please help me with that?\nChunk 4: I want to leave from Cambridge traveling to Norwich, arriving by 18:30.\nChunk 5: Yes I am looking for a particular restaurant called Shanghai Family Restaurant.\nChunk 6: What's the food type?\nChunk 7: No, that is all the information i need Thank you.", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, destination: cambridge and looking forward to try local. Next, the topic is train; the goal is search; day: monday. Next, the goal is request info. Next, time: 18:30; destination: norwich; departure point: cambridge traveling. Next, the topic is restaurant; acceptance: selected_option. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info.. destination: cambridge and looking forward to try local., norwich; day: monday.; time: 18:30; departure point: cambridge traveling.; acceptance: selected_option..", "trace": "C1 destination+=cambridge and looking forward to try local. C2 domain=train; goal=search; day+=monday. C3 goal=request_info. C4 time+=18:30; destination+=norwich; departure+=cambridge traveling. C5 domain=restaurant; acceptance=selected_option. C6 goal=request_info. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am traveling to Cambridge and looking forward to try local restaurants No, thank you!", "streaming_reasoning": "Initially, destination: cambridge and looking forward to try local..", "trace": "destination+=cambridge and looking forward to try local."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am looking for a train that departs on Monday, though.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: monday..", "trace": "domain=train; goal=search; day+=monday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you please help me with that?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I want to leave from Cambridge traveling to Norwich, arriving by 18:30.", "streaming_reasoning": "As more information arrives, time: 18:30; destination: norwich; departure point: cambridge traveling..", "trace": "time+=18:30; destination+=norwich; departure+=cambridge traveling."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes I am looking for a particular restaurant called Shanghai Family Restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; acceptance: selected_option..", "trace": "domain=restaurant; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What's the food type?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that is all the information i need Thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is cambridge and looking forward to try local; departure point is cambridge traveling; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=search, request_info; destination=cambridge and looking forward to try local, norwich; departure=cambridge traveling; when=monday, 18:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002873", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a moderately priced restaurant located in the south part of town.\nChunk 2: What type of food are they.\nChunk 3: What is their address?\nChunk 4: Thank you Good bye.", "streaming_reasoning": "C1 domain=restaurant; area+=south; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=request_info; area=south; price=moderate; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a moderately priced restaurant located in the south part of town.\nChunk 2: What type of food are they.\nChunk 3: What is their address?\nChunk 4: Thank you Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=south; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=request_info; area=south; price=moderate; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a moderately priced restaurant located in the south part of town.\nChunk 2: What type of food are they.\nChunk 3: What is their address?\nChunk 4: Thank you Good bye.", "input_token_count": 36, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: south; price: moderate. Next, intent: context_update. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: south; price: moderate.; intent: context_update.; requested information: address..", "trace": "C1 domain=restaurant; area+=south; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a moderately priced restaurant located in the south part of town.", "streaming_reasoning": "Initially, the topic is restaurant; area: south; price: moderate..", "trace": "domain=restaurant; area+=south; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What type of food are they.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is their address?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you Good bye.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is south; price is moderate; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info; area=south; price=moderate; requested_info=address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003573", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Oh, I will have a sweet dream Are you sleepy A little bit.\nChunk 2: I have to go to sleep though I don't want to.\nChunk 3: Yes, I do not want to see ur sleeping in the office.\nChunk 4: Thx.Bye for now Kisssssssssss.", "streaming_reasoning": "C1 casual_comment=will, sweet. C2 leaving_reason=needs_to_go. C3 casual_comment=not, see. C4 casual_comment=thx, bye.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Oh, I will have a sweet dream Are you sleepy A little bit.\nChunk 2: I have to go to sleep though I don't want to.\nChunk 3: Yes, I do not want to see ur sleeping in the office.\nChunk 4: Thx.Bye for now Kisssssssssss."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=will, sweet. C2 leaving_reason=needs_to_go. C3 casual_comment=not, see. C4 casual_comment=thx, bye.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Oh, I will have a sweet dream Are you sleepy A little bit.\nChunk 2: I have to go to sleep though I don't want to.\nChunk 3: Yes, I do not want to see ur sleeping in the office.\nChunk 4: Thx.Bye for now Kisssssssssss.", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on will. Next, leaving reason: needs_to_go. Next, the user comments on not. Finally, the user comments on thx. In summary, leaving reason: needs_to_go..", "trace": "C1 casual_comment=will, sweet. C2 leaving_reason=needs_to_go. C3 casual_comment=not, see. C4 casual_comment=thx, bye.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Oh, I will have a sweet dream Are you sleepy A little bit.", "streaming_reasoning": "Initially, the user comments on will.", "trace": "casual_comment=will, sweet."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I have to go to sleep though I don't want to.", "streaming_reasoning": "As more information arrives, leaving reason: needs_to_go..", "trace": "leaving_reason=needs_to_go."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I do not want to see ur sleeping in the office.", "streaming_reasoning": "As more information arrives, the user comments on not.", "trace": "casual_comment=not, see."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thx.Bye for now Kisssssssssss.", "streaming_reasoning": "Finally, the user comments on thx.", "trace": "casual_comment=thx, bye."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002874", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for a train from Stevenage to Cambridge.\nChunk 2: I am travelling on Monday and need to leave after 16:30 Yes please.\nChunk 3: What is the cost for this train?\nChunk 4: Yes, that would be great.\nChunk 5: Please book for 6 people.\nChunk 6: No, I think I'm all set.\nChunk 7: Thank you for your help!", "streaming_reasoning": "C1 domain=train; goal=search; destination+=cambridge; departure+=stevenage. C2 time+=16:30; day+=monday; destination+=leave after 16:30 yes please; acceptance=selected_option. C3 goal=request_info; requested_info+=price. C4 acceptance=selected_option. C5 goal=booking; party_size+=6 people. C6 goal=modify_constraint. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search, request_info, booking; party_size=6 people; destination=cambridge, leave after 16:30 yes please; departure=stevenage; requested_info=price; when=monday, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I'm looking for a train from Stevenage to Cambridge.\nChunk 2: I am travelling on Monday and need to leave after 16:30 Yes please.\nChunk 3: What is the cost for this train?\nChunk 4: Yes, that would be great.\nChunk 5: Please book for 6 people.\nChunk 6: No, I think I'm all set.\nChunk 7: Thank you for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=cambridge; departure+=stevenage. C2 time+=16:30; day+=monday; destination+=leave after 16:30 yes please; acceptance=selected_option. C3 goal=request_info; requested_info+=price. C4 acceptance=selected_option. C5 goal=booking; party_size+=6 people. C6 goal=modify_constraint. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking; party_size=6 people; destination=cambridge, leave after 16:30 yes please; departure=stevenage; requested_info=price; when=monday, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for a train from Stevenage to Cambridge.\nChunk 2: I am travelling on Monday and need to leave after 16:30 Yes please.\nChunk 3: What is the cost for this train?\nChunk 4: Yes, that would be great.\nChunk 5: Please book for 6 people.\nChunk 6: No, I think I'm all set.\nChunk 7: Thank you for your help!", "input_token_count": 66, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge; departure point: stevenage. Next, time: 16:30; day: monday; destination: leave after 16:30 yes please; acceptance: selected_option. Next, the goal is request info; requested information: price. Next, acceptance: selected_option. Next, the goal is booking; party size: 6 people. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is modify constraint.. destination: cambridge, leave after 16:30 yes please; departure point: stevenage.; time: 16:30; day: monday; acceptance: selected_option.; requested information: price.; party size: 6 people..", "trace": "C1 domain=train; goal=search; destination+=cambridge; departure+=stevenage. C2 time+=16:30; day+=monday; destination+=leave after 16:30 yes please; acceptance=selected_option. C3 goal=request_info; requested_info+=price. C4 acceptance=selected_option. C5 goal=booking; party_size+=6 people. C6 goal=modify_constraint. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I'm looking for a train from Stevenage to Cambridge.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge; departure point: stevenage..", "trace": "domain=train; goal=search; destination+=cambridge; departure+=stevenage."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am travelling on Monday and need to leave after 16:30 Yes please.", "streaming_reasoning": "As more information arrives, time: 16:30; day: monday; destination: leave after 16:30 yes please; acceptance: selected_option..", "trace": "time+=16:30; day+=monday; destination+=leave after 16:30 yes please; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the cost for this train?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, that would be great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please book for 6 people.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 6 people..", "trace": "goal=booking; party_size+=6 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, I think I'm all set.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your help!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 6 people; destination is cambridge; departure point is stevenage; requested information is price; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking; party_size=6 people; destination=cambridge, leave after 16:30 yes please; departure=stevenage; requested_info=price; when=monday, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002875", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a danish restaurant.\nChunk 2: How about north american food?\nChunk 3: What is their phone number and postcode?\nChunk 4: Is there anything else?\nChunk 5: could you give me the phone number and postcode?\nChunk 6: thank you good bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=danish. C2 goal=recommendation; area+=north. C3 goal=request_info; requested_info+=phone, postcode. C4 goal=compare_alternative. C5 goal=request_info. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=search, recommendation, request_info, compare_alternative; area=north; food=danish; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a danish restaurant.\nChunk 2: How about north american food?\nChunk 3: What is their phone number and postcode?\nChunk 4: Is there anything else?\nChunk 5: could you give me the phone number and postcode?\nChunk 6: thank you good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=danish. C2 goal=recommendation; area+=north. C3 goal=request_info; requested_info+=phone, postcode. C4 goal=compare_alternative. C5 goal=request_info. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, recommendation, request_info, compare_alternative; area=north; food=danish; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a danish restaurant.\nChunk 2: How about north american food?\nChunk 3: What is their phone number and postcode?\nChunk 4: Is there anything else?\nChunk 5: could you give me the phone number and postcode?\nChunk 6: thank you good bye.", "input_token_count": 48, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: danish. Next, the goal is recommendation; area: north. Next, the goal is request info; requested information: phone. Next, the goal is compare alternative. Finally, the goal is request info.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info.. cuisine: danish.; area: north.; requested information: phone.", "trace": "C1 domain=restaurant; goal=search; cuisine+=danish. C2 goal=recommendation; area+=north. C3 goal=request_info; requested_info+=phone, postcode. C4 goal=compare_alternative. C5 goal=request_info. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a danish restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: danish..", "trace": "domain=restaurant; goal=search; cuisine+=danish."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "How about north american food?", "streaming_reasoning": "As more information arrives, the goal is recommendation; area: north..", "trace": "goal=recommendation; area+=north."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is their phone number and postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is there anything else?", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "could you give me the phone number and postcode?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "thank you good bye.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; cuisine is danish; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, recommendation, request_info, compare_alternative; area=north; food=danish; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002876", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: am looking for a train.\nChunk 2: The train should arrive by 18:00 and should go to stevenage.\nChunk 3: I am departing from cambridge on Tuesday.\nChunk 4: What one gets me there before, but closest to 18:00?\nChunk 5: No, I have decided not to book today, thank you, goodbye.", "streaming_reasoning": "C1 domain=train; goal=search. C2 time+=18:00; destination+=stevenage. C3 day+=tuesday; departure+=cambridge on tuesday. C4 goal=request_info. C5 goal=booking; day+=today.", "deep_reasoning": "Need domain=train; goal=search, booking; destination=stevenage; departure=cambridge on tuesday; when=tuesday, today, 18:00.", "answer": "Got it. I will use train, tuesday, today, 18:00 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: am looking for a train.\nChunk 2: The train should arrive by 18:00 and should go to stevenage.\nChunk 3: I am departing from cambridge on Tuesday.\nChunk 4: What one gets me there before, but closest to 18:00?\nChunk 5: No, I have decided not to book today, thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 time+=18:00; destination+=stevenage. C3 day+=tuesday; departure+=cambridge on tuesday. C4 goal=request_info. C5 goal=booking; day+=today.\n\nDeep reasoning: Need domain=train; goal=search, booking; destination=stevenage; departure=cambridge on tuesday; when=tuesday, today, 18:00.\n\nAnswer: Got it. I will use train, tuesday, today, 18:00 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: am looking for a train.\nChunk 2: The train should arrive by 18:00 and should go to stevenage.\nChunk 3: I am departing from cambridge on Tuesday.\nChunk 4: What one gets me there before, but closest to 18:00?\nChunk 5: No, I have decided not to book today, thank you, goodbye.", "input_token_count": 56, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, time: 18:00; destination: stevenage. Next, day: tuesday; departure point: cambridge on tuesday. Next, the goal is request info. Finally, the goal is booking; day: today. In summary, The overall topic is train. the goal is booking. time: 18:00; destination: stevenage.; day: tuesday, today.; departure point: cambridge on tuesday..", "trace": "C1 domain=train; goal=search. C2 time+=18:00; destination+=stevenage. C3 day+=tuesday; departure+=cambridge on tuesday. C4 goal=request_info. C5 goal=booking; day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "am looking for a train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The train should arrive by 18:00 and should go to stevenage.", "streaming_reasoning": "As more information arrives, time: 18:00; destination: stevenage..", "trace": "time+=18:00; destination+=stevenage."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am departing from cambridge on Tuesday.", "streaming_reasoning": "As more information arrives, day: tuesday; departure point: cambridge on tuesday..", "trace": "day+=tuesday; departure+=cambridge on tuesday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What one gets me there before, but closest to 18:00?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, I have decided not to book today, thank you, goodbye.", "streaming_reasoning": "Finally, the goal is booking; day: today..", "trace": "goal=booking; day+=today."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is stevenage; departure point is cambridge on tuesday; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use train, tuesday, today, 18:00 and move the task forward.", "deep_reasoning_trace": "Need domain=train; goal=search, booking; destination=stevenage; departure=cambridge on tuesday; when=tuesday, today, 18:00."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002877", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: The time is 20:30.\nChunk 3: Please make a booking.\nChunk 4: No that will be all Thank you!", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 time+=20:30. C3 goal=booking. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking; destination=find a restaurant; when=20:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a restaurant.\nChunk 2: The time is 20:30.\nChunk 3: Please make a booking.\nChunk 4: No that will be all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 time+=20:30. C3 goal=booking. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking; destination=find a restaurant; when=20:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: The time is 20:30.\nChunk 3: Please make a booking.\nChunk 4: No that will be all Thank you!", "input_token_count": 30, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant. Next, time: 20:30. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking.. destination: find a restaurant.; time: 20:30..", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 time+=20:30. C3 goal=booking. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is 20:30.", "streaming_reasoning": "As more information arrives, time: 20:30..", "trace": "time+=20:30."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No that will be all Thank you!", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: destination is find a restaurant; timing is 20:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking; destination=find a restaurant; when=20:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002878", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Where can I find portuguese food Any area.\nChunk 2: What is the address No, thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=request_info; area+=any. C2 requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=any; requested_info=address.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Where can I find portuguese food Any area.\nChunk 2: What is the address No, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=request_info; area+=any. C2 requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=any; requested_info=address.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Where can I find portuguese food Any area.\nChunk 2: What is the address No, thank you.", "input_token_count": 19, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is request info; area: any. Finally, requested information: address. In summary, The overall topic is restaurant. the goal is request info. area: any.; requested information: address..", "trace": "C1 domain=restaurant; goal=request_info; area+=any. C2 requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Where can I find portuguese food Any area.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is request info; area: any..", "trace": "domain=restaurant; goal=request_info; area+=any."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the address No, thank you.", "streaming_reasoning": "Finally, requested information: address..", "trace": "requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is any; requested information is address.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=any; requested_info=address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003579", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok.\nChunk 2: Well, go to www.google.com, and type in Normandy Landing Oh, wow!\nChunk 3: There are lot of sites.\nChunk 4: Here, try this one.\nChunk 5: It's a good site about Normandy Landing.\nChunk 6: Thanks.\nChunk 7: For detailed information, however, you should read a history book.", "streaming_reasoning": "C1 [SKIP: backchannel_only]. C2 casual_comment=www, google. C3 casual_comment=lot, sites. C4 casual_comment=here, try. C5 casual_comment=site, normandy. C6 [SKIP: thanks_only]. C7 casual_comment=detailed, information.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Ok.\nChunk 2: Well, go to www.google.com, and type in Normandy Landing Oh, wow!\nChunk 3: There are lot of sites.\nChunk 4: Here, try this one.\nChunk 5: It's a good site about Normandy Landing.\nChunk 6: Thanks.\nChunk 7: For detailed information, however, you should read a history book."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: backchannel_only]. C2 casual_comment=www, google. C3 casual_comment=lot, sites. C4 casual_comment=here, try. C5 casual_comment=site, normandy. C6 [SKIP: thanks_only]. C7 casual_comment=detailed, information.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok.\nChunk 2: Well, go to www.google.com, and type in Normandy Landing Oh, wow!\nChunk 3: There are lot of sites.\nChunk 4: Here, try this one.\nChunk 5: It's a good site about Normandy Landing.\nChunk 6: Thanks.\nChunk 7: For detailed information, however, you should read a history book.", "input_token_count": 55, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on www. Next, the user comments on lot. Next, the user comments on here. Next, the user comments on site. Finally, the user comments on detailed.  Some chunks were skipped because they contained backchannel_only or thanks_only.", "trace": "C1 [SKIP: backchannel_only]. C2 casual_comment=www, google. C3 casual_comment=lot, sites. C4 casual_comment=here, try. C5 casual_comment=site, normandy. C6 [SKIP: thanks_only]. C7 casual_comment=detailed, information.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Ok.", "streaming_reasoning": "The content at C1 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Well, go to www.google.com, and type in Normandy Landing Oh, wow!", "streaming_reasoning": "As more information arrives, the user comments on www.", "trace": "casual_comment=www, google."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "There are lot of sites.", "streaming_reasoning": "As more information arrives, the user comments on lot.", "trace": "casual_comment=lot, sites."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Here, try this one.", "streaming_reasoning": "As more information arrives, the user comments on here.", "trace": "casual_comment=here, try."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It's a good site about Normandy Landing.", "streaming_reasoning": "As more information arrives, the user comments on site.", "trace": "casual_comment=site, normandy."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "For detailed information, however, you should read a history book.", "streaming_reasoning": "Finally, the user comments on detailed.", "trace": "casual_comment=detailed, information."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002879", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you try a moderate price place,4 stars in the east.\nChunk 2: A guesthouse is fine also.\nChunk 3: I want to find a hotel.\nChunk 4: It is for 4 people.\nChunk 5: The time is thursday.\nChunk 6: Please make a booking.\nChunk 7: I'm also looking for a place my friend recommended to eat The Peking restaurant?\nChunk 8: Can you find it for me?\nChunk 9: i am also looking for a restaurant called peking restaurant where is it found?\nChunk 10: and what is their food type?\nChunk 11: What area is the restaurant in Thank you!\nChunk 12: That will be all Goodbye!", "streaming_reasoning": "C1 area+=east; price+=moderate; stars+=4 stars; requested_info+=price. C2 domain=hotel; hotel_type+=guesthouse. C3 goal=search; hotel_type+=hotel; destination+=find a hotel. C4 party_size+=4 people. C5 day+=thursday. C6 goal=booking. C7 domain=restaurant; destination+=eat the peking restaurant. C8 [SKIP: repeated_information]. C9 goal=request_info. C10 goal=request_info. C11 intent=context_update. C12 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, booking, request_info; area=east; price=moderate; party_size=4 people; stars=4 stars; destination=find a hotel, eat the peking restaurant; requested_info=price; when=thursday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Could you try a moderate price place,4 stars in the east.\nChunk 2: A guesthouse is fine also.\nChunk 3: I want to find a hotel.\nChunk 4: It is for 4 people.\nChunk 5: The time is thursday.\nChunk 6: Please make a booking.\nChunk 7: I'm also looking for a place my friend recommended to eat The Peking restaurant?\nChunk 8: Can you find it for me?\nChunk 9: i am also looking for a restaurant called peking restaurant where is it found?\nChunk 10: and what is their food type?\nChunk 11: What area is the restaurant in Thank you!\nChunk 12: That will be all Goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=east; price+=moderate; stars+=4 stars; requested_info+=price. C2 domain=hotel; hotel_type+=guesthouse. C3 goal=search; hotel_type+=hotel; destination+=find a hotel. C4 party_size+=4 people. C5 day+=thursday. C6 goal=booking. C7 domain=restaurant; destination+=eat the peking restaurant. C8 [SKIP: repeated_information]. C9 goal=request_info. C10 goal=request_info. C11 intent=context_update. C12 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, booking, request_info; area=east; price=moderate; party_size=4 people; stars=4 stars; destination=find a hotel, eat the peking restaurant; requested_info=price; when=thursday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Could you try a moderate price place,4 stars in the east.\nChunk 2: A guesthouse is fine also.\nChunk 3: I want to find a hotel.\nChunk 4: It is for 4 people.\nChunk 5: The time is thursday.\nChunk 6: Please make a booking.\nChunk 7: I'm also looking for a place my friend recommended to eat The Peking restaurant?\nChunk 8: Can you find it for me?\nChunk 9: i am also looking for a restaurant called peking restaurant where is it found?\nChunk 10: and what is their food type?\nChunk 11: What area is the restaurant in Thank you!\nChunk 12: That will be all Goodbye!", "input_token_count": 113, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, area: east; price: moderate; star rating: 4 stars; requested information: price. Next, the topic is hotel; hotel type: guesthouse. Next, the goal is search; hotel type: hotel; destination: find a hotel. Next, party size: 4 people. Next, day: thursday. Next, the goal is booking. Next, the topic is restaurant; destination: eat the peking restaurant. Next, the goal is request info. Next, the goal is request info. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is restaurant. the goal is request info.. area: east; price: moderate; star rating: 4 stars; requested information: price.; hotel type: guesthouse., hotel; destination: find a hotel., eat the peking restaurant.; party size: 4 people.; day: thursday.; intent: context_update..", "trace": "C1 area+=east; price+=moderate; stars+=4 stars; requested_info+=price. C2 domain=hotel; hotel_type+=guesthouse. C3 goal=search; hotel_type+=hotel; destination+=find a hotel. C4 party_size+=4 people. C5 day+=thursday. C6 goal=booking. C7 domain=restaurant; destination+=eat the peking restaurant. C8 [SKIP: repeated_information]. C9 goal=request_info. C10 goal=request_info. C11 intent=context_update. C12 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Could you try a moderate price place,4 stars in the east.", "streaming_reasoning": "Initially, area: east; price: moderate; star rating: 4 stars; requested information: price..", "trace": "area+=east; price+=moderate; stars+=4 stars; requested_info+=price."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "A guesthouse is fine also.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: guesthouse..", "trace": "domain=hotel; hotel_type+=guesthouse."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the goal is search; hotel type: hotel; destination: find a hotel..", "trace": "goal=search; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "It is for 4 people.", "streaming_reasoning": "As more information arrives, party size: 4 people..", "trace": "party_size+=4 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "The time is thursday.", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'm also looking for a place my friend recommended to eat The Peking restaurant?", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: eat the peking restaurant..", "trace": "domain=restaurant; destination+=eat the peking restaurant."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Can you find it for me?", "streaming_reasoning": "The content at C8 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "i am also looking for a restaurant called peking restaurant where is it found?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "and what is their food type?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "What area is the restaurant in Thank you!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C12", "chunk_index": 11, "observed_text": "That will be all Goodbye!", "streaming_reasoning": "The content at C12 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is east; price is moderate; party size is 4 people; star rating is 4 stars; destination is find a hotel; requested information is price; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, booking, request_info; area=east; price=moderate; party_size=4 people; stars=4 stars; destination=find a hotel, eat the peking restaurant; requested_info=price; when=thursday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002880", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you.\nChunk 2: I also need a hotel in the south.\nChunk 3: No price range but I do want a 4 start That sounds great.\nChunk 4: I'll need a reservation for 6 people for 4 nights on Thursday.\nChunk 5: No, that takes care of everything I need.\nChunk 6: Thanks!\nChunk 7: I don't need a taxi, thanks for asking.\nChunk 8: Goodbye, and thanks again.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; area+=south; hotel_type+=hotel. C3 goal=modify_constraint. C4 goal=booking; day+=thursday; party_size+=6 people; stay_length+=4 nights. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only]. C7 domain=taxi. C8 intent=context_update.", "deep_reasoning": "Need domain=hotel, taxi; goal=search, booking; area=south; party_size=6 people; stay_length=4 nights; when=thursday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thank you.\nChunk 2: I also need a hotel in the south.\nChunk 3: No price range but I do want a 4 start That sounds great.\nChunk 4: I'll need a reservation for 6 people for 4 nights on Thursday.\nChunk 5: No, that takes care of everything I need.\nChunk 6: Thanks!\nChunk 7: I don't need a taxi, thanks for asking.\nChunk 8: Goodbye, and thanks again."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; area+=south; hotel_type+=hotel. C3 goal=modify_constraint. C4 goal=booking; day+=thursday; party_size+=6 people; stay_length+=4 nights. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only]. C7 domain=taxi. C8 intent=context_update.\n\nDeep reasoning: Need domain=hotel, taxi; goal=search, booking; area=south; party_size=6 people; stay_length=4 nights; when=thursday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thank you.\nChunk 2: I also need a hotel in the south.\nChunk 3: No price range but I do want a 4 start That sounds great.\nChunk 4: I'll need a reservation for 6 people for 4 nights on Thursday.\nChunk 5: No, that takes care of everything I need.\nChunk 6: Thanks!\nChunk 7: I don't need a taxi, thanks for asking.\nChunk 8: Goodbye, and thanks again.", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: south; hotel type: hotel. Next, the goal is modify constraint. Next, the goal is booking; day: thursday; party size: 6 people; stay length: 4 nights. Next, the topic is taxi. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is taxi.. the goal is booking. area: south; hotel type: hotel.; day: thursday; party size: 6 people; stay length: 4 nights.; intent: context_update..", "trace": "C1 [SKIP: thanks_only]. C2 domain=hotel; goal=search; area+=south; hotel_type+=hotel. C3 goal=modify_constraint. C4 goal=booking; day+=thursday; party_size+=6 people; stay_length+=4 nights. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only]. C7 domain=taxi. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thank you.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need a hotel in the south.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; area: south; hotel type: hotel..", "trace": "domain=hotel; goal=search; area+=south; hotel_type+=hotel."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No price range but I do want a 4 start That sounds great.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'll need a reservation for 6 people for 4 nights on Thursday.", "streaming_reasoning": "As more information arrives, the goal is booking; day: thursday; party size: 6 people; stay length: 4 nights..", "trace": "goal=booking; day+=thursday; party_size+=6 people; stay_length+=4 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, that takes care of everything I need.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I don't need a taxi, thanks for asking.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Goodbye, and thanks again.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is south; party size is 6 people; stay length is 4 nights; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, taxi; goal=search, booking; area=south; party_size=6 people; stay_length=4 nights; when=thursday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002881", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a local restaurant, and also places to go while I am in Cambridge.\nChunk 2: East part and where there is entertainment,I also need address and phone number Awesome.\nChunk 3: I'm also looking for the sitar tandoori That's the one.\nChunk 4: Could you book a table for 3 on Sunday?\nChunk 5: We'd like the reservation made for 13:00 if possible.\nChunk 6: No, you have been great.\nChunk 7: Have a great day.\nChunk 8: Bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=go while i am in cambridge. C2 goal=request_info; area+=east; requested_info+=address, phone. C3 intent=context_update. C4 goal=booking; day+=sunday. C5 time+=13:00. C6 goal=modify_constraint. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, booking; area=east; destination=go while i am in cambridge; requested_info=address, phone; when=sunday, 13:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a local restaurant, and also places to go while I am in Cambridge.\nChunk 2: East part and where there is entertainment,I also need address and phone number Awesome.\nChunk 3: I'm also looking for the sitar tandoori That's the one.\nChunk 4: Could you book a table for 3 on Sunday?\nChunk 5: We'd like the reservation made for 13:00 if possible.\nChunk 6: No, you have been great.\nChunk 7: Have a great day.\nChunk 8: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=go while i am in cambridge. C2 goal=request_info; area+=east; requested_info+=address, phone. C3 intent=context_update. C4 goal=booking; day+=sunday. C5 time+=13:00. C6 goal=modify_constraint. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, booking; area=east; destination=go while i am in cambridge; requested_info=address, phone; when=sunday, 13:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a local restaurant, and also places to go while I am in Cambridge.\nChunk 2: East part and where there is entertainment,I also need address and phone number Awesome.\nChunk 3: I'm also looking for the sitar tandoori That's the one.\nChunk 4: Could you book a table for 3 on Sunday?\nChunk 5: We'd like the reservation made for 13:00 if possible.\nChunk 6: No, you have been great.\nChunk 7: Have a great day.\nChunk 8: Bye.", "input_token_count": 87, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: go while i am in cambridge. Next, the goal is request info; area: east; requested information: address. Next, intent: context_update. Next, the goal is booking; day: sunday. Next, time: 13:00. Finally, the goal is modify constraint.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is modify constraint.. destination: go while i am in cambridge.; area: east; requested information: address; intent: context_update.; day: sunday.; time: 13:00..", "trace": "C1 domain=restaurant; goal=search; destination+=go while i am in cambridge. C2 goal=request_info; area+=east; requested_info+=address, phone. C3 intent=context_update. C4 goal=booking; day+=sunday. C5 time+=13:00. C6 goal=modify_constraint. C7 [SKIP: closing_only]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a local restaurant, and also places to go while I am in Cambridge.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: go while i am in cambridge..", "trace": "domain=restaurant; goal=search; destination+=go while i am in cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "East part and where there is entertainment,I also need address and phone number Awesome.", "streaming_reasoning": "As more information arrives, the goal is request info; area: east; requested information: address.", "trace": "goal=request_info; area+=east; requested_info+=address, phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm also looking for the sitar tandoori That's the one.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you book a table for 3 on Sunday?", "streaming_reasoning": "As more information arrives, the goal is booking; day: sunday..", "trace": "goal=booking; day+=sunday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "We'd like the reservation made for 13:00 if possible.", "streaming_reasoning": "As more information arrives, time: 13:00..", "trace": "time+=13:00."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, you have been great.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Bye.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is east; destination is go while i am in cambridge; requested information is address; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, booking; area=east; destination=go while i am in cambridge; requested_info=address, phone; when=sunday, 13:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002882", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to get to a restaurant known as the Lucky star.\nChunk 2: Thanks, please make a reservation there for 2 people at 18:00 on saturday.\nChunk 3: Sure, do they have any openings at 17:00?", "streaming_reasoning": "C1 domain=restaurant; goal=request_info. C2 [SKIP: thanks_only]. C3 time+=17:00.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; when=17:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to get to a restaurant known as the Lucky star.\nChunk 2: Thanks, please make a reservation there for 2 people at 18:00 on saturday.\nChunk 3: Sure, do they have any openings at 17:00?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=request_info. C2 [SKIP: thanks_only]. C3 time+=17:00.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; when=17:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to get to a restaurant known as the Lucky star.\nChunk 2: Thanks, please make a reservation there for 2 people at 18:00 on saturday.\nChunk 3: Sure, do they have any openings at 17:00?", "input_token_count": 41, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is request info. Finally, time: 17:00.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info.. time: 17:00..", "trace": "C1 domain=restaurant; goal=request_info. C2 [SKIP: thanks_only]. C3 time+=17:00.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to get to a restaurant known as the Lucky star.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is request info..", "trace": "domain=restaurant; goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks, please make a reservation there for 2 people at 18:00 on saturday.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Sure, do they have any openings at 17:00?", "streaming_reasoning": "Finally, time: 17:00..", "trace": "time+=17:00."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: timing is 17:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; when=17:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002883", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need information on the home from home hotel.\nChunk 2: Thanks so much for your help That's all.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need information on the home from home hotel.\nChunk 2: Thanks so much for your help That's all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel. C2 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need information on the home from home hotel.\nChunk 2: Thanks so much for your help That's all.", "input_token_count": 21, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is search. hotel type: hotel..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need information on the home from home hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks so much for your help That's all.", "streaming_reasoning": "The content at C2 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need domain=hotel; goal=search; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002884", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Does Finches Bed and Breakfast have free wifi?\nChunk 2: Since they both have free parking, I might as well go with the cheaper price.\nChunk 3: It is for 3 people.\nChunk 4: The time is wednesday, 4.\nChunk 5: Fantastic, I'd also like a train leaving on Sunday, please.\nChunk 6: Will be leaving Cambridge & going to Kings Lynn.\nChunk 7: Wanted to arrive by 12:00.\nChunk 8: No, I just need the departure time.\nChunk 9: How long of a trip is it?\nChunk 10: Thank you very much for your help.", "streaming_reasoning": "C1 domain=restaurant; amenities+=wifi, breakfast. C2 price+=cheap; amenities+=parking, free parking. C3 party_size+=3 people. C4 time+=4; day+=wednesday. C5 domain=train; day+=sunday. C6 destination+=kings lynn. C7 time+=12:00; destination+=arrive by 12:00. C8 goal=search. C9 requested_info+=travel_time. C10 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, train; goal=search; price=cheap; party_size=3 people; amenities=wifi, breakfast, parking, free parking; destination=kings lynn, arrive by 12:00; requested_info=travel_time; when=wednesday, sunday, 4, 12:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Does Finches Bed and Breakfast have free wifi?\nChunk 2: Since they both have free parking, I might as well go with the cheaper price.\nChunk 3: It is for 3 people.\nChunk 4: The time is wednesday, 4.\nChunk 5: Fantastic, I'd also like a train leaving on Sunday, please.\nChunk 6: Will be leaving Cambridge & going to Kings Lynn.\nChunk 7: Wanted to arrive by 12:00.\nChunk 8: No, I just need the departure time.\nChunk 9: How long of a trip is it?\nChunk 10: Thank you very much for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; amenities+=wifi, breakfast. C2 price+=cheap; amenities+=parking, free parking. C3 party_size+=3 people. C4 time+=4; day+=wednesday. C5 domain=train; day+=sunday. C6 destination+=kings lynn. C7 time+=12:00; destination+=arrive by 12:00. C8 goal=search. C9 requested_info+=travel_time. C10 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, train; goal=search; price=cheap; party_size=3 people; amenities=wifi, breakfast, parking, free parking; destination=kings lynn, arrive by 12:00; requested_info=travel_time; when=wednesday, sunday, 4, 12:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Does Finches Bed and Breakfast have free wifi?\nChunk 2: Since they both have free parking, I might as well go with the cheaper price.\nChunk 3: It is for 3 people.\nChunk 4: The time is wednesday, 4.\nChunk 5: Fantastic, I'd also like a train leaving on Sunday, please.\nChunk 6: Will be leaving Cambridge & going to Kings Lynn.\nChunk 7: Wanted to arrive by 12:00.\nChunk 8: No, I just need the departure time.\nChunk 9: How long of a trip is it?\nChunk 10: Thank you very much for your help.", "input_token_count": 98, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; amenities: wifi. Next, price: cheap; amenities: parking. Next, party size: 3 people. Next, time: 4; day: wednesday. Next, the topic is train; day: sunday. Next, destination: kings lynn. Next, time: 12:00; destination: arrive by 12:00. Next, the goal is search. Finally, requested information: travel_time.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is search.. amenities: wifi, parking; price: cheap; party size: 3 people.; time: 4, 12:00; day: wednesday., sunday.; destination: kings lynn., arrive by 12:00.; requested information: travel_time..", "trace": "C1 domain=restaurant; amenities+=wifi, breakfast. C2 price+=cheap; amenities+=parking, free parking. C3 party_size+=3 people. C4 time+=4; day+=wednesday. C5 domain=train; day+=sunday. C6 destination+=kings lynn. C7 time+=12:00; destination+=arrive by 12:00. C8 goal=search. C9 requested_info+=travel_time. C10 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Does Finches Bed and Breakfast have free wifi?", "streaming_reasoning": "Initially, the topic is restaurant; amenities: wifi.", "trace": "domain=restaurant; amenities+=wifi, breakfast."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Since they both have free parking, I might as well go with the cheaper price.", "streaming_reasoning": "As more information arrives, price: cheap; amenities: parking.", "trace": "price+=cheap; amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 3 people.", "streaming_reasoning": "As more information arrives, party size: 3 people..", "trace": "party_size+=3 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is wednesday, 4.", "streaming_reasoning": "As more information arrives, time: 4; day: wednesday..", "trace": "time+=4; day+=wednesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Fantastic, I'd also like a train leaving on Sunday, please.", "streaming_reasoning": "As more information arrives, the topic is train; day: sunday..", "trace": "domain=train; day+=sunday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Will be leaving Cambridge & going to Kings Lynn.", "streaming_reasoning": "As more information arrives, destination: kings lynn..", "trace": "destination+=kings lynn."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Wanted to arrive by 12:00.", "streaming_reasoning": "As more information arrives, time: 12:00; destination: arrive by 12:00..", "trace": "time+=12:00; destination+=arrive by 12:00."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, I just need the departure time.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "How long of a trip is it?", "streaming_reasoning": "As more information arrives, requested information: travel_time..", "trace": "requested_info+=travel_time."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thank you very much for your help.", "streaming_reasoning": "The content at C10 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: price is cheap; party size is 3 people; amenities is wifi; destination is kings lynn; requested information is travel_time; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, train; goal=search; price=cheap; party_size=3 people; amenities=wifi, breakfast, parking, free parking; destination=kings lynn, arrive by 12:00; requested_info=travel_time; when=wednesday, sunday, 4, 12:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002885", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to book a taxi from the hamilton lodge to restaurant one seven.\nChunk 2: I'd like to arrive by 21:30.\nChunk 3: Thank you for your help, goodbye!", "streaming_reasoning": "C1 domain=taxi; goal=booking; destination+=restaurant one seven; departure+=the hamilton lodge. C2 time+=21:30; destination+=arrive by 21:30. C3 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, taxi; goal=booking; destination=restaurant one seven, arrive by 21:30; departure=the hamilton lodge; when=21:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to book a taxi from the hamilton lodge to restaurant one seven.\nChunk 2: I'd like to arrive by 21:30.\nChunk 3: Thank you for your help, goodbye!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=booking; destination+=restaurant one seven; departure+=the hamilton lodge. C2 time+=21:30; destination+=arrive by 21:30. C3 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, taxi; goal=booking; destination=restaurant one seven, arrive by 21:30; departure=the hamilton lodge; when=21:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to book a taxi from the hamilton lodge to restaurant one seven.\nChunk 2: I'd like to arrive by 21:30.\nChunk 3: Thank you for your help, goodbye!", "input_token_count": 34, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is booking; destination: restaurant one seven; departure point: the hamilton lodge. Finally, time: 21:30; destination: arrive by 21:30.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is taxi. the goal is booking. destination: restaurant one seven, arrive by 21:30.; departure point: the hamilton lodge.; time: 21:30.", "trace": "C1 domain=taxi; goal=booking; destination+=restaurant one seven; departure+=the hamilton lodge. C2 time+=21:30; destination+=arrive by 21:30. C3 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to book a taxi from the hamilton lodge to restaurant one seven.", "streaming_reasoning": "Initially, the topic is taxi; the goal is booking; destination: restaurant one seven; departure point: the hamilton lodge..", "trace": "domain=taxi; goal=booking; destination+=restaurant one seven; departure+=the hamilton lodge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd like to arrive by 21:30.", "streaming_reasoning": "As more information arrives, time: 21:30; destination: arrive by 21:30..", "trace": "time+=21:30; destination+=arrive by 21:30."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you for your help, goodbye!", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: destination is restaurant one seven; departure point is the hamilton lodge; timing is 21:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi; goal=booking; destination=restaurant one seven, arrive by 21:30; departure=the hamilton lodge; when=21:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001927", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I went to the bowling alley yesterday all alone because my friends ditched me.\nChunk 2: I went to the bowling alley yesterday all alone - my friends ditched me.\nChunk 3: That sucks, did you still have fun No, not really.\nChunk 4: I went anyway, because I wanted to have a good time.\nChunk 5: It was rather lonely.", "streaming_reasoning": "C1 emotion=lonely; cause=my friends ditched me; need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 need=encouragement. C5 emotion=lonely; need=validation.", "deep_reasoning": "User feels lonely after my friends ditched me and needs validation.", "answer": "It makes sense to feel lonely after my friends ditched me. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I went to the bowling alley yesterday all alone because my friends ditched me.\nChunk 2: I went to the bowling alley yesterday all alone - my friends ditched me.\nChunk 3: That sucks, did you still have fun No, not really.\nChunk 4: I went anyway, because I wanted to have a good time.\nChunk 5: It was rather lonely."}, {"role": "assistant", "content": "Streaming reasoning: C1 emotion=lonely; cause=my friends ditched me; need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 need=encouragement. C5 emotion=lonely; need=validation.\n\nDeep reasoning: User feels lonely after my friends ditched me and needs validation.\n\nAnswer: It makes sense to feel lonely after my friends ditched me. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I went to the bowling alley yesterday all alone because my friends ditched me.\nChunk 2: I went to the bowling alley yesterday all alone - my friends ditched me.\nChunk 3: That sucks, did you still have fun No, not really.\nChunk 4: I went anyway, because I wanted to have a good time.\nChunk 5: It was rather lonely.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user expresses lonely about my friends ditched me; the user needs validation. Next, the user signals support or acknowledgment. Next, the user needs encouragement. Finally, the user expresses lonely; the user needs validation.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 emotion=lonely; cause=my friends ditched me; need=validation. C2 [SKIP: repeated_information]. C3 support_signal=received. C4 need=encouragement. C5 emotion=lonely; need=validation.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I went to the bowling alley yesterday all alone because my friends ditched me.", "streaming_reasoning": "Initially, the user expresses lonely about my friends ditched me; the user needs validation..", "trace": "emotion=lonely; cause=my friends ditched me; need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I went to the bowling alley yesterday all alone - my friends ditched me.", "streaming_reasoning": "The content at C2 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That sucks, did you still have fun No, not really.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I went anyway, because I wanted to have a good time.", "streaming_reasoning": "As more information arrives, the user needs encouragement..", "trace": "need=encouragement."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It was rather lonely.", "streaming_reasoning": "Finally, the user expresses lonely; the user needs validation..", "trace": "emotion=lonely; need=validation."}]}, "output": {"deep_reasoning": "User feels lonely after my friends ditched me and needs validation.", "answer": "It makes sense to feel lonely after my friends ditched me. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002886", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: where is the nearest police station?\nChunk 2: Yes, could you also give me their postcode?\nChunk 3: No, that will be all thank you.", "streaming_reasoning": "C1 domain=train. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=request_info; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: where is the nearest police station?\nChunk 2: Yes, could you also give me their postcode?\nChunk 3: No, that will be all thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=request_info; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: where is the nearest police station?\nChunk 2: Yes, could you also give me their postcode?\nChunk 3: No, that will be all thank you.", "input_token_count": 27, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train. Finally, the goal is request info; requested information: postcode; acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train.. the goal is request info. requested information: postcode; acceptance: selected_option..", "trace": "C1 domain=train. C2 goal=request_info; requested_info+=postcode; acceptance=selected_option. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "where is the nearest police station?", "streaming_reasoning": "Initially, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, could you also give me their postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=postcode; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, that will be all thank you.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=request_info; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002887", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok, great thanks.\nChunk 2: I also need to find a train going to cambridge.\nChunk 3: I need help with train.\nChunk 4: The time is tuesday, 18:00.\nChunk 5: I would like the travel time, arrival time and price, please Thank you.\nChunk 6: I would like to book that train.\nChunk 7: That was all the info I needed today, thank you.\nChunk 8: Thank you, that's all I need for now.", "streaming_reasoning": "C1 intent=context_update. C2 domain=train; goal=search; destination+=find a train going to cambridge. C3 intent=context_update. C4 time+=18:00; day+=tuesday. C5 goal=request_info; requested_info+=travel_time. C6 goal=booking. C7 day+=today. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info, booking; destination=find a train going to cambridge; requested_info=travel_time; when=tuesday, today, 18:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Ok, great thanks.\nChunk 2: I also need to find a train going to cambridge.\nChunk 3: I need help with train.\nChunk 4: The time is tuesday, 18:00.\nChunk 5: I would like the travel time, arrival time and price, please Thank you.\nChunk 6: I would like to book that train.\nChunk 7: That was all the info I needed today, thank you.\nChunk 8: Thank you, that's all I need for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 domain=train; goal=search; destination+=find a train going to cambridge. C3 intent=context_update. C4 time+=18:00; day+=tuesday. C5 goal=request_info; requested_info+=travel_time. C6 goal=booking. C7 day+=today. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking; destination=find a train going to cambridge; requested_info=travel_time; when=tuesday, today, 18:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Ok, great thanks.\nChunk 2: I also need to find a train going to cambridge.\nChunk 3: I need help with train.\nChunk 4: The time is tuesday, 18:00.\nChunk 5: I would like the travel time, arrival time and price, please Thank you.\nChunk 6: I would like to book that train.\nChunk 7: That was all the info I needed today, thank you.\nChunk 8: Thank you, that's all I need for now.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the topic is train; the goal is search; destination: find a train going to cambridge. Next, intent: context_update. Next, time: 18:00; day: tuesday. Next, the goal is request info; requested information: travel_time. Next, the goal is booking. Finally, day: today.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is booking.. intent: context_update.; destination: find a train going to cambridge.; time: 18:00; day: tuesday., today.; requested information: travel_time..", "trace": "C1 intent=context_update. C2 domain=train; goal=search; destination+=find a train going to cambridge. C3 intent=context_update. C4 time+=18:00; day+=tuesday. C5 goal=request_info; requested_info+=travel_time. C6 goal=booking. C7 day+=today. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Ok, great thanks.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need to find a train going to cambridge.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; destination: find a train going to cambridge..", "trace": "domain=train; goal=search; destination+=find a train going to cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is tuesday, 18:00.", "streaming_reasoning": "As more information arrives, time: 18:00; day: tuesday..", "trace": "time+=18:00; day+=tuesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like the travel time, arrival time and price, please Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I would like to book that train.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That was all the info I needed today, thank you.", "streaming_reasoning": "As more information arrives, day: today..", "trace": "day+=today."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you, that's all I need for now.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is find a train going to cambridge; requested information is travel_time; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking; destination=find a train going to cambridge; requested_info=travel_time; when=tuesday, today, 18:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002888", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with taxi.\nChunk 2: The time is 10:30 Thank you!\nChunk 3: That will be all.", "streaming_reasoning": "C1 domain=taxi; goal=search. C2 time+=10:30. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi; goal=search; when=10:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need help with taxi.\nChunk 2: The time is 10:30 Thank you!\nChunk 3: That will be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=search. C2 time+=10:30. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi; goal=search; when=10:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need help with taxi.\nChunk 2: The time is 10:30 Thank you!\nChunk 3: That will be all.", "input_token_count": 22, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is search. Finally, time: 10:30.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi. the goal is search.. time: 10:30..", "trace": "C1 domain=taxi; goal=search. C2 time+=10:30. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need help with taxi.", "streaming_reasoning": "Initially, the topic is taxi; the goal is search..", "trace": "domain=taxi; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is 10:30 Thank you!", "streaming_reasoning": "As more information arrives, time: 10:30..", "trace": "time+=10:30."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That will be all.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: timing is 10:30. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi; goal=search; when=10:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002889", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to to book it for 1 people and 5 nights starting from tuesday.\nChunk 2: I'm looking for a North Indian restaurant that's near the guesthouse.\nChunk 3: Can you find one?\nChunk 4: Can we find one that serves Italian food instead then?\nChunk 5: Yes that would be great, can you book that please?\nChunk 6: I need it for 18:15 for one person on a Tuesday Thanks so much.\nChunk 7: That is all I need.\nChunk 8: Have a great day.\nChunk 9: Bye.", "streaming_reasoning": "C1 goal=booking; time+=1, 5; day+=tuesday; party_size+=1 people; stay_length+=5 nights. C2 domain=hotel; goal=search; area+=north; cuisine+=indian; hotel_type+=guesthouse. C3 goal=request_info. C4 goal=compare_alternative; cuisine+=italian. C5 [SKIP: repeated_information]. C6 time+=18:15. C7 [SKIP: closing_only]. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, hotel; goal=booking, search, compare_alternative; area=north; food=indian, italian; party_size=1 people; stay_length=5 nights; when=tuesday, 1, 5, 18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'd like to to book it for 1 people and 5 nights starting from tuesday.\nChunk 2: I'm looking for a North Indian restaurant that's near the guesthouse.\nChunk 3: Can you find one?\nChunk 4: Can we find one that serves Italian food instead then?\nChunk 5: Yes that would be great, can you book that please?\nChunk 6: I need it for 18:15 for one person on a Tuesday Thanks so much.\nChunk 7: That is all I need.\nChunk 8: Have a great day.\nChunk 9: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking; time+=1, 5; day+=tuesday; party_size+=1 people; stay_length+=5 nights. C2 domain=hotel; goal=search; area+=north; cuisine+=indian; hotel_type+=guesthouse. C3 goal=request_info. C4 goal=compare_alternative; cuisine+=italian. C5 [SKIP: repeated_information]. C6 time+=18:15. C7 [SKIP: closing_only]. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, hotel; goal=booking, search, compare_alternative; area=north; food=indian, italian; party_size=1 people; stay_length=5 nights; when=tuesday, 1, 5, 18:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'd like to to book it for 1 people and 5 nights starting from tuesday.\nChunk 2: I'm looking for a North Indian restaurant that's near the guesthouse.\nChunk 3: Can you find one?\nChunk 4: Can we find one that serves Italian food instead then?\nChunk 5: Yes that would be great, can you book that please?\nChunk 6: I need it for 18:15 for one person on a Tuesday Thanks so much.\nChunk 7: That is all I need.\nChunk 8: Have a great day.\nChunk 9: Bye.", "input_token_count": 93, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking; time: 1; day: tuesday; party size: 1 people; stay length: 5 nights. Next, the topic is hotel; the goal is search; area: north; cuisine: indian; hotel type: guesthouse. Next, the goal is request info. Next, the goal is compare alternative; cuisine: italian. Finally, time: 18:15.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is hotel. the goal is compare alternative. time: 1, 18:15.; day: tuesday; party size: 1 people; stay length: 5 nights.; area: north; cuisine: indian, italian.; hotel type: guesthouse..", "trace": "C1 goal=booking; time+=1, 5; day+=tuesday; party_size+=1 people; stay_length+=5 nights. C2 domain=hotel; goal=search; area+=north; cuisine+=indian; hotel_type+=guesthouse. C3 goal=request_info. C4 goal=compare_alternative; cuisine+=italian. C5 [SKIP: repeated_information]. C6 time+=18:15. C7 [SKIP: closing_only]. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'd like to to book it for 1 people and 5 nights starting from tuesday.", "streaming_reasoning": "Initially, the goal is booking; time: 1; day: tuesday; party size: 1 people; stay length: 5 nights..", "trace": "goal=booking; time+=1, 5; day+=tuesday; party_size+=1 people; stay_length+=5 nights."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm looking for a North Indian restaurant that's near the guesthouse.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; area: north; cuisine: indian; hotel type: guesthouse..", "trace": "domain=hotel; goal=search; area+=north; cuisine+=indian; hotel_type+=guesthouse."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you find one?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can we find one that serves Italian food instead then?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; cuisine: italian..", "trace": "goal=compare_alternative; cuisine+=italian."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes that would be great, can you book that please?", "streaming_reasoning": "The content at C5 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need it for 18:15 for one person on a Tuesday Thanks so much.", "streaming_reasoning": "As more information arrives, time: 18:15..", "trace": "time+=18:15."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Bye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of booking. Key information: area is north; cuisine is indian; party size is 1 people; stay length is 5 nights; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, hotel; goal=booking, search, compare_alternative; area=north; food=indian, italian; party_size=1 people; stay_length=5 nights; when=tuesday, 1, 5, 18:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002890", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Does it also include free wifi?\nChunk 2: That sounds good, I would like to book that one.\nChunk 3: book it for the same group of people and 2 nights starting from the same day Sorry.\nChunk 4: For 3 people, starting Monday.\nChunk 5: Thank you, that's all I need.\nChunk 6: bye.\nChunk 7: have a good time.", "streaming_reasoning": "C1 amenities+=wifi. C2 goal=confirm_booking; goal=confirm_booking. C3 time+=2; stay_length+=2 nights. C4 time+=3; day+=monday; party_size+=3 people. C5 [SKIP: closing_only]. C6 [SKIP: closing_only]. C7 intent=context_update.", "deep_reasoning": "Need goal=booking, confirm_booking; party_size=3 people; stay_length=2 nights; amenities=wifi; when=monday, 2, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Does it also include free wifi?\nChunk 2: That sounds good, I would like to book that one.\nChunk 3: book it for the same group of people and 2 nights starting from the same day Sorry.\nChunk 4: For 3 people, starting Monday.\nChunk 5: Thank you, that's all I need.\nChunk 6: bye.\nChunk 7: have a good time."}, {"role": "assistant", "content": "Streaming reasoning: C1 amenities+=wifi. C2 goal=confirm_booking; goal=confirm_booking. C3 time+=2; stay_length+=2 nights. C4 time+=3; day+=monday; party_size+=3 people. C5 [SKIP: closing_only]. C6 [SKIP: closing_only]. C7 intent=context_update.\n\nDeep reasoning: Need goal=booking, confirm_booking; party_size=3 people; stay_length=2 nights; amenities=wifi; when=monday, 2, 3; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Does it also include free wifi?\nChunk 2: That sounds good, I would like to book that one.\nChunk 3: book it for the same group of people and 2 nights starting from the same day Sorry.\nChunk 4: For 3 people, starting Monday.\nChunk 5: Thank you, that's all I need.\nChunk 6: bye.\nChunk 7: have a good time.", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, amenities: wifi. Next, the goal is confirm booking. Next, time: 2; stay length: 2 nights. Next, time: 3; day: monday; party size: 3 people. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, the goal is confirm booking.. amenities: wifi.; time: 2, 3; stay length: 2 nights.; day: monday; party size: 3 people.; intent: context_update..", "trace": "C1 amenities+=wifi. C2 goal=confirm_booking; goal=confirm_booking. C3 time+=2; stay_length+=2 nights. C4 time+=3; day+=monday; party_size+=3 people. C5 [SKIP: closing_only]. C6 [SKIP: closing_only]. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Does it also include free wifi?", "streaming_reasoning": "Initially, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "That sounds good, I would like to book that one.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "book it for the same group of people and 2 nights starting from the same day Sorry.", "streaming_reasoning": "As more information arrives, time: 2; stay length: 2 nights..", "trace": "time+=2; stay_length+=2 nights."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "For 3 people, starting Monday.", "streaming_reasoning": "As more information arrives, time: 3; day: monday; party size: 3 people..", "trace": "time+=3; day+=monday; party_size+=3 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you, that's all I need.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "bye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "have a good time.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "Need goal=booking, confirm_booking; party_size=3 people; stay_length=2 nights; amenities=wifi; when=monday, 2, 3; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002892", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello.\nChunk 2: Can you please recommend a Korean restaurant for me?\nChunk 3: What is their phone number.\nChunk 4: What is the address Thank you, goodbye.", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=recommendation; cuisine+=korean. C3 goal=request_info; requested_info+=phone. C4 requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=recommendation, request_info; food=korean; requested_info=phone, address.", "answer": "I can help with that and include the phone, address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello.\nChunk 2: Can you please recommend a Korean restaurant for me?\nChunk 3: What is their phone number.\nChunk 4: What is the address Thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=recommendation; cuisine+=korean. C3 goal=request_info; requested_info+=phone. C4 requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=recommendation, request_info; food=korean; requested_info=phone, address.\n\nAnswer: I can help with that and include the phone, address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello.\nChunk 2: Can you please recommend a Korean restaurant for me?\nChunk 3: What is their phone number.\nChunk 4: What is the address Thank you, goodbye.", "input_token_count": 30, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is recommendation; cuisine: korean. Next, the goal is request info; requested information: phone. Finally, requested information: address.  Some chunks were skipped because they contained greeting_only. In summary, The overall topic is restaurant. the goal is request info. cuisine: korean.; requested information: phone., address..", "trace": "C1 [SKIP: greeting_only]. C2 domain=restaurant; goal=recommendation; cuisine+=korean. C3 goal=request_info; requested_info+=phone. C4 requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello.", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you please recommend a Korean restaurant for me?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is recommendation; cuisine: korean..", "trace": "domain=restaurant; goal=recommendation; cuisine+=korean."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is their phone number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is the address Thank you, goodbye.", "streaming_reasoning": "Finally, requested information: address..", "trace": "requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: cuisine is korean; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=recommendation, request_info; food=korean; requested_info=phone, address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002893", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for a train for my upcoming trip to Cambridge.\nChunk 2: Can you help me find one?\nChunk 3: I am departing from Bishops Stortfod on Friday.\nChunk 4: I can leave after 9:45.\nChunk 5: I need the train ID.\nChunk 6: Thank you I was also hoping to find a british place to eat in the centre.\nChunk 7: Lets do a moderate one.\nChunk 8: Which would you recommend Yes, please.\nChunk 9: I need the reservation to be for 5 people at 21:00 on Friday.", "streaming_reasoning": "C1 domain=train; goal=search; destination+=cambridge. C2 goal=request_info. C3 day+=friday; departure+=bishops stortfod on friday. C4 time+=9:45. C5 [SKIP: repeated_information]. C6 [SKIP: thanks_only]. C7 price+=moderate. C8 goal=recommendation; acceptance=selected_option. C9 goal=booking; time+=5, 21:00; party_size+=5 people; destination+=be for 5 people at 21:00 on friday.", "deep_reasoning": "Need domain=train; goal=search, recommendation, booking; price=moderate; party_size=5 people; destination=cambridge, be for 5 people at 21:00 on friday; departure=bishops stortfod on friday; when=friday, 9:45, 5, 21:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I'm looking for a train for my upcoming trip to Cambridge.\nChunk 2: Can you help me find one?\nChunk 3: I am departing from Bishops Stortfod on Friday.\nChunk 4: I can leave after 9:45.\nChunk 5: I need the train ID.\nChunk 6: Thank you I was also hoping to find a british place to eat in the centre.\nChunk 7: Lets do a moderate one.\nChunk 8: Which would you recommend Yes, please.\nChunk 9: I need the reservation to be for 5 people at 21:00 on Friday."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=cambridge. C2 goal=request_info. C3 day+=friday; departure+=bishops stortfod on friday. C4 time+=9:45. C5 [SKIP: repeated_information]. C6 [SKIP: thanks_only]. C7 price+=moderate. C8 goal=recommendation; acceptance=selected_option. C9 goal=booking; time+=5, 21:00; party_size+=5 people; destination+=be for 5 people at 21:00 on friday.\n\nDeep reasoning: Need domain=train; goal=search, recommendation, booking; price=moderate; party_size=5 people; destination=cambridge, be for 5 people at 21:00 on friday; departure=bishops stortfod on friday; when=friday, 9:45, 5, 21:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for a train for my upcoming trip to Cambridge.\nChunk 2: Can you help me find one?\nChunk 3: I am departing from Bishops Stortfod on Friday.\nChunk 4: I can leave after 9:45.\nChunk 5: I need the train ID.\nChunk 6: Thank you I was also hoping to find a british place to eat in the centre.\nChunk 7: Lets do a moderate one.\nChunk 8: Which would you recommend Yes, please.\nChunk 9: I need the reservation to be for 5 people at 21:00 on Friday.", "input_token_count": 96, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge. Next, the goal is request info. Next, day: friday; departure point: bishops stortfod on friday. Next, time: 9:45. Next, price: moderate. Next, the goal is recommendation; acceptance: selected_option. Finally, the goal is booking; time: 5; party size: 5 people; destination: be for 5 people at 21:00 on friday.  Some chunks were skipped because they contained repeated_information or thanks_only. In summary, The overall topic is train. the goal is booking. destination: cambridge., be for 5 people at 21:00 on friday.; day: friday; departure point: bishops stortfod on friday.; time: 9:45., 5; price: moderate.; acceptance: selected_option.; party size: 5 people.", "trace": "C1 domain=train; goal=search; destination+=cambridge. C2 goal=request_info. C3 day+=friday; departure+=bishops stortfod on friday. C4 time+=9:45. C5 [SKIP: repeated_information]. C6 [SKIP: thanks_only]. C7 price+=moderate. C8 goal=recommendation; acceptance=selected_option. C9 goal=booking; time+=5, 21:00; party_size+=5 people; destination+=be for 5 people at 21:00 on friday.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I'm looking for a train for my upcoming trip to Cambridge.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: cambridge..", "trace": "domain=train; goal=search; destination+=cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you help me find one?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am departing from Bishops Stortfod on Friday.", "streaming_reasoning": "As more information arrives, day: friday; departure point: bishops stortfod on friday..", "trace": "day+=friday; departure+=bishops stortfod on friday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I can leave after 9:45.", "streaming_reasoning": "As more information arrives, time: 9:45..", "trace": "time+=9:45."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need the train ID.", "streaming_reasoning": "The content at C5 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you I was also hoping to find a british place to eat in the centre.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Lets do a moderate one.", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Which would you recommend Yes, please.", "streaming_reasoning": "As more information arrives, the goal is recommendation; acceptance: selected_option..", "trace": "goal=recommendation; acceptance=selected_option."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I need the reservation to be for 5 people at 21:00 on Friday.", "streaming_reasoning": "Finally, the goal is booking; time: 5; party size: 5 people; destination: be for 5 people at 21:00 on friday..", "trace": "goal=booking; time+=5, 21:00; party_size+=5 people; destination+=be for 5 people at 21:00 on friday."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: price is moderate; party size is 5 people; destination is cambridge; departure point is bishops stortfod on friday; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, recommendation, booking; price=moderate; party_size=5 people; destination=cambridge, be for 5 people at 21:00 on friday; departure=bishops stortfod on friday; when=friday, 9:45, 5, 21:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002894", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find information on saint john's college?\nChunk 2: Is there an exact address, like a street number?\nChunk 3: Thanks!\nChunk 4: Yes, I'm also looking for a train that leaves on Friday after 11:15.\nChunk 5: cambridge is my destination and from leicester.\nChunk 6: Yes, can you book it for 1 person, please Great.\nChunk 7: Thanks for all your help!", "streaming_reasoning": "C1 domain=attraction; goal=search. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 domain=train; time+=11:15; day+=friday; acceptance=selected_option. C5 intent=context_update. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction, train; goal=search, request_info, booking, confirm_booking; requested_info=address; when=friday, 11:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you help me find information on saint john's college?\nChunk 2: Is there an exact address, like a street number?\nChunk 3: Thanks!\nChunk 4: Yes, I'm also looking for a train that leaves on Friday after 11:15.\nChunk 5: cambridge is my destination and from leicester.\nChunk 6: Yes, can you book it for 1 person, please Great.\nChunk 7: Thanks for all your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 domain=train; time+=11:15; day+=friday; acceptance=selected_option. C5 intent=context_update. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction, train; goal=search, request_info, booking, confirm_booking; requested_info=address; when=friday, 11:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you help me find information on saint john's college?\nChunk 2: Is there an exact address, like a street number?\nChunk 3: Thanks!\nChunk 4: Yes, I'm also looking for a train that leaves on Friday after 11:15.\nChunk 5: cambridge is my destination and from leicester.\nChunk 6: Yes, can you book it for 1 person, please Great.\nChunk 7: Thanks for all your help!", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search. Next, the goal is request info; requested information: address. Next, the topic is train; time: 11:15; day: friday; acceptance: selected_option. Next, intent: context_update. Finally, the goal is confirm booking.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is confirm booking.. requested information: address.; time: 11:15; day: friday; acceptance: selected_option.; intent: context_update..", "trace": "C1 domain=attraction; goal=search. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 domain=train; time+=11:15; day+=friday; acceptance=selected_option. C5 intent=context_update. C6 goal=confirm_booking; goal=confirm_booking. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you help me find information on saint john's college?", "streaming_reasoning": "Initially, the topic is attraction; the goal is search..", "trace": "domain=attraction; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there an exact address, like a street number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks!", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I'm also looking for a train that leaves on Friday after 11:15.", "streaming_reasoning": "As more information arrives, the topic is train; time: 11:15; day: friday; acceptance: selected_option..", "trace": "domain=train; time+=11:15; day+=friday; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "cambridge is my destination and from leicester.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, can you book it for 1 person, please Great.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks for all your help!", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, train; goal=search, request_info, booking, confirm_booking; requested_info=address; when=friday, 11:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002895", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks.\nChunk 2: I am also looking for a train from Cambridge to Norwich, could you help me find one?\nChunk 3: I would like to leave on Monday.\nChunk 4: 09:15 and should depart from cambridge.\nChunk 5: Actually, I need to arrive by 09:15.\nChunk 6: Is there anything early morning on Monday from Cambridge to Norwich?\nChunk 7: Yeah, what's the price and departure time on TR5773?\nChunk 8: That's all I needed.\nChunk 9: Thank you for your help.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 domain=train; goal=search; destination+=norwich; departure+=cambridge. C3 day+=monday; destination+=leave on monday. C4 time+=09:15. C5 destination+=arrive by 09:15. C6 goal=request_info. C7 goal=request_info; requested_info+=price. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=norwich, leave on monday, arrive by 09:15; departure=cambridge; requested_info=price; when=monday, 09:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thanks.\nChunk 2: I am also looking for a train from Cambridge to Norwich, could you help me find one?\nChunk 3: I would like to leave on Monday.\nChunk 4: 09:15 and should depart from cambridge.\nChunk 5: Actually, I need to arrive by 09:15.\nChunk 6: Is there anything early morning on Monday from Cambridge to Norwich?\nChunk 7: Yeah, what's the price and departure time on TR5773?\nChunk 8: That's all I needed.\nChunk 9: Thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 domain=train; goal=search; destination+=norwich; departure+=cambridge. C3 day+=monday; destination+=leave on monday. C4 time+=09:15. C5 destination+=arrive by 09:15. C6 goal=request_info. C7 goal=request_info; requested_info+=price. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=norwich, leave on monday, arrive by 09:15; departure=cambridge; requested_info=price; when=monday, 09:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks.\nChunk 2: I am also looking for a train from Cambridge to Norwich, could you help me find one?\nChunk 3: I would like to leave on Monday.\nChunk 4: 09:15 and should depart from cambridge.\nChunk 5: Actually, I need to arrive by 09:15.\nChunk 6: Is there anything early morning on Monday from Cambridge to Norwich?\nChunk 7: Yeah, what's the price and departure time on TR5773?\nChunk 8: That's all I needed.\nChunk 9: Thank you for your help.", "input_token_count": 87, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: norwich; departure point: cambridge. Next, day: monday; destination: leave on monday. Next, time: 09:15. Next, destination: arrive by 09:15. Next, the goal is request info. Finally, the goal is request info; requested information: price.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is train. the goal is request info. destination: norwich, leave on monday., arrive by 09:15.; departure point: cambridge.; day: monday; time: 09:15.; requested information: price..", "trace": "C1 [SKIP: thanks_only]. C2 domain=train; goal=search; destination+=norwich; departure+=cambridge. C3 day+=monday; destination+=leave on monday. C4 time+=09:15. C5 destination+=arrive by 09:15. C6 goal=request_info. C7 goal=request_info; requested_info+=price. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thanks.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am also looking for a train from Cambridge to Norwich, could you help me find one?", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; destination: norwich; departure point: cambridge..", "trace": "domain=train; goal=search; destination+=norwich; departure+=cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to leave on Monday.", "streaming_reasoning": "As more information arrives, day: monday; destination: leave on monday..", "trace": "day+=monday; destination+=leave on monday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "09:15 and should depart from cambridge.", "streaming_reasoning": "As more information arrives, time: 09:15..", "trace": "time+=09:15."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Actually, I need to arrive by 09:15.", "streaming_reasoning": "As more information arrives, destination: arrive by 09:15..", "trace": "destination+=arrive by 09:15."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Is there anything early morning on Monday from Cambridge to Norwich?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yeah, what's the price and departure time on TR5773?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's all I needed.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is norwich; departure point is cambridge; requested information is price; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=norwich, leave on monday, arrive by 09:15; departure=cambridge; requested_info=price; when=monday, 09:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002896", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a moderately priced restaurant in the north part of town.\nChunk 2: Is there anything else in the moderate price range on the north part of town No, thank you.\nChunk 3: That's all I need.", "streaming_reasoning": "C1 domain=restaurant; area+=north; price+=moderate. C2 goal=compare_alternative. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=compare_alternative; area=north; price=moderate; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a moderately priced restaurant in the north part of town.\nChunk 2: Is there anything else in the moderate price range on the north part of town No, thank you.\nChunk 3: That's all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=north; price+=moderate. C2 goal=compare_alternative. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=compare_alternative; area=north; price=moderate; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a moderately priced restaurant in the north part of town.\nChunk 2: Is there anything else in the moderate price range on the north part of town No, thank you.\nChunk 3: That's all I need.", "input_token_count": 41, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: north; price: moderate. Finally, the goal is compare alternative.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is compare alternative.. area: north; price: moderate..", "trace": "C1 domain=restaurant; area+=north; price+=moderate. C2 goal=compare_alternative. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a moderately priced restaurant in the north part of town.", "streaming_reasoning": "Initially, the topic is restaurant; area: north; price: moderate..", "trace": "domain=restaurant; area+=north; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there anything else in the moderate price range on the north part of town No, thank you.", "streaming_reasoning": "As more information arrives, the goal is compare alternative..", "trace": "goal=compare_alternative."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That's all I need.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of compare alternative. Key information: area is north; price is moderate. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=compare_alternative; area=north; price=moderate; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002897", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be traveling to broxbourne on monday from cambridge and need to leave after 8:00.\nChunk 2: Let's go with the one leaving at 08:01.\nChunk 3: Can you book that for five people for me?\nChunk 4: Can i get the reference number Excellent.\nChunk 5: I'm also look for a particular attraction called great saint mary's church.\nChunk 6: What is the address and postcode?\nChunk 7: That is all i need for now.", "streaming_reasoning": "C1 goal=search; time+=8:00; day+=monday; destination+=leave; departure+=cambridge and need. C2 time+=08:01. C3 goal=booking; party_size+=5 people. C4 goal=request_info; requested_info+=reference_number. C5 domain=attraction. C6 requested_info+=address, postcode. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction; goal=search, booking, request_info; party_size=5 people; destination=leave; departure=cambridge and need; requested_info=reference_number, address, postcode; when=monday, 8:00, 08:01; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I will be traveling to broxbourne on monday from cambridge and need to leave after 8:00.\nChunk 2: Let's go with the one leaving at 08:01.\nChunk 3: Can you book that for five people for me?\nChunk 4: Can i get the reference number Excellent.\nChunk 5: I'm also look for a particular attraction called great saint mary's church.\nChunk 6: What is the address and postcode?\nChunk 7: That is all i need for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; time+=8:00; day+=monday; destination+=leave; departure+=cambridge and need. C2 time+=08:01. C3 goal=booking; party_size+=5 people. C4 goal=request_info; requested_info+=reference_number. C5 domain=attraction. C6 requested_info+=address, postcode. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction; goal=search, booking, request_info; party_size=5 people; destination=leave; departure=cambridge and need; requested_info=reference_number, address, postcode; when=monday, 8:00, 08:01; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be traveling to broxbourne on monday from cambridge and need to leave after 8:00.\nChunk 2: Let's go with the one leaving at 08:01.\nChunk 3: Can you book that for five people for me?\nChunk 4: Can i get the reference number Excellent.\nChunk 5: I'm also look for a particular attraction called great saint mary's church.\nChunk 6: What is the address and postcode?\nChunk 7: That is all i need for now.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; time: 8:00; day: monday; destination: leave; departure point: cambridge and need. Next, time: 08:01. Next, the goal is booking; party size: 5 people. Next, the goal is request info; requested information: reference_number. Next, the topic is attraction. Finally, requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction.. the goal is request info. time: 8:00, 08:01.; day: monday; destination: leave; departure point: cambridge and need.; party size: 5 people.; requested information: reference_number., address.", "trace": "C1 goal=search; time+=8:00; day+=monday; destination+=leave; departure+=cambridge and need. C2 time+=08:01. C3 goal=booking; party_size+=5 people. C4 goal=request_info; requested_info+=reference_number. C5 domain=attraction. C6 requested_info+=address, postcode. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I will be traveling to broxbourne on monday from cambridge and need to leave after 8:00.", "streaming_reasoning": "Initially, the goal is search; time: 8:00; day: monday; destination: leave; departure point: cambridge and need..", "trace": "goal=search; time+=8:00; day+=monday; destination+=leave; departure+=cambridge and need."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Let's go with the one leaving at 08:01.", "streaming_reasoning": "As more information arrives, time: 08:01..", "trace": "time+=08:01."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you book that for five people for me?", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 5 people..", "trace": "goal=booking; party_size+=5 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can i get the reference number Excellent.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm also look for a particular attraction called great saint mary's church.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What is the address and postcode?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all i need for now.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: party size is 5 people; destination is leave; departure point is cambridge and need; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, booking, request_info; party_size=5 people; destination=leave; departure=cambridge and need; requested_info=reference_number, address, postcode; when=monday, 8:00, 08:01; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002898", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i need information about attractions in the centre.\nChunk 2: A nightclub would be nice.\nChunk 3: I want to find a british restaurant.\nChunk 4: I also need the phone.\nChunk 5: I also need the postcode Thank you!\nChunk 6: The price range that I would like is expensive.\nChunk 7: Yes please book one of your recommendation for Tuesday at 18:00 for 7 people Thank you goodbye.", "streaming_reasoning": "C1 goal=search; area+=centre. C2 intent=context_update. C3 domain=restaurant; cuisine+=british; destination+=find a british restaurant. C4 goal=request_info; requested_info+=phone. C5 requested_info+=postcode. C6 price+=expensive. C7 goal=confirm_booking; time+=18:00, 7; day+=tuesday; party_size+=7 people; goal=confirm_booking.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, booking, confirm_booking; area=centre; food=british; price=expensive; party_size=7 people; destination=find a british restaurant; requested_info=phone, postcode; when=tuesday, 18:00, 7.", "answer": "I can help with that and include the phone, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i need information about attractions in the centre.\nChunk 2: A nightclub would be nice.\nChunk 3: I want to find a british restaurant.\nChunk 4: I also need the phone.\nChunk 5: I also need the postcode Thank you!\nChunk 6: The price range that I would like is expensive.\nChunk 7: Yes please book one of your recommendation for Tuesday at 18:00 for 7 people Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=centre. C2 intent=context_update. C3 domain=restaurant; cuisine+=british; destination+=find a british restaurant. C4 goal=request_info; requested_info+=phone. C5 requested_info+=postcode. C6 price+=expensive. C7 goal=confirm_booking; time+=18:00, 7; day+=tuesday; party_size+=7 people; goal=confirm_booking.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, booking, confirm_booking; area=centre; food=british; price=expensive; party_size=7 people; destination=find a british restaurant; requested_info=phone, postcode; when=tuesday, 18:00, 7.\n\nAnswer: I can help with that and include the phone, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i need information about attractions in the centre.\nChunk 2: A nightclub would be nice.\nChunk 3: I want to find a british restaurant.\nChunk 4: I also need the phone.\nChunk 5: I also need the postcode Thank you!\nChunk 6: The price range that I would like is expensive.\nChunk 7: Yes please book one of your recommendation for Tuesday at 18:00 for 7 people Thank you goodbye.", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre. Next, intent: context_update. Next, the topic is restaurant; cuisine: british; destination: find a british restaurant. Next, the goal is request info; requested information: phone. Next, requested information: postcode. Next, price: expensive. Finally, the goal is confirm booking.; time: 18:00; day: tuesday; party size: 7 people. In summary, The overall topic is restaurant. the goal is confirm booking.. area: centre.; intent: context_update.; cuisine: british; destination: find a british restaurant.; requested information: phone., postcode.; price: expensive.; time: 18:00; day: tuesday; party size: 7 people.", "trace": "C1 goal=search; area+=centre. C2 intent=context_update. C3 domain=restaurant; cuisine+=british; destination+=find a british restaurant. C4 goal=request_info; requested_info+=phone. C5 requested_info+=postcode. C6 price+=expensive. C7 goal=confirm_booking; time+=18:00, 7; day+=tuesday; party_size+=7 people; goal=confirm_booking.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i need information about attractions in the centre.", "streaming_reasoning": "Initially, the goal is search; area: centre..", "trace": "goal=search; area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "A nightclub would be nice.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a british restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: british; destination: find a british restaurant..", "trace": "domain=restaurant; cuisine+=british; destination+=find a british restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the phone.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the postcode Thank you!", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The price range that I would like is expensive.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes please book one of your recommendation for Tuesday at 18:00 for 7 people Thank you goodbye.", "streaming_reasoning": "Finally, the goal is confirm booking.; time: 18:00; day: tuesday; party size: 7 people.", "trace": "goal=confirm_booking; time+=18:00, 7; day+=tuesday; party_size+=7 people; goal=confirm_booking."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is british; price is expensive; party size is 7 people; destination is find a british restaurant; requested information is phone; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, booking, confirm_booking; area=centre; food=british; price=expensive; party_size=7 people; destination=find a british restaurant; requested_info=phone, postcode; when=tuesday, 18:00, 7."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002899", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to leave bishops stafford and head into cambridge.\nChunk 2: Sounds right, would you book it for 6 people?\nChunk 3: I will need the reference number, thank you.\nChunk 4: I have heard wonderful things about the autumn house hotel.\nChunk 5: Could you provide me with some information on this hotel please?\nChunk 6: Perfect thanks for such great help.\nChunk 7: Could I please have the phone number for the Autumn House No thank you.\nChunk 8: But thank you very much.", "streaming_reasoning": "C1 goal=search; destination+=leave bishops stafford and head into camb. C2 goal=booking; party_size+=6 people. C3 goal=request_info; requested_info+=reference_number. C4 domain=hotel; hotel_type+=hotel. C5 goal=request_info. C6 goal=confirm_booking. C7 requested_info+=phone. C8 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=search, booking, request_info; party_size=6 people; destination=leave bishops stafford and head into camb; requested_info=reference_number, phone.", "answer": "I can help with that and include the reference number, phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need to leave bishops stafford and head into cambridge.\nChunk 2: Sounds right, would you book it for 6 people?\nChunk 3: I will need the reference number, thank you.\nChunk 4: I have heard wonderful things about the autumn house hotel.\nChunk 5: Could you provide me with some information on this hotel please?\nChunk 6: Perfect thanks for such great help.\nChunk 7: Could I please have the phone number for the Autumn House No thank you.\nChunk 8: But thank you very much."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; destination+=leave bishops stafford and head into camb. C2 goal=booking; party_size+=6 people. C3 goal=request_info; requested_info+=reference_number. C4 domain=hotel; hotel_type+=hotel. C5 goal=request_info. C6 goal=confirm_booking. C7 requested_info+=phone. C8 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=search, booking, request_info; party_size=6 people; destination=leave bishops stafford and head into camb; requested_info=reference_number, phone.\n\nAnswer: I can help with that and include the reference number, phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need to leave bishops stafford and head into cambridge.\nChunk 2: Sounds right, would you book it for 6 people?\nChunk 3: I will need the reference number, thank you.\nChunk 4: I have heard wonderful things about the autumn house hotel.\nChunk 5: Could you provide me with some information on this hotel please?\nChunk 6: Perfect thanks for such great help.\nChunk 7: Could I please have the phone number for the Autumn House No thank you.\nChunk 8: But thank you very much.", "input_token_count": 89, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; destination: leave bishops stafford and head into camb. Next, the goal is booking; party size: 6 people. Next, the goal is request info; requested information: reference_number. Next, the topic is hotel; hotel type: hotel. Next, the goal is request info. Next, the goal is confirm booking. Next, requested information: phone. Finally, intent: context_update. In summary, The overall topic is hotel. the goal is confirm booking.. destination: leave bishops stafford and head into camb.; party size: 6 people.; requested information: reference_number., phone.; hotel type: hotel.; intent: context_update..", "trace": "C1 goal=search; destination+=leave bishops stafford and head into camb. C2 goal=booking; party_size+=6 people. C3 goal=request_info; requested_info+=reference_number. C4 domain=hotel; hotel_type+=hotel. C5 goal=request_info. C6 goal=confirm_booking. C7 requested_info+=phone. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need to leave bishops stafford and head into cambridge.", "streaming_reasoning": "Initially, the goal is search; destination: leave bishops stafford and head into camb..", "trace": "goal=search; destination+=leave bishops stafford and head into camb."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Sounds right, would you book it for 6 people?", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 6 people..", "trace": "goal=booking; party_size+=6 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I will need the reference number, thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I have heard wonderful things about the autumn house hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel..", "trace": "domain=hotel; hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Could you provide me with some information on this hotel please?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Perfect thanks for such great help.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Could I please have the phone number for the Autumn House No thank you.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "But thank you very much.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 6 people; destination is leave bishops stafford and head into camb; requested information is reference_number. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number, phone once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking, request_info; party_size=6 people; destination=leave bishops stafford and head into camb; requested_info=reference_number, phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002901", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a college type of attraction Is there any?\nChunk 2: I am looking for something in the West.\nChunk 3: Thanks.\nChunk 4: May I also have the phone number, please.\nChunk 5: I need a taxi to the hotel, please.\nChunk 6: I woule like to leave the hotel at 7:00.\nChunk 7: I will be leaving the hotel, please.", "streaming_reasoning": "C1 domain=attraction; goal=search. C2 area+=west. C3 [SKIP: thanks_only]. C4 goal=request_info; requested_info+=phone. C5 domain=taxi; hotel_type+=hotel; destination+=the hotel. C6 time+=7:00; destination+=leave the hotel at 7:00. C7 intent=context_update.", "deep_reasoning": "Need domain=attraction, hotel, taxi; goal=search, request_info; area=west; destination=the hotel, leave the hotel at 7:00; requested_info=phone; when=7:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a college type of attraction Is there any?\nChunk 2: I am looking for something in the West.\nChunk 3: Thanks.\nChunk 4: May I also have the phone number, please.\nChunk 5: I need a taxi to the hotel, please.\nChunk 6: I woule like to leave the hotel at 7:00.\nChunk 7: I will be leaving the hotel, please."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search. C2 area+=west. C3 [SKIP: thanks_only]. C4 goal=request_info; requested_info+=phone. C5 domain=taxi; hotel_type+=hotel; destination+=the hotel. C6 time+=7:00; destination+=leave the hotel at 7:00. C7 intent=context_update.\n\nDeep reasoning: Need domain=attraction, hotel, taxi; goal=search, request_info; area=west; destination=the hotel, leave the hotel at 7:00; requested_info=phone; when=7:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a college type of attraction Is there any?\nChunk 2: I am looking for something in the West.\nChunk 3: Thanks.\nChunk 4: May I also have the phone number, please.\nChunk 5: I need a taxi to the hotel, please.\nChunk 6: I woule like to leave the hotel at 7:00.\nChunk 7: I will be leaving the hotel, please.", "input_token_count": 68, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search. Next, area: west. Next, the goal is request info; requested information: phone. Next, the topic is taxi; hotel type: hotel; destination: the hotel. Next, time: 7:00; destination: leave the hotel at 7:00. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is taxi. the goal is request info. area: west.; requested information: phone.; hotel type: hotel; destination: the hotel., leave the hotel at 7:00.; time: 7:00; intent: context_update..", "trace": "C1 domain=attraction; goal=search. C2 area+=west. C3 [SKIP: thanks_only]. C4 goal=request_info; requested_info+=phone. C5 domain=taxi; hotel_type+=hotel; destination+=the hotel. C6 time+=7:00; destination+=leave the hotel at 7:00. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a college type of attraction Is there any?", "streaming_reasoning": "Initially, the topic is attraction; the goal is search..", "trace": "domain=attraction; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am looking for something in the West.", "streaming_reasoning": "As more information arrives, area: west..", "trace": "area+=west."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "May I also have the phone number, please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need a taxi to the hotel, please.", "streaming_reasoning": "As more information arrives, the topic is taxi; hotel type: hotel; destination: the hotel..", "trace": "domain=taxi; hotel_type+=hotel; destination+=the hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I woule like to leave the hotel at 7:00.", "streaming_reasoning": "As more information arrives, time: 7:00; destination: leave the hotel at 7:00..", "trace": "time+=7:00; destination+=leave the hotel at 7:00."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I will be leaving the hotel, please.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is west; destination is the hotel; requested information is phone; timing is 7:00. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, hotel, taxi; goal=search, request_info; area=west; destination=the hotel, leave the hotel at 7:00; requested_info=phone; when=7:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002902", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for the Addenbrookes Hospital.\nChunk 2: Can I have the phone number please?\nChunk 3: That will be all.\nChunk 4: Thank you for your help.\nChunk 5: Thank you You, too Goodbye.", "streaming_reasoning": "C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only]. C5 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hospital; goal=search, request_info; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for the Addenbrookes Hospital.\nChunk 2: Can I have the phone number please?\nChunk 3: That will be all.\nChunk 4: Thank you for your help.\nChunk 5: Thank you You, too Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only]. C5 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for the Addenbrookes Hospital.\nChunk 2: Can I have the phone number please?\nChunk 3: That will be all.\nChunk 4: Thank you for your help.\nChunk 5: Thank you You, too Goodbye.", "input_token_count": 38, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hospital. the goal is request info. requested information: phone..", "trace": "C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=phone. C3 [SKIP: closing_only]. C4 [SKIP: thanks_only]. C5 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for the Addenbrookes Hospital.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search..", "trace": "domain=hospital; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I have the phone number please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That will be all.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thank you You, too Goodbye.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002903", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to go boating on the east side Both please.\nChunk 2: Also I still need the restaurant reference number.\nChunk 3: I also need information on a boat attraction on the east.\nChunk 4: Yes, the phone number would be great.\nChunk 5: What is the entrance fee please?\nChunk 6: No, thank you so much for your time.", "streaming_reasoning": "C1 goal=search; area+=east; destination+=go boating on the east side both please. C2 domain=restaurant; goal=request_info; requested_info+=reference_number. C3 domain=attraction. C4 requested_info+=phone; acceptance=selected_option. C5 requested_info+=entrance_fee. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant, attraction; goal=search, request_info; area=east; destination=go boating on the east side both please; requested_info=reference_number, phone, entrance_fee; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to go boating on the east side Both please.\nChunk 2: Also I still need the restaurant reference number.\nChunk 3: I also need information on a boat attraction on the east.\nChunk 4: Yes, the phone number would be great.\nChunk 5: What is the entrance fee please?\nChunk 6: No, thank you so much for your time."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; area+=east; destination+=go boating on the east side both please. C2 domain=restaurant; goal=request_info; requested_info+=reference_number. C3 domain=attraction. C4 requested_info+=phone; acceptance=selected_option. C5 requested_info+=entrance_fee. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant, attraction; goal=search, request_info; area=east; destination=go boating on the east side both please; requested_info=reference_number, phone, entrance_fee; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to go boating on the east side Both please.\nChunk 2: Also I still need the restaurant reference number.\nChunk 3: I also need information on a boat attraction on the east.\nChunk 4: Yes, the phone number would be great.\nChunk 5: What is the entrance fee please?\nChunk 6: No, thank you so much for your time.", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: east; destination: go boating on the east side both please. Next, the topic is restaurant; the goal is request info; requested information: reference_number. Next, the topic is attraction. Next, requested information: phone; acceptance: selected_option. Finally, requested information: entrance_fee.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction.. the goal is request info. area: east; destination: go boating on the east side both please.; requested information: reference_number., phone, entrance_fee.; acceptance: selected_option..", "trace": "C1 goal=search; area+=east; destination+=go boating on the east side both please. C2 domain=restaurant; goal=request_info; requested_info+=reference_number. C3 domain=attraction. C4 requested_info+=phone; acceptance=selected_option. C5 requested_info+=entrance_fee. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to go boating on the east side Both please.", "streaming_reasoning": "Initially, the goal is search; area: east; destination: go boating on the east side both please..", "trace": "goal=search; area+=east; destination+=go boating on the east side both please."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Also I still need the restaurant reference number.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is request info; requested information: reference_number..", "trace": "domain=restaurant; goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need information on a boat attraction on the east.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, the phone number would be great.", "streaming_reasoning": "As more information arrives, requested information: phone; acceptance: selected_option..", "trace": "requested_info+=phone; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What is the entrance fee please?", "streaming_reasoning": "As more information arrives, requested information: entrance_fee..", "trace": "requested_info+=entrance_fee."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, thank you so much for your time.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is east; destination is go boating on the east side both please; requested information is reference_number. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction; goal=search, request_info; area=east; destination=go boating on the east side both please; requested_info=reference_number, phone, entrance_fee; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002904", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: choose for me one that is good and get me the entrance fee and address.\nChunk 2: i also need a place to dine.\nChunk 3: Indian food, in the same area as Clare Hall.\nChunk 4: I would like it to be in the expensive price range.\nChunk 5: Yes.\nChunk 6: Tuesday, 13:00, for 5 people.\nChunk 7: That is all I need Cheers.", "streaming_reasoning": "C1 goal=request_info; requested_info+=address, entrance_fee. C2 destination+=dine. C3 domain=restaurant; goal=modify_constraint; cuisine+=indian. C4 price+=expensive; destination+=be in the expensive price range. C5 [SKIP: acknowledgement_only]. C6 time+=13:00; day+=tuesday; party_size+=5 people. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, modify_constraint; food=indian; price=expensive; party_size=5 people; destination=dine, be in the expensive price range; requested_info=address, entrance_fee; when=tuesday, 13:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: choose for me one that is good and get me the entrance fee and address.\nChunk 2: i also need a place to dine.\nChunk 3: Indian food, in the same area as Clare Hall.\nChunk 4: I would like it to be in the expensive price range.\nChunk 5: Yes.\nChunk 6: Tuesday, 13:00, for 5 people.\nChunk 7: That is all I need Cheers."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address, entrance_fee. C2 destination+=dine. C3 domain=restaurant; goal=modify_constraint; cuisine+=indian. C4 price+=expensive; destination+=be in the expensive price range. C5 [SKIP: acknowledgement_only]. C6 time+=13:00; day+=tuesday; party_size+=5 people. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, modify_constraint; food=indian; price=expensive; party_size=5 people; destination=dine, be in the expensive price range; requested_info=address, entrance_fee; when=tuesday, 13:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: choose for me one that is good and get me the entrance fee and address.\nChunk 2: i also need a place to dine.\nChunk 3: Indian food, in the same area as Clare Hall.\nChunk 4: I would like it to be in the expensive price range.\nChunk 5: Yes.\nChunk 6: Tuesday, 13:00, for 5 people.\nChunk 7: That is all I need Cheers.", "input_token_count": 69, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, destination: dine. Next, the topic is restaurant; the goal is modify constraint; cuisine: indian. Next, price: expensive; destination: be in the expensive price range. Finally, time: 13:00; day: tuesday; party size: 5 people.  Some chunks were skipped because they contained acknowledgement_only or closing_only. In summary, The overall topic is restaurant. the goal is modify constraint. requested information: address; destination: dine., be in the expensive price range.; cuisine: indian.; price: expensive; time: 13:00; day: tuesday; party size: 5 people..", "trace": "C1 goal=request_info; requested_info+=address, entrance_fee. C2 destination+=dine. C3 domain=restaurant; goal=modify_constraint; cuisine+=indian. C4 price+=expensive; destination+=be in the expensive price range. C5 [SKIP: acknowledgement_only]. C6 time+=13:00; day+=tuesday; party_size+=5 people. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "choose for me one that is good and get me the entrance fee and address.", "streaming_reasoning": "Initially, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, entrance_fee."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "i also need a place to dine.", "streaming_reasoning": "As more information arrives, destination: dine..", "trace": "destination+=dine."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Indian food, in the same area as Clare Hall.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is modify constraint; cuisine: indian..", "trace": "domain=restaurant; goal=modify_constraint; cuisine+=indian."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I would like it to be in the expensive price range.", "streaming_reasoning": "As more information arrives, price: expensive; destination: be in the expensive price range..", "trace": "price+=expensive; destination+=be in the expensive price range."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes.", "streaming_reasoning": "The content at C5 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Tuesday, 13:00, for 5 people.", "streaming_reasoning": "As more information arrives, time: 13:00; day: tuesday; party size: 5 people..", "trace": "time+=13:00; day+=tuesday; party_size+=5 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is all I need Cheers.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: cuisine is indian; price is expensive; party size is 5 people; destination is dine; requested information is address; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, modify_constraint; food=indian; price=expensive; party_size=5 people; destination=dine, be in the expensive price range; requested_info=address, entrance_fee; when=tuesday, 13:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002905", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: north part of town restaurant please Chinese I don't care.\nChunk 2: Yes, and I need one of their names please Sound perfect!\nChunk 3: What is their phone number thank you, goodbye.", "streaming_reasoning": "C1 domain=restaurant; area+=north; cuisine+=chinese. C2 goal=confirm_booking; acceptance=selected_option. C3 goal=request_info; requested_info+=phone.", "deep_reasoning": "Need domain=restaurant; goal=search, confirm_booking, request_info; area=north; food=chinese; requested_info=phone.", "answer": "I can help with that and include the phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: north part of town restaurant please Chinese I don't care.\nChunk 2: Yes, and I need one of their names please Sound perfect!\nChunk 3: What is their phone number thank you, goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=north; cuisine+=chinese. C2 goal=confirm_booking; acceptance=selected_option. C3 goal=request_info; requested_info+=phone.\n\nDeep reasoning: Need domain=restaurant; goal=search, confirm_booking, request_info; area=north; food=chinese; requested_info=phone.\n\nAnswer: I can help with that and include the phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: north part of town restaurant please Chinese I don't care.\nChunk 2: Yes, and I need one of their names please Sound perfect!\nChunk 3: What is their phone number thank you, goodbye.", "input_token_count": 35, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: north; cuisine: chinese. Next, the goal is confirm booking; acceptance: selected_option. Finally, the goal is request info; requested information: phone. In summary, The overall topic is restaurant. the goal is request info. area: north; cuisine: chinese.; acceptance: selected_option.; requested information: phone..", "trace": "C1 domain=restaurant; area+=north; cuisine+=chinese. C2 goal=confirm_booking; acceptance=selected_option. C3 goal=request_info; requested_info+=phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "north part of town restaurant please Chinese I don't care.", "streaming_reasoning": "Initially, the topic is restaurant; area: north; cuisine: chinese..", "trace": "domain=restaurant; area+=north; cuisine+=chinese."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, and I need one of their names please Sound perfect!", "streaming_reasoning": "As more information arrives, the goal is confirm booking; acceptance: selected_option..", "trace": "goal=confirm_booking; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is their phone number thank you, goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; cuisine is chinese; requested information is phone.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, confirm_booking, request_info; area=north; food=chinese; requested_info=phone."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002906", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: am looking for a train.\nChunk 2: The train should depart from peterborough and should go to cambridge.\nChunk 3: I am looking for a cheap restaurant on the north side of town.\nChunk 4: Let's try the da vinci pizzeria.\nChunk 5: I'll need the address and phone number too, please.\nChunk 6: Great, thanks for all of your help!", "streaming_reasoning": "C1 domain=train; goal=search. C2 destination+=cambridge; departure+=peterborough and should go, peterborough and should go to cambridge. C3 domain=restaurant; area+=north; price+=cheap. C4 intent=context_update. C5 goal=request_info; requested_info+=address, phone. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, restaurant; goal=search, request_info; area=north; price=cheap; destination=cambridge; departure=peterborough and should go, peterborough and should go to cambridge; requested_info=address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: am looking for a train.\nChunk 2: The train should depart from peterborough and should go to cambridge.\nChunk 3: I am looking for a cheap restaurant on the north side of town.\nChunk 4: Let's try the da vinci pizzeria.\nChunk 5: I'll need the address and phone number too, please.\nChunk 6: Great, thanks for all of your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 destination+=cambridge; departure+=peterborough and should go, peterborough and should go to cambridge. C3 domain=restaurant; area+=north; price+=cheap. C4 intent=context_update. C5 goal=request_info; requested_info+=address, phone. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=search, request_info; area=north; price=cheap; destination=cambridge; departure=peterborough and should go, peterborough and should go to cambridge; requested_info=address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: am looking for a train.\nChunk 2: The train should depart from peterborough and should go to cambridge.\nChunk 3: I am looking for a cheap restaurant on the north side of town.\nChunk 4: Let's try the da vinci pizzeria.\nChunk 5: I'll need the address and phone number too, please.\nChunk 6: Great, thanks for all of your help!", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, destination: cambridge; departure point: peterborough and should go. Next, the topic is restaurant; area: north; price: cheap. Next, intent: context_update. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is request info. destination: cambridge; departure point: peterborough and should go; area: north; price: cheap.; intent: context_update.; requested information: address.", "trace": "C1 domain=train; goal=search. C2 destination+=cambridge; departure+=peterborough and should go, peterborough and should go to cambridge. C3 domain=restaurant; area+=north; price+=cheap. C4 intent=context_update. C5 goal=request_info; requested_info+=address, phone. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "am looking for a train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The train should depart from peterborough and should go to cambridge.", "streaming_reasoning": "As more information arrives, destination: cambridge; departure point: peterborough and should go.", "trace": "destination+=cambridge; departure+=peterborough and should go, peterborough and should go to cambridge."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am looking for a cheap restaurant on the north side of town.", "streaming_reasoning": "As more information arrives, the topic is restaurant; area: north; price: cheap..", "trace": "domain=restaurant; area+=north; price+=cheap."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Let's try the da vinci pizzeria.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'll need the address and phone number too, please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Great, thanks for all of your help!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is north; price is cheap; destination is cambridge; departure point is peterborough and should go; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=search, request_info; area=north; price=cheap; destination=cambridge; departure=peterborough and should go, peterborough and should go to cambridge; requested_info=address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002907", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Train leaving cambridge going to stansted airport on wednesday anytime after 18:45.\nChunk 2: No, not at this time.\nChunk 3: I would like to know the travel time and price, please Great, thanks.\nChunk 4: I also am interested in the People's portraits exhibition at the Girton College, can you tell me more about that?\nChunk 5: Could you tell me if they have an entrance fee?\nChunk 6: What type of attraction is is?\nChunk 7: that will be all, thanks!", "streaming_reasoning": "C1 domain=train; time+=18:45; day+=wednesday; destination+=stansted airport on wednesday anytime aft. C2 goal=modify_constraint. C3 goal=request_info; destination+=know the travel time and price; requested_info+=travel_time. C4 domain=attraction. C5 requested_info+=entrance_fee. C6 goal=request_info. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, attraction; goal=request_info; destination=stansted airport on wednesday anytime aft, know the travel time and price; requested_info=travel_time, entrance_fee; when=wednesday, 18:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Train leaving cambridge going to stansted airport on wednesday anytime after 18:45.\nChunk 2: No, not at this time.\nChunk 3: I would like to know the travel time and price, please Great, thanks.\nChunk 4: I also am interested in the People's portraits exhibition at the Girton College, can you tell me more about that?\nChunk 5: Could you tell me if they have an entrance fee?\nChunk 6: What type of attraction is is?\nChunk 7: that will be all, thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; time+=18:45; day+=wednesday; destination+=stansted airport on wednesday anytime aft. C2 goal=modify_constraint. C3 goal=request_info; destination+=know the travel time and price; requested_info+=travel_time. C4 domain=attraction. C5 requested_info+=entrance_fee. C6 goal=request_info. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, attraction; goal=request_info; destination=stansted airport on wednesday anytime aft, know the travel time and price; requested_info=travel_time, entrance_fee; when=wednesday, 18:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Train leaving cambridge going to stansted airport on wednesday anytime after 18:45.\nChunk 2: No, not at this time.\nChunk 3: I would like to know the travel time and price, please Great, thanks.\nChunk 4: I also am interested in the People's portraits exhibition at the Girton College, can you tell me more about that?\nChunk 5: Could you tell me if they have an entrance fee?\nChunk 6: What type of attraction is is?\nChunk 7: that will be all, thanks!", "input_token_count": 86, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; time: 18:45; day: wednesday; destination: stansted airport on wednesday anytime aft. Next, the goal is modify constraint. Next, the goal is request info; destination: know the travel time and price; requested information: travel_time. Next, the topic is attraction. Next, requested information: entrance_fee. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction.. the goal is request info.. time: 18:45; day: wednesday; destination: stansted airport on wednesday anytime aft., know the travel time and price; requested information: travel_time., entrance_fee..", "trace": "C1 domain=train; time+=18:45; day+=wednesday; destination+=stansted airport on wednesday anytime aft. C2 goal=modify_constraint. C3 goal=request_info; destination+=know the travel time and price; requested_info+=travel_time. C4 domain=attraction. C5 requested_info+=entrance_fee. C6 goal=request_info. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Train leaving cambridge going to stansted airport on wednesday anytime after 18:45.", "streaming_reasoning": "Initially, the topic is train; time: 18:45; day: wednesday; destination: stansted airport on wednesday anytime aft..", "trace": "domain=train; time+=18:45; day+=wednesday; destination+=stansted airport on wednesday anytime aft."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, not at this time.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to know the travel time and price, please Great, thanks.", "streaming_reasoning": "As more information arrives, the goal is request info; destination: know the travel time and price; requested information: travel_time..", "trace": "goal=request_info; destination+=know the travel time and price; requested_info+=travel_time."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also am interested in the People's portraits exhibition at the Girton College, can you tell me more about that?", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Could you tell me if they have an entrance fee?", "streaming_reasoning": "As more information arrives, requested information: entrance_fee..", "trace": "requested_info+=entrance_fee."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What type of attraction is is?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "that will be all, thanks!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: destination is stansted airport on wednesday anytime aft; requested information is travel_time; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=request_info; destination=stansted airport on wednesday anytime aft, know the travel time and price; requested_info=travel_time, entrance_fee; when=wednesday, 18:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002908", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a train to Broxbourne.\nChunk 2: I would like to leave on Tuesday after 21:00 from cambridge Can you accommodate?\nChunk 3: 2 tickets on the 21:01, please.\nChunk 4: And can you give me the reference number once that's booked?\nChunk 5: Thanks.\nChunk 6: I would also like to go a museum on the east side.\nChunk 7: Just the address, please.\nChunk 8: Thank you very much Should be all.", "streaming_reasoning": "C1 domain=train; goal=search; destination+=broxbourne. C2 time+=21:00; day+=tuesday. C3 time+=21:01. C4 goal=request_info; requested_info+=reference_number. C5 [SKIP: thanks_only]. C6 domain=attraction; area+=east; destination+=go a museum on the east side. C7 requested_info+=address. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, attraction; goal=search, request_info; area=east; destination=broxbourne, go a museum on the east side; requested_info=reference_number, address; when=tuesday, 21:00, 21:01; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a train to Broxbourne.\nChunk 2: I would like to leave on Tuesday after 21:00 from cambridge Can you accommodate?\nChunk 3: 2 tickets on the 21:01, please.\nChunk 4: And can you give me the reference number once that's booked?\nChunk 5: Thanks.\nChunk 6: I would also like to go a museum on the east side.\nChunk 7: Just the address, please.\nChunk 8: Thank you very much Should be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=broxbourne. C2 time+=21:00; day+=tuesday. C3 time+=21:01. C4 goal=request_info; requested_info+=reference_number. C5 [SKIP: thanks_only]. C6 domain=attraction; area+=east; destination+=go a museum on the east side. C7 requested_info+=address. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, attraction; goal=search, request_info; area=east; destination=broxbourne, go a museum on the east side; requested_info=reference_number, address; when=tuesday, 21:00, 21:01; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a train to Broxbourne.\nChunk 2: I would like to leave on Tuesday after 21:00 from cambridge Can you accommodate?\nChunk 3: 2 tickets on the 21:01, please.\nChunk 4: And can you give me the reference number once that's booked?\nChunk 5: Thanks.\nChunk 6: I would also like to go a museum on the east side.\nChunk 7: Just the address, please.\nChunk 8: Thank you very much Should be all.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: broxbourne. Next, time: 21:00; day: tuesday. Next, time: 21:01. Next, the goal is request info; requested information: reference_number. Next, the topic is attraction; area: east; destination: go a museum on the east side. Finally, requested information: address.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction. the goal is request info. destination: broxbourne., go a museum on the east side.; time: 21:00, 21:01.; day: tuesday.; requested information: reference_number., address.; area: east.", "trace": "C1 domain=train; goal=search; destination+=broxbourne. C2 time+=21:00; day+=tuesday. C3 time+=21:01. C4 goal=request_info; requested_info+=reference_number. C5 [SKIP: thanks_only]. C6 domain=attraction; area+=east; destination+=go a museum on the east side. C7 requested_info+=address. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a train to Broxbourne.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: broxbourne..", "trace": "domain=train; goal=search; destination+=broxbourne."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to leave on Tuesday after 21:00 from cambridge Can you accommodate?", "streaming_reasoning": "As more information arrives, time: 21:00; day: tuesday..", "trace": "time+=21:00; day+=tuesday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "2 tickets on the 21:01, please.", "streaming_reasoning": "As more information arrives, time: 21:01..", "trace": "time+=21:01."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "And can you give me the reference number once that's booked?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I would also like to go a museum on the east side.", "streaming_reasoning": "As more information arrives, the topic is attraction; area: east; destination: go a museum on the east side..", "trace": "domain=attraction; area+=east; destination+=go a museum on the east side."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Just the address, please.", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you very much Should be all.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is east; destination is broxbourne; requested information is reference_number; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=search, request_info; area=east; destination=broxbourne, go a museum on the east side; requested_info=reference_number, address; when=tuesday, 21:00, 21:01; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002909", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a place to eat.\nChunk 2: I want expensive malaysian food Can you help?\nChunk 3: Well I need it to be in the south of town Chinese sounds good.\nChunk 4: Can you give me any suggestions Sounds great.\nChunk 5: Make a reservation for 4 on Friday at 11:00.\nChunk 6: How about!0:00 instead, is that available Friday?\nChunk 7: Thanks, that's all I need.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=eat. C2 price+=expensive. C3 area+=south; cuisine+=chinese; destination+=be in the south of town chinese sounds go; acceptance=selected_option. C4 goal=request_info. C5 goal=booking; time+=4, 11:00; day+=friday. C6 goal=compare_alternative; time+=0:00. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, booking, recommendation, compare_alternative; area=south; food=chinese; price=expensive; destination=eat, be in the south of town chinese sounds go; when=friday, 4, 11:00, 0:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a place to eat.\nChunk 2: I want expensive malaysian food Can you help?\nChunk 3: Well I need it to be in the south of town Chinese sounds good.\nChunk 4: Can you give me any suggestions Sounds great.\nChunk 5: Make a reservation for 4 on Friday at 11:00.\nChunk 6: How about!0:00 instead, is that available Friday?\nChunk 7: Thanks, that's all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=eat. C2 price+=expensive. C3 area+=south; cuisine+=chinese; destination+=be in the south of town chinese sounds go; acceptance=selected_option. C4 goal=request_info. C5 goal=booking; time+=4, 11:00; day+=friday. C6 goal=compare_alternative; time+=0:00. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, booking, recommendation, compare_alternative; area=south; food=chinese; price=expensive; destination=eat, be in the south of town chinese sounds go; when=friday, 4, 11:00, 0:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a place to eat.\nChunk 2: I want expensive malaysian food Can you help?\nChunk 3: Well I need it to be in the south of town Chinese sounds good.\nChunk 4: Can you give me any suggestions Sounds great.\nChunk 5: Make a reservation for 4 on Friday at 11:00.\nChunk 6: How about!0:00 instead, is that available Friday?\nChunk 7: Thanks, that's all I need.", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: eat. Next, price: expensive. Next, area: south; cuisine: chinese; destination: be in the south of town chinese sounds go; acceptance: selected_option. Next, the goal is request info. Next, the goal is booking; time: 4; day: friday. Finally, the goal is compare alternative; time: 0:00.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is compare alternative. destination: eat., be in the south of town chinese sounds go; price: expensive.; area: south; cuisine: chinese; acceptance: selected_option.; time: 4, 0:00.; day: friday..", "trace": "C1 domain=restaurant; goal=search; destination+=eat. C2 price+=expensive. C3 area+=south; cuisine+=chinese; destination+=be in the south of town chinese sounds go; acceptance=selected_option. C4 goal=request_info. C5 goal=booking; time+=4, 11:00; day+=friday. C6 goal=compare_alternative; time+=0:00. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a place to eat.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: eat..", "trace": "domain=restaurant; goal=search; destination+=eat."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I want expensive malaysian food Can you help?", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Well I need it to be in the south of town Chinese sounds good.", "streaming_reasoning": "As more information arrives, area: south; cuisine: chinese; destination: be in the south of town chinese sounds go; acceptance: selected_option..", "trace": "area+=south; cuisine+=chinese; destination+=be in the south of town chinese sounds go; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you give me any suggestions Sounds great.", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Make a reservation for 4 on Friday at 11:00.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 4; day: friday..", "trace": "goal=booking; time+=4, 11:00; day+=friday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "How about!0:00 instead, is that available Friday?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; time: 0:00..", "trace": "goal=compare_alternative; time+=0:00."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks, that's all I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is south; cuisine is chinese; price is expensive; destination is eat; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, booking, recommendation, compare_alternative; area=south; food=chinese; price=expensive; destination=eat, be in the south of town chinese sounds go; when=friday, 4, 11:00, 0:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002910", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a moderate priced Chinese food place.\nChunk 2: I need one in the centre, doesn't matter which Yes please.\nChunk 3: I will need it at 20:00 on Saturday for 8 people Thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=chinese; price+=moderate. C2 goal=confirm_booking; area+=centre; acceptance=selected_option. C3 time+=20:00, 8; day+=saturday; party_size+=8 people.", "deep_reasoning": "Need domain=restaurant; goal=search, confirm_booking; area=centre; food=chinese; price=moderate; party_size=8 people; when=saturday, 20:00, 8.", "answer": "Got it. I will use restaurant, centre, chinese, moderate, 8 people, saturday, 20:00, 8 and move the task forward.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a moderate priced Chinese food place.\nChunk 2: I need one in the centre, doesn't matter which Yes please.\nChunk 3: I will need it at 20:00 on Saturday for 8 people Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=chinese; price+=moderate. C2 goal=confirm_booking; area+=centre; acceptance=selected_option. C3 time+=20:00, 8; day+=saturday; party_size+=8 people.\n\nDeep reasoning: Need domain=restaurant; goal=search, confirm_booking; area=centre; food=chinese; price=moderate; party_size=8 people; when=saturday, 20:00, 8.\n\nAnswer: Got it. I will use restaurant, centre, chinese, moderate, 8 people, saturday, 20:00, 8 and move the task forward."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a moderate priced Chinese food place.\nChunk 2: I need one in the centre, doesn't matter which Yes please.\nChunk 3: I will need it at 20:00 on Saturday for 8 people Thank you.", "input_token_count": 41, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: chinese; price: moderate. Next, the goal is confirm booking; area: centre; acceptance: selected_option. Finally, time: 20:00; day: saturday; party size: 8 people. In summary, The overall topic is restaurant. the goal is confirm booking. cuisine: chinese; price: moderate.; area: centre; acceptance: selected_option.; time: 20:00; day: saturday; party size: 8 people..", "trace": "C1 domain=restaurant; goal=search; cuisine+=chinese; price+=moderate. C2 goal=confirm_booking; area+=centre; acceptance=selected_option. C3 time+=20:00, 8; day+=saturday; party_size+=8 people.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a moderate priced Chinese food place.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: chinese; price: moderate..", "trace": "domain=restaurant; goal=search; cuisine+=chinese; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need one in the centre, doesn't matter which Yes please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking; area: centre; acceptance: selected_option..", "trace": "goal=confirm_booking; area+=centre; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I will need it at 20:00 on Saturday for 8 people Thank you.", "streaming_reasoning": "Finally, time: 20:00; day: saturday; party size: 8 people..", "trace": "time+=20:00, 8; day+=saturday; party_size+=8 people."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; price is moderate; party size is 8 people; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "Got it. I will use restaurant, centre, chinese, moderate, 8 people, saturday, 20:00, 8 and move the task forward.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, confirm_booking; area=centre; food=chinese; price=moderate; party_size=8 people; when=saturday, 20:00, 8."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002911", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train departing from Cambridge.\nChunk 2: I need to get to Peterborough on Friday, and I have to leave after 12:30.\nChunk 3: I'd like to book this train for 7 people, if possible Great.\nChunk 4: Thanks for all your help.", "streaming_reasoning": "C1 domain=train; goal=search; departure+=cambridge. C2 goal=request_info; time+=12:30; day+=friday. C3 goal=booking; party_size+=7 people. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train; goal=search, request_info, booking; party_size=7 people; departure=cambridge; when=friday, 12:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a train departing from Cambridge.\nChunk 2: I need to get to Peterborough on Friday, and I have to leave after 12:30.\nChunk 3: I'd like to book this train for 7 people, if possible Great.\nChunk 4: Thanks for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; departure+=cambridge. C2 goal=request_info; time+=12:30; day+=friday. C3 goal=booking; party_size+=7 people. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info, booking; party_size=7 people; departure=cambridge; when=friday, 12:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train departing from Cambridge.\nChunk 2: I need to get to Peterborough on Friday, and I have to leave after 12:30.\nChunk 3: I'd like to book this train for 7 people, if possible Great.\nChunk 4: Thanks for all your help.", "input_token_count": 50, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; departure point: cambridge. Next, the goal is request info; time: 12:30; day: friday. Finally, the goal is booking; party size: 7 people.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is train. the goal is booking. departure point: cambridge.; time: 12:30; day: friday.; party size: 7 people..", "trace": "C1 domain=train; goal=search; departure+=cambridge. C2 goal=request_info; time+=12:30; day+=friday. C3 goal=booking; party_size+=7 people. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a train departing from Cambridge.", "streaming_reasoning": "Initially, the topic is train; the goal is search; departure point: cambridge..", "trace": "domain=train; goal=search; departure+=cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need to get to Peterborough on Friday, and I have to leave after 12:30.", "streaming_reasoning": "As more information arrives, the goal is request info; time: 12:30; day: friday..", "trace": "goal=request_info; time+=12:30; day+=friday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'd like to book this train for 7 people, if possible Great.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 7 people..", "trace": "goal=booking; party_size+=7 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks for all your help.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 7 people; departure point is cambridge; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, booking; party_size=7 people; departure=cambridge; when=friday, 12:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002912", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a table for 2 people on Monday at 14:30.\nChunk 2: Can you try 13:30 instead?\nChunk 3: Thanks.\nChunk 4: Thanks, I'm also looking for a place to go in the same area.\nChunk 5: Something in the centre of town.\nChunk 6: Do you have any suggestions for a museum maybe?\nChunk 7: Yes, could you please give me their phone number?\nChunk 8: No that is all.\nChunk 9: Thank you for your help Goodbye.", "streaming_reasoning": "C1 goal=search; time+=2, 14:30; day+=monday; party_size+=2 people. C2 goal=compare_alternative; time+=13:30. C3 [SKIP: thanks_only]. C4 [SKIP: thanks_only]. C5 area+=centre. C6 domain=attraction. C7 goal=request_info; requested_info+=phone; acceptance=selected_option. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=attraction; goal=search, compare_alternative, request_info; area=centre; party_size=2 people; requested_info=phone; when=monday, 2, 14:30, 13:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a table for 2 people on Monday at 14:30.\nChunk 2: Can you try 13:30 instead?\nChunk 3: Thanks.\nChunk 4: Thanks, I'm also looking for a place to go in the same area.\nChunk 5: Something in the centre of town.\nChunk 6: Do you have any suggestions for a museum maybe?\nChunk 7: Yes, could you please give me their phone number?\nChunk 8: No that is all.\nChunk 9: Thank you for your help Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; time+=2, 14:30; day+=monday; party_size+=2 people. C2 goal=compare_alternative; time+=13:30. C3 [SKIP: thanks_only]. C4 [SKIP: thanks_only]. C5 area+=centre. C6 domain=attraction. C7 goal=request_info; requested_info+=phone; acceptance=selected_option. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=attraction; goal=search, compare_alternative, request_info; area=centre; party_size=2 people; requested_info=phone; when=monday, 2, 14:30, 13:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a table for 2 people on Monday at 14:30.\nChunk 2: Can you try 13:30 instead?\nChunk 3: Thanks.\nChunk 4: Thanks, I'm also looking for a place to go in the same area.\nChunk 5: Something in the centre of town.\nChunk 6: Do you have any suggestions for a museum maybe?\nChunk 7: Yes, could you please give me their phone number?\nChunk 8: No that is all.\nChunk 9: Thank you for your help Goodbye.", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; time: 2; day: monday; party size: 2 people. Next, the goal is compare alternative; time: 13:30. Next, area: centre. Next, the topic is attraction. Finally, the goal is request info; requested information: phone; acceptance: selected_option.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction.. the goal is request info. time: 2, 13:30.; day: monday; party size: 2 people.; area: centre.; requested information: phone; acceptance: selected_option..", "trace": "C1 goal=search; time+=2, 14:30; day+=monday; party_size+=2 people. C2 goal=compare_alternative; time+=13:30. C3 [SKIP: thanks_only]. C4 [SKIP: thanks_only]. C5 area+=centre. C6 domain=attraction. C7 goal=request_info; requested_info+=phone; acceptance=selected_option. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a table for 2 people on Monday at 14:30.", "streaming_reasoning": "Initially, the goal is search; time: 2; day: monday; party size: 2 people..", "trace": "goal=search; time+=2, 14:30; day+=monday; party_size+=2 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you try 13:30 instead?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; time: 13:30..", "trace": "goal=compare_alternative; time+=13:30."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thanks.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks, I'm also looking for a place to go in the same area.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Something in the centre of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Do you have any suggestions for a museum maybe?", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes, could you please give me their phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=phone; acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No that is all.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you for your help Goodbye.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; party size is 2 people; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, compare_alternative, request_info; area=centre; party_size=2 people; requested_info=phone; when=monday, 2, 14:30, 13:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002913", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a college type attraction.\nChunk 2: I would like to visit on in town centre please.\nChunk 3: Okay, may I have their postcode, entrance fee, and phone number?\nChunk 4: Can you find an Indian restaurant for me that is also in the town centre?\nChunk 5: Can I get the postcode, price range, and phone number of one?\nChunk 6: No thank you, I'll just give them a call.\nChunk 7: That's all I needed for now.", "streaming_reasoning": "C1 domain=attraction; goal=search. C2 area+=centre; destination+=visit on in town centre please. C3 goal=request_info; requested_info+=phone, postcode, entrance_fee. C4 domain=restaurant; cuisine+=indian. C5 requested_info+=price. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, restaurant; goal=search, request_info; area=centre; food=indian; destination=visit on in town centre please; requested_info=phone, postcode, entrance_fee, price; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm looking for a college type attraction.\nChunk 2: I would like to visit on in town centre please.\nChunk 3: Okay, may I have their postcode, entrance fee, and phone number?\nChunk 4: Can you find an Indian restaurant for me that is also in the town centre?\nChunk 5: Can I get the postcode, price range, and phone number of one?\nChunk 6: No thank you, I'll just give them a call.\nChunk 7: That's all I needed for now."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search. C2 area+=centre; destination+=visit on in town centre please. C3 goal=request_info; requested_info+=phone, postcode, entrance_fee. C4 domain=restaurant; cuisine+=indian. C5 requested_info+=price. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, restaurant; goal=search, request_info; area=centre; food=indian; destination=visit on in town centre please; requested_info=phone, postcode, entrance_fee, price; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm looking for a college type attraction.\nChunk 2: I would like to visit on in town centre please.\nChunk 3: Okay, may I have their postcode, entrance fee, and phone number?\nChunk 4: Can you find an Indian restaurant for me that is also in the town centre?\nChunk 5: Can I get the postcode, price range, and phone number of one?\nChunk 6: No thank you, I'll just give them a call.\nChunk 7: That's all I needed for now.", "input_token_count": 84, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search. Next, area: centre; destination: visit on in town centre please. Next, the goal is request info; requested information: phone. Next, the topic is restaurant; cuisine: indian. Finally, requested information: price.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: centre; destination: visit on in town centre please.; requested information: phone, price.; cuisine: indian..", "trace": "C1 domain=attraction; goal=search. C2 area+=centre; destination+=visit on in town centre please. C3 goal=request_info; requested_info+=phone, postcode, entrance_fee. C4 domain=restaurant; cuisine+=indian. C5 requested_info+=price. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm looking for a college type attraction.", "streaming_reasoning": "Initially, the topic is attraction; the goal is search..", "trace": "domain=attraction; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to visit on in town centre please.", "streaming_reasoning": "As more information arrives, area: centre; destination: visit on in town centre please..", "trace": "area+=centre; destination+=visit on in town centre please."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Okay, may I have their postcode, entrance fee, and phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode, entrance_fee."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you find an Indian restaurant for me that is also in the town centre?", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: indian..", "trace": "domain=restaurant; cuisine+=indian."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get the postcode, price range, and phone number of one?", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No thank you, I'll just give them a call.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's all I needed for now.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; cuisine is indian; destination is visit on in town centre please; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, restaurant; goal=search, request_info; area=centre; food=indian; destination=visit on in town centre please; requested_info=phone, postcode, entrance_fee, price; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001946", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Am thankful to my parents for bringing me up.\nChunk 2: That made us good children.\nChunk 3: What made you good children?\nChunk 4: For the way we were brought up.", "streaming_reasoning": "C1 cause=Am thankful to my parents for bringing me up; need=encouragement. C2 emotion=frustrated; need=validation. C3 [SKIP: repeated_information]. C4 support_signal=received.", "deep_reasoning": "User feels frustrated after Am thankful to my parents for bringing me up and needs validation.", "answer": "It makes sense to feel frustrated after Am thankful to my parents for bringing me up. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Am thankful to my parents for bringing me up.\nChunk 2: That made us good children.\nChunk 3: What made you good children?\nChunk 4: For the way we were brought up."}, {"role": "assistant", "content": "Streaming reasoning: C1 cause=Am thankful to my parents for bringing me up; need=encouragement. C2 emotion=frustrated; need=validation. C3 [SKIP: repeated_information]. C4 support_signal=received.\n\nDeep reasoning: User feels frustrated after Am thankful to my parents for bringing me up and needs validation.\n\nAnswer: It makes sense to feel frustrated after Am thankful to my parents for bringing me up. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Am thankful to my parents for bringing me up.\nChunk 2: That made us good children.\nChunk 3: What made you good children?\nChunk 4: For the way we were brought up.", "input_token_count": 34, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user mentions Am thankful to my parents for bringing me up; the user needs encouragement. Next, the user expresses frustrated; the user needs validation. Finally, the user signals support or acknowledgment.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 cause=Am thankful to my parents for bringing me up; need=encouragement. C2 emotion=frustrated; need=validation. C3 [SKIP: repeated_information]. C4 support_signal=received.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Am thankful to my parents for bringing me up.", "streaming_reasoning": "Initially, the user mentions Am thankful to my parents for bringing me up; the user needs encouragement..", "trace": "cause=Am thankful to my parents for bringing me up; need=encouragement."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "That made us good children.", "streaming_reasoning": "As more information arrives, the user expresses frustrated; the user needs validation..", "trace": "emotion=frustrated; need=validation."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What made you good children?", "streaming_reasoning": "The content at C3 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "For the way we were brought up.", "streaming_reasoning": "Finally, the user signals support or acknowledgment.", "trace": "support_signal=received."}]}, "output": {"deep_reasoning": "User feels frustrated after Am thankful to my parents for bringing me up and needs validation.", "answer": "It makes sense to feel frustrated after Am thankful to my parents for bringing me up. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002914", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Moderate pricing and I dont care where they charge for parking or not.\nChunk 2: Yes, four star please.\nChunk 3: Not at this time.\nChunk 4: Could I get the address for the Hotel?\nChunk 5: I'm also looking for information on pizza express Fen Ditton.\nChunk 6: Could you make a reservation for 7 people for Friday at 11:45, please I appreciate it.\nChunk 7: Fantastic thats everything thanks!", "streaming_reasoning": "C1 price+=moderate; amenities+=parking. C2 acceptance=selected_option. C3 goal=modify_constraint. C4 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=address. C5 goal=search. C6 goal=booking; time+=7, 11:45; day+=friday; party_size+=7 people. C7 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=request_info, search, booking; price=moderate; party_size=7 people; amenities=parking; requested_info=address; when=friday, 7, 11:45.", "answer": "I can help with that and include the address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Moderate pricing and I dont care where they charge for parking or not.\nChunk 2: Yes, four star please.\nChunk 3: Not at this time.\nChunk 4: Could I get the address for the Hotel?\nChunk 5: I'm also looking for information on pizza express Fen Ditton.\nChunk 6: Could you make a reservation for 7 people for Friday at 11:45, please I appreciate it.\nChunk 7: Fantastic thats everything thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 price+=moderate; amenities+=parking. C2 acceptance=selected_option. C3 goal=modify_constraint. C4 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=address. C5 goal=search. C6 goal=booking; time+=7, 11:45; day+=friday; party_size+=7 people. C7 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=request_info, search, booking; price=moderate; party_size=7 people; amenities=parking; requested_info=address; when=friday, 7, 11:45.\n\nAnswer: I can help with that and include the address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Moderate pricing and I dont care where they charge for parking or not.\nChunk 2: Yes, four star please.\nChunk 3: Not at this time.\nChunk 4: Could I get the address for the Hotel?\nChunk 5: I'm also looking for information on pizza express Fen Ditton.\nChunk 6: Could you make a reservation for 7 people for Friday at 11:45, please I appreciate it.\nChunk 7: Fantastic thats everything thanks!", "input_token_count": 74, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, price: moderate; amenities: parking. Next, acceptance: selected_option. Next, the goal is modify constraint. Next, the topic is hotel; the goal is request info; hotel type: hotel; requested information: address. Next, the goal is search. Next, the goal is booking; time: 7; day: friday; party size: 7 people. Finally, intent: context_update. In summary, The overall topic is hotel. the goal is booking. price: moderate; amenities: parking.; acceptance: selected_option.; hotel type: hotel; requested information: address.; time: 7; day: friday; party size: 7 people.; intent: context_update..", "trace": "C1 price+=moderate; amenities+=parking. C2 acceptance=selected_option. C3 goal=modify_constraint. C4 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=address. C5 goal=search. C6 goal=booking; time+=7, 11:45; day+=friday; party_size+=7 people. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Moderate pricing and I dont care where they charge for parking or not.", "streaming_reasoning": "Initially, price: moderate; amenities: parking..", "trace": "price+=moderate; amenities+=parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, four star please.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Not at this time.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could I get the address for the Hotel?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is request info; hotel type: hotel; requested information: address..", "trace": "domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=address."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'm also looking for information on pizza express Fen Ditton.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could you make a reservation for 7 people for Friday at 11:45, please I appreciate it.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 7; day: friday; party size: 7 people..", "trace": "goal=booking; time+=7, 11:45; day+=friday; party_size+=7 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Fantastic thats everything thanks!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of request info. Key information: price is moderate; party size is 7 people; amenities is parking; requested information is address; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=request_info, search, booking; price=moderate; party_size=7 people; amenities=parking; requested_info=address; when=friday, 7, 11:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002916", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: yes book please for 1 Thank you.\nChunk 2: Can you also recommend places to go in the centre of town that involves multiple sports?\nChunk 3: How about a museum in the centre of town?\nChunk 4: I need the postcode.\nChunk 5: Thanks for your help!\nChunk 6: No thanks you were great!\nChunk 7: Have a good day.", "streaming_reasoning": "C1 goal=confirm_booking; goal=confirm_booking. C2 goal=recommendation; area+=centre; destination+=go in the centre of town that involves mu; type+=sports. C3 domain=attraction. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: thanks_only]. C6 [SKIP: thanks_only]. C7 intent=context_update.", "deep_reasoning": "Need domain=attraction; goal=booking, confirm_booking, recommendation, search, request_info; area=centre; destination=go in the centre of town that involves mu; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: yes book please for 1 Thank you.\nChunk 2: Can you also recommend places to go in the centre of town that involves multiple sports?\nChunk 3: How about a museum in the centre of town?\nChunk 4: I need the postcode.\nChunk 5: Thanks for your help!\nChunk 6: No thanks you were great!\nChunk 7: Have a good day."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=confirm_booking; goal=confirm_booking. C2 goal=recommendation; area+=centre; destination+=go in the centre of town that involves mu; type+=sports. C3 domain=attraction. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: thanks_only]. C6 [SKIP: thanks_only]. C7 intent=context_update.\n\nDeep reasoning: Need domain=attraction; goal=booking, confirm_booking, recommendation, search, request_info; area=centre; destination=go in the centre of town that involves mu; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: yes book please for 1 Thank you.\nChunk 2: Can you also recommend places to go in the centre of town that involves multiple sports?\nChunk 3: How about a museum in the centre of town?\nChunk 4: I need the postcode.\nChunk 5: Thanks for your help!\nChunk 6: No thanks you were great!\nChunk 7: Have a good day.", "input_token_count": 63, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is confirm booking. Next, the goal is recommendation; area: centre; destination: go in the centre of town that involves mu; type: sports. Next, the topic is attraction. Next, the goal is request info; requested information: postcode. Finally, intent: context_update.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is attraction.. the goal is request info. area: centre; destination: go in the centre of town that involves mu; type: sports.; requested information: postcode.; intent: context_update..", "trace": "C1 goal=confirm_booking; goal=confirm_booking. C2 goal=recommendation; area+=centre; destination+=go in the centre of town that involves mu; type+=sports. C3 domain=attraction. C4 goal=request_info; requested_info+=postcode. C5 [SKIP: thanks_only]. C6 [SKIP: thanks_only]. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "yes book please for 1 Thank you.", "streaming_reasoning": "Initially, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you also recommend places to go in the centre of town that involves multiple sports?", "streaming_reasoning": "As more information arrives, the goal is recommendation; area: centre; destination: go in the centre of town that involves mu; type: sports..", "trace": "goal=recommendation; area+=centre; destination+=go in the centre of town that involves mu; type+=sports."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about a museum in the centre of town?", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need the postcode.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks for your help!", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No thanks you were great!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Have a good day.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of booking. Key information: area is centre; destination is go in the centre of town that involves mu; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=booking, confirm_booking, recommendation, search, request_info; area=centre; destination=go in the centre of town that involves mu; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002917", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi I am looking for a place to stay in the expensive price range.\nChunk 2: I am not particular about the area.\nChunk 3: It is all right if the hotel doesn't have free parking.\nChunk 4: I actually don't want free parking.\nChunk 5: Is there a hotel that doesn't have free parking?", "streaming_reasoning": "C1 domain=hotel; goal=search; price+=expensive; destination+=stay in the expensive price range. C2 goal=modify_constraint. C3 hotel_type+=hotel; amenities+=parking, free parking. C4 intent=context_update. C5 [SKIP: repeated_information].", "deep_reasoning": "Need domain=hotel; goal=search; price=expensive; amenities=parking, free parking; destination=stay in the expensive price range.", "answer": "What area, date should I use for the search?", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi I am looking for a place to stay in the expensive price range.\nChunk 2: I am not particular about the area.\nChunk 3: It is all right if the hotel doesn't have free parking.\nChunk 4: I actually don't want free parking.\nChunk 5: Is there a hotel that doesn't have free parking?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; price+=expensive; destination+=stay in the expensive price range. C2 goal=modify_constraint. C3 hotel_type+=hotel; amenities+=parking, free parking. C4 intent=context_update. C5 [SKIP: repeated_information].\n\nDeep reasoning: Need domain=hotel; goal=search; price=expensive; amenities=parking, free parking; destination=stay in the expensive price range.\n\nAnswer: What area, date should I use for the search?"}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi I am looking for a place to stay in the expensive price range.\nChunk 2: I am not particular about the area.\nChunk 3: It is all right if the hotel doesn't have free parking.\nChunk 4: I actually don't want free parking.\nChunk 5: Is there a hotel that doesn't have free parking?", "input_token_count": 57, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: expensive; destination: stay in the expensive price range. Next, the goal is modify constraint. Next, hotel type: hotel; amenities: parking. Finally, intent: context_update.  Some chunks were skipped because they contained repeated_information. In summary, The overall topic is hotel. the goal is modify constraint.. price: expensive; destination: stay in the expensive price range.; hotel type: hotel; amenities: parking; intent: context_update..", "trace": "C1 domain=hotel; goal=search; price+=expensive; destination+=stay in the expensive price range. C2 goal=modify_constraint. C3 hotel_type+=hotel; amenities+=parking, free parking. C4 intent=context_update. C5 [SKIP: repeated_information].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi I am looking for a place to stay in the expensive price range.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; price: expensive; destination: stay in the expensive price range..", "trace": "domain=hotel; goal=search; price+=expensive; destination+=stay in the expensive price range."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am not particular about the area.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is all right if the hotel doesn't have free parking.", "streaming_reasoning": "As more information arrives, hotel type: hotel; amenities: parking.", "trace": "hotel_type+=hotel; amenities+=parking, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I actually don't want free parking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Is there a hotel that doesn't have free parking?", "streaming_reasoning": "The content at C5 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is expensive; amenities is parking; destination is stay in the expensive price range.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "What area, date should I use for the search?", "deep_reasoning_trace": "Need domain=hotel; goal=search; price=expensive; amenities=parking, free parking; destination=stay in the expensive price range."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002918", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant.\nChunk 2: Not sure of that, I am looking for a restaurant named \"ask.\".\nChunk 3: I would like to book a table for 5 people on Sunday at 14:15.\nChunk 4: Yes, a different restaurant in the same area and with the same price range.\nChunk 5: Type of food doesn't matter.\nChunk 6: Which is the best one?\nChunk 7: I'll book that.\nChunk 8: That is all Thank you!", "streaming_reasoning": "C1 domain=restaurant; goal=search. C2 goal=modify_constraint. C3 goal=booking; time+=5, 14:15; day+=sunday; party_size+=5 people. C4 goal=modify_constraint; price+=same price; goal=confirm_booking. C5 intent=context_update. C6 goal=request_info. C7 intent=context_update. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, booking, compare_alternative, modify_constraint; price=same price; party_size=5 people; when=sunday, 5, 14:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant.\nChunk 2: Not sure of that, I am looking for a restaurant named \"ask.\".\nChunk 3: I would like to book a table for 5 people on Sunday at 14:15.\nChunk 4: Yes, a different restaurant in the same area and with the same price range.\nChunk 5: Type of food doesn't matter.\nChunk 6: Which is the best one?\nChunk 7: I'll book that.\nChunk 8: That is all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search. C2 goal=modify_constraint. C3 goal=booking; time+=5, 14:15; day+=sunday; party_size+=5 people. C4 goal=modify_constraint; price+=same price; goal=confirm_booking. C5 intent=context_update. C6 goal=request_info. C7 intent=context_update. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, booking, compare_alternative, modify_constraint; price=same price; party_size=5 people; when=sunday, 5, 14:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant.\nChunk 2: Not sure of that, I am looking for a restaurant named \"ask.\".\nChunk 3: I would like to book a table for 5 people on Sunday at 14:15.\nChunk 4: Yes, a different restaurant in the same area and with the same price range.\nChunk 5: Type of food doesn't matter.\nChunk 6: Which is the best one?\nChunk 7: I'll book that.\nChunk 8: That is all Thank you!", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search. Next, the goal is modify constraint. Next, the goal is booking; time: 5; day: sunday; party size: 5 people. Next, the goal is confirm booking.; price: same price. Next, intent: context_update. Next, the goal is request info. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info.. time: 5; day: sunday; party size: 5 people.; price: same price; intent: context_update..", "trace": "C1 domain=restaurant; goal=search. C2 goal=modify_constraint. C3 goal=booking; time+=5, 14:15; day+=sunday; party_size+=5 people. C4 goal=modify_constraint; price+=same price; goal=confirm_booking. C5 intent=context_update. C6 goal=request_info. C7 intent=context_update. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search..", "trace": "domain=restaurant; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Not sure of that, I am looking for a restaurant named \"ask.\".", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would like to book a table for 5 people on Sunday at 14:15.", "streaming_reasoning": "As more information arrives, the goal is booking; time: 5; day: sunday; party size: 5 people..", "trace": "goal=booking; time+=5, 14:15; day+=sunday; party_size+=5 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, a different restaurant in the same area and with the same price range.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; price: same price.", "trace": "goal=modify_constraint; price+=same price; goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Type of food doesn't matter.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Which is the best one?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'll book that.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That is all Thank you!", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: price is same price; party size is 5 people; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking, compare_alternative, modify_constraint; price=same price; party_size=5 people; when=sunday, 5, 14:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003622", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Will you come round next Tuesday?\nChunk 2: Next Tuesday Just a moment!\nChunk 3: It will be the 21st of May Oh, dear Arm...\nChunk 4: I promised my aunt I would be at her birthday party.\nChunk 5: What do you say to next Wednesday then?\nChunk 6: Let me see Yes, Mary.\nChunk 7: Let's make it next Wednesday.\nChunk 8: Ok.\nChunk 9: Bye.", "streaming_reasoning": "C1 question=true. C2 casual_comment=next, tuesday. C3 casual_comment=will, may. C4 casual_comment=promised, aunt. C5 question=true. C6 casual_comment=let, see. C7 casual_comment=let's, make. C8 [SKIP: backchannel_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Will you come round next Tuesday?\nChunk 2: Next Tuesday Just a moment!\nChunk 3: It will be the 21st of May Oh, dear Arm...\nChunk 4: I promised my aunt I would be at her birthday party.\nChunk 5: What do you say to next Wednesday then?\nChunk 6: Let me see Yes, Mary.\nChunk 7: Let's make it next Wednesday.\nChunk 8: Ok.\nChunk 9: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 question=true. C2 casual_comment=next, tuesday. C3 casual_comment=will, may. C4 casual_comment=promised, aunt. C5 question=true. C6 casual_comment=let, see. C7 casual_comment=let's, make. C8 [SKIP: backchannel_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Will you come round next Tuesday?\nChunk 2: Next Tuesday Just a moment!\nChunk 3: It will be the 21st of May Oh, dear Arm...\nChunk 4: I promised my aunt I would be at her birthday party.\nChunk 5: What do you say to next Wednesday then?\nChunk 6: Let me see Yes, Mary.\nChunk 7: Let's make it next Wednesday.\nChunk 8: Ok.\nChunk 9: Bye.", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the input provides additional context about question=true. Next, the user comments on next. Next, the user comments on will. Next, the user comments on promised. Next, the input provides additional context about question=true. Next, the user comments on let. Finally, the user comments on let's.  Some chunks were skipped because they contained backchannel_only or closing_only.", "trace": "C1 question=true. C2 casual_comment=next, tuesday. C3 casual_comment=will, may. C4 casual_comment=promised, aunt. C5 question=true. C6 casual_comment=let, see. C7 casual_comment=let's, make. C8 [SKIP: backchannel_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Will you come round next Tuesday?", "streaming_reasoning": "Initially, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Next Tuesday Just a moment!", "streaming_reasoning": "As more information arrives, the user comments on next.", "trace": "casual_comment=next, tuesday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It will be the 21st of May Oh, dear Arm...", "streaming_reasoning": "As more information arrives, the user comments on will.", "trace": "casual_comment=will, may."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I promised my aunt I would be at her birthday party.", "streaming_reasoning": "As more information arrives, the user comments on promised.", "trace": "casual_comment=promised, aunt."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What do you say to next Wednesday then?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Let me see Yes, Mary.", "streaming_reasoning": "As more information arrives, the user comments on let.", "trace": "casual_comment=let, see."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Let's make it next Wednesday.", "streaming_reasoning": "As more information arrives, the user comments on let's.", "trace": "casual_comment=let's, make."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Ok.", "streaming_reasoning": "The content at C8 was skipped (backchannel_only).", "trace": "[SKIP: backchannel_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Bye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002919", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I'm looking for a 1 star hotel with free parking in the west.\nChunk 2: Can we try a 4 star rating instead?\nChunk 3: I do not have a price range just need a hotel booked for 7 people.\nChunk 4: We'll be arriving on Friday, and we'd like to stay for 2 nights.\nChunk 5: No, that was everything.\nChunk 6: Thank you for the help.", "streaming_reasoning": "C1 domain=hotel; goal=search; area+=west; hotel_type+=hotel; stars+=1 stars; amenities+=parking, free parking. C2 goal=compare_alternative; stars+=4 stars. C3 party_size+=7 people; requested_info+=price. C4 day+=friday; stay_length+=2 nights; destination+=stay for 2 nights. C5 goal=modify_constraint. C6 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, compare_alternative; area=west; party_size=7 people; stay_length=2 nights; stars=1 stars, 4 stars; amenities=parking, free parking; destination=stay for 2 nights; requested_info=price; when=friday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, I'm looking for a 1 star hotel with free parking in the west.\nChunk 2: Can we try a 4 star rating instead?\nChunk 3: I do not have a price range just need a hotel booked for 7 people.\nChunk 4: We'll be arriving on Friday, and we'd like to stay for 2 nights.\nChunk 5: No, that was everything.\nChunk 6: Thank you for the help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; area+=west; hotel_type+=hotel; stars+=1 stars; amenities+=parking, free parking. C2 goal=compare_alternative; stars+=4 stars. C3 party_size+=7 people; requested_info+=price. C4 day+=friday; stay_length+=2 nights; destination+=stay for 2 nights. C5 goal=modify_constraint. C6 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, compare_alternative; area=west; party_size=7 people; stay_length=2 nights; stars=1 stars, 4 stars; amenities=parking, free parking; destination=stay for 2 nights; requested_info=price; when=friday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I'm looking for a 1 star hotel with free parking in the west.\nChunk 2: Can we try a 4 star rating instead?\nChunk 3: I do not have a price range just need a hotel booked for 7 people.\nChunk 4: We'll be arriving on Friday, and we'd like to stay for 2 nights.\nChunk 5: No, that was everything.\nChunk 6: Thank you for the help.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: west; hotel type: hotel; star rating: 1 stars; amenities: parking. Next, the goal is compare alternative; star rating: 4 stars. Next, party size: 7 people; requested information: price. Next, day: friday; stay length: 2 nights; destination: stay for 2 nights. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is modify constraint.. area: west; hotel type: hotel; star rating: 1 stars, 4 stars.; amenities: parking; party size: 7 people; requested information: price.; day: friday; stay length: 2 nights; destination: stay for 2 nights..", "trace": "C1 domain=hotel; goal=search; area+=west; hotel_type+=hotel; stars+=1 stars; amenities+=parking, free parking. C2 goal=compare_alternative; stars+=4 stars. C3 party_size+=7 people; requested_info+=price. C4 day+=friday; stay_length+=2 nights; destination+=stay for 2 nights. C5 goal=modify_constraint. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, I'm looking for a 1 star hotel with free parking in the west.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; area: west; hotel type: hotel; star rating: 1 stars; amenities: parking.", "trace": "domain=hotel; goal=search; area+=west; hotel_type+=hotel; stars+=1 stars; amenities+=parking, free parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can we try a 4 star rating instead?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; star rating: 4 stars..", "trace": "goal=compare_alternative; stars+=4 stars."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I do not have a price range just need a hotel booked for 7 people.", "streaming_reasoning": "As more information arrives, party size: 7 people; requested information: price..", "trace": "party_size+=7 people; requested_info+=price."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "We'll be arriving on Friday, and we'd like to stay for 2 nights.", "streaming_reasoning": "As more information arrives, day: friday; stay length: 2 nights; destination: stay for 2 nights..", "trace": "day+=friday; stay_length+=2 nights; destination+=stay for 2 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "No, that was everything.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you for the help.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is west; party size is 7 people; stay length is 2 nights; star rating is 1 stars; amenities is parking; destination is stay for 2 nights; requested information is price; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, compare_alternative; area=west; party_size=7 people; stay_length=2 nights; stars=1 stars, 4 stars; amenities=parking, free parking; destination=stay for 2 nights; requested_info=price; when=friday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002921", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: From Cambridge, which is why I asked the Cambridge TownInfo centre On Saturday.\nChunk 2: Is there a train that will arrive by 15:15?\nChunk 3: No need to book it.\nChunk 4: Thanks.\nChunk 5: But can you help me find a cheap restaurant in the south?\nChunk 6: The Lucky Star sounds good.\nChunk 7: That's all I need.\nChunk 8: Can you also tell me the postcode?\nChunk 9: Thanks for your help Good bye.", "streaming_reasoning": "C1 area+=centre; day+=saturday. C2 domain=train; time+=15:15. C3 goal=booking. C4 [SKIP: thanks_only]. C5 domain=restaurant; area+=south; price+=cheap. C6 goal=confirm_booking. C7 [SKIP: closing_only]. C8 goal=request_info; requested_info+=postcode. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, restaurant; goal=search, booking, request_info; area=centre, south; price=cheap; requested_info=postcode; when=saturday, 15:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: From Cambridge, which is why I asked the Cambridge TownInfo centre On Saturday.\nChunk 2: Is there a train that will arrive by 15:15?\nChunk 3: No need to book it.\nChunk 4: Thanks.\nChunk 5: But can you help me find a cheap restaurant in the south?\nChunk 6: The Lucky Star sounds good.\nChunk 7: That's all I need.\nChunk 8: Can you also tell me the postcode?\nChunk 9: Thanks for your help Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 area+=centre; day+=saturday. C2 domain=train; time+=15:15. C3 goal=booking. C4 [SKIP: thanks_only]. C5 domain=restaurant; area+=south; price+=cheap. C6 goal=confirm_booking. C7 [SKIP: closing_only]. C8 goal=request_info; requested_info+=postcode. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=search, booking, request_info; area=centre, south; price=cheap; requested_info=postcode; when=saturday, 15:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: From Cambridge, which is why I asked the Cambridge TownInfo centre On Saturday.\nChunk 2: Is there a train that will arrive by 15:15?\nChunk 3: No need to book it.\nChunk 4: Thanks.\nChunk 5: But can you help me find a cheap restaurant in the south?\nChunk 6: The Lucky Star sounds good.\nChunk 7: That's all I need.\nChunk 8: Can you also tell me the postcode?\nChunk 9: Thanks for your help Good bye.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, area: centre; day: saturday. Next, the topic is train; time: 15:15. Next, the goal is booking. Next, the topic is restaurant; area: south; price: cheap. Next, the goal is confirm booking. Finally, the goal is request info; requested information: postcode.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is request info. area: centre, south; day: saturday.; time: 15:15.; price: cheap.; requested information: postcode..", "trace": "C1 area+=centre; day+=saturday. C2 domain=train; time+=15:15. C3 goal=booking. C4 [SKIP: thanks_only]. C5 domain=restaurant; area+=south; price+=cheap. C6 goal=confirm_booking. C7 [SKIP: closing_only]. C8 goal=request_info; requested_info+=postcode. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "From Cambridge, which is why I asked the Cambridge TownInfo centre On Saturday.", "streaming_reasoning": "Initially, area: centre; day: saturday..", "trace": "area+=centre; day+=saturday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Is there a train that will arrive by 15:15?", "streaming_reasoning": "As more information arrives, the topic is train; time: 15:15..", "trace": "domain=train; time+=15:15."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No need to book it.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thanks.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "But can you help me find a cheap restaurant in the south?", "streaming_reasoning": "As more information arrives, the topic is restaurant; area: south; price: cheap..", "trace": "domain=restaurant; area+=south; price+=cheap."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The Lucky Star sounds good.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's all I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Can you also tell me the postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks for your help Good bye.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is centre; price is cheap; requested information is postcode; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=search, booking, request_info; area=centre, south; price=cheap; requested_info=postcode; when=saturday, 15:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002923", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I would like to go to Leicester.\nChunk 3: What trains are available?\nChunk 4: I will go with the earlier departure, and I would like 2 seats please.\nChunk 5: I will also need a reference number.\nChunk 6: Great, I also need a place to go in the east part of town.\nChunk 7: Sure,a museum sounds good, what do you have that's free?\nChunk 8: Hmm, I guess the St Barnabas thing sound interesting.\nChunk 9: Is it expensive, though?\nChunk 10: Great thank you that's all the help I need today.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 destination+=go to leicester. C3 goal=request_info. C4 intent=context_update. C5 goal=request_info; requested_info+=reference_number. C6 area+=east; destination+=go in the east part of town. C7 domain=attraction; acceptance=selected_option. C8 intent=context_update. C9 price+=expensive. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction; goal=search, request_info; area=east; price=expensive; destination=go to leicester, go in the east part of town; requested_info=reference_number; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I would like to go to Leicester.\nChunk 3: What trains are available?\nChunk 4: I will go with the earlier departure, and I would like 2 seats please.\nChunk 5: I will also need a reference number.\nChunk 6: Great, I also need a place to go in the east part of town.\nChunk 7: Sure,a museum sounds good, what do you have that's free?\nChunk 8: Hmm, I guess the St Barnabas thing sound interesting.\nChunk 9: Is it expensive, though?\nChunk 10: Great thank you that's all the help I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 destination+=go to leicester. C3 goal=request_info. C4 intent=context_update. C5 goal=request_info; requested_info+=reference_number. C6 area+=east; destination+=go in the east part of town. C7 domain=attraction; acceptance=selected_option. C8 intent=context_update. C9 price+=expensive. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; area=east; price=expensive; destination=go to leicester, go in the east part of town; requested_info=reference_number; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I would like to go to Leicester.\nChunk 3: What trains are available?\nChunk 4: I will go with the earlier departure, and I would like 2 seats please.\nChunk 5: I will also need a reference number.\nChunk 6: Great, I also need a place to go in the east part of town.\nChunk 7: Sure,a museum sounds good, what do you have that's free?\nChunk 8: Hmm, I guess the St Barnabas thing sound interesting.\nChunk 9: Is it expensive, though?\nChunk 10: Great thank you that's all the help I need today.", "input_token_count": 101, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, destination: go to leicester. Next, the goal is request info. Next, intent: context_update. Next, the goal is request info; requested information: reference_number. Next, area: east; destination: go in the east part of town. Next, the topic is attraction; acceptance: selected_option. Next, intent: context_update. Finally, price: expensive.  Some chunks were skipped because they contained acknowledgement_only or closing_only. In summary, The overall topic is attraction. the goal is request info. destination: go to leicester., go in the east part of town.; intent: context_update.; requested information: reference_number.; area: east; acceptance: selected_option.; price: expensive..", "trace": "C1 [SKIP: acknowledgement_only]. C2 destination+=go to leicester. C3 goal=request_info. C4 intent=context_update. C5 goal=request_info; requested_info+=reference_number. C6 area+=east; destination+=go in the east part of town. C7 domain=attraction; acceptance=selected_option. C8 intent=context_update. C9 price+=expensive. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like to go to Leicester.", "streaming_reasoning": "As more information arrives, destination: go to leicester..", "trace": "destination+=go to leicester."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What trains are available?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I will go with the earlier departure, and I would like 2 seats please.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will also need a reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Great, I also need a place to go in the east part of town.", "streaming_reasoning": "As more information arrives, area: east; destination: go in the east part of town..", "trace": "area+=east; destination+=go in the east part of town."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Sure,a museum sounds good, what do you have that's free?", "streaming_reasoning": "As more information arrives, the topic is attraction; acceptance: selected_option..", "trace": "domain=attraction; acceptance=selected_option."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Hmm, I guess the St Barnabas thing sound interesting.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Is it expensive, though?", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Great thank you that's all the help I need today.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is east; price is expensive; destination is go to leicester; requested information is reference_number. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; area=east; price=expensive; destination=go to leicester, go in the east part of town; requested_info=reference_number; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002924", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a place in the centre that serves african food.\nChunk 2: What is the price range?\nChunk 3: No thanks what is their postcode though?\nChunk 4: Yes, I am also looking for a museum in the same area as the restaurant.\nChunk 5: Thanks for the good suggestion.\nChunk 6: What is the postcode for Primavera?\nChunk 7: No, that's everything I needed.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre. C2 goal=request_info; requested_info+=price. C3 requested_info+=postcode. C4 domain=attraction; goal=modify_constraint; acceptance=selected_option. C5 [SKIP: thanks_only]. C6 goal=request_info. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, attraction; goal=search, request_info, modify_constraint; area=centre; requested_info=price, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a place in the centre that serves african food.\nChunk 2: What is the price range?\nChunk 3: No thanks what is their postcode though?\nChunk 4: Yes, I am also looking for a museum in the same area as the restaurant.\nChunk 5: Thanks for the good suggestion.\nChunk 6: What is the postcode for Primavera?\nChunk 7: No, that's everything I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre. C2 goal=request_info; requested_info+=price. C3 requested_info+=postcode. C4 domain=attraction; goal=modify_constraint; acceptance=selected_option. C5 [SKIP: thanks_only]. C6 goal=request_info. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, attraction; goal=search, request_info, modify_constraint; area=centre; requested_info=price, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a place in the centre that serves african food.\nChunk 2: What is the price range?\nChunk 3: No thanks what is their postcode though?\nChunk 4: Yes, I am also looking for a museum in the same area as the restaurant.\nChunk 5: Thanks for the good suggestion.\nChunk 6: What is the postcode for Primavera?\nChunk 7: No, that's everything I needed.", "input_token_count": 68, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre. Next, the goal is request info; requested information: price. Next, requested information: postcode. Next, the topic is attraction; the goal is modify constraint; acceptance: selected_option. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction. the goal is request info.. area: centre.; requested information: price., postcode.; acceptance: selected_option..", "trace": "C1 domain=restaurant; goal=search; area+=centre. C2 goal=request_info; requested_info+=price. C3 requested_info+=postcode. C4 domain=attraction; goal=modify_constraint; acceptance=selected_option. C5 [SKIP: thanks_only]. C6 goal=request_info. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a place in the centre that serves african food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre..", "trace": "domain=restaurant; goal=search; area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the price range?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No thanks what is their postcode though?", "streaming_reasoning": "As more information arrives, requested information: postcode..", "trace": "requested_info+=postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, I am also looking for a museum in the same area as the restaurant.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is modify constraint; acceptance: selected_option..", "trace": "domain=attraction; goal=modify_constraint; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks for the good suggestion.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What is the postcode for Primavera?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that's everything I needed.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; requested information is price. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction; goal=search, request_info, modify_constraint; area=centre; requested_info=price, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002925", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am trying to find a hospital that has a transplant high dependency unit.\nChunk 2: No, that's all I need Thank you!", "streaming_reasoning": "C1 domain=hospital; goal=search; destination+=find a hospital that has a transplant hig. C2 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search; destination=find a hospital that has a transplant hig; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am trying to find a hospital that has a transplant high dependency unit.\nChunk 2: No, that's all I need Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search; destination+=find a hospital that has a transplant hig. C2 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search; destination=find a hospital that has a transplant hig; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am trying to find a hospital that has a transplant high dependency unit.\nChunk 2: No, that's all I need Thank you!", "input_token_count": 25, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital that has a transplant hig.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital. the goal is search. destination: find a hospital that has a transplant hig..", "trace": "C1 domain=hospital; goal=search; destination+=find a hospital that has a transplant hig. C2 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am trying to find a hospital that has a transplant high dependency unit.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital that has a transplant hig..", "trace": "domain=hospital; goal=search; destination+=find a hospital that has a transplant hig."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, that's all I need Thank you!", "streaming_reasoning": "The content at C2 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: destination is find a hospital that has a transplant hig. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search; destination=find a hospital that has a transplant hig; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002926", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you give me the postcode and address please?\nChunk 2: Yes, I'm looking for colleges to see in town.\nChunk 3: Can you help me with that?\nChunk 4: I don't care about that but I would like the address and area of the college I visit.\nChunk 5: What is the address for Gonville and Caius College?\nChunk 6: The gonville caius college would be a nice attraction.\nChunk 7: Could I get the address please Thank you.\nChunk 8: I look forward to the day in town Goodbye.", "streaming_reasoning": "C1 goal=request_info; requested_info+=address, postcode. C2 goal=search; acceptance=selected_option. C3 goal=request_info. C4 domain=attraction. C5 goal=request_info. C6 intent=context_update. C7 intent=context_update. C8 destination+=the day in town goodbye.", "deep_reasoning": "Need domain=attraction; goal=request_info, search; destination=the day in town goodbye; requested_info=address, postcode.", "answer": "I can help with that and include the address, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you give me the postcode and address please?\nChunk 2: Yes, I'm looking for colleges to see in town.\nChunk 3: Can you help me with that?\nChunk 4: I don't care about that but I would like the address and area of the college I visit.\nChunk 5: What is the address for Gonville and Caius College?\nChunk 6: The gonville caius college would be a nice attraction.\nChunk 7: Could I get the address please Thank you.\nChunk 8: I look forward to the day in town Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; requested_info+=address, postcode. C2 goal=search; acceptance=selected_option. C3 goal=request_info. C4 domain=attraction. C5 goal=request_info. C6 intent=context_update. C7 intent=context_update. C8 destination+=the day in town goodbye.\n\nDeep reasoning: Need domain=attraction; goal=request_info, search; destination=the day in town goodbye; requested_info=address, postcode.\n\nAnswer: I can help with that and include the address, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you give me the postcode and address please?\nChunk 2: Yes, I'm looking for colleges to see in town.\nChunk 3: Can you help me with that?\nChunk 4: I don't care about that but I would like the address and area of the college I visit.\nChunk 5: What is the address for Gonville and Caius College?\nChunk 6: The gonville caius college would be a nice attraction.\nChunk 7: Could I get the address please Thank you.\nChunk 8: I look forward to the day in town Goodbye.", "input_token_count": 93, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; requested information: address. Next, the goal is search; acceptance: selected_option. Next, the goal is request info. Next, the topic is attraction. Next, the goal is request info. Next, intent: context_update. Next, intent: context_update. Finally, destination: the day in town goodbye. In summary, The overall topic is attraction.. the goal is request info.. requested information: address; acceptance: selected_option.; intent: context_update.; destination: the day in town goodbye..", "trace": "C1 goal=request_info; requested_info+=address, postcode. C2 goal=search; acceptance=selected_option. C3 goal=request_info. C4 domain=attraction. C5 goal=request_info. C6 intent=context_update. C7 intent=context_update. C8 destination+=the day in town goodbye.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you give me the postcode and address please?", "streaming_reasoning": "Initially, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I'm looking for colleges to see in town.", "streaming_reasoning": "As more information arrives, the goal is search; acceptance: selected_option..", "trace": "goal=search; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you help me with that?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I don't care about that but I would like the address and area of the college I visit.", "streaming_reasoning": "As more information arrives, the topic is attraction..", "trace": "domain=attraction."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What is the address for Gonville and Caius College?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The gonville caius college would be a nice attraction.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Could I get the address please Thank you.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I look forward to the day in town Goodbye.", "streaming_reasoning": "Finally, destination: the day in town goodbye..", "trace": "destination+=the day in town goodbye."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: destination is the day in town goodbye; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=attraction; goal=request_info, search; destination=the day in town goodbye; requested_info=address, postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002927", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: ok, i need to book it for the same day.\nChunk 2: 3 nights, 3 people, please.\nChunk 3: I want to find a restaurant.\nChunk 4: The time is 14:45.\nChunk 5: Okay thank you,that's all I need for now.\nChunk 6: Thank you so much.\nChunk 7: You have a wonderful day as well and again, thank you!", "streaming_reasoning": "C1 goal=booking. C2 party_size+=3 people; stay_length+=3 nights. C3 domain=restaurant; destination+=find a restaurant. C4 time+=14:45. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only]. C7 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, booking; party_size=3 people; stay_length=3 nights; destination=find a restaurant; when=14:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: ok, i need to book it for the same day.\nChunk 2: 3 nights, 3 people, please.\nChunk 3: I want to find a restaurant.\nChunk 4: The time is 14:45.\nChunk 5: Okay thank you,that's all I need for now.\nChunk 6: Thank you so much.\nChunk 7: You have a wonderful day as well and again, thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=booking. C2 party_size+=3 people; stay_length+=3 nights. C3 domain=restaurant; destination+=find a restaurant. C4 time+=14:45. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only]. C7 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, booking; party_size=3 people; stay_length=3 nights; destination=find a restaurant; when=14:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: ok, i need to book it for the same day.\nChunk 2: 3 nights, 3 people, please.\nChunk 3: I want to find a restaurant.\nChunk 4: The time is 14:45.\nChunk 5: Okay thank you,that's all I need for now.\nChunk 6: Thank you so much.\nChunk 7: You have a wonderful day as well and again, thank you!", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is booking. Next, party size: 3 people; stay length: 3 nights. Next, the topic is restaurant; destination: find a restaurant. Next, time: 14:45. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is booking.. party size: 3 people; stay length: 3 nights.; destination: find a restaurant.; time: 14:45.; intent: context_update..", "trace": "C1 goal=booking. C2 party_size+=3 people; stay_length+=3 nights. C3 domain=restaurant; destination+=find a restaurant. C4 time+=14:45. C5 [SKIP: closing_only]. C6 [SKIP: thanks_only]. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "ok, i need to book it for the same day.", "streaming_reasoning": "Initially, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "3 nights, 3 people, please.", "streaming_reasoning": "As more information arrives, party size: 3 people; stay length: 3 nights..", "trace": "party_size+=3 people; stay_length+=3 nights."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: find a restaurant..", "trace": "domain=restaurant; destination+=find a restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is 14:45.", "streaming_reasoning": "As more information arrives, time: 14:45..", "trace": "time+=14:45."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Okay thank you,that's all I need for now.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you so much.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "You have a wonderful day as well and again, thank you!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: party size is 3 people; stay length is 3 nights; destination is find a restaurant; timing is 14:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, booking; party_size=3 people; stay_length=3 nights; destination=find a restaurant; when=14:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002928", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That sounds like it might be great - how many stars does the Ashley have?\nChunk 2: I also need a taxi to take me somewhere.\nChunk 3: I just need to get to the restaurant by the time the reservation starts.\nChunk 4: Please have the taxi pick me up at the hotel.\nChunk 5: Can I get the taxi contact number and car type?\nChunk 6: An hour after I arrive at the restaurant sounds about right.\nChunk 7: Great thank you so much that's all I needed today.", "streaming_reasoning": "C1 goal=request_info. C2 domain=taxi; goal=search; destination+=take me somewhere. C3 domain=restaurant; goal=request_info. C4 domain=hotel; hotel_type+=hotel. C5 goal=request_info. C6 destination+=the restaurant sounds about right. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi, restaurant, hotel; goal=search, booking, request_info; destination=take me somewhere, the restaurant sounds about right; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: That sounds like it might be great - how many stars does the Ashley have?\nChunk 2: I also need a taxi to take me somewhere.\nChunk 3: I just need to get to the restaurant by the time the reservation starts.\nChunk 4: Please have the taxi pick me up at the hotel.\nChunk 5: Can I get the taxi contact number and car type?\nChunk 6: An hour after I arrive at the restaurant sounds about right.\nChunk 7: Great thank you so much that's all I needed today."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 domain=taxi; goal=search; destination+=take me somewhere. C3 domain=restaurant; goal=request_info. C4 domain=hotel; hotel_type+=hotel. C5 goal=request_info. C6 destination+=the restaurant sounds about right. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi, restaurant, hotel; goal=search, booking, request_info; destination=take me somewhere, the restaurant sounds about right; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: That sounds like it might be great - how many stars does the Ashley have?\nChunk 2: I also need a taxi to take me somewhere.\nChunk 3: I just need to get to the restaurant by the time the reservation starts.\nChunk 4: Please have the taxi pick me up at the hotel.\nChunk 5: Can I get the taxi contact number and car type?\nChunk 6: An hour after I arrive at the restaurant sounds about right.\nChunk 7: Great thank you so much that's all I needed today.", "input_token_count": 92, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, the topic is taxi; the goal is search; destination: take me somewhere. Next, the topic is restaurant; the goal is request info. Next, the topic is hotel; hotel type: hotel. Next, the goal is request info. Finally, destination: the restaurant sounds about right.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info.. destination: take me somewhere., the restaurant sounds about right.; hotel type: hotel..", "trace": "C1 goal=request_info. C2 domain=taxi; goal=search; destination+=take me somewhere. C3 domain=restaurant; goal=request_info. C4 domain=hotel; hotel_type+=hotel. C5 goal=request_info. C6 destination+=the restaurant sounds about right. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "That sounds like it might be great - how many stars does the Ashley have?", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I also need a taxi to take me somewhere.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is search; destination: take me somewhere..", "trace": "domain=taxi; goal=search; destination+=take me somewhere."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I just need to get to the restaurant by the time the reservation starts.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is request info..", "trace": "domain=restaurant; goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please have the taxi pick me up at the hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel..", "trace": "domain=hotel; hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can I get the taxi contact number and car type?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "An hour after I arrive at the restaurant sounds about right.", "streaming_reasoning": "As more information arrives, destination: the restaurant sounds about right..", "trace": "destination+=the restaurant sounds about right."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Great thank you so much that's all I needed today.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is take me somewhere. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, restaurant, hotel; goal=search, booking, request_info; destination=take me somewhere, the restaurant sounds about right; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002929", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hospital in town.\nChunk 2: No thank you that is all I needed.", "streaming_reasoning": "C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search; destination=find a hospital in town; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a hospital in town.\nChunk 2: No thank you that is all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search; destination=find a hospital in town; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a hospital in town.\nChunk 2: No thank you that is all I needed.", "input_token_count": 20, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital in town.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital. the goal is search. destination: find a hospital in town..", "trace": "C1 domain=hospital; goal=search; destination+=find a hospital in town. C2 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a hospital in town.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search; destination: find a hospital in town..", "trace": "domain=hospital; goal=search; destination+=find a hospital in town."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No thank you that is all I needed.", "streaming_reasoning": "The content at C2 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: destination is find a hospital in town. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search; destination=find a hospital in town; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002930", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I would like the train to depart from Cambridge and arrive by 18:15 saint andrew street.\nChunk 3: I need help with train.\nChunk 4: The time is tuesday, 18:15.\nChunk 5: That should work thank you very much.\nChunk 6: Can I get tickets for 5 people?\nChunk 7: No, that will be all Thank you!", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 domain=train; time+=18:15; departure+=cambridge and arrive by 18:15 saint andrew street. C3 goal=search. C4 day+=tuesday. C5 intent=context_update. C6 goal=request_info; party_size+=5 people. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; party_size=5 people; departure=cambridge and arrive by 18:15 saint andrew street; when=tuesday, 18:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes.\nChunk 2: I would like the train to depart from Cambridge and arrive by 18:15 saint andrew street.\nChunk 3: I need help with train.\nChunk 4: The time is tuesday, 18:15.\nChunk 5: That should work thank you very much.\nChunk 6: Can I get tickets for 5 people?\nChunk 7: No, that will be all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 domain=train; time+=18:15; departure+=cambridge and arrive by 18:15 saint andrew street. C3 goal=search. C4 day+=tuesday. C5 intent=context_update. C6 goal=request_info; party_size+=5 people. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; party_size=5 people; departure=cambridge and arrive by 18:15 saint andrew street; when=tuesday, 18:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes.\nChunk 2: I would like the train to depart from Cambridge and arrive by 18:15 saint andrew street.\nChunk 3: I need help with train.\nChunk 4: The time is tuesday, 18:15.\nChunk 5: That should work thank you very much.\nChunk 6: Can I get tickets for 5 people?\nChunk 7: No, that will be all Thank you!", "input_token_count": 64, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; time: 18:15; departure point: cambridge and arrive by 18:15 saint andrew street. Next, the goal is search. Next, day: tuesday. Next, intent: context_update. Finally, the goal is request info; party size: 5 people.  Some chunks were skipped because they contained acknowledgement_only or closing_only. In summary, The overall topic is train. the goal is request info. time: 18:15; departure point: cambridge and arrive by 18:15 saint andrew street.; day: tuesday.; intent: context_update.; party size: 5 people..", "trace": "C1 [SKIP: acknowledgement_only]. C2 domain=train; time+=18:15; departure+=cambridge and arrive by 18:15 saint andrew street. C3 goal=search. C4 day+=tuesday. C5 intent=context_update. C6 goal=request_info; party_size+=5 people. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like the train to depart from Cambridge and arrive by 18:15 saint andrew street.", "streaming_reasoning": "As more information arrives, the topic is train; time: 18:15; departure point: cambridge and arrive by 18:15 saint andrew street..", "trace": "domain=train; time+=18:15; departure+=cambridge and arrive by 18:15 saint andrew street."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need help with train.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is tuesday, 18:15.", "streaming_reasoning": "As more information arrives, day: tuesday..", "trace": "day+=tuesday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That should work thank you very much.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I get tickets for 5 people?", "streaming_reasoning": "As more information arrives, the goal is request info; party size: 5 people..", "trace": "goal=request_info; party_size+=5 people."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that will be all Thank you!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 5 people; departure point is cambridge and arrive by 18:15 saint andrew street; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; party_size=5 people; departure=cambridge and arrive by 18:15 saint andrew street; when=tuesday, 18:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002931", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are you sure?\nChunk 2: It does NOT need to have free parking.\nChunk 3: I want to find a moderate restaurant.\nChunk 4: I also need the price.\nChunk 5: yes, i want to book it for 1 people and 2 nights starting from thursday.\nChunk 6: I also need to book a table for 1 on Thursday at 16:45 at India House.\nChunk 7: Can you do that for me?\nChunk 8: I need help with taxi.\nChunk 9: The time is 16:45.\nChunk 10: Please make a booking.\nChunk 11: well thank you thats all for today.", "streaming_reasoning": "C1 goal=request_info. C2 goal=search; amenities+=parking, free parking; destination+=have free parking. C3 domain=restaurant; price+=moderate; destination+=find a moderate restaurant. C4 requested_info+=price. C5 goal=confirm_booking; time+=1, 2; day+=thursday; party_size+=1 people; stay_length+=2 nights; goal=confirm_booking. C6 time+=16:45. C7 goal=request_info. C8 domain=taxi. C9 intent=context_update. C10 intent=context_update. C11 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi; goal=search, booking, confirm_booking; price=moderate; party_size=1 people; stay_length=2 nights; amenities=parking, free parking; destination=have free parking, find a moderate restaurant; requested_info=price; when=thursday, 1, 2, 16:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Are you sure?\nChunk 2: It does NOT need to have free parking.\nChunk 3: I want to find a moderate restaurant.\nChunk 4: I also need the price.\nChunk 5: yes, i want to book it for 1 people and 2 nights starting from thursday.\nChunk 6: I also need to book a table for 1 on Thursday at 16:45 at India House.\nChunk 7: Can you do that for me?\nChunk 8: I need help with taxi.\nChunk 9: The time is 16:45.\nChunk 10: Please make a booking.\nChunk 11: well thank you thats all for today."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 goal=search; amenities+=parking, free parking; destination+=have free parking. C3 domain=restaurant; price+=moderate; destination+=find a moderate restaurant. C4 requested_info+=price. C5 goal=confirm_booking; time+=1, 2; day+=thursday; party_size+=1 people; stay_length+=2 nights; goal=confirm_booking. C6 time+=16:45. C7 goal=request_info. C8 domain=taxi. C9 intent=context_update. C10 intent=context_update. C11 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi; goal=search, booking, confirm_booking; price=moderate; party_size=1 people; stay_length=2 nights; amenities=parking, free parking; destination=have free parking, find a moderate restaurant; requested_info=price; when=thursday, 1, 2, 16:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Are you sure?\nChunk 2: It does NOT need to have free parking.\nChunk 3: I want to find a moderate restaurant.\nChunk 4: I also need the price.\nChunk 5: yes, i want to book it for 1 people and 2 nights starting from thursday.\nChunk 6: I also need to book a table for 1 on Thursday at 16:45 at India House.\nChunk 7: Can you do that for me?\nChunk 8: I need help with taxi.\nChunk 9: The time is 16:45.\nChunk 10: Please make a booking.\nChunk 11: well thank you thats all for today.", "input_token_count": 104, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, the goal is search; amenities: parking; destination: have free parking. Next, the topic is restaurant; price: moderate; destination: find a moderate restaurant. Next, requested information: price. Next, the goal is confirm booking.; time: 1; day: thursday; party size: 1 people; stay length: 2 nights. Next, time: 16:45. Next, the goal is request info. Next, the topic is taxi. Next, intent: context_update. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi.. the goal is request info.. amenities: parking; destination: have free parking., find a moderate restaurant.; price: moderate; requested information: price.; time: 1, 16:45.; day: thursday; party size: 1 people; stay length: 2 nights; intent: context_update..", "trace": "C1 goal=request_info. C2 goal=search; amenities+=parking, free parking; destination+=have free parking. C3 domain=restaurant; price+=moderate; destination+=find a moderate restaurant. C4 requested_info+=price. C5 goal=confirm_booking; time+=1, 2; day+=thursday; party_size+=1 people; stay_length+=2 nights; goal=confirm_booking. C6 time+=16:45. C7 goal=request_info. C8 domain=taxi. C9 intent=context_update. C10 intent=context_update. C11 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Are you sure?", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It does NOT need to have free parking.", "streaming_reasoning": "As more information arrives, the goal is search; amenities: parking; destination: have free parking..", "trace": "goal=search; amenities+=parking, free parking; destination+=have free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a moderate restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; price: moderate; destination: find a moderate restaurant..", "trace": "domain=restaurant; price+=moderate; destination+=find a moderate restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "yes, i want to book it for 1 people and 2 nights starting from thursday.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 1; day: thursday; party size: 1 people; stay length: 2 nights.", "trace": "goal=confirm_booking; time+=1, 2; day+=thursday; party_size+=1 people; stay_length+=2 nights; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need to book a table for 1 on Thursday at 16:45 at India House.", "streaming_reasoning": "As more information arrives, time: 16:45..", "trace": "time+=16:45."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can you do that for me?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I need help with taxi.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "The time is 16:45.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "well thank you thats all for today.", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: price is moderate; party size is 1 people; stay length is 2 nights; amenities is parking; destination is have free parking; requested information is price; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi; goal=search, booking, confirm_booking; price=moderate; party_size=1 people; stay_length=2 nights; amenities=parking, free parking; destination=have free parking, find a moderate restaurant; requested_info=price; when=thursday, 1, 2, 16:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002932", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sounds good can I make a booking for 7 people at 14:00 on saturday?\nChunk 2: Beautiful, just need some info on the express by holiday inn cambridge.\nChunk 3: yeah i want to book that hotel too.\nChunk 4: for the same group of people.\nChunk 5: I will need thursday at 17:00 please.\nChunk 6: 4 nights, please Reference number, please.\nChunk 7: Great, that will do it, I appreciate your help today Thank you.", "streaming_reasoning": "C1 goal=request_info; time+=7, 14:00; day+=saturday; party_size+=7 people; goal=confirm_booking. C2 goal=search. C3 domain=hotel; hotel_type+=hotel. C4 intent=context_update. C5 time+=17:00; day+=thursday. C6 stay_length+=4 nights; requested_info+=reference_number. C7 day+=today.", "deep_reasoning": "Need domain=hotel; goal=booking, request_info, search; party_size=7 people; stay_length=4 nights; requested_info=reference_number; when=saturday, thursday, today, 7, 14:00, 17:00.", "answer": "I can help with that and include the reference number once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Sounds good can I make a booking for 7 people at 14:00 on saturday?\nChunk 2: Beautiful, just need some info on the express by holiday inn cambridge.\nChunk 3: yeah i want to book that hotel too.\nChunk 4: for the same group of people.\nChunk 5: I will need thursday at 17:00 please.\nChunk 6: 4 nights, please Reference number, please.\nChunk 7: Great, that will do it, I appreciate your help today Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info; time+=7, 14:00; day+=saturday; party_size+=7 people; goal=confirm_booking. C2 goal=search. C3 domain=hotel; hotel_type+=hotel. C4 intent=context_update. C5 time+=17:00; day+=thursday. C6 stay_length+=4 nights; requested_info+=reference_number. C7 day+=today.\n\nDeep reasoning: Need domain=hotel; goal=booking, request_info, search; party_size=7 people; stay_length=4 nights; requested_info=reference_number; when=saturday, thursday, today, 7, 14:00, 17:00.\n\nAnswer: I can help with that and include the reference number once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Sounds good can I make a booking for 7 people at 14:00 on saturday?\nChunk 2: Beautiful, just need some info on the express by holiday inn cambridge.\nChunk 3: yeah i want to book that hotel too.\nChunk 4: for the same group of people.\nChunk 5: I will need thursday at 17:00 please.\nChunk 6: 4 nights, please Reference number, please.\nChunk 7: Great, that will do it, I appreciate your help today Thank you.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is confirm booking.; time: 7; day: saturday; party size: 7 people. Next, the goal is search. Next, the topic is hotel; hotel type: hotel. Next, intent: context_update. Next, time: 17:00; day: thursday. Next, stay length: 4 nights; requested information: reference_number. Finally, day: today. In summary, The overall topic is hotel. the goal is search.. time: 7, 17:00; day: saturday, thursday., today.; party size: 7 people; hotel type: hotel.; intent: context_update.; stay length: 4 nights; requested information: reference_number..", "trace": "C1 goal=request_info; time+=7, 14:00; day+=saturday; party_size+=7 people; goal=confirm_booking. C2 goal=search. C3 domain=hotel; hotel_type+=hotel. C4 intent=context_update. C5 time+=17:00; day+=thursday. C6 stay_length+=4 nights; requested_info+=reference_number. C7 day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Sounds good can I make a booking for 7 people at 14:00 on saturday?", "streaming_reasoning": "Initially, the goal is confirm booking.; time: 7; day: saturday; party size: 7 people.", "trace": "goal=request_info; time+=7, 14:00; day+=saturday; party_size+=7 people; goal=confirm_booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Beautiful, just need some info on the express by holiday inn cambridge.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "yeah i want to book that hotel too.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel..", "trace": "domain=hotel; hotel_type+=hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "for the same group of people.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will need thursday at 17:00 please.", "streaming_reasoning": "As more information arrives, time: 17:00; day: thursday..", "trace": "time+=17:00; day+=thursday."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "4 nights, please Reference number, please.", "streaming_reasoning": "As more information arrives, stay length: 4 nights; requested information: reference_number..", "trace": "stay_length+=4 nights; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Great, that will do it, I appreciate your help today Thank you.", "streaming_reasoning": "Finally, day: today..", "trace": "day+=today."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: party size is 7 people; stay length is 4 nights; requested information is reference_number; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the reference number once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, request_info, search; party_size=7 people; stay_length=4 nights; requested_info=reference_number; when=saturday, thursday, today, 7, 14:00, 17:00."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002933", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: I'm looking for somewhere to go in the centre area.\nChunk 3: I would love to maybe tour a college if I can.\nChunk 4: Yes, and do you have the address and phone number No thank you.\nChunk 5: You have been very helpful.\nChunk 6: Have a great day.", "streaming_reasoning": "C1 [SKIP: greeting_only]. C2 goal=search; area+=centre; destination+=go in the centre area. C3 domain=attraction; destination+=maybe tour a college if i can. C4 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C5 intent=context_update. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction; goal=search, request_info; area=centre; destination=go in the centre area, maybe tour a college if i can; requested_info=address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi!\nChunk 2: I'm looking for somewhere to go in the centre area.\nChunk 3: I would love to maybe tour a college if I can.\nChunk 4: Yes, and do you have the address and phone number No thank you.\nChunk 5: You have been very helpful.\nChunk 6: Have a great day."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: greeting_only]. C2 goal=search; area+=centre; destination+=go in the centre area. C3 domain=attraction; destination+=maybe tour a college if i can. C4 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C5 intent=context_update. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; area=centre; destination=go in the centre area, maybe tour a college if i can; requested_info=address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi!\nChunk 2: I'm looking for somewhere to go in the centre area.\nChunk 3: I would love to maybe tour a college if I can.\nChunk 4: Yes, and do you have the address and phone number No thank you.\nChunk 5: You have been very helpful.\nChunk 6: Have a great day.", "input_token_count": 56, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; area: centre; destination: go in the centre area. Next, the topic is attraction; destination: maybe tour a college if i can. Next, the goal is request info; requested information: address; acceptance: selected_option. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or greeting_only. In summary, The overall topic is attraction. the goal is request info. area: centre; destination: go in the centre area., maybe tour a college if i can.; requested information: address; acceptance: selected_option.; intent: context_update..", "trace": "C1 [SKIP: greeting_only]. C2 goal=search; area+=centre; destination+=go in the centre area. C3 domain=attraction; destination+=maybe tour a college if i can. C4 goal=request_info; requested_info+=address, phone; acceptance=selected_option. C5 intent=context_update. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi!", "streaming_reasoning": "The content at C1 was skipped (greeting_only).", "trace": "[SKIP: greeting_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm looking for somewhere to go in the centre area.", "streaming_reasoning": "As more information arrives, the goal is search; area: centre; destination: go in the centre area..", "trace": "goal=search; area+=centre; destination+=go in the centre area."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would love to maybe tour a college if I can.", "streaming_reasoning": "As more information arrives, the topic is attraction; destination: maybe tour a college if i can..", "trace": "domain=attraction; destination+=maybe tour a college if i can."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, and do you have the address and phone number No thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address; acceptance: selected_option..", "trace": "goal=request_info; requested_info+=address, phone; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "You have been very helpful.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; destination is go in the centre area; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; area=centre; destination=go in the centre area, maybe tour a college if i can; requested_info=address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002934", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I need a train to kings lynn and it should arrive by 14:45.\nChunk 2: Yes, I will be leaving Cambridge on Saturday.\nChunk 3: Thats perfect information,thank ytoiuy.\nChunk 4: Before you do, can you tell me how much it will cost?\nChunk 5: Do you know how long the train ride will take?\nChunk 6: Nope, that should do it, thanks!", "streaming_reasoning": "C1 domain=train; goal=search; time+=14:45; destination+=kings lynn and it should arrive by 14:45; acceptance=selected_option. C2 day+=saturday; acceptance=selected_option. C3 acceptance=selected_option. C4 goal=request_info; requested_info+=price. C5 requested_info+=travel_time. C6 intent=context_update.", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=kings lynn and it should arrive by 14:45; requested_info=price, travel_time; when=saturday, 14:45.", "answer": "I can help with that and include the price, travel time once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, I need a train to kings lynn and it should arrive by 14:45.\nChunk 2: Yes, I will be leaving Cambridge on Saturday.\nChunk 3: Thats perfect information,thank ytoiuy.\nChunk 4: Before you do, can you tell me how much it will cost?\nChunk 5: Do you know how long the train ride will take?\nChunk 6: Nope, that should do it, thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; time+=14:45; destination+=kings lynn and it should arrive by 14:45; acceptance=selected_option. C2 day+=saturday; acceptance=selected_option. C3 acceptance=selected_option. C4 goal=request_info; requested_info+=price. C5 requested_info+=travel_time. C6 intent=context_update.\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=kings lynn and it should arrive by 14:45; requested_info=price, travel_time; when=saturday, 14:45.\n\nAnswer: I can help with that and include the price, travel time once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, I need a train to kings lynn and it should arrive by 14:45.\nChunk 2: Yes, I will be leaving Cambridge on Saturday.\nChunk 3: Thats perfect information,thank ytoiuy.\nChunk 4: Before you do, can you tell me how much it will cost?\nChunk 5: Do you know how long the train ride will take?\nChunk 6: Nope, that should do it, thanks!", "input_token_count": 68, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; time: 14:45; destination: kings lynn and it should arrive by 14:45; acceptance: selected_option. Next, day: saturday; acceptance: selected_option. Next, acceptance: selected_option. Next, the goal is request info; requested information: price. Next, requested information: travel_time. Finally, intent: context_update. In summary, The overall topic is train. the goal is request info. time: 14:45; destination: kings lynn and it should arrive by 14:45; acceptance: selected_option.; day: saturday; requested information: price., travel_time.; intent: context_update..", "trace": "C1 domain=train; goal=search; time+=14:45; destination+=kings lynn and it should arrive by 14:45; acceptance=selected_option. C2 day+=saturday; acceptance=selected_option. C3 acceptance=selected_option. C4 goal=request_info; requested_info+=price. C5 requested_info+=travel_time. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, I need a train to kings lynn and it should arrive by 14:45.", "streaming_reasoning": "Initially, the topic is train; the goal is search; time: 14:45; destination: kings lynn and it should arrive by 14:45; acceptance: selected_option..", "trace": "domain=train; goal=search; time+=14:45; destination+=kings lynn and it should arrive by 14:45; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, I will be leaving Cambridge on Saturday.", "streaming_reasoning": "As more information arrives, day: saturday; acceptance: selected_option..", "trace": "day+=saturday; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thats perfect information,thank ytoiuy.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Before you do, can you tell me how much it will cost?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Do you know how long the train ride will take?", "streaming_reasoning": "As more information arrives, requested information: travel_time..", "trace": "requested_info+=travel_time."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Nope, that should do it, thanks!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is kings lynn and it should arrive by 14:45; requested information is price; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the price, travel time once I find the matching option.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=kings lynn and it should arrive by 14:45; requested_info=price, travel_time; when=saturday, 14:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002935", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need it for Saturday.\nChunk 2: I just need to get there by 12:30 so that train would be good.\nChunk 3: What time do I depart?\nChunk 4: No thanks, I just wanted to know the information.\nChunk 5: I do need a moderately priced hotel, with free parking.\nChunk 6: Can I get more information?\nChunk 7: I'd rather have a hotel.\nChunk 8: Are there any available?\nChunk 9: No thank you that will be all.", "streaming_reasoning": "C1 goal=search; day+=saturday. C2 domain=train; goal=request_info; time+=12:30. C3 goal=request_info. C4 [SKIP: thanks_only]. C5 domain=hotel; price+=moderate; hotel_type+=hotel; amenities+=parking, free parking. C6 [SKIP: repeated_information]. C7 intent=context_update. C8 goal=request_info. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, hotel; goal=search, request_info; price=moderate; amenities=parking, free parking; when=saturday, 12:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need it for Saturday.\nChunk 2: I just need to get there by 12:30 so that train would be good.\nChunk 3: What time do I depart?\nChunk 4: No thanks, I just wanted to know the information.\nChunk 5: I do need a moderately priced hotel, with free parking.\nChunk 6: Can I get more information?\nChunk 7: I'd rather have a hotel.\nChunk 8: Are there any available?\nChunk 9: No thank you that will be all."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; day+=saturday. C2 domain=train; goal=request_info; time+=12:30. C3 goal=request_info. C4 [SKIP: thanks_only]. C5 domain=hotel; price+=moderate; hotel_type+=hotel; amenities+=parking, free parking. C6 [SKIP: repeated_information]. C7 intent=context_update. C8 goal=request_info. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, hotel; goal=search, request_info; price=moderate; amenities=parking, free parking; when=saturday, 12:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need it for Saturday.\nChunk 2: I just need to get there by 12:30 so that train would be good.\nChunk 3: What time do I depart?\nChunk 4: No thanks, I just wanted to know the information.\nChunk 5: I do need a moderately priced hotel, with free parking.\nChunk 6: Can I get more information?\nChunk 7: I'd rather have a hotel.\nChunk 8: Are there any available?\nChunk 9: No thank you that will be all.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; day: saturday. Next, the topic is train; the goal is request info; time: 12:30. Next, the goal is request info. Next, the topic is hotel; price: moderate; hotel type: hotel; amenities: parking. Next, intent: context_update. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or repeated_information or thanks_only. In summary, The overall topic is hotel. the goal is request info.. day: saturday.; time: 12:30.; price: moderate; hotel type: hotel; amenities: parking; intent: context_update..", "trace": "C1 goal=search; day+=saturday. C2 domain=train; goal=request_info; time+=12:30. C3 goal=request_info. C4 [SKIP: thanks_only]. C5 domain=hotel; price+=moderate; hotel_type+=hotel; amenities+=parking, free parking. C6 [SKIP: repeated_information]. C7 intent=context_update. C8 goal=request_info. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need it for Saturday.", "streaming_reasoning": "Initially, the goal is search; day: saturday..", "trace": "goal=search; day+=saturday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I just need to get there by 12:30 so that train would be good.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is request info; time: 12:30..", "trace": "domain=train; goal=request_info; time+=12:30."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What time do I depart?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No thanks, I just wanted to know the information.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I do need a moderately priced hotel, with free parking.", "streaming_reasoning": "As more information arrives, the topic is hotel; price: moderate; hotel type: hotel; amenities: parking.", "trace": "domain=hotel; price+=moderate; hotel_type+=hotel; amenities+=parking, free parking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I get more information?", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'd rather have a hotel.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Are there any available?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No thank you that will be all.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: price is moderate; amenities is parking; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, request_info; price=moderate; amenities=parking, free parking; when=saturday, 12:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002936", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant in the west part of town and is in the moderate price range.\nChunk 2: I don't have a preference.\nChunk 3: What is the address No, thank you.\nChunk 4: That is all I wanted to know Good bye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=west; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=west; price=moderate; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a restaurant in the west part of town and is in the moderate price range.\nChunk 2: I don't have a preference.\nChunk 3: What is the address No, thank you.\nChunk 4: That is all I wanted to know Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=west; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=west; price=moderate; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a restaurant in the west part of town and is in the moderate price range.\nChunk 2: I don't have a preference.\nChunk 3: What is the address No, thank you.\nChunk 4: That is all I wanted to know Good bye.", "input_token_count": 48, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: west; price: moderate. Next, intent: context_update. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. area: west; price: moderate.; intent: context_update.; requested information: address..", "trace": "C1 domain=restaurant; goal=search; area+=west; price+=moderate. C2 intent=context_update. C3 goal=request_info; requested_info+=address. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a restaurant in the west part of town and is in the moderate price range.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: west; price: moderate..", "trace": "domain=restaurant; goal=search; area+=west; price+=moderate."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I don't have a preference.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What is the address No, thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That is all I wanted to know Good bye.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is west; price is moderate; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=west; price=moderate; requested_info=address; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002937", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No.\nChunk 2: Please book one of for 6 people and let me know the reference number please Thank you.\nChunk 3: I am also looking for places to go in town.\nChunk 4: Are there any architecture sights in the city centre That sounds wonderful.\nChunk 5: Can you give me their address, phone number and postcode?\nChunk 6: Can you give me another idea -- just to have a choice?\nChunk 7: I am interested in the old schools on Trinity Lane, can you give me the information of one?\nChunk 8: Nope, that's all I needed.\nChunk 9: You've been quite helpful.", "streaming_reasoning": "C1 [SKIP: acknowledgement_only]. C2 goal=request_info; party_size+=6 people; requested_info+=reference_number. C3 goal=search; destination+=go in town. C4 area+=centre. C5 requested_info+=address, phone, postcode. C6 goal=compare_alternative; destination+=have a choice. C7 goal=request_info. C8 [SKIP: closing_only]. C9 intent=context_update.", "deep_reasoning": "Need goal=booking, request_info, search, compare_alternative; area=centre; party_size=6 people; destination=go in town, have a choice; requested_info=reference_number, address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No.\nChunk 2: Please book one of for 6 people and let me know the reference number please Thank you.\nChunk 3: I am also looking for places to go in town.\nChunk 4: Are there any architecture sights in the city centre That sounds wonderful.\nChunk 5: Can you give me their address, phone number and postcode?\nChunk 6: Can you give me another idea -- just to have a choice?\nChunk 7: I am interested in the old schools on Trinity Lane, can you give me the information of one?\nChunk 8: Nope, that's all I needed.\nChunk 9: You've been quite helpful."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: acknowledgement_only]. C2 goal=request_info; party_size+=6 people; requested_info+=reference_number. C3 goal=search; destination+=go in town. C4 area+=centre. C5 requested_info+=address, phone, postcode. C6 goal=compare_alternative; destination+=have a choice. C7 goal=request_info. C8 [SKIP: closing_only]. C9 intent=context_update.\n\nDeep reasoning: Need goal=booking, request_info, search, compare_alternative; area=centre; party_size=6 people; destination=go in town, have a choice; requested_info=reference_number, address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No.\nChunk 2: Please book one of for 6 people and let me know the reference number please Thank you.\nChunk 3: I am also looking for places to go in town.\nChunk 4: Are there any architecture sights in the city centre That sounds wonderful.\nChunk 5: Can you give me their address, phone number and postcode?\nChunk 6: Can you give me another idea -- just to have a choice?\nChunk 7: I am interested in the old schools on Trinity Lane, can you give me the information of one?\nChunk 8: Nope, that's all I needed.\nChunk 9: You've been quite helpful.", "input_token_count": 106, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info; party size: 6 people; requested information: reference_number. Next, the goal is search; destination: go in town. Next, area: centre. Next, requested information: address. Next, the goal is compare alternative; destination: have a choice. Next, the goal is request info. Finally, intent: context_update.  Some chunks were skipped because they contained acknowledgement_only or closing_only. In summary, the goal is request info.. party size: 6 people; requested information: reference_number., address; destination: go in town., have a choice.; area: centre.; intent: context_update..", "trace": "C1 [SKIP: acknowledgement_only]. C2 goal=request_info; party_size+=6 people; requested_info+=reference_number. C3 goal=search; destination+=go in town. C4 area+=centre. C5 requested_info+=address, phone, postcode. C6 goal=compare_alternative; destination+=have a choice. C7 goal=request_info. C8 [SKIP: closing_only]. C9 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No.", "streaming_reasoning": "The content at C1 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Please book one of for 6 people and let me know the reference number please Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; party size: 6 people; requested information: reference_number..", "trace": "goal=request_info; party_size+=6 people; requested_info+=reference_number."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am also looking for places to go in town.", "streaming_reasoning": "As more information arrives, the goal is search; destination: go in town..", "trace": "goal=search; destination+=go in town."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Are there any architecture sights in the city centre That sounds wonderful.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you give me their address, phone number and postcode?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, phone, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you give me another idea -- just to have a choice?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; destination: have a choice..", "trace": "goal=compare_alternative; destination+=have a choice."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am interested in the old schools on Trinity Lane, can you give me the information of one?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Nope, that's all I needed.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "You've been quite helpful.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "Need goal=booking, request_info, search, compare_alternative; area=centre; party_size=6 people; destination=go in town, have a choice; requested_info=reference_number, address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002939", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Try changing from no internet to free wifi and see what happens.\nChunk 2: I need one with wifi.\nChunk 3: Yes, please just forward me the area, hotel type and their phone number.\nChunk 4: The Huntington Marriott in the west would be great.\nChunk 5: What is the hotel type and phone number thanks for helping.\nChunk 6: No, I think I will wait on booking at this time.\nChunk 7: Thank you for your assistance.", "streaming_reasoning": "C1 amenities+=wifi, internet; destination+=free wifi and see what happens; departure+=no internet. C2 goal=search. C3 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone; acceptance=selected_option. C4 area+=west. C5 intent=context_update. C6 goal=booking. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info, booking; area=west; amenities=wifi, internet; destination=free wifi and see what happens; departure=no internet; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Try changing from no internet to free wifi and see what happens.\nChunk 2: I need one with wifi.\nChunk 3: Yes, please just forward me the area, hotel type and their phone number.\nChunk 4: The Huntington Marriott in the west would be great.\nChunk 5: What is the hotel type and phone number thanks for helping.\nChunk 6: No, I think I will wait on booking at this time.\nChunk 7: Thank you for your assistance."}, {"role": "assistant", "content": "Streaming reasoning: C1 amenities+=wifi, internet; destination+=free wifi and see what happens; departure+=no internet. C2 goal=search. C3 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone; acceptance=selected_option. C4 area+=west. C5 intent=context_update. C6 goal=booking. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info, booking; area=west; amenities=wifi, internet; destination=free wifi and see what happens; departure=no internet; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Try changing from no internet to free wifi and see what happens.\nChunk 2: I need one with wifi.\nChunk 3: Yes, please just forward me the area, hotel type and their phone number.\nChunk 4: The Huntington Marriott in the west would be great.\nChunk 5: What is the hotel type and phone number thanks for helping.\nChunk 6: No, I think I will wait on booking at this time.\nChunk 7: Thank you for your assistance.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, amenities: wifi; destination: free wifi and see what happens; departure point: no internet. Next, the goal is search. Next, the topic is hotel; the goal is request info; hotel type: hotel; requested information: phone; acceptance: selected_option. Next, area: west. Next, intent: context_update. Finally, the goal is booking.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is hotel. the goal is booking.. amenities: wifi; destination: free wifi and see what happens; departure point: no internet.; hotel type: hotel; requested information: phone; acceptance: selected_option.; area: west.; intent: context_update..", "trace": "C1 amenities+=wifi, internet; destination+=free wifi and see what happens; departure+=no internet. C2 goal=search. C3 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone; acceptance=selected_option. C4 area+=west. C5 intent=context_update. C6 goal=booking. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Try changing from no internet to free wifi and see what happens.", "streaming_reasoning": "Initially, amenities: wifi; destination: free wifi and see what happens; departure point: no internet..", "trace": "amenities+=wifi, internet; destination+=free wifi and see what happens; departure+=no internet."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I need one with wifi.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, please just forward me the area, hotel type and their phone number.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is request info; hotel type: hotel; requested information: phone; acceptance: selected_option..", "trace": "domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The Huntington Marriott in the west would be great.", "streaming_reasoning": "As more information arrives, area: west..", "trace": "area+=west."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What is the hotel type and phone number thanks for helping.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, I think I will wait on booking at this time.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you for your assistance.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is west; amenities is wifi; destination is free wifi and see what happens; departure point is no internet; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info, booking; area=west; amenities=wifi, internet; destination=free wifi and see what happens; departure=no internet; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002940", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a restaurant in the north part of town that serves french food.\nChunk 2: What is their address, number, and price range?\nChunk 3: No, that takes care of it.\nChunk 4: Thank you for your help.", "streaming_reasoning": "C1 domain=restaurant; area+=north; cuisine+=french. C2 goal=request_info; requested_info+=address, price. C3 goal=modify_constraint. C4 [SKIP: thanks_only].", "deep_reasoning": "Need domain=restaurant; goal=request_info; area=north; food=french; requested_info=address, price; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a restaurant in the north part of town that serves french food.\nChunk 2: What is their address, number, and price range?\nChunk 3: No, that takes care of it.\nChunk 4: Thank you for your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=north; cuisine+=french. C2 goal=request_info; requested_info+=address, price. C3 goal=modify_constraint. C4 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=restaurant; goal=request_info; area=north; food=french; requested_info=address, price; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a restaurant in the north part of town that serves french food.\nChunk 2: What is their address, number, and price range?\nChunk 3: No, that takes care of it.\nChunk 4: Thank you for your help.", "input_token_count": 42, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: north; cuisine: french. Next, the goal is request info; requested information: address. Finally, the goal is modify constraint.  Some chunks were skipped because they contained thanks_only. In summary, The overall topic is restaurant. the goal is modify constraint.. area: north; cuisine: french.; requested information: address.", "trace": "C1 domain=restaurant; area+=north; cuisine+=french. C2 goal=request_info; requested_info+=address, price. C3 goal=modify_constraint. C4 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a restaurant in the north part of town that serves french food.", "streaming_reasoning": "Initially, the topic is restaurant; area: north; cuisine: french..", "trace": "domain=restaurant; area+=north; cuisine+=french."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is their address, number, and price range?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, price."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "No, that takes care of it.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is north; cuisine is french; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info; area=north; food=french; requested_info=address, price; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002943", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would any of the ones you mention have a 4-star rating as well as free parking?\nChunk 2: It is for 2 people.\nChunk 3: The time is monday, 2, 5.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: Yes, I also need something to do in the east part of town as well please.\nChunk 7: No, not really just get me the address to something good.\nChunk 8: I want to find a hotel.\nChunk 9: I also need the address.\nChunk 10: Thanks, that's all I need.\nChunk 11: Have a nice day.", "streaming_reasoning": "C1 amenities+=parking, free parking. C2 party_size+=2 people. C3 time+=2, 5; day+=monday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 area+=east; destination+=do in the east part of town as well pleas; goal=confirm_booking. C7 destination+=something good; requested_info+=address. C8 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C9 [SKIP: repeated_information]. C10 [SKIP: closing_only]. C11 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=booking, search, request_info; area=east; party_size=2 people; amenities=parking, free parking; destination=do in the east part of town as well pleas, something good, find a hotel; requested_info=reference_number, address; when=monday, 2, 5; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Would any of the ones you mention have a 4-star rating as well as free parking?\nChunk 2: It is for 2 people.\nChunk 3: The time is monday, 2, 5.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: Yes, I also need something to do in the east part of town as well please.\nChunk 7: No, not really just get me the address to something good.\nChunk 8: I want to find a hotel.\nChunk 9: I also need the address.\nChunk 10: Thanks, that's all I need.\nChunk 11: Have a nice day."}, {"role": "assistant", "content": "Streaming reasoning: C1 amenities+=parking, free parking. C2 party_size+=2 people. C3 time+=2, 5; day+=monday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 area+=east; destination+=do in the east part of town as well pleas; goal=confirm_booking. C7 destination+=something good; requested_info+=address. C8 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C9 [SKIP: repeated_information]. C10 [SKIP: closing_only]. C11 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=booking, search, request_info; area=east; party_size=2 people; amenities=parking, free parking; destination=do in the east part of town as well pleas, something good, find a hotel; requested_info=reference_number, address; when=monday, 2, 5; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would any of the ones you mention have a 4-star rating as well as free parking?\nChunk 2: It is for 2 people.\nChunk 3: The time is monday, 2, 5.\nChunk 4: Please make a booking.\nChunk 5: I also need the reference number.\nChunk 6: Yes, I also need something to do in the east part of town as well please.\nChunk 7: No, not really just get me the address to something good.\nChunk 8: I want to find a hotel.\nChunk 9: I also need the address.\nChunk 10: Thanks, that's all I need.\nChunk 11: Have a nice day.", "input_token_count": 106, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, amenities: parking. Next, party size: 2 people. Next, time: 2; day: monday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the goal is confirm booking.; area: east; destination: do in the east part of town as well pleas. Next, destination: something good; requested information: address. Finally, the topic is hotel; hotel type: hotel; destination: find a hotel.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is hotel. the goal is confirm booking.. amenities: parking; party size: 2 people.; time: 2; day: monday.; requested information: reference_number., address.; area: east; destination: do in the east part of town as well pleas, something good, find a hotel.; hotel type: hotel.", "trace": "C1 amenities+=parking, free parking. C2 party_size+=2 people. C3 time+=2, 5; day+=monday. C4 goal=booking. C5 goal=request_info; requested_info+=reference_number. C6 area+=east; destination+=do in the east part of town as well pleas; goal=confirm_booking. C7 destination+=something good; requested_info+=address. C8 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C9 [SKIP: repeated_information]. C10 [SKIP: closing_only]. C11 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Would any of the ones you mention have a 4-star rating as well as free parking?", "streaming_reasoning": "Initially, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It is for 2 people.", "streaming_reasoning": "As more information arrives, party size: 2 people..", "trace": "party_size+=2 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is monday, 2, 5.", "streaming_reasoning": "As more information arrives, time: 2; day: monday..", "trace": "time+=2, 5; day+=monday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, I also need something to do in the east part of town as well please.", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; area: east; destination: do in the east part of town as well pleas.", "trace": "area+=east; destination+=do in the east part of town as well pleas; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, not really just get me the address to something good.", "streaming_reasoning": "As more information arrives, destination: something good; requested information: address..", "trace": "destination+=something good; requested_info+=address."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I also need the address.", "streaming_reasoning": "The content at C9 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Thanks, that's all I need.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "Have a nice day.", "streaming_reasoning": "The content at C11 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: area is east; party size is 2 people; amenities is parking; destination is do in the east part of town as well pleas; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, search, request_info; area=east; party_size=2 people; amenities=parking, free parking; destination=do in the east part of town as well pleas, something good, find a hotel; requested_info=reference_number, address; when=monday, 2, 5; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002944", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can I get a train to Cambridge on Friday?\nChunk 2: Actually, I need to depart from leicester after 12:15.\nChunk 3: Yes.\nChunk 4: Could you give me the Train ID?\nChunk 5: I need to find a cheap modern European restaurant.\nChunk 6: Can I please have the phone number and postcode?\nChunk 7: No, that should be all.\nChunk 8: Thank you for all your help.", "streaming_reasoning": "C1 domain=train; goal=request_info; day+=friday; destination+=cambridge on friday. C2 goal=search; time+=12:15; departure+=leicester after 12:15. C3 [SKIP: acknowledgement_only]. C4 goal=request_info. C5 domain=restaurant; cuisine+=european; price+=cheap; destination+=find a cheap modern european restaurant. C6 requested_info+=phone, postcode. C7 goal=modify_constraint. C8 [SKIP: thanks_only].", "deep_reasoning": "Need domain=train, restaurant; goal=request_info, search; food=european; price=cheap; destination=cambridge on friday, find a cheap modern european restaurant; departure=leicester after 12:15; requested_info=phone, postcode; when=friday, 12:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can I get a train to Cambridge on Friday?\nChunk 2: Actually, I need to depart from leicester after 12:15.\nChunk 3: Yes.\nChunk 4: Could you give me the Train ID?\nChunk 5: I need to find a cheap modern European restaurant.\nChunk 6: Can I please have the phone number and postcode?\nChunk 7: No, that should be all.\nChunk 8: Thank you for all your help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=request_info; day+=friday; destination+=cambridge on friday. C2 goal=search; time+=12:15; departure+=leicester after 12:15. C3 [SKIP: acknowledgement_only]. C4 goal=request_info. C5 domain=restaurant; cuisine+=european; price+=cheap; destination+=find a cheap modern european restaurant. C6 requested_info+=phone, postcode. C7 goal=modify_constraint. C8 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=request_info, search; food=european; price=cheap; destination=cambridge on friday, find a cheap modern european restaurant; departure=leicester after 12:15; requested_info=phone, postcode; when=friday, 12:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can I get a train to Cambridge on Friday?\nChunk 2: Actually, I need to depart from leicester after 12:15.\nChunk 3: Yes.\nChunk 4: Could you give me the Train ID?\nChunk 5: I need to find a cheap modern European restaurant.\nChunk 6: Can I please have the phone number and postcode?\nChunk 7: No, that should be all.\nChunk 8: Thank you for all your help.", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is request info; day: friday; destination: cambridge on friday. Next, the goal is search; time: 12:15; departure point: leicester after 12:15. Next, the goal is request info. Next, the topic is restaurant; cuisine: european; price: cheap; destination: find a cheap modern european restaurant. Next, requested information: phone. Finally, the goal is modify constraint.  Some chunks were skipped because they contained acknowledgement_only or thanks_only. In summary, The overall topic is restaurant. the goal is modify constraint.. day: friday; destination: cambridge on friday., find a cheap modern european restaurant.; time: 12:15; departure point: leicester after 12:15.; cuisine: european; price: cheap; requested information: phone.", "trace": "C1 domain=train; goal=request_info; day+=friday; destination+=cambridge on friday. C2 goal=search; time+=12:15; departure+=leicester after 12:15. C3 [SKIP: acknowledgement_only]. C4 goal=request_info. C5 domain=restaurant; cuisine+=european; price+=cheap; destination+=find a cheap modern european restaurant. C6 requested_info+=phone, postcode. C7 goal=modify_constraint. C8 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can I get a train to Cambridge on Friday?", "streaming_reasoning": "Initially, the topic is train; the goal is request info; day: friday; destination: cambridge on friday..", "trace": "domain=train; goal=request_info; day+=friday; destination+=cambridge on friday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Actually, I need to depart from leicester after 12:15.", "streaming_reasoning": "As more information arrives, the goal is search; time: 12:15; departure point: leicester after 12:15..", "trace": "goal=search; time+=12:15; departure+=leicester after 12:15."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes.", "streaming_reasoning": "The content at C3 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could you give me the Train ID?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need to find a cheap modern European restaurant.", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: european; price: cheap; destination: find a cheap modern european restaurant..", "trace": "domain=restaurant; cuisine+=european; price+=cheap; destination+=find a cheap modern european restaurant."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can I please have the phone number and postcode?", "streaming_reasoning": "As more information arrives, requested information: phone.", "trace": "requested_info+=phone, postcode."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that should be all.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Thank you for all your help.", "streaming_reasoning": "The content at C8 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: cuisine is european; price is cheap; destination is cambridge on friday; departure point is leicester after 12:15; requested information is phone; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=request_info, search; food=european; price=cheap; destination=cambridge on friday, find a cheap modern european restaurant; departure=leicester after 12:15; requested_info=phone, postcode; when=friday, 12:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002945", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, the hotel should include free wifi.\nChunk 2: As long as it has a 3 star rating, please book the Gonville Hotel for me.\nChunk 3: I need it for Tuesday for 5 nights for 1 person.\nChunk 4: Can you check to see if that hotel can be booked for 1 night instead Thank you.\nChunk 5: That's all I need.\nChunk 6: You definitely did, thanks so much!", "streaming_reasoning": "C1 domain=hotel; hotel_type+=hotel; amenities+=wifi; acceptance=selected_option. C2 goal=booking; stars+=3 stars. C3 goal=search; day+=tuesday; stay_length+=5 nights. C4 goal=compare_alternative; stay_length+=1 nights. C5 [SKIP: closing_only]. C6 intent=context_update.", "deep_reasoning": "Need domain=hotel; goal=booking, search, compare_alternative; stay_length=5 nights, 1 nights; stars=3 stars; amenities=wifi; when=tuesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, the hotel should include free wifi.\nChunk 2: As long as it has a 3 star rating, please book the Gonville Hotel for me.\nChunk 3: I need it for Tuesday for 5 nights for 1 person.\nChunk 4: Can you check to see if that hotel can be booked for 1 night instead Thank you.\nChunk 5: That's all I need.\nChunk 6: You definitely did, thanks so much!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; hotel_type+=hotel; amenities+=wifi; acceptance=selected_option. C2 goal=booking; stars+=3 stars. C3 goal=search; day+=tuesday; stay_length+=5 nights. C4 goal=compare_alternative; stay_length+=1 nights. C5 [SKIP: closing_only]. C6 intent=context_update.\n\nDeep reasoning: Need domain=hotel; goal=booking, search, compare_alternative; stay_length=5 nights, 1 nights; stars=3 stars; amenities=wifi; when=tuesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, the hotel should include free wifi.\nChunk 2: As long as it has a 3 star rating, please book the Gonville Hotel for me.\nChunk 3: I need it for Tuesday for 5 nights for 1 person.\nChunk 4: Can you check to see if that hotel can be booked for 1 night instead Thank you.\nChunk 5: That's all I need.\nChunk 6: You definitely did, thanks so much!", "input_token_count": 73, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; hotel type: hotel; amenities: wifi; acceptance: selected_option. Next, the goal is booking; star rating: 3 stars. Next, the goal is search; day: tuesday; stay length: 5 nights. Next, the goal is compare alternative; stay length: 1 nights. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is compare alternative. hotel type: hotel; amenities: wifi; acceptance: selected_option.; star rating: 3 stars.; day: tuesday; stay length: 5 nights., 1 nights.; intent: context_update..", "trace": "C1 domain=hotel; hotel_type+=hotel; amenities+=wifi; acceptance=selected_option. C2 goal=booking; stars+=3 stars. C3 goal=search; day+=tuesday; stay_length+=5 nights. C4 goal=compare_alternative; stay_length+=1 nights. C5 [SKIP: closing_only]. C6 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, the hotel should include free wifi.", "streaming_reasoning": "Initially, the topic is hotel; hotel type: hotel; amenities: wifi; acceptance: selected_option..", "trace": "domain=hotel; hotel_type+=hotel; amenities+=wifi; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "As long as it has a 3 star rating, please book the Gonville Hotel for me.", "streaming_reasoning": "As more information arrives, the goal is booking; star rating: 3 stars..", "trace": "goal=booking; stars+=3 stars."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need it for Tuesday for 5 nights for 1 person.", "streaming_reasoning": "As more information arrives, the goal is search; day: tuesday; stay length: 5 nights..", "trace": "goal=search; day+=tuesday; stay_length+=5 nights."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you check to see if that hotel can be booked for 1 night instead Thank you.", "streaming_reasoning": "As more information arrives, the goal is compare alternative; stay length: 1 nights..", "trace": "goal=compare_alternative; stay_length+=1 nights."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That's all I need.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "You definitely did, thanks so much!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: stay length is 5 nights; star rating is 3 stars; amenities is wifi; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=booking, search, compare_alternative; stay_length=5 nights, 1 nights; stars=3 stars; amenities=wifi; when=tuesday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002946", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want a train departing from Cambridge, going to Ely.\nChunk 2: Saturday, arrival by 21:45.\nChunk 3: That's a good time.\nChunk 4: Please book TR7349 for 5 people, please.\nChunk 5: I am also looking for a place to stay that is cheap and 4 stars.\nChunk 6: Yes, i need a guesthouse in the east please Great!\nChunk 7: May I please have the phone number and postcode?\nChunk 8: I got it.Thank you.", "streaming_reasoning": "C1 domain=train; goal=search; destination+=ely; departure+=cambridge,, cambridge. C2 time+=21:45; day+=saturday. C3 intent=context_update. C4 goal=booking; party_size+=5 people. C5 domain=hotel; price+=cheap; stars+=4 stars; destination+=stay that is cheap and 4 stars. C6 area+=east; hotel_type+=guesthouse; goal=confirm_booking. C7 goal=request_info; requested_info+=phone, postcode. C8 intent=context_update.", "deep_reasoning": "Need domain=train, hotel; goal=search, booking, request_info; area=east; price=cheap; party_size=5 people; stars=4 stars; destination=ely, stay that is cheap and 4 stars; departure=cambridge,, cambridge; requested_info=phone, postcode; when=saturday, 21:45.", "answer": "I can help with that and include the phone, postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want a train departing from Cambridge, going to Ely.\nChunk 2: Saturday, arrival by 21:45.\nChunk 3: That's a good time.\nChunk 4: Please book TR7349 for 5 people, please.\nChunk 5: I am also looking for a place to stay that is cheap and 4 stars.\nChunk 6: Yes, i need a guesthouse in the east please Great!\nChunk 7: May I please have the phone number and postcode?\nChunk 8: I got it.Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; destination+=ely; departure+=cambridge,, cambridge. C2 time+=21:45; day+=saturday. C3 intent=context_update. C4 goal=booking; party_size+=5 people. C5 domain=hotel; price+=cheap; stars+=4 stars; destination+=stay that is cheap and 4 stars. C6 area+=east; hotel_type+=guesthouse; goal=confirm_booking. C7 goal=request_info; requested_info+=phone, postcode. C8 intent=context_update.\n\nDeep reasoning: Need domain=train, hotel; goal=search, booking, request_info; area=east; price=cheap; party_size=5 people; stars=4 stars; destination=ely, stay that is cheap and 4 stars; departure=cambridge,, cambridge; requested_info=phone, postcode; when=saturday, 21:45.\n\nAnswer: I can help with that and include the phone, postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want a train departing from Cambridge, going to Ely.\nChunk 2: Saturday, arrival by 21:45.\nChunk 3: That's a good time.\nChunk 4: Please book TR7349 for 5 people, please.\nChunk 5: I am also looking for a place to stay that is cheap and 4 stars.\nChunk 6: Yes, i need a guesthouse in the east please Great!\nChunk 7: May I please have the phone number and postcode?\nChunk 8: I got it.Thank you.", "input_token_count": 81, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; destination: ely; departure point: cambridge. Next, time: 21:45; day: saturday. Next, intent: context_update. Next, the goal is booking; party size: 5 people. Next, the topic is hotel; price: cheap; star rating: 4 stars; destination: stay that is cheap and 4 stars. Next, the goal is confirm booking.; area: east; hotel type: guesthouse. Next, the goal is request info; requested information: phone. Finally, intent: context_update. In summary, The overall topic is hotel. the goal is request info. destination: ely, stay that is cheap and 4 stars.; departure point: cambridge; time: 21:45; day: saturday.; intent: context_update.; party size: 5 people.; price: cheap; star rating: 4 stars; area: east; hotel type: guesthouse; requested information: phone.", "trace": "C1 domain=train; goal=search; destination+=ely; departure+=cambridge,, cambridge. C2 time+=21:45; day+=saturday. C3 intent=context_update. C4 goal=booking; party_size+=5 people. C5 domain=hotel; price+=cheap; stars+=4 stars; destination+=stay that is cheap and 4 stars. C6 area+=east; hotel_type+=guesthouse; goal=confirm_booking. C7 goal=request_info; requested_info+=phone, postcode. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want a train departing from Cambridge, going to Ely.", "streaming_reasoning": "Initially, the topic is train; the goal is search; destination: ely; departure point: cambridge.", "trace": "domain=train; goal=search; destination+=ely; departure+=cambridge,, cambridge."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Saturday, arrival by 21:45.", "streaming_reasoning": "As more information arrives, time: 21:45; day: saturday..", "trace": "time+=21:45; day+=saturday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That's a good time.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please book TR7349 for 5 people, please.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 5 people..", "trace": "goal=booking; party_size+=5 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I am also looking for a place to stay that is cheap and 4 stars.", "streaming_reasoning": "As more information arrives, the topic is hotel; price: cheap; star rating: 4 stars; destination: stay that is cheap and 4 stars..", "trace": "domain=hotel; price+=cheap; stars+=4 stars; destination+=stay that is cheap and 4 stars."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes, i need a guesthouse in the east please Great!", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; area: east; hotel type: guesthouse.", "trace": "area+=east; hotel_type+=guesthouse; goal=confirm_booking."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "May I please have the phone number and postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I got it.Thank you.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is east; price is cheap; party size is 5 people; star rating is 4 stars; destination is ely; departure point is cambridge; requested information is phone; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=train, hotel; goal=search, booking, request_info; area=east; price=cheap; party_size=5 people; stars=4 stars; destination=ely, stay that is cheap and 4 stars; departure=cambridge,, cambridge; requested_info=phone, postcode; when=saturday, 21:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002947", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would you be able to help me find a room that has free wifi?\nChunk 2: I'm looking for a guesthouse, and I misspoke earlier.\nChunk 3: I actually don't care about the internet, but I do need free parking.\nChunk 4: The area doesn't matter.\nChunk 5: Yes.\nChunk 6: I would like to book that for 4 people for 4 nights staring on Wednesday.\nChunk 7: Can you get it for 2 nights?\nChunk 8: That's all, thank you.", "streaming_reasoning": "C1 domain=hotel; goal=search; amenities+=wifi. C2 hotel_type+=guesthouse. C3 amenities+=parking, internet, free parking. C4 intent=context_update. C5 [SKIP: acknowledgement_only]. C6 goal=booking; day+=wednesday; party_size+=4 people; stay_length+=4 nights. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, booking; party_size=4 people; stay_length=4 nights; amenities=wifi, parking, internet, free parking; when=wednesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Would you be able to help me find a room that has free wifi?\nChunk 2: I'm looking for a guesthouse, and I misspoke earlier.\nChunk 3: I actually don't care about the internet, but I do need free parking.\nChunk 4: The area doesn't matter.\nChunk 5: Yes.\nChunk 6: I would like to book that for 4 people for 4 nights staring on Wednesday.\nChunk 7: Can you get it for 2 nights?\nChunk 8: That's all, thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; amenities+=wifi. C2 hotel_type+=guesthouse. C3 amenities+=parking, internet, free parking. C4 intent=context_update. C5 [SKIP: acknowledgement_only]. C6 goal=booking; day+=wednesday; party_size+=4 people; stay_length+=4 nights. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, booking; party_size=4 people; stay_length=4 nights; amenities=wifi, parking, internet, free parking; when=wednesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would you be able to help me find a room that has free wifi?\nChunk 2: I'm looking for a guesthouse, and I misspoke earlier.\nChunk 3: I actually don't care about the internet, but I do need free parking.\nChunk 4: The area doesn't matter.\nChunk 5: Yes.\nChunk 6: I would like to book that for 4 people for 4 nights staring on Wednesday.\nChunk 7: Can you get it for 2 nights?\nChunk 8: That's all, thank you.", "input_token_count": 83, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; amenities: wifi. Next, hotel type: guesthouse. Next, amenities: parking. Next, intent: context_update. Finally, the goal is booking; day: wednesday; party size: 4 people; stay length: 4 nights.  Some chunks were skipped because they contained acknowledgement_only or closing_only or repeated_information. In summary, The overall topic is hotel. the goal is booking. amenities: wifi., parking; hotel type: guesthouse.; intent: context_update.; day: wednesday; party size: 4 people; stay length: 4 nights..", "trace": "C1 domain=hotel; goal=search; amenities+=wifi. C2 hotel_type+=guesthouse. C3 amenities+=parking, internet, free parking. C4 intent=context_update. C5 [SKIP: acknowledgement_only]. C6 goal=booking; day+=wednesday; party_size+=4 people; stay_length+=4 nights. C7 [SKIP: repeated_information]. C8 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Would you be able to help me find a room that has free wifi?", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; amenities: wifi..", "trace": "domain=hotel; goal=search; amenities+=wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm looking for a guesthouse, and I misspoke earlier.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse..", "trace": "hotel_type+=guesthouse."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I actually don't care about the internet, but I do need free parking.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, internet, free parking."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The area doesn't matter.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes.", "streaming_reasoning": "The content at C5 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I would like to book that for 4 people for 4 nights staring on Wednesday.", "streaming_reasoning": "As more information arrives, the goal is booking; day: wednesday; party size: 4 people; stay length: 4 nights..", "trace": "goal=booking; day+=wednesday; party_size+=4 people; stay_length+=4 nights."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Can you get it for 2 nights?", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That's all, thank you.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: party size is 4 people; stay length is 4 nights; amenities is wifi; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, booking; party_size=4 people; stay_length=4 nights; amenities=wifi, parking, internet, free parking; when=wednesday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002948", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What's a good mid price restaurant?\nChunk 2: I would like Catalan food.\nChunk 3: How about Spanish food?\nChunk 4: Could i have the address, phone number and postcode please thank you, goodbye.\nChunk 5: Bye.", "streaming_reasoning": "C1 domain=restaurant; goal=request_info; requested_info+=price. C2 intent=context_update. C3 goal=recommendation. C4 requested_info+=address, phone, postcode. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=request_info, recommendation; requested_info=price, address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What's a good mid price restaurant?\nChunk 2: I would like Catalan food.\nChunk 3: How about Spanish food?\nChunk 4: Could i have the address, phone number and postcode please thank you, goodbye.\nChunk 5: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=request_info; requested_info+=price. C2 intent=context_update. C3 goal=recommendation. C4 requested_info+=address, phone, postcode. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=request_info, recommendation; requested_info=price, address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What's a good mid price restaurant?\nChunk 2: I would like Catalan food.\nChunk 3: How about Spanish food?\nChunk 4: Could i have the address, phone number and postcode please thank you, goodbye.\nChunk 5: Bye.", "input_token_count": 39, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is request info; requested information: price. Next, intent: context_update. Next, the goal is recommendation. Finally, requested information: address.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is recommendation.. requested information: price., address; intent: context_update..", "trace": "C1 domain=restaurant; goal=request_info; requested_info+=price. C2 intent=context_update. C3 goal=recommendation. C4 requested_info+=address, phone, postcode. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What's a good mid price restaurant?", "streaming_reasoning": "Initially, the topic is restaurant; the goal is request info; requested information: price..", "trace": "domain=restaurant; goal=request_info; requested_info+=price."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like Catalan food.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How about Spanish food?", "streaming_reasoning": "As more information arrives, the goal is recommendation..", "trace": "goal=recommendation."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Could i have the address, phone number and postcode please thank you, goodbye.", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, phone, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Bye.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: requested information is price. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info, recommendation; requested_info=price, address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003662", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, this is my first.Last week I went to a cookout for new professors at Dean Barksdale ' s home.\nChunk 2: I took a taxi because I didn ' t want to be late.But I was the first one.\nChunk 3: Cookouts often start slowly.\nChunk 4: A two o'clock start means you arrive any time after two.\nChunk 5: Thanks for telling me this.\nChunk 6: I was late getting back from the mall, but I'm hurrying.\nChunk 7: Why are you in such a hurry?\nChunk 8: They said, Dinner at eight, and it ' s only seven-fifteen.\nChunk 9: I don ' t want to be the first one there again.", "streaming_reasoning": "C1 casual_comment=first, last. C2 casual_comment=took, taxi. C3 casual_comment=cookouts, often. C4 casual_comment=two, o'clock. C5 [SKIP: thanks_only]. C6 casual_comment=late, getting. C7 question=true. C8 casual_comment=said, dinner. C9 casual_comment=don, first.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, this is my first.Last week I went to a cookout for new professors at Dean Barksdale ' s home.\nChunk 2: I took a taxi because I didn ' t want to be late.But I was the first one.\nChunk 3: Cookouts often start slowly.\nChunk 4: A two o'clock start means you arrive any time after two.\nChunk 5: Thanks for telling me this.\nChunk 6: I was late getting back from the mall, but I'm hurrying.\nChunk 7: Why are you in such a hurry?\nChunk 8: They said, Dinner at eight, and it ' s only seven-fifteen.\nChunk 9: I don ' t want to be the first one there again."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=first, last. C2 casual_comment=took, taxi. C3 casual_comment=cookouts, often. C4 casual_comment=two, o'clock. C5 [SKIP: thanks_only]. C6 casual_comment=late, getting. C7 question=true. C8 casual_comment=said, dinner. C9 casual_comment=don, first.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, this is my first.Last week I went to a cookout for new professors at Dean Barksdale ' s home.\nChunk 2: I took a taxi because I didn ' t want to be late.But I was the first one.\nChunk 3: Cookouts often start slowly.\nChunk 4: A two o'clock start means you arrive any time after two.\nChunk 5: Thanks for telling me this.\nChunk 6: I was late getting back from the mall, but I'm hurrying.\nChunk 7: Why are you in such a hurry?\nChunk 8: They said, Dinner at eight, and it ' s only seven-fifteen.\nChunk 9: I don ' t want to be the first one there again.", "input_token_count": 115, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the user comments on first. Next, the user comments on took. Next, the user comments on cookouts. Next, the user comments on two. Next, the user comments on late. Next, the input provides additional context about question=true. Next, the user comments on said. Finally, the user comments on don.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=first, last. C2 casual_comment=took, taxi. C3 casual_comment=cookouts, often. C4 casual_comment=two, o'clock. C5 [SKIP: thanks_only]. C6 casual_comment=late, getting. C7 question=true. C8 casual_comment=said, dinner. C9 casual_comment=don, first.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, this is my first.Last week I went to a cookout for new professors at Dean Barksdale ' s home.", "streaming_reasoning": "Initially, the user comments on first.", "trace": "casual_comment=first, last."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I took a taxi because I didn ' t want to be late.But I was the first one.", "streaming_reasoning": "As more information arrives, the user comments on took.", "trace": "casual_comment=took, taxi."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Cookouts often start slowly.", "streaming_reasoning": "As more information arrives, the user comments on cookouts.", "trace": "casual_comment=cookouts, often."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "A two o'clock start means you arrive any time after two.", "streaming_reasoning": "As more information arrives, the user comments on two.", "trace": "casual_comment=two, o'clock."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Thanks for telling me this.", "streaming_reasoning": "The content at C5 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I was late getting back from the mall, but I'm hurrying.", "streaming_reasoning": "As more information arrives, the user comments on late.", "trace": "casual_comment=late, getting."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Why are you in such a hurry?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "They said, Dinner at eight, and it ' s only seven-fifteen.", "streaming_reasoning": "As more information arrives, the user comments on said.", "trace": "casual_comment=said, dinner."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I don ' t want to be the first one there again.", "streaming_reasoning": "Finally, the user comments on don.", "trace": "casual_comment=don, first."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003663", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would you like something to eat Thank you.\nChunk 2: No.\nChunk 3: I'm late for dinner at my house.\nChunk 4: I really have to go.\nChunk 5: Would you like to call home I'd appreciate that.\nChunk 6: Please use the phone.", "streaming_reasoning": "C1 invitation=true. C2 refusal=true. C3 casual_comment=i'm, late. C4 leaving_reason=needs_to_go. C5 invitation=true. C6 casual_comment=use, phone.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Would you like something to eat Thank you.\nChunk 2: No.\nChunk 3: I'm late for dinner at my house.\nChunk 4: I really have to go.\nChunk 5: Would you like to call home I'd appreciate that.\nChunk 6: Please use the phone."}, {"role": "assistant", "content": "Streaming reasoning: C1 invitation=true. C2 refusal=true. C3 casual_comment=i'm, late. C4 leaving_reason=needs_to_go. C5 invitation=true. C6 casual_comment=use, phone.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Would you like something to eat Thank you.\nChunk 2: No.\nChunk 3: I'm late for dinner at my house.\nChunk 4: I really have to go.\nChunk 5: Would you like to call home I'd appreciate that.\nChunk 6: Please use the phone.", "input_token_count": 46, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, invitation: true. Next, refusal: true. Next, the user comments on i'm. Next, leaving reason: needs_to_go. Next, invitation: true. Finally, the user comments on use. In summary, invitation: true.; refusal: true.; leaving reason: needs_to_go..", "trace": "C1 invitation=true. C2 refusal=true. C3 casual_comment=i'm, late. C4 leaving_reason=needs_to_go. C5 invitation=true. C6 casual_comment=use, phone.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Would you like something to eat Thank you.", "streaming_reasoning": "Initially, invitation: true..", "trace": "invitation=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No.", "streaming_reasoning": "As more information arrives, refusal: true..", "trace": "refusal=true."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm late for dinner at my house.", "streaming_reasoning": "As more information arrives, the user comments on i'm.", "trace": "casual_comment=i'm, late."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I really have to go.", "streaming_reasoning": "As more information arrives, leaving reason: needs_to_go..", "trace": "leaving_reason=needs_to_go."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Would you like to call home I'd appreciate that.", "streaming_reasoning": "As more information arrives, invitation: true..", "trace": "invitation=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Please use the phone.", "streaming_reasoning": "Finally, the user comments on use.", "trace": "casual_comment=use, phone."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002949", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a cheap restaurant in the west part of town.\nChunk 2: Can you give me the telephone number of the vietnamese restaurant?\nChunk 3: Can you give me the address for Thanh Binh as well please Thank you Goodbye.", "streaming_reasoning": "C1 domain=restaurant; area+=west; price+=cheap. C2 goal=request_info; requested_info+=phone. C3 requested_info+=address.", "deep_reasoning": "Need domain=restaurant; goal=request_info; area=west; price=cheap; requested_info=phone, address.", "answer": "I can help with that and include the phone, address once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like a cheap restaurant in the west part of town.\nChunk 2: Can you give me the telephone number of the vietnamese restaurant?\nChunk 3: Can you give me the address for Thanh Binh as well please Thank you Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; area+=west; price+=cheap. C2 goal=request_info; requested_info+=phone. C3 requested_info+=address.\n\nDeep reasoning: Need domain=restaurant; goal=request_info; area=west; price=cheap; requested_info=phone, address.\n\nAnswer: I can help with that and include the phone, address once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like a cheap restaurant in the west part of town.\nChunk 2: Can you give me the telephone number of the vietnamese restaurant?\nChunk 3: Can you give me the address for Thanh Binh as well please Thank you Goodbye.", "input_token_count": 44, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; area: west; price: cheap. Next, the goal is request info; requested information: phone. Finally, requested information: address. In summary, The overall topic is restaurant. the goal is request info. area: west; price: cheap.; requested information: phone., address..", "trace": "C1 domain=restaurant; area+=west; price+=cheap. C2 goal=request_info; requested_info+=phone. C3 requested_info+=address.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like a cheap restaurant in the west part of town.", "streaming_reasoning": "Initially, the topic is restaurant; area: west; price: cheap..", "trace": "domain=restaurant; area+=west; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you give me the telephone number of the vietnamese restaurant?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you give me the address for Thanh Binh as well please Thank you Goodbye.", "streaming_reasoning": "Finally, requested information: address..", "trace": "requested_info+=address."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: area is west; price is cheap; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone, address once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info; area=west; price=cheap; requested_info=phone, address."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002950", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Wednesday at 19:45 the table is only for me.\nChunk 2: I'm also looking for a guesthouse with free parking.\nChunk 3: something that is in the same part of town as the restaurant would be good Price doesn't matter.\nChunk 4: Just something with the free parking.\nChunk 5: Wifi is great but not needed.\nChunk 6: i just want the address for now Great, thanks!\nChunk 7: That's all I needed right now!", "streaming_reasoning": "C1 time+=19:45; day+=wednesday. C2 domain=hotel; goal=search; hotel_type+=guesthouse; amenities+=parking, free parking. C3 domain=restaurant. C4 [SKIP: repeated_information]. C5 amenities+=wifi. C6 goal=request_info; requested_info+=address. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, request_info; amenities=parking, free parking, wifi; requested_info=address; when=wednesday, 19:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Wednesday at 19:45 the table is only for me.\nChunk 2: I'm also looking for a guesthouse with free parking.\nChunk 3: something that is in the same part of town as the restaurant would be good Price doesn't matter.\nChunk 4: Just something with the free parking.\nChunk 5: Wifi is great but not needed.\nChunk 6: i just want the address for now Great, thanks!\nChunk 7: That's all I needed right now!"}, {"role": "assistant", "content": "Streaming reasoning: C1 time+=19:45; day+=wednesday. C2 domain=hotel; goal=search; hotel_type+=guesthouse; amenities+=parking, free parking. C3 domain=restaurant. C4 [SKIP: repeated_information]. C5 amenities+=wifi. C6 goal=request_info; requested_info+=address. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, request_info; amenities=parking, free parking, wifi; requested_info=address; when=wednesday, 19:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Wednesday at 19:45 the table is only for me.\nChunk 2: I'm also looking for a guesthouse with free parking.\nChunk 3: something that is in the same part of town as the restaurant would be good Price doesn't matter.\nChunk 4: Just something with the free parking.\nChunk 5: Wifi is great but not needed.\nChunk 6: i just want the address for now Great, thanks!\nChunk 7: That's all I needed right now!", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, time: 19:45; day: wednesday. Next, the topic is hotel; the goal is search; hotel type: guesthouse; amenities: parking. Next, the topic is restaurant. Next, amenities: wifi. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is restaurant.. the goal is request info. time: 19:45; day: wednesday.; hotel type: guesthouse; amenities: parking, wifi.; requested information: address..", "trace": "C1 time+=19:45; day+=wednesday. C2 domain=hotel; goal=search; hotel_type+=guesthouse; amenities+=parking, free parking. C3 domain=restaurant. C4 [SKIP: repeated_information]. C5 amenities+=wifi. C6 goal=request_info; requested_info+=address. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Wednesday at 19:45 the table is only for me.", "streaming_reasoning": "Initially, time: 19:45; day: wednesday..", "trace": "time+=19:45; day+=wednesday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm also looking for a guesthouse with free parking.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is search; hotel type: guesthouse; amenities: parking.", "trace": "domain=hotel; goal=search; hotel_type+=guesthouse; amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "something that is in the same part of town as the restaurant would be good Price doesn't matter.", "streaming_reasoning": "As more information arrives, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Just something with the free parking.", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Wifi is great but not needed.", "streaming_reasoning": "As more information arrives, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "i just want the address for now Great, thanks!", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's all I needed right now!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: amenities is parking; requested information is address; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, request_info; amenities=parking, free parking, wifi; requested_info=address; when=wednesday, 19:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002951", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need an indian restaurant in the centre.\nChunk 2: I would like it to be in the expensive range of food, is that place expensive?\nChunk 3: Could you give me the phone number and postcode Great Thank you!\nChunk 4: That is all I need.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=indian. C2 price+=expensive; destination+=be in the expensive range of food. C3 goal=request_info; requested_info+=phone, postcode. C4 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=centre; food=indian; price=expensive; destination=be in the expensive range of food; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need an indian restaurant in the centre.\nChunk 2: I would like it to be in the expensive range of food, is that place expensive?\nChunk 3: Could you give me the phone number and postcode Great Thank you!\nChunk 4: That is all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; cuisine+=indian. C2 price+=expensive; destination+=be in the expensive range of food. C3 goal=request_info; requested_info+=phone, postcode. C4 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=centre; food=indian; price=expensive; destination=be in the expensive range of food; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need an indian restaurant in the centre.\nChunk 2: I would like it to be in the expensive range of food, is that place expensive?\nChunk 3: Could you give me the phone number and postcode Great Thank you!\nChunk 4: That is all I need.", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: indian. Next, price: expensive; destination: be in the expensive range of food. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. area: centre; cuisine: indian.; price: expensive; destination: be in the expensive range of food.; requested information: phone.", "trace": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=indian. C2 price+=expensive; destination+=be in the expensive range of food. C3 goal=request_info; requested_info+=phone, postcode. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need an indian restaurant in the centre.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: indian..", "trace": "domain=restaurant; goal=search; area+=centre; cuisine+=indian."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like it to be in the expensive range of food, is that place expensive?", "streaming_reasoning": "As more information arrives, price: expensive; destination: be in the expensive range of food..", "trace": "price+=expensive; destination+=be in the expensive range of food."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Could you give me the phone number and postcode Great Thank you!", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That is all I need.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is indian; price is expensive; destination is be in the expensive range of food; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=centre; food=indian; price=expensive; destination=be in the expensive range of food; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002952", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be departing from Norwich on Wednesday.\nChunk 2: That would be fine.\nChunk 3: How long is the trip?\nChunk 4: Thank you for the information!\nChunk 5: Yes, one ticket is fine Nope, that's it!\nChunk 6: Thanks!\nChunk 7: That's all thank you.", "streaming_reasoning": "C1 day+=wednesday; departure+=norwich on wednesday. C2 intent=context_update. C3 requested_info+=travel_time. C4 [SKIP: thanks_only]. C5 goal=confirm_booking; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need goal=confirm_booking; departure=norwich on wednesday; requested_info=travel_time; when=wednesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I will be departing from Norwich on Wednesday.\nChunk 2: That would be fine.\nChunk 3: How long is the trip?\nChunk 4: Thank you for the information!\nChunk 5: Yes, one ticket is fine Nope, that's it!\nChunk 6: Thanks!\nChunk 7: That's all thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=wednesday; departure+=norwich on wednesday. C2 intent=context_update. C3 requested_info+=travel_time. C4 [SKIP: thanks_only]. C5 goal=confirm_booking; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need goal=confirm_booking; departure=norwich on wednesday; requested_info=travel_time; when=wednesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I will be departing from Norwich on Wednesday.\nChunk 2: That would be fine.\nChunk 3: How long is the trip?\nChunk 4: Thank you for the information!\nChunk 5: Yes, one ticket is fine Nope, that's it!\nChunk 6: Thanks!\nChunk 7: That's all thank you.", "input_token_count": 49, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, day: wednesday; departure point: norwich on wednesday. Next, intent: context_update. Next, requested information: travel_time. Finally, the goal is confirm booking; acceptance: selected_option.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is confirm booking. day: wednesday; departure point: norwich on wednesday.; intent: context_update.; requested information: travel_time.; acceptance: selected_option..", "trace": "C1 day+=wednesday; departure+=norwich on wednesday. C2 intent=context_update. C3 requested_info+=travel_time. C4 [SKIP: thanks_only]. C5 goal=confirm_booking; acceptance=selected_option. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I will be departing from Norwich on Wednesday.", "streaming_reasoning": "Initially, day: wednesday; departure point: norwich on wednesday..", "trace": "day+=wednesday; departure+=norwich on wednesday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "That would be fine.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "How long is the trip?", "streaming_reasoning": "As more information arrives, requested information: travel_time..", "trace": "requested_info+=travel_time."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you for the information!", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, one ticket is fine Nope, that's it!", "streaming_reasoning": "As more information arrives, the goal is confirm booking; acceptance: selected_option..", "trace": "goal=confirm_booking; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's all thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=confirm_booking; departure=norwich on wednesday; requested_info=travel_time; when=wednesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002953", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I can do that.\nChunk 2: I am looking for places to go in town, a park.\nChunk 3: In the East preferably.\nChunk 4: Can you tell me the postcode?\nChunk 5: Can you also confirm the area that is in please?\nChunk 6: Thank you so much!\nChunk 7: Thank you that will be all I need.", "streaming_reasoning": "C1 goal=modify_constraint. C2 domain=attraction; goal=search; destination+=go in town; type+=park. C3 area+=east. C4 goal=request_info; requested_info+=postcode. C5 goal=request_info. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction; goal=search, request_info; area=east; destination=go in town; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, I can do that.\nChunk 2: I am looking for places to go in town, a park.\nChunk 3: In the East preferably.\nChunk 4: Can you tell me the postcode?\nChunk 5: Can you also confirm the area that is in please?\nChunk 6: Thank you so much!\nChunk 7: Thank you that will be all I need."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=modify_constraint. C2 domain=attraction; goal=search; destination+=go in town; type+=park. C3 area+=east. C4 goal=request_info; requested_info+=postcode. C5 goal=request_info. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; area=east; destination=go in town; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I can do that.\nChunk 2: I am looking for places to go in town, a park.\nChunk 3: In the East preferably.\nChunk 4: Can you tell me the postcode?\nChunk 5: Can you also confirm the area that is in please?\nChunk 6: Thank you so much!\nChunk 7: Thank you that will be all I need.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is modify constraint. Next, the topic is attraction; the goal is search; destination: go in town; type: park. Next, area: east. Next, the goal is request info; requested information: postcode. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is attraction. the goal is request info.. destination: go in town; type: park.; area: east.; requested information: postcode..", "trace": "C1 goal=modify_constraint. C2 domain=attraction; goal=search; destination+=go in town; type+=park. C3 area+=east. C4 goal=request_info; requested_info+=postcode. C5 goal=request_info. C6 [SKIP: thanks_only]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, I can do that.", "streaming_reasoning": "Initially, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I am looking for places to go in town, a park.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is search; destination: go in town; type: park..", "trace": "domain=attraction; goal=search; destination+=go in town; type+=park."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "In the East preferably.", "streaming_reasoning": "As more information arrives, area: east..", "trace": "area+=east."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you tell me the postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you also confirm the area that is in please?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thank you so much!", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thank you that will be all I need.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is east; destination is go in town; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; area=east; destination=go in town; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003666", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Alison, would you like to have some more?\nChunk 2: No thanks I've had enough.\nChunk 3: Actually you haven't had much.\nChunk 4: To tell you the truth, I am on the diet.\nChunk 5: That sounds ridiculous Why?", "streaming_reasoning": "C1 invitation=true. C2 [SKIP: thanks_only]. C3 casual_comment=actually, haven't. C4 casual_comment=tell, truth. C5 question=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Alison, would you like to have some more?\nChunk 2: No thanks I've had enough.\nChunk 3: Actually you haven't had much.\nChunk 4: To tell you the truth, I am on the diet.\nChunk 5: That sounds ridiculous Why?"}, {"role": "assistant", "content": "Streaming reasoning: C1 invitation=true. C2 [SKIP: thanks_only]. C3 casual_comment=actually, haven't. C4 casual_comment=tell, truth. C5 question=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Alison, would you like to have some more?\nChunk 2: No thanks I've had enough.\nChunk 3: Actually you haven't had much.\nChunk 4: To tell you the truth, I am on the diet.\nChunk 5: That sounds ridiculous Why?", "input_token_count": 42, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, invitation: true. Next, the user comments on actually. Next, the user comments on tell. Finally, the input provides additional context about question=true.  Some chunks were skipped because they contained thanks_only. In summary, invitation: true..", "trace": "C1 invitation=true. C2 [SKIP: thanks_only]. C3 casual_comment=actually, haven't. C4 casual_comment=tell, truth. C5 question=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Alison, would you like to have some more?", "streaming_reasoning": "Initially, invitation: true..", "trace": "invitation=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No thanks I've had enough.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Actually you haven't had much.", "streaming_reasoning": "As more information arrives, the user comments on actually.", "trace": "casual_comment=actually, haven't."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "To tell you the truth, I am on the diet.", "streaming_reasoning": "As more information arrives, the user comments on tell.", "trace": "casual_comment=tell, truth."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That sounds ridiculous Why?", "streaming_reasoning": "Finally, additional context is provided.", "trace": "question=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001973", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Back in October of last year I had my first drink.\nChunk 2: At that time I had never drank or tried any drugs or anything, so I was very nervous about trying anything mind altering like that.\nChunk 3: I had my first real drink back in October with some of my friends and I was really nervous about it.\nChunk 4: Why were you nervous about it?\nChunk 5: Usually drinking means to loosen up and have fun.\nChunk 6: It does, but I had never tried anything like drugs or alcohol before so I didn't know what to expect.", "streaming_reasoning": "C1 need=validation. C2 emotion=anxious; cause=trying anything mind altering like that; need=reassurance. C3 emotion=anxious; cause=I had my first real drink back in October with some of. C4 emotion=anxious; need=clarification. C5 support_signal=received. C6 support_signal=received.", "deep_reasoning": "User feels anxious after I had my first real drink back in October with some of and needs clarification.", "answer": "It makes sense to feel anxious after I had my first real drink back in October with some of. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Back in October of last year I had my first drink.\nChunk 2: At that time I had never drank or tried any drugs or anything, so I was very nervous about trying anything mind altering like that.\nChunk 3: I had my first real drink back in October with some of my friends and I was really nervous about it.\nChunk 4: Why were you nervous about it?\nChunk 5: Usually drinking means to loosen up and have fun.\nChunk 6: It does, but I had never tried anything like drugs or alcohol before so I didn't know what to expect."}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 emotion=anxious; cause=trying anything mind altering like that; need=reassurance. C3 emotion=anxious; cause=I had my first real drink back in October with some of. C4 emotion=anxious; need=clarification. C5 support_signal=received. C6 support_signal=received.\n\nDeep reasoning: User feels anxious after I had my first real drink back in October with some of and needs clarification.\n\nAnswer: It makes sense to feel anxious after I had my first real drink back in October with some of. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Back in October of last year I had my first drink.\nChunk 2: At that time I had never drank or tried any drugs or anything, so I was very nervous about trying anything mind altering like that.\nChunk 3: I had my first real drink back in October with some of my friends and I was really nervous about it.\nChunk 4: Why were you nervous about it?\nChunk 5: Usually drinking means to loosen up and have fun.\nChunk 6: It does, but I had never tried anything like drugs or alcohol before so I didn't know what to expect.", "input_token_count": 104, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user expresses anxious about trying anything mind altering like that; the user needs reassurance. Next, the user expresses anxious about I had my first real drink back in October with some of. Next, the user expresses anxious; the user needs clarification. Next, the user signals support or acknowledgment. Finally, the user signals support or acknowledgment.", "trace": "C1 need=validation. C2 emotion=anxious; cause=trying anything mind altering like that; need=reassurance. C3 emotion=anxious; cause=I had my first real drink back in October with some of. C4 emotion=anxious; need=clarification. C5 support_signal=received. C6 support_signal=received.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Back in October of last year I had my first drink.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "At that time I had never drank or tried any drugs or anything, so I was very nervous about trying anything mind altering like that.", "streaming_reasoning": "As more information arrives, the user expresses anxious about trying anything mind altering like that; the user needs reassurance..", "trace": "emotion=anxious; cause=trying anything mind altering like that; need=reassurance."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I had my first real drink back in October with some of my friends and I was really nervous about it.", "streaming_reasoning": "As more information arrives, the user expresses anxious about I had my first real drink back in October with some of..", "trace": "emotion=anxious; cause=I had my first real drink back in October with some of."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Why were you nervous about it?", "streaming_reasoning": "As more information arrives, the user expresses anxious; the user needs clarification..", "trace": "emotion=anxious; need=clarification."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Usually drinking means to loosen up and have fun.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It does, but I had never tried anything like drugs or alcohol before so I didn't know what to expect.", "streaming_reasoning": "Finally, the user signals support or acknowledgment.", "trace": "support_signal=received."}]}, "output": {"deep_reasoning": "User feels anxious after I had my first real drink back in October with some of and needs clarification.", "answer": "It makes sense to feel anxious after I had my first real drink back in October with some of. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002954", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place in the centre of town serving indian food.\nChunk 2: I would like an expensive restaurant.\nChunk 3: the curry garden sounds good.\nChunk 4: Can you please provide me with the address and postcode Thank you.\nChunk 5: Yeah, I would like to know about an attraction called saint barnabas press gallery.\nChunk 6: Thanks so much - that's all I need today.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=indian. C2 price+=expensive. C3 acceptance=selected_option. C4 goal=request_info; requested_info+=address, postcode. C5 domain=attraction; destination+=know about an attraction called saint bar. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, attraction; goal=search, request_info; area=centre; food=indian; price=expensive; destination=know about an attraction called saint bar; requested_info=address, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a place in the centre of town serving indian food.\nChunk 2: I would like an expensive restaurant.\nChunk 3: the curry garden sounds good.\nChunk 4: Can you please provide me with the address and postcode Thank you.\nChunk 5: Yeah, I would like to know about an attraction called saint barnabas press gallery.\nChunk 6: Thanks so much - that's all I need today."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=centre; cuisine+=indian. C2 price+=expensive. C3 acceptance=selected_option. C4 goal=request_info; requested_info+=address, postcode. C5 domain=attraction; destination+=know about an attraction called saint bar. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, attraction; goal=search, request_info; area=centre; food=indian; price=expensive; destination=know about an attraction called saint bar; requested_info=address, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a place in the centre of town serving indian food.\nChunk 2: I would like an expensive restaurant.\nChunk 3: the curry garden sounds good.\nChunk 4: Can you please provide me with the address and postcode Thank you.\nChunk 5: Yeah, I would like to know about an attraction called saint barnabas press gallery.\nChunk 6: Thanks so much - that's all I need today.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: indian. Next, price: expensive. Next, acceptance: selected_option. Next, the goal is request info; requested information: address. Finally, the topic is attraction; destination: know about an attraction called saint bar.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is request info. area: centre; cuisine: indian.; price: expensive.; acceptance: selected_option.; requested information: address; destination: know about an attraction called saint bar..", "trace": "C1 domain=restaurant; goal=search; area+=centre; cuisine+=indian. C2 price+=expensive. C3 acceptance=selected_option. C4 goal=request_info; requested_info+=address, postcode. C5 domain=attraction; destination+=know about an attraction called saint bar. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a place in the centre of town serving indian food.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: centre; cuisine: indian..", "trace": "domain=restaurant; goal=search; area+=centre; cuisine+=indian."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I would like an expensive restaurant.", "streaming_reasoning": "As more information arrives, price: expensive..", "trace": "price+=expensive."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "the curry garden sounds good.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you please provide me with the address and postcode Thank you.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yeah, I would like to know about an attraction called saint barnabas press gallery.", "streaming_reasoning": "As more information arrives, the topic is attraction; destination: know about an attraction called saint bar..", "trace": "domain=attraction; destination+=know about an attraction called saint bar."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks so much - that's all I need today.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is indian; price is expensive; destination is know about an attraction called saint bar; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction; goal=search, request_info; area=centre; food=indian; price=expensive; destination=know about an attraction called saint bar; requested_info=address, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002955", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need a hotel.\nChunk 2: Yes in the Centre please and 4 star.\nChunk 3: Can I book University Arms for 5 nights starting Sunday for 3 people?\nChunk 4: Yes.\nChunk 5: I also need a taxi leaving Whale of Time at 17:45.\nChunk 6: I need to go to the University Arms.\nChunk 7: That's all I need at this time, thanks for your help!", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=centre; stars+=4 stars; acceptance=selected_option. C3 goal=request_info; time+=5, 3; day+=sunday; party_size+=3 people; stay_length+=5 nights. C4 goal=confirm_booking. C5 domain=taxi; time+=17:45. C6 [SKIP: repeated_information]. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel, taxi; goal=search, booking, request_info; area=centre; party_size=3 people; stay_length=5 nights; stars=4 stars; when=sunday, 5, 3, 17:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also need a hotel.\nChunk 2: Yes in the Centre please and 4 star.\nChunk 3: Can I book University Arms for 5 nights starting Sunday for 3 people?\nChunk 4: Yes.\nChunk 5: I also need a taxi leaving Whale of Time at 17:45.\nChunk 6: I need to go to the University Arms.\nChunk 7: That's all I need at this time, thanks for your help!"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=centre; stars+=4 stars; acceptance=selected_option. C3 goal=request_info; time+=5, 3; day+=sunday; party_size+=3 people; stay_length+=5 nights. C4 goal=confirm_booking. C5 domain=taxi; time+=17:45. C6 [SKIP: repeated_information]. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel, taxi; goal=search, booking, request_info; area=centre; party_size=3 people; stay_length=5 nights; stars=4 stars; when=sunday, 5, 3, 17:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also need a hotel.\nChunk 2: Yes in the Centre please and 4 star.\nChunk 3: Can I book University Arms for 5 nights starting Sunday for 3 people?\nChunk 4: Yes.\nChunk 5: I also need a taxi leaving Whale of Time at 17:45.\nChunk 6: I need to go to the University Arms.\nChunk 7: That's all I need at this time, thanks for your help!", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel. Next, area: centre; star rating: 4 stars; acceptance: selected_option. Next, the goal is request info; time: 5; day: sunday; party size: 3 people; stay length: 5 nights. Next, the goal is confirm booking. Finally, the topic is taxi; time: 17:45.  Some chunks were skipped because they contained closing_only or repeated_information. In summary, The overall topic is taxi. the goal is confirm booking.. hotel type: hotel.; area: centre; star rating: 4 stars; acceptance: selected_option.; time: 5, 17:45.; day: sunday; party size: 3 people; stay length: 5 nights..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 area+=centre; stars+=4 stars; acceptance=selected_option. C3 goal=request_info; time+=5, 3; day+=sunday; party_size+=3 people; stay_length+=5 nights. C4 goal=confirm_booking. C5 domain=taxi; time+=17:45. C6 [SKIP: repeated_information]. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also need a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes in the Centre please and 4 star.", "streaming_reasoning": "As more information arrives, area: centre; star rating: 4 stars; acceptance: selected_option..", "trace": "area+=centre; stars+=4 stars; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can I book University Arms for 5 nights starting Sunday for 3 people?", "streaming_reasoning": "As more information arrives, the goal is request info; time: 5; day: sunday; party size: 3 people; stay length: 5 nights..", "trace": "goal=request_info; time+=5, 3; day+=sunday; party_size+=3 people; stay_length+=5 nights."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also need a taxi leaving Whale of Time at 17:45.", "streaming_reasoning": "As more information arrives, the topic is taxi; time: 17:45..", "trace": "domain=taxi; time+=17:45."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need to go to the University Arms.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That's all I need at this time, thanks for your help!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; party size is 3 people; stay length is 5 nights; star rating is 4 stars; timing is sunday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel, taxi; goal=search, booking, request_info; area=centre; party_size=3 people; stay_length=5 nights; stars=4 stars; when=sunday, 5, 3, 17:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001975", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My son had been working so hard practicing for his big track meet.\nChunk 2: He was so nervous.He did great and got first place.\nChunk 3: My son just had a track meet that he has been working so hard practicing for.\nChunk 4: He was so nervous.\nChunk 5: oh, tell him not to feel nervous.\nChunk 6: He worked very hard indeed.\nChunk 7: He did so well!\nChunk 8: He got first place!", "streaming_reasoning": "C1 need=validation. C2 emotion=anxious; need=reassurance. C3 support_signal=received. C4 [SKIP: repeated_information]. C5 emotion=anxious. C6 support_signal=received. C7 [SKIP: repeated_information]. C8 [SKIP: repeated_information].", "deep_reasoning": "User feels anxious after the situation and needs reassurance.", "answer": "It makes sense to feel anxious after what happened. Slow down, check what is actually known, and take one small step before deciding what comes next.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: My son had been working so hard practicing for his big track meet.\nChunk 2: He was so nervous.He did great and got first place.\nChunk 3: My son just had a track meet that he has been working so hard practicing for.\nChunk 4: He was so nervous.\nChunk 5: oh, tell him not to feel nervous.\nChunk 6: He worked very hard indeed.\nChunk 7: He did so well!\nChunk 8: He got first place!"}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 emotion=anxious; need=reassurance. C3 support_signal=received. C4 [SKIP: repeated_information]. C5 emotion=anxious. C6 support_signal=received. C7 [SKIP: repeated_information]. C8 [SKIP: repeated_information].\n\nDeep reasoning: User feels anxious after the situation and needs reassurance.\n\nAnswer: It makes sense to feel anxious after what happened. Slow down, check what is actually known, and take one small step before deciding what comes next."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: My son had been working so hard practicing for his big track meet.\nChunk 2: He was so nervous.He did great and got first place.\nChunk 3: My son just had a track meet that he has been working so hard practicing for.\nChunk 4: He was so nervous.\nChunk 5: oh, tell him not to feel nervous.\nChunk 6: He worked very hard indeed.\nChunk 7: He did so well!\nChunk 8: He got first place!", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user expresses anxious; the user needs reassurance. Next, the user signals support or acknowledgment. Next, the user expresses anxious. Finally, the user signals support or acknowledgment.  Some chunks were skipped because they contained repeated_information.", "trace": "C1 need=validation. C2 emotion=anxious; need=reassurance. C3 support_signal=received. C4 [SKIP: repeated_information]. C5 emotion=anxious. C6 support_signal=received. C7 [SKIP: repeated_information]. C8 [SKIP: repeated_information].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "My son had been working so hard practicing for his big track meet.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "He was so nervous.He did great and got first place.", "streaming_reasoning": "As more information arrives, the user expresses anxious; the user needs reassurance..", "trace": "emotion=anxious; need=reassurance."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "My son just had a track meet that he has been working so hard practicing for.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "He was so nervous.", "streaming_reasoning": "The content at C4 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "oh, tell him not to feel nervous.", "streaming_reasoning": "As more information arrives, the user expresses anxious..", "trace": "emotion=anxious."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "He worked very hard indeed.", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "He did so well!", "streaming_reasoning": "The content at C7 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "He got first place!", "streaming_reasoning": "The content at C8 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}]}, "output": {"deep_reasoning": "User feels anxious after the situation and needs reassurance.", "answer": "It makes sense to feel anxious after what happened. Slow down, check what is actually known, and take one small step before deciding what comes next."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002956", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please connect me to a hospital with an emergency department.\nChunk 2: Thanks, what is the postcode?\nChunk 3: That is all we needed Thank you.", "streaming_reasoning": "C1 domain=hospital; destination+=a hospital with an emergency department. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=request_info; destination=a hospital with an emergency department; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Please connect me to a hospital with an emergency department.\nChunk 2: Thanks, what is the postcode?\nChunk 3: That is all we needed Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; destination+=a hospital with an emergency department. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=request_info; destination=a hospital with an emergency department; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please connect me to a hospital with an emergency department.\nChunk 2: Thanks, what is the postcode?\nChunk 3: That is all we needed Thank you.", "input_token_count": 28, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; destination: a hospital with an emergency department. Finally, the goal is request info; requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital. the goal is request info. destination: a hospital with an emergency department.; requested information: postcode..", "trace": "C1 domain=hospital; destination+=a hospital with an emergency department. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Please connect me to a hospital with an emergency department.", "streaming_reasoning": "Initially, the topic is hospital; destination: a hospital with an emergency department..", "trace": "domain=hospital; destination+=a hospital with an emergency department."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks, what is the postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That is all we needed Thank you.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of request info. Key information: destination is a hospital with an emergency department; requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=request_info; destination=a hospital with an emergency department; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002957", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to think on it if possible But perhaps.\nChunk 2: Could you also help me find a chinese diner located in the centre?\nChunk 3: It needs to be cheap also.\nChunk 4: What is the postcode of the restaurant?\nChunk 5: I don't need a reservation, I just need the postcode.\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 6:15.\nChunk 8: And what type of car will be picking me up No, thank you.\nChunk 9: You have been very helpful!", "streaming_reasoning": "C1 destination+=think on it if possible but perhaps. C2 goal=search; area+=centre; cuisine+=chinese. C3 price+=cheap; destination+=be cheap also. C4 domain=restaurant; goal=request_info; requested_info+=postcode. C5 goal=booking. C6 [SKIP: repeated_information]. C7 time+=6:15. C8 goal=modify_constraint. C9 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=search, request_info, booking; area=centre; food=chinese; price=cheap; destination=think on it if possible but perhaps, be cheap also; requested_info=postcode; when=6:15.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I would like to think on it if possible But perhaps.\nChunk 2: Could you also help me find a chinese diner located in the centre?\nChunk 3: It needs to be cheap also.\nChunk 4: What is the postcode of the restaurant?\nChunk 5: I don't need a reservation, I just need the postcode.\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 6:15.\nChunk 8: And what type of car will be picking me up No, thank you.\nChunk 9: You have been very helpful!"}, {"role": "assistant", "content": "Streaming reasoning: C1 destination+=think on it if possible but perhaps. C2 goal=search; area+=centre; cuisine+=chinese. C3 price+=cheap; destination+=be cheap also. C4 domain=restaurant; goal=request_info; requested_info+=postcode. C5 goal=booking. C6 [SKIP: repeated_information]. C7 time+=6:15. C8 goal=modify_constraint. C9 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info, booking; area=centre; food=chinese; price=cheap; destination=think on it if possible but perhaps, be cheap also; requested_info=postcode; when=6:15.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I would like to think on it if possible But perhaps.\nChunk 2: Could you also help me find a chinese diner located in the centre?\nChunk 3: It needs to be cheap also.\nChunk 4: What is the postcode of the restaurant?\nChunk 5: I don't need a reservation, I just need the postcode.\nChunk 6: I want to find a restaurant.\nChunk 7: The time is 6:15.\nChunk 8: And what type of car will be picking me up No, thank you.\nChunk 9: You have been very helpful!", "input_token_count": 94, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, destination: think on it if possible but perhaps. Next, the goal is search; area: centre; cuisine: chinese. Next, price: cheap; destination: be cheap also. Next, the topic is restaurant; the goal is request info; requested information: postcode. Next, the goal is booking. Next, time: 6:15. Next, the goal is modify constraint. Finally, intent: context_update.  Some chunks were skipped because they contained repeated_information. In summary, The overall topic is restaurant. the goal is modify constraint.. destination: think on it if possible but perhaps., be cheap also.; area: centre; cuisine: chinese.; price: cheap; requested information: postcode.; time: 6:15.; intent: context_update..", "trace": "C1 destination+=think on it if possible but perhaps. C2 goal=search; area+=centre; cuisine+=chinese. C3 price+=cheap; destination+=be cheap also. C4 domain=restaurant; goal=request_info; requested_info+=postcode. C5 goal=booking. C6 [SKIP: repeated_information]. C7 time+=6:15. C8 goal=modify_constraint. C9 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I would like to think on it if possible But perhaps.", "streaming_reasoning": "Initially, destination: think on it if possible but perhaps..", "trace": "destination+=think on it if possible but perhaps."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Could you also help me find a chinese diner located in the centre?", "streaming_reasoning": "As more information arrives, the goal is search; area: centre; cuisine: chinese..", "trace": "goal=search; area+=centre; cuisine+=chinese."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It needs to be cheap also.", "streaming_reasoning": "As more information arrives, price: cheap; destination: be cheap also..", "trace": "price+=cheap; destination+=be cheap also."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is the postcode of the restaurant?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is request info; requested information: postcode..", "trace": "domain=restaurant; goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I don't need a reservation, I just need the postcode.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "The content at C6 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 6:15.", "streaming_reasoning": "As more information arrives, time: 6:15..", "trace": "time+=6:15."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "And what type of car will be picking me up No, thank you.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "You have been very helpful!", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is chinese; price is cheap; destination is think on it if possible but perhaps; requested information is postcode; timing is 6:15.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info, booking; area=centre; food=chinese; price=cheap; destination=think on it if possible but perhaps, be cheap also; requested_info=postcode; when=6:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002958", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I got into a fender-bender with my rental car, and now I need help resolving the dispute with the owner of the other car.\nChunk 2: Can I get the full mailing address for that location?\nChunk 3: Thank you for your help.\nChunk 4: That is all I need right now.", "streaming_reasoning": "C1 goal=search. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].", "deep_reasoning": "Need goal=search, request_info; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I got into a fender-bender with my rental car, and now I need help resolving the dispute with the owner of the other car.\nChunk 2: Can I get the full mailing address for that location?\nChunk 3: Thank you for your help.\nChunk 4: That is all I need right now."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].\n\nDeep reasoning: Need goal=search, request_info; requested_info=address; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I got into a fender-bender with my rental car, and now I need help resolving the dispute with the owner of the other car.\nChunk 2: Can I get the full mailing address for that location?\nChunk 3: Thank you for your help.\nChunk 4: That is all I need right now.", "input_token_count": 54, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Finally, the goal is request info; requested information: address.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, the goal is request info. requested information: address..", "trace": "C1 goal=search. C2 goal=request_info; requested_info+=address. C3 [SKIP: thanks_only]. C4 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I got into a fender-bender with my rental car, and now I need help resolving the dispute with the owner of the other car.", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I get the full mailing address for that location?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: address..", "trace": "goal=request_info; requested_info+=address."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you for your help.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "That is all I need right now.", "streaming_reasoning": "The content at C4 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "Need goal=search, request_info; requested_info=address; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002959", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: One person, and I'd like to arrive on Tuesday.\nChunk 2: After that I'm also going to need the reference number.\nChunk 3: OK, now can you tell me about some of the attractions in the center of town?\nChunk 4: Can you please provide me with the address, telephone number and the cost of admission.\nChunk 5: I want to find a hotel.\nChunk 6: The time is 15:45.\nChunk 7: Please make a booking.\nChunk 8: No, that is all Thanks so much.\nChunk 9: Bye.", "streaming_reasoning": "C1 day+=tuesday; destination+=arrive on tuesday. C2 goal=request_info; destination+=need the reference number; requested_info+=reference_number. C3 area+=centre. C4 requested_info+=address, phone, entrance_fee, price. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 time+=15:45. C7 goal=booking. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info, booking; area=centre; destination=arrive on tuesday, need the reference number, find a hotel; requested_info=reference_number, address, phone, entrance_fee, price; when=tuesday, 15:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: One person, and I'd like to arrive on Tuesday.\nChunk 2: After that I'm also going to need the reference number.\nChunk 3: OK, now can you tell me about some of the attractions in the center of town?\nChunk 4: Can you please provide me with the address, telephone number and the cost of admission.\nChunk 5: I want to find a hotel.\nChunk 6: The time is 15:45.\nChunk 7: Please make a booking.\nChunk 8: No, that is all Thanks so much.\nChunk 9: Bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 day+=tuesday; destination+=arrive on tuesday. C2 goal=request_info; destination+=need the reference number; requested_info+=reference_number. C3 area+=centre. C4 requested_info+=address, phone, entrance_fee, price. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 time+=15:45. C7 goal=booking. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info, booking; area=centre; destination=arrive on tuesday, need the reference number, find a hotel; requested_info=reference_number, address, phone, entrance_fee, price; when=tuesday, 15:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: One person, and I'd like to arrive on Tuesday.\nChunk 2: After that I'm also going to need the reference number.\nChunk 3: OK, now can you tell me about some of the attractions in the center of town?\nChunk 4: Can you please provide me with the address, telephone number and the cost of admission.\nChunk 5: I want to find a hotel.\nChunk 6: The time is 15:45.\nChunk 7: Please make a booking.\nChunk 8: No, that is all Thanks so much.\nChunk 9: Bye.", "input_token_count": 91, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, day: tuesday; destination: arrive on tuesday. Next, the goal is request info; destination: need the reference number; requested information: reference_number. Next, area: centre. Next, requested information: address. Next, the topic is hotel; hotel type: hotel; destination: find a hotel. Next, time: 15:45. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking.. day: tuesday; destination: arrive on tuesday., need the reference number, find a hotel.; requested information: reference_number., address; area: centre.; hotel type: hotel; time: 15:45..", "trace": "C1 day+=tuesday; destination+=arrive on tuesday. C2 goal=request_info; destination+=need the reference number; requested_info+=reference_number. C3 area+=centre. C4 requested_info+=address, phone, entrance_fee, price. C5 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C6 time+=15:45. C7 goal=booking. C8 [SKIP: closing_only]. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "One person, and I'd like to arrive on Tuesday.", "streaming_reasoning": "Initially, day: tuesday; destination: arrive on tuesday..", "trace": "day+=tuesday; destination+=arrive on tuesday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "After that I'm also going to need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; destination: need the reference number; requested information: reference_number..", "trace": "goal=request_info; destination+=need the reference number; requested_info+=reference_number."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "OK, now can you tell me about some of the attractions in the center of town?", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you please provide me with the address, telephone number and the cost of admission.", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, phone, entrance_fee, price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "The time is 15:45.", "streaming_reasoning": "As more information arrives, time: 15:45..", "trace": "time+=15:45."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, that is all Thanks so much.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Bye.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; destination is arrive on tuesday; requested information is reference_number; timing is tuesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info, booking; area=centre; destination=arrive on tuesday, need the reference number, find a hotel; requested_info=reference_number, address, phone, entrance_fee, price; when=tuesday, 15:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002960", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a place to stay with free wifi.\nChunk 2: Location doesn't really matter as long as there's free parking available.\nChunk 3: Between $100-$300 per night.\nChunk 4: What is their postcode?", "streaming_reasoning": "C1 domain=hotel; goal=search; amenities+=wifi; destination+=stay with free wifi. C2 amenities+=parking, free parking. C3 intent=context_update. C4 goal=request_info; requested_info+=postcode.", "deep_reasoning": "Need domain=hotel; goal=search, request_info; amenities=wifi, parking, free parking; destination=stay with free wifi; requested_info=postcode.", "answer": "I can help with that and include the postcode once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I need a place to stay with free wifi.\nChunk 2: Location doesn't really matter as long as there's free parking available.\nChunk 3: Between $100-$300 per night.\nChunk 4: What is their postcode?"}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; amenities+=wifi; destination+=stay with free wifi. C2 amenities+=parking, free parking. C3 intent=context_update. C4 goal=request_info; requested_info+=postcode.\n\nDeep reasoning: Need domain=hotel; goal=search, request_info; amenities=wifi, parking, free parking; destination=stay with free wifi; requested_info=postcode.\n\nAnswer: I can help with that and include the postcode once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I need a place to stay with free wifi.\nChunk 2: Location doesn't really matter as long as there's free parking available.\nChunk 3: Between $100-$300 per night.\nChunk 4: What is their postcode?", "input_token_count": 37, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; amenities: wifi; destination: stay with free wifi. Next, amenities: parking. Next, intent: context_update. Finally, the goal is request info; requested information: postcode. In summary, The overall topic is hotel. the goal is request info. amenities: wifi, parking; destination: stay with free wifi.; intent: context_update.; requested information: postcode..", "trace": "C1 domain=hotel; goal=search; amenities+=wifi; destination+=stay with free wifi. C2 amenities+=parking, free parking. C3 intent=context_update. C4 goal=request_info; requested_info+=postcode.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I need a place to stay with free wifi.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; amenities: wifi; destination: stay with free wifi..", "trace": "domain=hotel; goal=search; amenities+=wifi; destination+=stay with free wifi."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Location doesn't really matter as long as there's free parking available.", "streaming_reasoning": "As more information arrives, amenities: parking.", "trace": "amenities+=parking, free parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Between $100-$300 per night.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "What is their postcode?", "streaming_reasoning": "Finally, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: amenities is wifi; destination is stay with free wifi; requested information is postcode.. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the postcode once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info; amenities=wifi, parking, free parking; destination=stay with free wifi; requested_info=postcode."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003677", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks for inviting me.\nChunk 2: Here is the gift for you Happy birthday, Francis!\nChunk 3: Many more happy and healthy years for you!\nChunk 4: Thank you, shall I open it now Yes, please do.\nChunk 5: Wow, a remote car model and my favorite brand.\nChunk 6: I really like it.\nChunk 7: That is so nice of you.\nChunk 8: Yeah, I was really struggling whether I should give you this nice little car.\nChunk 9: It was the last one they had and I really like it so much myself.", "streaming_reasoning": "C1 [SKIP: thanks_only]. C2 casual_comment=here, gift. C3 casual_comment=many, happy. C4 [SKIP: thanks_only]. C5 preference=true. C6 preference=true. C7 casual_comment=nice. C8 casual_comment=struggling, whether. C9 preference=true.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Thanks for inviting me.\nChunk 2: Here is the gift for you Happy birthday, Francis!\nChunk 3: Many more happy and healthy years for you!\nChunk 4: Thank you, shall I open it now Yes, please do.\nChunk 5: Wow, a remote car model and my favorite brand.\nChunk 6: I really like it.\nChunk 7: That is so nice of you.\nChunk 8: Yeah, I was really struggling whether I should give you this nice little car.\nChunk 9: It was the last one they had and I really like it so much myself."}, {"role": "assistant", "content": "Streaming reasoning: C1 [SKIP: thanks_only]. C2 casual_comment=here, gift. C3 casual_comment=many, happy. C4 [SKIP: thanks_only]. C5 preference=true. C6 preference=true. C7 casual_comment=nice. C8 casual_comment=struggling, whether. C9 preference=true.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Thanks for inviting me.\nChunk 2: Here is the gift for you Happy birthday, Francis!\nChunk 3: Many more happy and healthy years for you!\nChunk 4: Thank you, shall I open it now Yes, please do.\nChunk 5: Wow, a remote car model and my favorite brand.\nChunk 6: I really like it.\nChunk 7: That is so nice of you.\nChunk 8: Yeah, I was really struggling whether I should give you this nice little car.\nChunk 9: It was the last one they had and I really like it so much myself.", "input_token_count": 97, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on here. Next, the user comments on many. Next, preference: true. Next, preference: true. Next, the user comments on nice. Next, the user comments on struggling. Finally, preference: true.  Some chunks were skipped because they contained thanks_only. In summary, preference: true..", "trace": "C1 [SKIP: thanks_only]. C2 casual_comment=here, gift. C3 casual_comment=many, happy. C4 [SKIP: thanks_only]. C5 preference=true. C6 preference=true. C7 casual_comment=nice. C8 casual_comment=struggling, whether. C9 preference=true.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Thanks for inviting me.", "streaming_reasoning": "The content at C1 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Here is the gift for you Happy birthday, Francis!", "streaming_reasoning": "As more information arrives, the user comments on here.", "trace": "casual_comment=here, gift."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Many more happy and healthy years for you!", "streaming_reasoning": "As more information arrives, the user comments on many.", "trace": "casual_comment=many, happy."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you, shall I open it now Yes, please do.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Wow, a remote car model and my favorite brand.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I really like it.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "That is so nice of you.", "streaming_reasoning": "As more information arrives, the user comments on nice..", "trace": "casual_comment=nice."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Yeah, I was really struggling whether I should give you this nice little car.", "streaming_reasoning": "As more information arrives, the user comments on struggling.", "trace": "casual_comment=struggling, whether."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "It was the last one they had and I really like it so much myself.", "streaming_reasoning": "Finally, preference: true..", "trace": "preference=true."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002961", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Im looking for a restaurant in the north part of town in the cheap price range.\nChunk 2: Does it serve bistro food?\nChunk 3: I would settle for British.\nChunk 4: I'd prefer moderately priced, actually, and location doesn't matter.\nChunk 5: What is the phone number?\nChunk 6: No, thank you, that is all I need Goodbye Goodbye.", "streaming_reasoning": "C1 domain=restaurant; goal=search; area+=north; price+=cheap. C2 goal=request_info. C3 cuisine+=british. C4 price+=moderate. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=search, request_info; area=north; food=british; price=cheap, moderate; requested_info=phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Im looking for a restaurant in the north part of town in the cheap price range.\nChunk 2: Does it serve bistro food?\nChunk 3: I would settle for British.\nChunk 4: I'd prefer moderately priced, actually, and location doesn't matter.\nChunk 5: What is the phone number?\nChunk 6: No, thank you, that is all I need Goodbye Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; area+=north; price+=cheap. C2 goal=request_info. C3 cuisine+=british. C4 price+=moderate. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=search, request_info; area=north; food=british; price=cheap, moderate; requested_info=phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Im looking for a restaurant in the north part of town in the cheap price range.\nChunk 2: Does it serve bistro food?\nChunk 3: I would settle for British.\nChunk 4: I'd prefer moderately priced, actually, and location doesn't matter.\nChunk 5: What is the phone number?\nChunk 6: No, thank you, that is all I need Goodbye Goodbye.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: north; price: cheap. Next, the goal is request info. Next, cuisine: british. Next, price: moderate. Finally, the goal is request info; requested information: phone.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is request info. area: north; price: cheap., moderate.; cuisine: british.; requested information: phone..", "trace": "C1 domain=restaurant; goal=search; area+=north; price+=cheap. C2 goal=request_info. C3 cuisine+=british. C4 price+=moderate. C5 goal=request_info; requested_info+=phone. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Im looking for a restaurant in the north part of town in the cheap price range.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; area: north; price: cheap..", "trace": "domain=restaurant; goal=search; area+=north; price+=cheap."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Does it serve bistro food?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I would settle for British.", "streaming_reasoning": "As more information arrives, cuisine: british..", "trace": "cuisine+=british."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'd prefer moderately priced, actually, and location doesn't matter.", "streaming_reasoning": "As more information arrives, price: moderate..", "trace": "price+=moderate."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "What is the phone number?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No, thank you, that is all I need Goodbye Goodbye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is north; cuisine is british; price is cheap; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=search, request_info; area=north; food=british; price=cheap, moderate; requested_info=phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002964", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I am looking for information on a train.\nChunk 2: I'm headed to Cambridge from the Stansted Airport.\nChunk 3: Can you find information for Thursday please?\nChunk 4: I need to arrive in Cambridge by 14:45 so I will need to leave in time to get there by then.\nChunk 5: That won't work, I need to arrive in Cambridge by 14:45 (2:45pm).", "streaming_reasoning": "C1 domain=train; goal=search. C2 intent=context_update. C3 day+=thursday. C4 goal=request_info; time+=14:45; destination+=arrive in cambridge by 14:45 so i will ne. C5 time+=2:45pm; destination+=arrive in cambridge by 14:45 (2:45pm).", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=arrive in cambridge by 14:45 so i will ne, arrive in cambridge by 14:45 (2:45pm); when=thursday, 14:45, 2:45pm.", "answer": "What departure should I use for the search?", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hello, I am looking for information on a train.\nChunk 2: I'm headed to Cambridge from the Stansted Airport.\nChunk 3: Can you find information for Thursday please?\nChunk 4: I need to arrive in Cambridge by 14:45 so I will need to leave in time to get there by then.\nChunk 5: That won't work, I need to arrive in Cambridge by 14:45 (2:45pm)."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 intent=context_update. C3 day+=thursday. C4 goal=request_info; time+=14:45; destination+=arrive in cambridge by 14:45 so i will ne. C5 time+=2:45pm; destination+=arrive in cambridge by 14:45 (2:45pm).\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=arrive in cambridge by 14:45 so i will ne, arrive in cambridge by 14:45 (2:45pm); when=thursday, 14:45, 2:45pm.\n\nAnswer: What departure should I use for the search?"}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hello, I am looking for information on a train.\nChunk 2: I'm headed to Cambridge from the Stansted Airport.\nChunk 3: Can you find information for Thursday please?\nChunk 4: I need to arrive in Cambridge by 14:45 so I will need to leave in time to get there by then.\nChunk 5: That won't work, I need to arrive in Cambridge by 14:45 (2:45pm).", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, intent: context_update. Next, day: thursday. Next, the goal is request info; time: 14:45; destination: arrive in cambridge by 14:45 so i will ne. Finally, time: 2:45pm; destination: arrive in cambridge by 14:45 (2:45pm). In summary, The overall topic is train. the goal is request info. intent: context_update.; day: thursday.; time: 14:45, 2:45pm; destination: arrive in cambridge by 14:45 so i will ne., arrive in cambridge by 14:45 (2:45pm)..", "trace": "C1 domain=train; goal=search. C2 intent=context_update. C3 day+=thursday. C4 goal=request_info; time+=14:45; destination+=arrive in cambridge by 14:45 so i will ne. C5 time+=2:45pm; destination+=arrive in cambridge by 14:45 (2:45pm).", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hello, I am looking for information on a train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'm headed to Cambridge from the Stansted Airport.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you find information for Thursday please?", "streaming_reasoning": "As more information arrives, day: thursday..", "trace": "day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to arrive in Cambridge by 14:45 so I will need to leave in time to get there by then.", "streaming_reasoning": "As more information arrives, the goal is request info; time: 14:45; destination: arrive in cambridge by 14:45 so i will ne..", "trace": "goal=request_info; time+=14:45; destination+=arrive in cambridge by 14:45 so i will ne."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "That won't work, I need to arrive in Cambridge by 14:45 (2:45pm).", "streaming_reasoning": "Finally, time: 2:45pm; destination: arrive in cambridge by 14:45 (2:45pm)..", "trace": "time+=2:45pm; destination+=arrive in cambridge by 14:45 (2:45pm)."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is arrive in cambridge by 14:45 so i will ne; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "What departure should I use for the search?", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=arrive in cambridge by 14:45 so i will ne, arrive in cambridge by 14:45 (2:45pm); when=thursday, 14:45, 2:45pm."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002965", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train that departs from Cambridge on Thursday.\nChunk 2: No, I actually need to leave after 12:00.\nChunk 3: I need to go to ely after 12:00.\nChunk 4: Yes, that would be great.\nChunk 5: Can you book tickets for 7 people please.\nChunk 6: And I'll need a reference number for it.\nChunk 7: No thank you That is all.", "streaming_reasoning": "C1 domain=train; goal=search; day+=thursday. C2 time+=12:00; destination+=leave after 12:00. C3 destination+=go to ely after 12:00. C4 acceptance=selected_option. C5 goal=booking; party_size+=7 people. C6 goal=request_info; requested_info+=reference_number. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, booking, request_info; party_size=7 people; destination=leave after 12:00, go to ely after 12:00; requested_info=reference_number; when=thursday, 12:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am looking for a train that departs from Cambridge on Thursday.\nChunk 2: No, I actually need to leave after 12:00.\nChunk 3: I need to go to ely after 12:00.\nChunk 4: Yes, that would be great.\nChunk 5: Can you book tickets for 7 people please.\nChunk 6: And I'll need a reference number for it.\nChunk 7: No thank you That is all."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search; day+=thursday. C2 time+=12:00; destination+=leave after 12:00. C3 destination+=go to ely after 12:00. C4 acceptance=selected_option. C5 goal=booking; party_size+=7 people. C6 goal=request_info; requested_info+=reference_number. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, booking, request_info; party_size=7 people; destination=leave after 12:00, go to ely after 12:00; requested_info=reference_number; when=thursday, 12:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am looking for a train that departs from Cambridge on Thursday.\nChunk 2: No, I actually need to leave after 12:00.\nChunk 3: I need to go to ely after 12:00.\nChunk 4: Yes, that would be great.\nChunk 5: Can you book tickets for 7 people please.\nChunk 6: And I'll need a reference number for it.\nChunk 7: No thank you That is all.", "input_token_count": 71, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search; day: thursday. Next, time: 12:00; destination: leave after 12:00. Next, destination: go to ely after 12:00. Next, acceptance: selected_option. Next, the goal is booking; party size: 7 people. Finally, the goal is request info; requested information: reference_number.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info. day: thursday.; time: 12:00; destination: leave after 12:00., go to ely after 12:00.; acceptance: selected_option.; party size: 7 people.; requested information: reference_number..", "trace": "C1 domain=train; goal=search; day+=thursday. C2 time+=12:00; destination+=leave after 12:00. C3 destination+=go to ely after 12:00. C4 acceptance=selected_option. C5 goal=booking; party_size+=7 people. C6 goal=request_info; requested_info+=reference_number. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am looking for a train that departs from Cambridge on Thursday.", "streaming_reasoning": "Initially, the topic is train; the goal is search; day: thursday..", "trace": "domain=train; goal=search; day+=thursday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, I actually need to leave after 12:00.", "streaming_reasoning": "As more information arrives, time: 12:00; destination: leave after 12:00..", "trace": "time+=12:00; destination+=leave after 12:00."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to go to ely after 12:00.", "streaming_reasoning": "As more information arrives, destination: go to ely after 12:00..", "trace": "destination+=go to ely after 12:00."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes, that would be great.", "streaming_reasoning": "As more information arrives, acceptance: selected_option..", "trace": "acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you book tickets for 7 people please.", "streaming_reasoning": "As more information arrives, the goal is booking; party size: 7 people..", "trace": "goal=booking; party_size+=7 people."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "And I'll need a reference number for it.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No thank you That is all.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: party size is 7 people; destination is leave after 12:00; requested information is reference_number; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, booking, request_info; party_size=7 people; destination=leave after 12:00, go to ely after 12:00; requested_info=reference_number; when=thursday, 12:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000619", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Mirror from Mac to Apple TV.\nChunk 2: Connect the Mac and Apple TV to the same Wi-Fi network.\nChunk 3: Click the Apple menu.\nChunk 4: Select Apple TV from the \"AirPlay Display\" menu.\nChunk 5: Click the back button and select Sound.", "streaming_reasoning": "C1 task=mirror_from_mac_to. C2 step=connect_the_mac_and. C3 step=click_the_apple_menu. C4 step=select_apple_tv_from. C5 step=click_the_back_button.", "deep_reasoning": "Procedure for Mirror from Mac to Apple TV: Connect the Mac and Apple TV to the same Wi-Fi, Click the Apple menu, Select Apple TV from the \"AirPlay Display\" menu, Click the back button and select Sound.", "answer": "For Mirror from Mac to Apple TV, follow the steps in order: Connect the Mac and Apple TV to the same Wi-Fi, Click the Apple menu, Select Apple TV from the \"AirPlay Display\" menu, Click the back button and select Sound.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Mirror from Mac to Apple TV.\nChunk 2: Connect the Mac and Apple TV to the same Wi-Fi network.\nChunk 3: Click the Apple menu.\nChunk 4: Select Apple TV from the \"AirPlay Display\" menu.\nChunk 5: Click the back button and select Sound."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=mirror_from_mac_to. C2 step=connect_the_mac_and. C3 step=click_the_apple_menu. C4 step=select_apple_tv_from. C5 step=click_the_back_button.\n\nDeep reasoning: Procedure for Mirror from Mac to Apple TV: Connect the Mac and Apple TV to the same Wi-Fi, Click the Apple menu, Select Apple TV from the \"AirPlay Display\" menu, Click the back button and select Sound.\n\nAnswer: For Mirror from Mac to Apple TV, follow the steps in order: Connect the Mac and Apple TV to the same Wi-Fi, Click the Apple menu, Select Apple TV from the \"AirPlay Display\" menu, Click the back button and select Sound."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Mirror from Mac to Apple TV.\nChunk 2: Connect the Mac and Apple TV to the same Wi-Fi network.\nChunk 3: Click the Apple menu.\nChunk 4: Select Apple TV from the \"AirPlay Display\" menu.\nChunk 5: Click the back button and select Sound.", "input_token_count": 47, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, task: mirror_from_mac_to. Next, step: connect_the_mac_and. Next, step: click_the_apple_menu. Next, step: select_apple_tv_from. Finally, step: click_the_back_button. In summary, task: mirror_from_mac_to.; step: connect_the_mac_and., click_the_apple_menu., select_apple_tv_from., click_the_back_button..", "trace": "C1 task=mirror_from_mac_to. C2 step=connect_the_mac_and. C3 step=click_the_apple_menu. C4 step=select_apple_tv_from. C5 step=click_the_back_button.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Mirror from Mac to Apple TV.", "streaming_reasoning": "Initially, task: mirror_from_mac_to..", "trace": "task=mirror_from_mac_to."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Connect the Mac and Apple TV to the same Wi-Fi network.", "streaming_reasoning": "As more information arrives, step: connect_the_mac_and..", "trace": "step=connect_the_mac_and."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Click the Apple menu.", "streaming_reasoning": "As more information arrives, step: click_the_apple_menu..", "trace": "step=click_the_apple_menu."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Select Apple TV from the \"AirPlay Display\" menu.", "streaming_reasoning": "As more information arrives, step: select_apple_tv_from..", "trace": "step=select_apple_tv_from."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Click the back button and select Sound.", "streaming_reasoning": "Finally, step: click_the_back_button..", "trace": "step=click_the_back_button."}]}, "output": {"deep_reasoning": "Procedure for Mirror from Mac to Apple TV: Connect the Mac and Apple TV to the same Wi-Fi, Click the Apple menu, Select Apple TV from the \"AirPlay Display\" menu, Click the back button and select Sound.", "answer": "For Mirror from Mac to Apple TV, follow the steps in order: Connect the Mac and Apple TV to the same Wi-Fi, Click the Apple menu, Select Apple TV from the \"AirPlay Display\" menu, Click the back button and select Sound."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003680", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: She'd better not start crying like she usually does.\nChunk 2: I know, but she is going to miss you something awful.\nChunk 3: Have I told you how proud I am of you?\nChunk 4: Dad, now don't you go getting mush on me I mean it.\nChunk 5: You have really shown us that you are prepared to take on the adult world.\nChunk 6: That means a lot to me Dad.\nChunk 7: Thanks.", "streaming_reasoning": "C1 preference=true. C2 casual_comment=she, going. C3 question=true. C4 casual_comment=dad, now. C5 casual_comment=shown, prepared. C6 casual_comment=means, lot. C7 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: She'd better not start crying like she usually does.\nChunk 2: I know, but she is going to miss you something awful.\nChunk 3: Have I told you how proud I am of you?\nChunk 4: Dad, now don't you go getting mush on me I mean it.\nChunk 5: You have really shown us that you are prepared to take on the adult world.\nChunk 6: That means a lot to me Dad.\nChunk 7: Thanks."}, {"role": "assistant", "content": "Streaming reasoning: C1 preference=true. C2 casual_comment=she, going. C3 question=true. C4 casual_comment=dad, now. C5 casual_comment=shown, prepared. C6 casual_comment=means, lot. C7 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: She'd better not start crying like she usually does.\nChunk 2: I know, but she is going to miss you something awful.\nChunk 3: Have I told you how proud I am of you?\nChunk 4: Dad, now don't you go getting mush on me I mean it.\nChunk 5: You have really shown us that you are prepared to take on the adult world.\nChunk 6: That means a lot to me Dad.\nChunk 7: Thanks.", "input_token_count": 79, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, preference: true. Next, the user comments on she. Next, the input provides additional context about question=true. Next, the user comments on dad. Next, the user comments on shown. Finally, the user comments on means.  Some chunks were skipped because they contained thanks_only. In summary, preference: true..", "trace": "C1 preference=true. C2 casual_comment=she, going. C3 question=true. C4 casual_comment=dad, now. C5 casual_comment=shown, prepared. C6 casual_comment=means, lot. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "She'd better not start crying like she usually does.", "streaming_reasoning": "Initially, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I know, but she is going to miss you something awful.", "streaming_reasoning": "As more information arrives, the user comments on she.", "trace": "casual_comment=she, going."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Have I told you how proud I am of you?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Dad, now don't you go getting mush on me I mean it.", "streaming_reasoning": "As more information arrives, the user comments on dad.", "trace": "casual_comment=dad, now."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "You have really shown us that you are prepared to take on the adult world.", "streaming_reasoning": "As more information arrives, the user comments on shown.", "trace": "casual_comment=shown, prepared."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That means a lot to me Dad.", "streaming_reasoning": "As more information arrives, the user comments on means.", "trace": "casual_comment=means, lot."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002966", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: A nightclub sounds like fun Recommend one please Yes, please.\nChunk 2: Can I get the phone number and postcode?\nChunk 3: I also need a cab by the booked time, contact number and car type please.\nChunk 4: The cab has to pick me up from the restaurant to the nightclub.\nChunk 5: Actually, I'm confused I apologize.\nChunk 6: I'll need a taxi that will take me from the nightclub to the restaurant.\nChunk 7: I'd like to arrive by the booked time for the restaurant.\nChunk 8: That will be all for today.\nChunk 9: Thank you so much Goodbye.", "streaming_reasoning": "C1 goal=confirm_booking; acceptance=selected_option. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=taxi; goal=search. C4 domain=restaurant; destination+=the nightclub; departure+=the restaurant. C5 intent=context_update. C6 destination+=the restaurant; departure+=the nightclub. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=taxi, restaurant; goal=recommendation, confirm_booking, request_info, search; destination=the nightclub, the restaurant; departure=the restaurant, the nightclub; requested_info=phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: A nightclub sounds like fun Recommend one please Yes, please.\nChunk 2: Can I get the phone number and postcode?\nChunk 3: I also need a cab by the booked time, contact number and car type please.\nChunk 4: The cab has to pick me up from the restaurant to the nightclub.\nChunk 5: Actually, I'm confused I apologize.\nChunk 6: I'll need a taxi that will take me from the nightclub to the restaurant.\nChunk 7: I'd like to arrive by the booked time for the restaurant.\nChunk 8: That will be all for today.\nChunk 9: Thank you so much Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=confirm_booking; acceptance=selected_option. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=taxi; goal=search. C4 domain=restaurant; destination+=the nightclub; departure+=the restaurant. C5 intent=context_update. C6 destination+=the restaurant; departure+=the nightclub. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=taxi, restaurant; goal=recommendation, confirm_booking, request_info, search; destination=the nightclub, the restaurant; departure=the restaurant, the nightclub; requested_info=phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: A nightclub sounds like fun Recommend one please Yes, please.\nChunk 2: Can I get the phone number and postcode?\nChunk 3: I also need a cab by the booked time, contact number and car type please.\nChunk 4: The cab has to pick me up from the restaurant to the nightclub.\nChunk 5: Actually, I'm confused I apologize.\nChunk 6: I'll need a taxi that will take me from the nightclub to the restaurant.\nChunk 7: I'd like to arrive by the booked time for the restaurant.\nChunk 8: That will be all for today.\nChunk 9: Thank you so much Goodbye.", "input_token_count": 105, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the goal is confirm booking; acceptance: selected_option. Next, the goal is request info; requested information: phone. Next, the topic is taxi; the goal is search. Next, the topic is restaurant; destination: the nightclub; departure point: the restaurant. Next, intent: context_update. Next, destination: the restaurant; departure point: the nightclub. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is restaurant. the goal is search.. acceptance: selected_option.; requested information: phone; destination: the nightclub, the restaurant; departure point: the restaurant., the nightclub.; intent: context_update..", "trace": "C1 goal=confirm_booking; acceptance=selected_option. C2 goal=request_info; requested_info+=phone, postcode. C3 domain=taxi; goal=search. C4 domain=restaurant; destination+=the nightclub; departure+=the restaurant. C5 intent=context_update. C6 destination+=the restaurant; departure+=the nightclub. C7 intent=context_update. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "A nightclub sounds like fun Recommend one please Yes, please.", "streaming_reasoning": "Initially, the goal is confirm booking; acceptance: selected_option..", "trace": "goal=confirm_booking; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can I get the phone number and postcode?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone.", "trace": "goal=request_info; requested_info+=phone, postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need a cab by the booked time, contact number and car type please.", "streaming_reasoning": "As more information arrives, the topic is taxi; the goal is search..", "trace": "domain=taxi; goal=search."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The cab has to pick me up from the restaurant to the nightclub.", "streaming_reasoning": "As more information arrives, the topic is restaurant; destination: the nightclub; departure point: the restaurant..", "trace": "domain=restaurant; destination+=the nightclub; departure+=the restaurant."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Actually, I'm confused I apologize.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'll need a taxi that will take me from the nightclub to the restaurant.", "streaming_reasoning": "As more information arrives, destination: the restaurant; departure point: the nightclub..", "trace": "destination+=the restaurant; departure+=the nightclub."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'd like to arrive by the booked time for the restaurant.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "That will be all for today.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thank you so much Goodbye.", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of recommendation. Key information: destination is the nightclub; departure point is the restaurant; requested information is phone. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, restaurant; goal=recommendation, confirm_booking, request_info, search; destination=the nightclub, the restaurant; departure=the restaurant, the nightclub; requested_info=phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002967", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should depart from broxbourne train station.\nChunk 3: I need to leave by 20:15 and am headed to city stop restaurant Thank you.\nChunk 4: I am all set.\nChunk 5: Have a great day.", "streaming_reasoning": "C1 domain=taxi; goal=booking. C2 domain=train; departure+=broxbourne train station. C3 domain=restaurant; time+=20:15; destination+=leave by 20:15 and am headed to city stop. C4 intent=context_update. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=taxi, train, restaurant; goal=search, booking; destination=leave by 20:15 and am headed to city stop; departure=broxbourne train station; when=20:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i want to book a taxi.\nChunk 2: The taxi should depart from broxbourne train station.\nChunk 3: I need to leave by 20:15 and am headed to city stop restaurant Thank you.\nChunk 4: I am all set.\nChunk 5: Have a great day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=taxi; goal=booking. C2 domain=train; departure+=broxbourne train station. C3 domain=restaurant; time+=20:15; destination+=leave by 20:15 and am headed to city stop. C4 intent=context_update. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=taxi, train, restaurant; goal=search, booking; destination=leave by 20:15 and am headed to city stop; departure=broxbourne train station; when=20:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i want to book a taxi.\nChunk 2: The taxi should depart from broxbourne train station.\nChunk 3: I need to leave by 20:15 and am headed to city stop restaurant Thank you.\nChunk 4: I am all set.\nChunk 5: Have a great day.", "input_token_count": 48, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is taxi; the goal is booking. Next, the topic is train; departure point: broxbourne train station. Next, the topic is restaurant; time: 20:15; destination: leave by 20:15 and am headed to city stop. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking.. departure point: broxbourne train station.; time: 20:15; destination: leave by 20:15 and am headed to city stop.; intent: context_update..", "trace": "C1 domain=taxi; goal=booking. C2 domain=train; departure+=broxbourne train station. C3 domain=restaurant; time+=20:15; destination+=leave by 20:15 and am headed to city stop. C4 intent=context_update. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i want to book a taxi.", "streaming_reasoning": "Initially, the topic is taxi; the goal is booking..", "trace": "domain=taxi; goal=booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The taxi should depart from broxbourne train station.", "streaming_reasoning": "As more information arrives, the topic is train; departure point: broxbourne train station..", "trace": "domain=train; departure+=broxbourne train station."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I need to leave by 20:15 and am headed to city stop restaurant Thank you.", "streaming_reasoning": "As more information arrives, the topic is restaurant; time: 20:15; destination: leave by 20:15 and am headed to city stop..", "trace": "domain=restaurant; time+=20:15; destination+=leave by 20:15 and am headed to city stop."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am all set.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Have a great day.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a taxi task with the goal of search. Key information: destination is leave by 20:15 and am headed to city stop; departure point is broxbourne train station; timing is 20:15. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=taxi, train, restaurant; goal=search, booking; destination=leave by 20:15 and am headed to city stop; departure=broxbourne train station; when=20:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002968", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I need to leave on Wednesday.\nChunk 2: What's available for that day?\nChunk 3: What time will I arrive in Cambridge on that train?\nChunk 4: No, I need help finding a cinema located in the east Either is fine.\nChunk 5: I just need a phone number so I can call one of them.\nChunk 6: Thanks.\nChunk 7: I'm sorry, but if their is no cinema in the east, can you find me a swimming pool instead?\nChunk 8: No.\nChunk 9: You've been very helpful today Thank you.", "streaming_reasoning": "C1 goal=search; day+=wednesday; destination+=leave on wednesday. C2 goal=request_info. C3 domain=train. C4 area+=east. C5 requested_info+=phone. C6 [SKIP: thanks_only]. C7 goal=compare_alternative; amenities+=pool. C8 [SKIP: acknowledgement_only]. C9 day+=today.", "deep_reasoning": "Need domain=train; goal=search, request_info, compare_alternative; area=east; amenities=pool; destination=leave on wednesday; requested_info=phone; when=wednesday, today; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: No, I need to leave on Wednesday.\nChunk 2: What's available for that day?\nChunk 3: What time will I arrive in Cambridge on that train?\nChunk 4: No, I need help finding a cinema located in the east Either is fine.\nChunk 5: I just need a phone number so I can call one of them.\nChunk 6: Thanks.\nChunk 7: I'm sorry, but if their is no cinema in the east, can you find me a swimming pool instead?\nChunk 8: No.\nChunk 9: You've been very helpful today Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search; day+=wednesday; destination+=leave on wednesday. C2 goal=request_info. C3 domain=train. C4 area+=east. C5 requested_info+=phone. C6 [SKIP: thanks_only]. C7 goal=compare_alternative; amenities+=pool. C8 [SKIP: acknowledgement_only]. C9 day+=today.\n\nDeep reasoning: Need domain=train; goal=search, request_info, compare_alternative; area=east; amenities=pool; destination=leave on wednesday; requested_info=phone; when=wednesday, today; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: No, I need to leave on Wednesday.\nChunk 2: What's available for that day?\nChunk 3: What time will I arrive in Cambridge on that train?\nChunk 4: No, I need help finding a cinema located in the east Either is fine.\nChunk 5: I just need a phone number so I can call one of them.\nChunk 6: Thanks.\nChunk 7: I'm sorry, but if their is no cinema in the east, can you find me a swimming pool instead?\nChunk 8: No.\nChunk 9: You've been very helpful today Thank you.", "input_token_count": 95, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search; day: wednesday; destination: leave on wednesday. Next, the goal is request info. Next, the topic is train. Next, area: east. Next, requested information: phone. Next, the goal is compare alternative; amenities: pool. Finally, day: today.  Some chunks were skipped because they contained acknowledgement_only or thanks_only. In summary, The overall topic is train.. the goal is compare alternative. day: wednesday, today.; destination: leave on wednesday.; area: east.; requested information: phone.; amenities: pool..", "trace": "C1 goal=search; day+=wednesday; destination+=leave on wednesday. C2 goal=request_info. C3 domain=train. C4 area+=east. C5 requested_info+=phone. C6 [SKIP: thanks_only]. C7 goal=compare_alternative; amenities+=pool. C8 [SKIP: acknowledgement_only]. C9 day+=today.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "No, I need to leave on Wednesday.", "streaming_reasoning": "Initially, the goal is search; day: wednesday; destination: leave on wednesday..", "trace": "goal=search; day+=wednesday; destination+=leave on wednesday."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What's available for that day?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "What time will I arrive in Cambridge on that train?", "streaming_reasoning": "As more information arrives, the topic is train..", "trace": "domain=train."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "No, I need help finding a cinema located in the east Either is fine.", "streaming_reasoning": "As more information arrives, area: east..", "trace": "area+=east."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I just need a phone number so I can call one of them.", "streaming_reasoning": "As more information arrives, requested information: phone..", "trace": "requested_info+=phone."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'm sorry, but if their is no cinema in the east, can you find me a swimming pool instead?", "streaming_reasoning": "As more information arrives, the goal is compare alternative; amenities: pool..", "trace": "goal=compare_alternative; amenities+=pool."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No.", "streaming_reasoning": "The content at C8 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "You've been very helpful today Thank you.", "streaming_reasoning": "Finally, day: today..", "trace": "day+=today."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: area is east; amenities is pool; destination is leave on wednesday; requested information is phone; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info, compare_alternative; area=east; amenities=pool; destination=leave on wednesday; requested_info=phone; when=wednesday, today; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002969", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also will need a hotel.\nChunk 2: It doesn't matter, I'd like it to be a guesthouse in the moderate price range.\nChunk 3: Do they have free wifi?\nChunk 4: Thank you for all of your help Yes, please.\nChunk 5: I'd like a room for 5 people on Wednesday for 3 nights.\nChunk 6: That's all I needed tonight.\nChunk 7: Thanks for the help.", "streaming_reasoning": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 price+=moderate; hotel_type+=guesthouse; destination+=be a guesthouse in the moderate price ran. C3 amenities+=wifi. C4 [SKIP: thanks_only]. C5 day+=wednesday; party_size+=5 people; stay_length+=3 nights. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search; price=moderate; party_size=5 people; stay_length=3 nights; amenities=wifi; destination=be a guesthouse in the moderate price ran; when=wednesday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I also will need a hotel.\nChunk 2: It doesn't matter, I'd like it to be a guesthouse in the moderate price range.\nChunk 3: Do they have free wifi?\nChunk 4: Thank you for all of your help Yes, please.\nChunk 5: I'd like a room for 5 people on Wednesday for 3 nights.\nChunk 6: That's all I needed tonight.\nChunk 7: Thanks for the help."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=search; hotel_type+=hotel. C2 price+=moderate; hotel_type+=guesthouse; destination+=be a guesthouse in the moderate price ran. C3 amenities+=wifi. C4 [SKIP: thanks_only]. C5 day+=wednesday; party_size+=5 people; stay_length+=3 nights. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search; price=moderate; party_size=5 people; stay_length=3 nights; amenities=wifi; destination=be a guesthouse in the moderate price ran; when=wednesday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I also will need a hotel.\nChunk 2: It doesn't matter, I'd like it to be a guesthouse in the moderate price range.\nChunk 3: Do they have free wifi?\nChunk 4: Thank you for all of your help Yes, please.\nChunk 5: I'd like a room for 5 people on Wednesday for 3 nights.\nChunk 6: That's all I needed tonight.\nChunk 7: Thanks for the help.", "input_token_count": 70, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel. Next, price: moderate; hotel type: guesthouse; destination: be a guesthouse in the moderate price ran. Next, amenities: wifi. Finally, day: wednesday; party size: 5 people; stay length: 3 nights.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is search. hotel type: hotel., guesthouse; price: moderate; destination: be a guesthouse in the moderate price ran.; amenities: wifi.; day: wednesday; party size: 5 people; stay length: 3 nights..", "trace": "C1 domain=hotel; goal=search; hotel_type+=hotel. C2 price+=moderate; hotel_type+=guesthouse; destination+=be a guesthouse in the moderate price ran. C3 amenities+=wifi. C4 [SKIP: thanks_only]. C5 day+=wednesday; party_size+=5 people; stay_length+=3 nights. C6 [SKIP: closing_only]. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I also will need a hotel.", "streaming_reasoning": "Initially, the topic is hotel; the goal is search; hotel type: hotel..", "trace": "domain=hotel; goal=search; hotel_type+=hotel."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It doesn't matter, I'd like it to be a guesthouse in the moderate price range.", "streaming_reasoning": "As more information arrives, price: moderate; hotel type: guesthouse; destination: be a guesthouse in the moderate price ran..", "trace": "price+=moderate; hotel_type+=guesthouse; destination+=be a guesthouse in the moderate price ran."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Do they have free wifi?", "streaming_reasoning": "As more information arrives, amenities: wifi..", "trace": "amenities+=wifi."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Thank you for all of your help Yes, please.", "streaming_reasoning": "The content at C4 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I'd like a room for 5 people on Wednesday for 3 nights.", "streaming_reasoning": "As more information arrives, day: wednesday; party size: 5 people; stay length: 3 nights..", "trace": "day+=wednesday; party_size+=5 people; stay_length+=3 nights."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That's all I needed tonight.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks for the help.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: price is moderate; party size is 5 people; stay length is 3 nights; amenities is wifi; destination is be a guesthouse in the moderate price ran; timing is wednesday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search; price=moderate; party_size=5 people; stay_length=3 nights; amenities=wifi; destination=be a guesthouse in the moderate price ran; when=wednesday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002970", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a italian restaurant.\nChunk 2: It should be in the centre part of town.\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 14:00.\nChunk 5: Please make a booking.\nChunk 6: I also need the reference number.\nChunk 7: Yes.\nChunk 8: Are there any colleges nearby that I can visit Thank you!\nChunk 9: What is the address/postcode for Hughes Hall?\nChunk 10: Yes, I would like to book a taxi to get from the restaurant to the college.\nChunk 11: I need to arrive by 14:00 Great!\nChunk 12: That was all I needed/.", "streaming_reasoning": "C1 domain=restaurant; goal=search; cuisine+=italian; destination+=find a italian restaurant. C2 area+=centre. C3 party_size+=6 people. C4 time+=6, 14:00; day+=monday. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 goal=confirm_booking. C8 intent=context_update. C9 requested_info+=address, postcode. C10 domain=attraction; goal=confirm_booking; destination+=the college; departure+=the restaurant; goal=confirm_booking. C11 destination+=arrive by 14:00 great!. C12 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, taxi, attraction; goal=search, booking, request_info, confirm_booking; area=centre; food=italian; party_size=6 people; destination=find a italian restaurant, the college, arrive by 14:00 great!; departure=the restaurant; requested_info=reference_number, address, postcode; when=monday, 6, 14:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a italian restaurant.\nChunk 2: It should be in the centre part of town.\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 14:00.\nChunk 5: Please make a booking.\nChunk 6: I also need the reference number.\nChunk 7: Yes.\nChunk 8: Are there any colleges nearby that I can visit Thank you!\nChunk 9: What is the address/postcode for Hughes Hall?\nChunk 10: Yes, I would like to book a taxi to get from the restaurant to the college.\nChunk 11: I need to arrive by 14:00 Great!\nChunk 12: That was all I needed/."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; cuisine+=italian; destination+=find a italian restaurant. C2 area+=centre. C3 party_size+=6 people. C4 time+=6, 14:00; day+=monday. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 goal=confirm_booking. C8 intent=context_update. C9 requested_info+=address, postcode. C10 domain=attraction; goal=confirm_booking; destination+=the college; departure+=the restaurant; goal=confirm_booking. C11 destination+=arrive by 14:00 great!. C12 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, taxi, attraction; goal=search, booking, request_info, confirm_booking; area=centre; food=italian; party_size=6 people; destination=find a italian restaurant, the college, arrive by 14:00 great!; departure=the restaurant; requested_info=reference_number, address, postcode; when=monday, 6, 14:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a italian restaurant.\nChunk 2: It should be in the centre part of town.\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 14:00.\nChunk 5: Please make a booking.\nChunk 6: I also need the reference number.\nChunk 7: Yes.\nChunk 8: Are there any colleges nearby that I can visit Thank you!\nChunk 9: What is the address/postcode for Hughes Hall?\nChunk 10: Yes, I would like to book a taxi to get from the restaurant to the college.\nChunk 11: I need to arrive by 14:00 Great!\nChunk 12: That was all I needed/.", "input_token_count": 111, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: italian; destination: find a italian restaurant. Next, area: centre. Next, party size: 6 people. Next, time: 6; day: monday. Next, the goal is booking. Next, the goal is request info; requested information: reference_number. Next, the goal is confirm booking. Next, intent: context_update. Next, requested information: address. Next, the topic is attraction; the goal is confirm booking.; destination: the college; departure point: the restaurant. Finally, destination: arrive by 14:00 great!.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is confirm booking.. cuisine: italian; destination: find a italian restaurant., the college, arrive by 14:00 great!.; area: centre.; party size: 6 people.; time: 6; day: monday.; requested information: reference_number., address; intent: context_update.; departure point: the restaurant.", "trace": "C1 domain=restaurant; goal=search; cuisine+=italian; destination+=find a italian restaurant. C2 area+=centre. C3 party_size+=6 people. C4 time+=6, 14:00; day+=monday. C5 goal=booking. C6 goal=request_info; requested_info+=reference_number. C7 goal=confirm_booking. C8 intent=context_update. C9 requested_info+=address, postcode. C10 domain=attraction; goal=confirm_booking; destination+=the college; departure+=the restaurant; goal=confirm_booking. C11 destination+=arrive by 14:00 great!. C12 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a italian restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; cuisine: italian; destination: find a italian restaurant..", "trace": "domain=restaurant; goal=search; cuisine+=italian; destination+=find a italian restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It should be in the centre part of town.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 6 people.", "streaming_reasoning": "As more information arrives, party size: 6 people..", "trace": "party_size+=6 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is monday, 6, 14:00.", "streaming_reasoning": "As more information arrives, time: 6; day: monday..", "trace": "time+=6, 14:00; day+=monday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Yes.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Are there any colleges nearby that I can visit Thank you!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "What is the address/postcode for Hughes Hall?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, postcode."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "Yes, I would like to book a taxi to get from the restaurant to the college.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is confirm booking.; destination: the college; departure point: the restaurant.", "trace": "domain=attraction; goal=confirm_booking; destination+=the college; departure+=the restaurant; goal=confirm_booking."}, {"checkpoint_id": "C11", "chunk_index": 10, "observed_text": "I need to arrive by 14:00 Great!", "streaming_reasoning": "As more information arrives, destination: arrive by 14:00 great!..", "trace": "destination+=arrive by 14:00 great!."}, {"checkpoint_id": "C12", "chunk_index": 11, "observed_text": "That was all I needed/.", "streaming_reasoning": "The content at C12 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is centre; cuisine is italian; party size is 6 people; destination is find a italian restaurant; departure point is the restaurant; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, taxi, attraction; goal=search, booking, request_info, confirm_booking; area=centre; food=italian; party_size=6 people; destination=find a italian restaurant, the college, arrive by 14:00 great!; departure=the restaurant; requested_info=reference_number, address, postcode; when=monday, 6, 14:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002971", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes can I get the train ID and arrival time please?\nChunk 2: I'd also like to find an expensive restaurant that serves european food In the north.\nChunk 3: Can you book it for me and get a reference number?\nChunk 4: 2 people, on monday at 14:00.\nChunk 5: Have a nice day.", "streaming_reasoning": "C1 domain=train; goal=request_info; acceptance=selected_option. C2 domain=restaurant; goal=search; area+=north; cuisine+=european; price+=expensive; destination+=find an expensive restaurant that serves. C3 goal=booking; requested_info+=reference_number. C4 time+=2, 14:00; day+=monday; party_size+=2 people. C5 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, restaurant; goal=request_info, search, booking; area=north; food=european; price=expensive; party_size=2 people; destination=find an expensive restaurant that serves; requested_info=reference_number; when=monday, 2, 14:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes can I get the train ID and arrival time please?\nChunk 2: I'd also like to find an expensive restaurant that serves european food In the north.\nChunk 3: Can you book it for me and get a reference number?\nChunk 4: 2 people, on monday at 14:00.\nChunk 5: Have a nice day."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=request_info; acceptance=selected_option. C2 domain=restaurant; goal=search; area+=north; cuisine+=european; price+=expensive; destination+=find an expensive restaurant that serves. C3 goal=booking; requested_info+=reference_number. C4 time+=2, 14:00; day+=monday; party_size+=2 people. C5 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, restaurant; goal=request_info, search, booking; area=north; food=european; price=expensive; party_size=2 people; destination=find an expensive restaurant that serves; requested_info=reference_number; when=monday, 2, 14:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes can I get the train ID and arrival time please?\nChunk 2: I'd also like to find an expensive restaurant that serves european food In the north.\nChunk 3: Can you book it for me and get a reference number?\nChunk 4: 2 people, on monday at 14:00.\nChunk 5: Have a nice day.", "input_token_count": 58, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is request info; acceptance: selected_option. Next, the topic is restaurant; the goal is search; area: north; cuisine: european; price: expensive; destination: find an expensive restaurant that serves. Next, the goal is booking; requested information: reference_number. Finally, time: 2; day: monday; party size: 2 people.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is booking. acceptance: selected_option.; area: north; cuisine: european; price: expensive; destination: find an expensive restaurant that serves.; requested information: reference_number.; time: 2; day: monday; party size: 2 people..", "trace": "C1 domain=train; goal=request_info; acceptance=selected_option. C2 domain=restaurant; goal=search; area+=north; cuisine+=european; price+=expensive; destination+=find an expensive restaurant that serves. C3 goal=booking; requested_info+=reference_number. C4 time+=2, 14:00; day+=monday; party_size+=2 people. C5 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes can I get the train ID and arrival time please?", "streaming_reasoning": "Initially, the topic is train; the goal is request info; acceptance: selected_option..", "trace": "domain=train; goal=request_info; acceptance=selected_option."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I'd also like to find an expensive restaurant that serves european food In the north.", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is search; area: north; cuisine: european; price: expensive; destination: find an expensive restaurant that serves..", "trace": "domain=restaurant; goal=search; area+=north; cuisine+=european; price+=expensive; destination+=find an expensive restaurant that serves."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Can you book it for me and get a reference number?", "streaming_reasoning": "As more information arrives, the goal is booking; requested information: reference_number..", "trace": "goal=booking; requested_info+=reference_number."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "2 people, on monday at 14:00.", "streaming_reasoning": "As more information arrives, time: 2; day: monday; party size: 2 people..", "trace": "time+=2, 14:00; day+=monday; party_size+=2 people."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Have a nice day.", "streaming_reasoning": "The content at C5 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of request info. Key information: area is north; cuisine is european; price is expensive; party size is 2 people; destination is find an expensive restaurant that serves; requested information is reference_number; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, restaurant; goal=request_info, search, booking; area=north; food=european; price=expensive; party_size=2 people; destination=find an expensive restaurant that serves; requested_info=reference_number; when=monday, 2, 14:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003692", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I got a job offer from Dell That's great.\nChunk 2: I thought you said you didn't get the job.\nChunk 3: I thought I did bad on the interview, but I guess I was wrong.\nChunk 4: I'm so happy right now.\nChunk 5: I bet That's great news.\nChunk 6: I'm very happy for you.\nChunk 7: Thanks.\nChunk 8: I feel like celebrating.\nChunk 9: Let's go have a beer It's on me.", "streaming_reasoning": "C1 casual_comment=job, offer. C2 casual_comment=thought, said. C3 casual_comment=thought, did. C4 casual_comment=i'm, happy. C5 casual_comment=bet, that's. C6 casual_comment=i'm, very. C7 [SKIP: thanks_only]. C8 preference=true. C9 casual_comment=let's, beer.", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I got a job offer from Dell That's great.\nChunk 2: I thought you said you didn't get the job.\nChunk 3: I thought I did bad on the interview, but I guess I was wrong.\nChunk 4: I'm so happy right now.\nChunk 5: I bet That's great news.\nChunk 6: I'm very happy for you.\nChunk 7: Thanks.\nChunk 8: I feel like celebrating.\nChunk 9: Let's go have a beer It's on me."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=job, offer. C2 casual_comment=thought, said. C3 casual_comment=thought, did. C4 casual_comment=i'm, happy. C5 casual_comment=bet, that's. C6 casual_comment=i'm, very. C7 [SKIP: thanks_only]. C8 preference=true. C9 casual_comment=let's, beer.\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I got a job offer from Dell That's great.\nChunk 2: I thought you said you didn't get the job.\nChunk 3: I thought I did bad on the interview, but I guess I was wrong.\nChunk 4: I'm so happy right now.\nChunk 5: I bet That's great news.\nChunk 6: I'm very happy for you.\nChunk 7: Thanks.\nChunk 8: I feel like celebrating.\nChunk 9: Let's go have a beer It's on me.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on job. Next, the user comments on thought. Next, the user comments on thought. Next, the user comments on i'm. Next, the user comments on bet. Next, the user comments on i'm. Next, preference: true. Finally, the user comments on let's.  Some chunks were skipped because they contained thanks_only. In summary, preference: true..", "trace": "C1 casual_comment=job, offer. C2 casual_comment=thought, said. C3 casual_comment=thought, did. C4 casual_comment=i'm, happy. C5 casual_comment=bet, that's. C6 casual_comment=i'm, very. C7 [SKIP: thanks_only]. C8 preference=true. C9 casual_comment=let's, beer.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I got a job offer from Dell That's great.", "streaming_reasoning": "Initially, the user comments on job.", "trace": "casual_comment=job, offer."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I thought you said you didn't get the job.", "streaming_reasoning": "As more information arrives, the user comments on thought.", "trace": "casual_comment=thought, said."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I thought I did bad on the interview, but I guess I was wrong.", "streaming_reasoning": "As more information arrives, the user comments on thought.", "trace": "casual_comment=thought, did."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm so happy right now.", "streaming_reasoning": "As more information arrives, the user comments on i'm.", "trace": "casual_comment=i'm, happy."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I bet That's great news.", "streaming_reasoning": "As more information arrives, the user comments on bet.", "trace": "casual_comment=bet, that's."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I'm very happy for you.", "streaming_reasoning": "As more information arrives, the user comments on i'm.", "trace": "casual_comment=i'm, very."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks.", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I feel like celebrating.", "streaming_reasoning": "As more information arrives, preference: true..", "trace": "preference=true."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Let's go have a beer It's on me.", "streaming_reasoning": "Finally, the user comments on let's.", "trace": "casual_comment=let's, beer."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002973", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, can you please book me a room for 4 people for 5 nights starting Saturday.\nChunk 2: Yes.\nChunk 3: I am looking to go to london Kings cross on thursday via train.\nChunk 4: Is this something you can assist with?\nChunk 5: I will be departing from Cabridge.\nChunk 6: I need the train to leave after 16:45 Sure.\nChunk 7: What is the cost and what time will it arrive thankyou so much.", "streaming_reasoning": "C1 domain=hotel; goal=confirm_booking; time+=4, 5; day+=saturday; party_size+=4 people; stay_length+=5 nights; goal=confirm_booking. C2 goal=confirm_booking. C3 domain=train; day+=thursday; destination+=go to london kings cross on thursday via. C4 goal=search. C5 departure+=cabridge. C6 time+=16:45; destination+=leave after 16:45 sure. C7 goal=request_info; requested_info+=price.", "deep_reasoning": "Need domain=hotel, train; goal=booking, confirm_booking, search, request_info; party_size=4 people; stay_length=5 nights; destination=go to london kings cross on thursday via, leave after 16:45 sure; departure=cabridge; requested_info=price; when=saturday, thursday, 4, 5, 16:45.", "answer": "I can help with that and include the price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes, can you please book me a room for 4 people for 5 nights starting Saturday.\nChunk 2: Yes.\nChunk 3: I am looking to go to london Kings cross on thursday via train.\nChunk 4: Is this something you can assist with?\nChunk 5: I will be departing from Cabridge.\nChunk 6: I need the train to leave after 16:45 Sure.\nChunk 7: What is the cost and what time will it arrive thankyou so much."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hotel; goal=confirm_booking; time+=4, 5; day+=saturday; party_size+=4 people; stay_length+=5 nights; goal=confirm_booking. C2 goal=confirm_booking. C3 domain=train; day+=thursday; destination+=go to london kings cross on thursday via. C4 goal=search. C5 departure+=cabridge. C6 time+=16:45; destination+=leave after 16:45 sure. C7 goal=request_info; requested_info+=price.\n\nDeep reasoning: Need domain=hotel, train; goal=booking, confirm_booking, search, request_info; party_size=4 people; stay_length=5 nights; destination=go to london kings cross on thursday via, leave after 16:45 sure; departure=cabridge; requested_info=price; when=saturday, thursday, 4, 5, 16:45.\n\nAnswer: I can help with that and include the price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes, can you please book me a room for 4 people for 5 nights starting Saturday.\nChunk 2: Yes.\nChunk 3: I am looking to go to london Kings cross on thursday via train.\nChunk 4: Is this something you can assist with?\nChunk 5: I will be departing from Cabridge.\nChunk 6: I need the train to leave after 16:45 Sure.\nChunk 7: What is the cost and what time will it arrive thankyou so much.", "input_token_count": 80, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hotel; the goal is confirm booking.; time: 4; day: saturday; party size: 4 people; stay length: 5 nights. Next, the goal is confirm booking. Next, the topic is train; day: thursday; destination: go to london kings cross on thursday via. Next, the goal is search. Next, departure point: cabridge. Next, time: 16:45; destination: leave after 16:45 sure. Finally, the goal is request info; requested information: price. In summary, The overall topic is train. the goal is request info. time: 4, 16:45; day: saturday, thursday; party size: 4 people; stay length: 5 nights; destination: go to london kings cross on thursday via., leave after 16:45 sure.; departure point: cabridge.; requested information: price..", "trace": "C1 domain=hotel; goal=confirm_booking; time+=4, 5; day+=saturday; party_size+=4 people; stay_length+=5 nights; goal=confirm_booking. C2 goal=confirm_booking. C3 domain=train; day+=thursday; destination+=go to london kings cross on thursday via. C4 goal=search. C5 departure+=cabridge. C6 time+=16:45; destination+=leave after 16:45 sure. C7 goal=request_info; requested_info+=price.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes, can you please book me a room for 4 people for 5 nights starting Saturday.", "streaming_reasoning": "Initially, the topic is hotel; the goal is confirm booking.; time: 4; day: saturday; party size: 4 people; stay length: 5 nights.", "trace": "domain=hotel; goal=confirm_booking; time+=4, 5; day+=saturday; party_size+=4 people; stay_length+=5 nights; goal=confirm_booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes.", "streaming_reasoning": "As more information arrives, the goal is confirm booking..", "trace": "goal=confirm_booking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am looking to go to london Kings cross on thursday via train.", "streaming_reasoning": "As more information arrives, the topic is train; day: thursday; destination: go to london kings cross on thursday via..", "trace": "domain=train; day+=thursday; destination+=go to london kings cross on thursday via."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Is this something you can assist with?", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I will be departing from Cabridge.", "streaming_reasoning": "As more information arrives, departure point: cabridge..", "trace": "departure+=cabridge."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I need the train to leave after 16:45 Sure.", "streaming_reasoning": "As more information arrives, time: 16:45; destination: leave after 16:45 sure..", "trace": "time+=16:45; destination+=leave after 16:45 sure."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "What is the cost and what time will it arrive thankyou so much.", "streaming_reasoning": "Finally, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of booking. Key information: party size is 4 people; stay length is 5 nights; destination is go to london kings cross on thursday via; departure point is cabridge; requested information is price; timing is saturday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the price once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel, train; goal=booking, confirm_booking, search, request_info; party_size=4 people; stay_length=5 nights; destination=go to london kings cross on thursday via, leave after 16:45 sure; departure=cabridge; requested_info=price; when=saturday, thursday, 4, 5, 16:45."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002974", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Am injured and are looking for a hospital nearby it should have the neurology neurosurgery department.\nChunk 2: No, I just need the postcode, please.\nChunk 3: Thank you, I think that is all I needed.", "streaming_reasoning": "C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].", "deep_reasoning": "Need domain=hospital; goal=search, request_info; requested_info=postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Am injured and are looking for a hospital nearby it should have the neurology neurosurgery department.\nChunk 2: No, I just need the postcode, please.\nChunk 3: Thank you, I think that is all I needed."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hospital; goal=search, request_info; requested_info=postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Am injured and are looking for a hospital nearby it should have the neurology neurosurgery department.\nChunk 2: No, I just need the postcode, please.\nChunk 3: Thank you, I think that is all I needed.", "input_token_count": 38, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search. Finally, the goal is request info; requested information: postcode.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hospital. the goal is request info. requested information: postcode..", "trace": "C1 domain=hospital; goal=search. C2 goal=request_info; requested_info+=postcode. C3 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Am injured and are looking for a hospital nearby it should have the neurology neurosurgery department.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search..", "trace": "domain=hospital; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No, I just need the postcode, please.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: postcode..", "trace": "goal=request_info; requested_info+=postcode."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you, I think that is all I needed.", "streaming_reasoning": "The content at C3 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hospital task with the goal of search. Key information: requested information is postcode. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hospital; goal=search, request_info; requested_info=postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_emotional_support_001990", "domain": "emotional_support", "source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I went back to my home state to visit.\nChunk 2: It made me think of the past.\nChunk 3: I recently went back to my home state to visit Oh how nice!\nChunk 4: Did you get to visit with friends and family Yes I did.\nChunk 5: It made me think of the past It was bittersweet.", "streaming_reasoning": "C1 need=validation. C2 emotion=frustrated. C3 support_signal=received. C4 cause=Did you get to visit with friends and family Yes I did; need=encouragement. C5 emotion=frustrated; need=validation.", "deep_reasoning": "User feels frustrated after Did you get to visit with friends and family Yes I did and needs validation.", "answer": "It makes sense to feel frustrated after Did you get to visit with friends and family Yes I did. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I went back to my home state to visit.\nChunk 2: It made me think of the past.\nChunk 3: I recently went back to my home state to visit Oh how nice!\nChunk 4: Did you get to visit with friends and family Yes I did.\nChunk 5: It made me think of the past It was bittersweet."}, {"role": "assistant", "content": "Streaming reasoning: C1 need=validation. C2 emotion=frustrated. C3 support_signal=received. C4 cause=Did you get to visit with friends and family Yes I did; need=encouragement. C5 emotion=frustrated; need=validation.\n\nDeep reasoning: User feels frustrated after Did you get to visit with friends and family Yes I did and needs validation.\n\nAnswer: It makes sense to feel frustrated after Did you get to visit with friends and family Yes I did. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "conflict_deescalation", "intent_type": "supportive_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I went back to my home state to visit.\nChunk 2: It made me think of the past.\nChunk 3: I recently went back to my home state to visit Oh how nice!\nChunk 4: Did you get to visit with friends and family Yes I did.\nChunk 5: It made me think of the past It was bittersweet.", "input_token_count": 61, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user needs validation. Next, the user expresses frustrated. Next, the user signals support or acknowledgment. Next, the user mentions Did you get to visit with friends and family Yes I did; the user needs encouragement. Finally, the user expresses frustrated; the user needs validation.", "trace": "C1 need=validation. C2 emotion=frustrated. C3 support_signal=received. C4 cause=Did you get to visit with friends and family Yes I did; need=encouragement. C5 emotion=frustrated; need=validation.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I went back to my home state to visit.", "streaming_reasoning": "Initially, the user needs validation..", "trace": "need=validation."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It made me think of the past.", "streaming_reasoning": "As more information arrives, the user expresses frustrated..", "trace": "emotion=frustrated."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I recently went back to my home state to visit Oh how nice!", "streaming_reasoning": "As more information arrives, the user signals support or acknowledgment.", "trace": "support_signal=received."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Did you get to visit with friends and family Yes I did.", "streaming_reasoning": "As more information arrives, the user mentions Did you get to visit with friends and family Yes I did; the user needs encouragement..", "trace": "cause=Did you get to visit with friends and family Yes I did; need=encouragement."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "It made me think of the past It was bittersweet.", "streaming_reasoning": "Finally, the user expresses frustrated; the user needs validation..", "trace": "emotion=frustrated; need=validation."}]}, "output": {"deep_reasoning": "User feels frustrated after Did you get to visit with friends and family Yes I did and needs validation.", "answer": "It makes sense to feel frustrated after Did you get to visit with friends and family Yes I did. Give yourself a moment, then choose one manageable action instead of trying to solve everything at once."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/empathetic_dialogues_for_lm", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002975", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It is for 4 people.\nChunk 2: The time is friday, 19:00, 4.\nChunk 3: I also need the reference number.\nChunk 4: I am also looking for a hotel in the same area with zero stars Are you sure?\nChunk 5: A 0 star HOTEL in the west side of time Please check again.\nChunk 6: Could you try looking for a guesthouse in the 4 star range Okay, great.\nChunk 7: I'll need to book for Friday, 2 nights, and 4 people, please?\nChunk 8: No, that's all I need for today.\nChunk 9: Thanks!", "streaming_reasoning": "C1 party_size+=4 people. C2 time+=19:00, 4; day+=friday. C3 goal=request_info; requested_info+=reference_number. C4 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C5 area+=west; stars+=0 stars. C6 hotel_type+=guesthouse; stars+=4 stars. C7 goal=booking; stay_length+=2 nights. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info, modify_constraint, booking; area=west; party_size=4 people; stay_length=2 nights; stars=0 stars, 4 stars; requested_info=reference_number; when=friday, 19:00, 4; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: It is for 4 people.\nChunk 2: The time is friday, 19:00, 4.\nChunk 3: I also need the reference number.\nChunk 4: I am also looking for a hotel in the same area with zero stars Are you sure?\nChunk 5: A 0 star HOTEL in the west side of time Please check again.\nChunk 6: Could you try looking for a guesthouse in the 4 star range Okay, great.\nChunk 7: I'll need to book for Friday, 2 nights, and 4 people, please?\nChunk 8: No, that's all I need for today.\nChunk 9: Thanks!"}, {"role": "assistant", "content": "Streaming reasoning: C1 party_size+=4 people. C2 time+=19:00, 4; day+=friday. C3 goal=request_info; requested_info+=reference_number. C4 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C5 area+=west; stars+=0 stars. C6 hotel_type+=guesthouse; stars+=4 stars. C7 goal=booking; stay_length+=2 nights. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info, modify_constraint, booking; area=west; party_size=4 people; stay_length=2 nights; stars=0 stars, 4 stars; requested_info=reference_number; when=friday, 19:00, 4; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: It is for 4 people.\nChunk 2: The time is friday, 19:00, 4.\nChunk 3: I also need the reference number.\nChunk 4: I am also looking for a hotel in the same area with zero stars Are you sure?\nChunk 5: A 0 star HOTEL in the west side of time Please check again.\nChunk 6: Could you try looking for a guesthouse in the 4 star range Okay, great.\nChunk 7: I'll need to book for Friday, 2 nights, and 4 people, please?\nChunk 8: No, that's all I need for today.\nChunk 9: Thanks!", "input_token_count": 100, "length_bucket": "short_medium"}, "streaming": {"streaming_reasoning": "Initially, party size: 4 people. Next, time: 19:00; day: friday. Next, the goal is request info; requested information: reference_number. Next, the topic is hotel; the goal is modify constraint; hotel type: hotel. Next, area: west; star rating: 0 stars. Next, hotel type: guesthouse; star rating: 4 stars. Finally, the goal is booking; stay length: 2 nights.  Some chunks were skipped because they contained closing_only or thanks_only. In summary, The overall topic is hotel. the goal is booking. party size: 4 people.; time: 19:00; day: friday.; requested information: reference_number.; hotel type: hotel., guesthouse; area: west; star rating: 0 stars., 4 stars.; stay length: 2 nights..", "trace": "C1 party_size+=4 people. C2 time+=19:00, 4; day+=friday. C3 goal=request_info; requested_info+=reference_number. C4 domain=hotel; goal=modify_constraint; hotel_type+=hotel. C5 area+=west; stars+=0 stars. C6 hotel_type+=guesthouse; stars+=4 stars. C7 goal=booking; stay_length+=2 nights. C8 [SKIP: closing_only]. C9 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "It is for 4 people.", "streaming_reasoning": "Initially, party size: 4 people..", "trace": "party_size+=4 people."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The time is friday, 19:00, 4.", "streaming_reasoning": "As more information arrives, time: 19:00; day: friday..", "trace": "time+=19:00, 4; day+=friday."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need the reference number.", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: reference_number..", "trace": "goal=request_info; requested_info+=reference_number."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I am also looking for a hotel in the same area with zero stars Are you sure?", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is modify constraint; hotel type: hotel..", "trace": "domain=hotel; goal=modify_constraint; hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "A 0 star HOTEL in the west side of time Please check again.", "streaming_reasoning": "As more information arrives, area: west; star rating: 0 stars..", "trace": "area+=west; stars+=0 stars."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Could you try looking for a guesthouse in the 4 star range Okay, great.", "streaming_reasoning": "As more information arrives, hotel type: guesthouse; star rating: 4 stars..", "trace": "hotel_type+=guesthouse; stars+=4 stars."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I'll need to book for Friday, 2 nights, and 4 people, please?", "streaming_reasoning": "As more information arrives, the goal is booking; stay length: 2 nights..", "trace": "goal=booking; stay_length+=2 nights."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "No, that's all I need for today.", "streaming_reasoning": "The content at C8 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "Thanks!", "streaming_reasoning": "The content at C9 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is west; party size is 4 people; stay length is 2 nights; star rating is 0 stars; requested information is reference_number; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info, modify_constraint, booking; area=west; party_size=4 people; stay_length=2 nights; stars=0 stars, 4 stars; requested_info=reference_number; when=friday, 19:00, 4; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002976", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I don't have a preference.\nChunk 2: I will need parking too.\nChunk 3: getme its price range, phone number and hotel type.\nChunk 4: Do you have any restaurants near there with Chinese food?\nChunk 5: I would like somewhere moderately priced Yes please.\nChunk 6: Can you book a for a table of 5 at 17:30 on Monday?\nChunk 7: No.\nChunk 8: I am all set thank you.", "streaming_reasoning": "C1 intent=context_update. C2 goal=search; amenities+=parking. C3 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone. C4 domain=restaurant; cuisine+=chinese. C5 price+=moderate; acceptance=selected_option. C6 goal=booking; time+=5, 17:30; day+=monday. C7 goal=modify_constraint. C8 intent=context_update.", "deep_reasoning": "Need domain=hotel, restaurant; goal=search, request_info, booking; food=chinese; price=moderate; amenities=parking; requested_info=phone; when=monday, 5, 17:30.", "answer": "I can help with that and include the phone once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I don't have a preference.\nChunk 2: I will need parking too.\nChunk 3: getme its price range, phone number and hotel type.\nChunk 4: Do you have any restaurants near there with Chinese food?\nChunk 5: I would like somewhere moderately priced Yes please.\nChunk 6: Can you book a for a table of 5 at 17:30 on Monday?\nChunk 7: No.\nChunk 8: I am all set thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 intent=context_update. C2 goal=search; amenities+=parking. C3 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone. C4 domain=restaurant; cuisine+=chinese. C5 price+=moderate; acceptance=selected_option. C6 goal=booking; time+=5, 17:30; day+=monday. C7 goal=modify_constraint. C8 intent=context_update.\n\nDeep reasoning: Need domain=hotel, restaurant; goal=search, request_info, booking; food=chinese; price=moderate; amenities=parking; requested_info=phone; when=monday, 5, 17:30.\n\nAnswer: I can help with that and include the phone once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I don't have a preference.\nChunk 2: I will need parking too.\nChunk 3: getme its price range, phone number and hotel type.\nChunk 4: Do you have any restaurants near there with Chinese food?\nChunk 5: I would like somewhere moderately priced Yes please.\nChunk 6: Can you book a for a table of 5 at 17:30 on Monday?\nChunk 7: No.\nChunk 8: I am all set thank you.", "input_token_count": 74, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, intent: context_update. Next, the goal is search; amenities: parking. Next, the topic is hotel; the goal is request info; hotel type: hotel; requested information: phone. Next, the topic is restaurant; cuisine: chinese. Next, price: moderate; acceptance: selected_option. Next, the goal is booking; time: 5; day: monday. Next, the goal is modify constraint. Finally, intent: context_update. In summary, The overall topic is restaurant. the goal is modify constraint.. intent: context_update.; amenities: parking.; hotel type: hotel; requested information: phone.; cuisine: chinese.; price: moderate; acceptance: selected_option.; time: 5; day: monday..", "trace": "C1 intent=context_update. C2 goal=search; amenities+=parking. C3 domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone. C4 domain=restaurant; cuisine+=chinese. C5 price+=moderate; acceptance=selected_option. C6 goal=booking; time+=5, 17:30; day+=monday. C7 goal=modify_constraint. C8 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I don't have a preference.", "streaming_reasoning": "Initially, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "I will need parking too.", "streaming_reasoning": "As more information arrives, the goal is search; amenities: parking..", "trace": "goal=search; amenities+=parking."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "getme its price range, phone number and hotel type.", "streaming_reasoning": "As more information arrives, the topic is hotel; the goal is request info; hotel type: hotel; requested information: phone..", "trace": "domain=hotel; goal=request_info; hotel_type+=hotel; requested_info+=phone."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Do you have any restaurants near there with Chinese food?", "streaming_reasoning": "As more information arrives, the topic is restaurant; cuisine: chinese..", "trace": "domain=restaurant; cuisine+=chinese."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I would like somewhere moderately priced Yes please.", "streaming_reasoning": "As more information arrives, price: moderate; acceptance: selected_option..", "trace": "price+=moderate; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Can you book a for a table of 5 at 17:30 on Monday?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 5; day: monday..", "trace": "goal=booking; time+=5, 17:30; day+=monday."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I am all set thank you.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: cuisine is chinese; price is moderate; amenities is parking; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the phone once I find the matching option.", "deep_reasoning_trace": "Need domain=hotel, restaurant; goal=search, request_info, booking; food=chinese; price=moderate; amenities=parking; requested_info=phone; when=monday, 5, 17:30."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003703", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I honestly think it looks great.\nChunk 2: Thanks.\nChunk 3: I'm glad that I did a good job.\nChunk 4: How much is it for my hair?\nChunk 5: Just give me $ 55.\nChunk 6: Thanks for doing such a good job.", "streaming_reasoning": "C1 casual_comment=honestly, think. C2 [SKIP: thanks_only]. C3 casual_comment=i'm, glad. C4 question=true. C5 casual_comment=give. C6 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I honestly think it looks great.\nChunk 2: Thanks.\nChunk 3: I'm glad that I did a good job.\nChunk 4: How much is it for my hair?\nChunk 5: Just give me $ 55.\nChunk 6: Thanks for doing such a good job."}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=honestly, think. C2 [SKIP: thanks_only]. C3 casual_comment=i'm, glad. C4 question=true. C5 casual_comment=give. C6 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I honestly think it looks great.\nChunk 2: Thanks.\nChunk 3: I'm glad that I did a good job.\nChunk 4: How much is it for my hair?\nChunk 5: Just give me $ 55.\nChunk 6: Thanks for doing such a good job.", "input_token_count": 45, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on honestly. Next, the user comments on i'm. Next, the input provides additional context about question=true. Finally, the user comments on give.  Some chunks were skipped because they contained thanks_only.", "trace": "C1 casual_comment=honestly, think. C2 [SKIP: thanks_only]. C3 casual_comment=i'm, glad. C4 question=true. C5 casual_comment=give. C6 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I honestly think it looks great.", "streaming_reasoning": "Initially, the user comments on honestly.", "trace": "casual_comment=honestly, think."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Thanks.", "streaming_reasoning": "The content at C2 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I'm glad that I did a good job.", "streaming_reasoning": "As more information arrives, the user comments on i'm.", "trace": "casual_comment=i'm, glad."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "How much is it for my hair?", "streaming_reasoning": "As more information arrives, additional context is provided.", "trace": "question=true."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Just give me $ 55.", "streaming_reasoning": "As more information arrives, the user comments on give..", "trace": "casual_comment=give."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Thanks for doing such a good job.", "streaming_reasoning": "The content at C6 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002977", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please give me information on the star rating and their number.\nChunk 2: Can you also provide me with their address please?\nChunk 3: Yes, I am looking for a theatre.\nChunk 4: Possibly in the centre.\nChunk 5: Perfect, could I have the phone number please?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 05:45.\nChunk 8: Please make a booking.\nChunk 9: No,that is all Thank you!", "streaming_reasoning": "C1 goal=request_info. C2 requested_info+=address. C3 domain=attraction; goal=search; acceptance=selected_option. C4 area+=centre. C5 requested_info+=phone; acceptance=selected_option. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 time+=05:45. C8 goal=booking. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, hotel; goal=request_info, search, booking; area=centre; destination=find a hotel; requested_info=address, phone; when=05:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Please give me information on the star rating and their number.\nChunk 2: Can you also provide me with their address please?\nChunk 3: Yes, I am looking for a theatre.\nChunk 4: Possibly in the centre.\nChunk 5: Perfect, could I have the phone number please?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 05:45.\nChunk 8: Please make a booking.\nChunk 9: No,that is all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 requested_info+=address. C3 domain=attraction; goal=search; acceptance=selected_option. C4 area+=centre. C5 requested_info+=phone; acceptance=selected_option. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 time+=05:45. C8 goal=booking. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, hotel; goal=request_info, search, booking; area=centre; destination=find a hotel; requested_info=address, phone; when=05:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Please give me information on the star rating and their number.\nChunk 2: Can you also provide me with their address please?\nChunk 3: Yes, I am looking for a theatre.\nChunk 4: Possibly in the centre.\nChunk 5: Perfect, could I have the phone number please?\nChunk 6: I want to find a hotel.\nChunk 7: The time is 05:45.\nChunk 8: Please make a booking.\nChunk 9: No,that is all Thank you!", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, requested information: address. Next, the topic is attraction; the goal is search; acceptance: selected_option. Next, area: centre. Next, requested information: phone; acceptance: selected_option. Next, the topic is hotel; hotel type: hotel; destination: find a hotel. Next, time: 05:45. Finally, the goal is booking.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is booking.. requested information: address., phone; acceptance: selected_option.; area: centre.; hotel type: hotel; destination: find a hotel.; time: 05:45..", "trace": "C1 goal=request_info. C2 requested_info+=address. C3 domain=attraction; goal=search; acceptance=selected_option. C4 area+=centre. C5 requested_info+=phone; acceptance=selected_option. C6 domain=hotel; hotel_type+=hotel; destination+=find a hotel. C7 time+=05:45. C8 goal=booking. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Please give me information on the star rating and their number.", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you also provide me with their address please?", "streaming_reasoning": "As more information arrives, requested information: address..", "trace": "requested_info+=address."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Yes, I am looking for a theatre.", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is search; acceptance: selected_option..", "trace": "domain=attraction; goal=search; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Possibly in the centre.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Perfect, could I have the phone number please?", "streaming_reasoning": "As more information arrives, requested information: phone; acceptance: selected_option..", "trace": "requested_info+=phone; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I want to find a hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel; destination: find a hotel..", "trace": "domain=hotel; hotel_type+=hotel; destination+=find a hotel."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "The time is 05:45.", "streaming_reasoning": "As more information arrives, time: 05:45..", "trace": "time+=05:45."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "No,that is all Thank you!", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: area is centre; destination is find a hotel; requested information is address; timing is 05:45. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, hotel; goal=request_info, search, booking; area=centre; destination=find a hotel; requested_info=address, phone; when=05:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002978", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i am looking for information about cineworld cinema.\nChunk 2: Could i get the phone number please?\nChunk 3: I want to find a moderate hotel.\nChunk 4: I also need the price.\nChunk 5: I need a hotel located in the town centre.\nChunk 6: Yes.\nChunk 7: Book it for Monday.\nChunk 8: 5 nights and 6 people.\nChunk 9: thanks that is all.", "streaming_reasoning": "C1 goal=search. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; price+=moderate; hotel_type+=hotel; destination+=find a moderate hotel. C4 requested_info+=price. C5 area+=centre. C6 [SKIP: acknowledgement_only]. C7 goal=booking; day+=monday. C8 party_size+=6 people; stay_length+=5 nights. C9 [SKIP: closing_only].", "deep_reasoning": "Need domain=hotel; goal=search, request_info, booking; area=centre; price=moderate; party_size=6 people; stay_length=5 nights; destination=find a moderate hotel; requested_info=phone, price; when=monday; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: i am looking for information about cineworld cinema.\nChunk 2: Could i get the phone number please?\nChunk 3: I want to find a moderate hotel.\nChunk 4: I also need the price.\nChunk 5: I need a hotel located in the town centre.\nChunk 6: Yes.\nChunk 7: Book it for Monday.\nChunk 8: 5 nights and 6 people.\nChunk 9: thanks that is all."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; price+=moderate; hotel_type+=hotel; destination+=find a moderate hotel. C4 requested_info+=price. C5 area+=centre. C6 [SKIP: acknowledgement_only]. C7 goal=booking; day+=monday. C8 party_size+=6 people; stay_length+=5 nights. C9 [SKIP: closing_only].\n\nDeep reasoning: Need domain=hotel; goal=search, request_info, booking; area=centre; price=moderate; party_size=6 people; stay_length=5 nights; destination=find a moderate hotel; requested_info=phone, price; when=monday; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: i am looking for information about cineworld cinema.\nChunk 2: Could i get the phone number please?\nChunk 3: I want to find a moderate hotel.\nChunk 4: I also need the price.\nChunk 5: I need a hotel located in the town centre.\nChunk 6: Yes.\nChunk 7: Book it for Monday.\nChunk 8: 5 nights and 6 people.\nChunk 9: thanks that is all.", "input_token_count": 68, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, the goal is request info; requested information: phone. Next, the topic is hotel; price: moderate; hotel type: hotel; destination: find a moderate hotel. Next, requested information: price. Next, area: centre. Next, the goal is booking; day: monday. Finally, party size: 6 people; stay length: 5 nights.  Some chunks were skipped because they contained acknowledgement_only or closing_only. In summary, The overall topic is hotel. the goal is booking. requested information: phone., price.; price: moderate; hotel type: hotel; destination: find a moderate hotel.; area: centre.; day: monday.; party size: 6 people; stay length: 5 nights..", "trace": "C1 goal=search. C2 goal=request_info; requested_info+=phone. C3 domain=hotel; price+=moderate; hotel_type+=hotel; destination+=find a moderate hotel. C4 requested_info+=price. C5 area+=centre. C6 [SKIP: acknowledgement_only]. C7 goal=booking; day+=monday. C8 party_size+=6 people; stay_length+=5 nights. C9 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "i am looking for information about cineworld cinema.", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Could i get the phone number please?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: phone..", "trace": "goal=request_info; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I want to find a moderate hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; price: moderate; hotel type: hotel; destination: find a moderate hotel..", "trace": "domain=hotel; price+=moderate; hotel_type+=hotel; destination+=find a moderate hotel."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I also need the price.", "streaming_reasoning": "As more information arrives, requested information: price..", "trace": "requested_info+=price."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I need a hotel located in the town centre.", "streaming_reasoning": "As more information arrives, area: centre..", "trace": "area+=centre."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Yes.", "streaming_reasoning": "The content at C6 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Book it for Monday.", "streaming_reasoning": "As more information arrives, the goal is booking; day: monday..", "trace": "goal=booking; day+=monday."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "5 nights and 6 people.", "streaming_reasoning": "As more information arrives, party size: 6 people; stay length: 5 nights..", "trace": "party_size+=6 people; stay_length+=5 nights."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "thanks that is all.", "streaming_reasoning": "The content at C9 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a hotel task with the goal of search. Key information: area is centre; price is moderate; party size is 6 people; stay length is 5 nights; destination is find a moderate hotel; requested information is phone; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=hotel; goal=search, request_info, booking; area=centre; price=moderate; party_size=6 people; stay_length=5 nights; destination=find a moderate hotel; requested_info=phone, price; when=monday; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002979", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you find me an attraction in the centre?\nChunk 2: Not looking for anything specific.\nChunk 3: Maybe a college or museum if you can give me the address and entrance fee Thank you goodbye.", "streaming_reasoning": "C1 domain=attraction; goal=search; area+=centre. C2 goal=modify_constraint. C3 goal=request_info; requested_info+=address, entrance_fee.", "deep_reasoning": "Need domain=attraction; goal=search, request_info; area=centre; requested_info=address, entrance_fee.", "answer": "I can help with that and include the address, entrance fee once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Can you find me an attraction in the centre?\nChunk 2: Not looking for anything specific.\nChunk 3: Maybe a college or museum if you can give me the address and entrance fee Thank you goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=attraction; goal=search; area+=centre. C2 goal=modify_constraint. C3 goal=request_info; requested_info+=address, entrance_fee.\n\nDeep reasoning: Need domain=attraction; goal=search, request_info; area=centre; requested_info=address, entrance_fee.\n\nAnswer: I can help with that and include the address, entrance fee once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Can you find me an attraction in the centre?\nChunk 2: Not looking for anything specific.\nChunk 3: Maybe a college or museum if you can give me the address and entrance fee Thank you goodbye.", "input_token_count": 38, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is attraction; the goal is search; area: centre. Next, the goal is modify constraint. Finally, the goal is request info; requested information: address. In summary, The overall topic is attraction. the goal is request info. area: centre.; requested information: address.", "trace": "C1 domain=attraction; goal=search; area+=centre. C2 goal=modify_constraint. C3 goal=request_info; requested_info+=address, entrance_fee.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Can you find me an attraction in the centre?", "streaming_reasoning": "Initially, the topic is attraction; the goal is search; area: centre..", "trace": "domain=attraction; goal=search; area+=centre."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Not looking for anything specific.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Maybe a college or museum if you can give me the address and entrance fee Thank you goodbye.", "streaming_reasoning": "Finally, the goal is request info; requested information: address.", "trace": "goal=request_info; requested_info+=address, entrance_fee."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: area is centre; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the address, entrance fee once I find the matching option.", "deep_reasoning_trace": "Need domain=attraction; goal=search, request_info; area=centre; requested_info=address, entrance_fee."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002980", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What museums can I visit in town That sounds great.\nChunk 2: Can you give me the area and phone number for that museum?\nChunk 3: I also need a train that is leaving on Thursday going to Cambridge.\nChunk 4: Yes as long as it arrives by 16:30 and I will be departing from Stevenage.\nChunk 5: ok, yeah get me a ticket.\nChunk 6: That will be all Thank you!", "streaming_reasoning": "C1 goal=request_info. C2 domain=attraction; requested_info+=phone. C3 domain=train; goal=search; day+=thursday; destination+=cambridge. C4 time+=16:30; departure+=stevenage; acceptance=selected_option. C5 intent=context_update. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, train; goal=request_info, search; destination=cambridge; departure=stevenage; requested_info=phone; when=thursday, 16:30; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: What museums can I visit in town That sounds great.\nChunk 2: Can you give me the area and phone number for that museum?\nChunk 3: I also need a train that is leaving on Thursday going to Cambridge.\nChunk 4: Yes as long as it arrives by 16:30 and I will be departing from Stevenage.\nChunk 5: ok, yeah get me a ticket.\nChunk 6: That will be all Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=request_info. C2 domain=attraction; requested_info+=phone. C3 domain=train; goal=search; day+=thursday; destination+=cambridge. C4 time+=16:30; departure+=stevenage; acceptance=selected_option. C5 intent=context_update. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, train; goal=request_info, search; destination=cambridge; departure=stevenage; requested_info=phone; when=thursday, 16:30; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: What museums can I visit in town That sounds great.\nChunk 2: Can you give me the area and phone number for that museum?\nChunk 3: I also need a train that is leaving on Thursday going to Cambridge.\nChunk 4: Yes as long as it arrives by 16:30 and I will be departing from Stevenage.\nChunk 5: ok, yeah get me a ticket.\nChunk 6: That will be all Thank you!", "input_token_count": 75, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is request info. Next, the topic is attraction; requested information: phone. Next, the topic is train; the goal is search; day: thursday; destination: cambridge. Next, time: 16:30; departure point: stevenage; acceptance: selected_option. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is search. requested information: phone.; day: thursday; destination: cambridge.; time: 16:30; departure point: stevenage; acceptance: selected_option.; intent: context_update..", "trace": "C1 goal=request_info. C2 domain=attraction; requested_info+=phone. C3 domain=train; goal=search; day+=thursday; destination+=cambridge. C4 time+=16:30; departure+=stevenage; acceptance=selected_option. C5 intent=context_update. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "What museums can I visit in town That sounds great.", "streaming_reasoning": "Initially, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you give me the area and phone number for that museum?", "streaming_reasoning": "As more information arrives, the topic is attraction; requested information: phone..", "trace": "domain=attraction; requested_info+=phone."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I also need a train that is leaving on Thursday going to Cambridge.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is search; day: thursday; destination: cambridge..", "trace": "domain=train; goal=search; day+=thursday; destination+=cambridge."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Yes as long as it arrives by 16:30 and I will be departing from Stevenage.", "streaming_reasoning": "As more information arrives, time: 16:30; departure point: stevenage; acceptance: selected_option..", "trace": "time+=16:30; departure+=stevenage; acceptance=selected_option."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "ok, yeah get me a ticket.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That will be all Thank you!", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of request info. Key information: destination is cambridge; departure point is stevenage; requested information is phone; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, train; goal=request_info, search; destination=cambridge; departure=stevenage; requested_info=phone; when=thursday, 16:30; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_daily_dialogue_003705", "domain": "daily_dialogue", "source_dataset": "pixelsandpointers/better_daily_dialog", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: There won't be anyone there to appreciate how cute you are Who cares!\nChunk 2: Well, the smart guys get there early.\nChunk 3: That's the kind of guy I want to meet.\nChunk 4: Let's go!\nChunk 5: If you are going to husband hunting in a bikini, then I want to wear one, too.\nChunk 6: Ok, you could borrow one of mine.\nChunk 7: Thanks, how about the green and black one?", "streaming_reasoning": "C1 casual_comment=won't, anyone. C2 casual_comment=smart, guys. C3 casual_comment=that's, kind. C4 [SKIP: low_information]. C5 casual_comment=going, husband. C6 casual_comment=borrow, one. C7 [SKIP: thanks_only].", "deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: There won't be anyone there to appreciate how cute you are Who cares!\nChunk 2: Well, the smart guys get there early.\nChunk 3: That's the kind of guy I want to meet.\nChunk 4: Let's go!\nChunk 5: If you are going to husband hunting in a bikini, then I want to wear one, too.\nChunk 6: Ok, you could borrow one of mine.\nChunk 7: Thanks, how about the green and black one?"}, {"role": "assistant", "content": "Streaming reasoning: C1 casual_comment=won't, anyone. C2 casual_comment=smart, guys. C3 casual_comment=that's, kind. C4 [SKIP: low_information]. C5 casual_comment=going, husband. C6 casual_comment=borrow, one. C7 [SKIP: thanks_only].\n\nDeep reasoning: Conversation is closing; answer politely without adding a new task.\n\nAnswer: Sounds good. Take care, and see you next time."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "social_communication", "subcategory": "message_reply", "intent_type": "dialogue_reply", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: There won't be anyone there to appreciate how cute you are Who cares!\nChunk 2: Well, the smart guys get there early.\nChunk 3: That's the kind of guy I want to meet.\nChunk 4: Let's go!\nChunk 5: If you are going to husband hunting in a bikini, then I want to wear one, too.\nChunk 6: Ok, you could borrow one of mine.\nChunk 7: Thanks, how about the green and black one?", "input_token_count": 77, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the user comments on won't. Next, the user comments on smart. Next, the user comments on that's. Next, the user comments on going. Finally, the user comments on borrow.  Some chunks were skipped because they contained low_information or thanks_only.", "trace": "C1 casual_comment=won't, anyone. C2 casual_comment=smart, guys. C3 casual_comment=that's, kind. C4 [SKIP: low_information]. C5 casual_comment=going, husband. C6 casual_comment=borrow, one. C7 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "There won't be anyone there to appreciate how cute you are Who cares!", "streaming_reasoning": "Initially, the user comments on won't.", "trace": "casual_comment=won't, anyone."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Well, the smart guys get there early.", "streaming_reasoning": "As more information arrives, the user comments on smart.", "trace": "casual_comment=smart, guys."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "That's the kind of guy I want to meet.", "streaming_reasoning": "As more information arrives, the user comments on that's.", "trace": "casual_comment=that's, kind."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Let's go!", "streaming_reasoning": "The content at C4 was skipped (low_information).", "trace": "[SKIP: low_information]."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "If you are going to husband hunting in a bikini, then I want to wear one, too.", "streaming_reasoning": "As more information arrives, the user comments on going.", "trace": "casual_comment=going, husband."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Ok, you could borrow one of mine.", "streaming_reasoning": "As more information arrives, the user comments on borrow.", "trace": "casual_comment=borrow, one."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Thanks, how about the green and black one?", "streaming_reasoning": "The content at C7 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Conversation is closing; answer politely without adding a new task.", "answer": "Sounds good. Take care, and see you next time."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pixelsandpointers/better_daily_dialog", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002981", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am injured and need a nearby hospital.\nChunk 2: No.\nChunk 3: Thank you so much.", "streaming_reasoning": "C1 domain=hospital; goal=search. C2 [SKIP: acknowledgement_only]. C3 [SKIP: thanks_only].", "deep_reasoning": "Need domain=hospital; goal=search; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am injured and need a nearby hospital.\nChunk 2: No.\nChunk 3: Thank you so much."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=hospital; goal=search. C2 [SKIP: acknowledgement_only]. C3 [SKIP: thanks_only].\n\nDeep reasoning: Need domain=hospital; goal=search; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am injured and need a nearby hospital.\nChunk 2: No.\nChunk 3: Thank you so much.", "input_token_count": 19, "length_bucket": "very_short"}, "streaming": {"streaming_reasoning": "Initially, the topic is hospital; the goal is search.  Some chunks were skipped because they contained acknowledgement_only or thanks_only. In summary, The overall topic is hospital. the goal is search..", "trace": "C1 domain=hospital; goal=search. C2 [SKIP: acknowledgement_only]. C3 [SKIP: thanks_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am injured and need a nearby hospital.", "streaming_reasoning": "Initially, the topic is hospital; the goal is search..", "trace": "domain=hospital; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "No.", "streaming_reasoning": "The content at C2 was skipped (acknowledgement_only).", "trace": "[SKIP: acknowledgement_only]."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Thank you so much.", "streaming_reasoning": "The content at C3 was skipped (thanks_only).", "trace": "[SKIP: thanks_only]."}]}, "output": {"deep_reasoning": "Need domain=hospital; goal=search; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002982", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for some information about the Cambridge Corn Exchange.\nChunk 2: Yes, can I get the attraction type, the phone number, and the address please?\nChunk 3: This sounds like it would be a great place Thank you!\nChunk 4: I'm also looking for information on the Gonville Hotel.\nChunk 5: Yes please, do they offer free wifi and parking Thank you.\nChunk 6: That is all the information I need at this time.", "streaming_reasoning": "C1 goal=search. C2 domain=attraction; goal=request_info; requested_info+=address, phone; acceptance=selected_option. C3 intent=context_update. C4 domain=hotel; hotel_type+=hotel. C5 amenities+=parking, wifi; acceptance=selected_option. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=attraction, hotel; goal=search, request_info; amenities=parking, wifi; requested_info=address, phone; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Hi, I'm looking for some information about the Cambridge Corn Exchange.\nChunk 2: Yes, can I get the attraction type, the phone number, and the address please?\nChunk 3: This sounds like it would be a great place Thank you!\nChunk 4: I'm also looking for information on the Gonville Hotel.\nChunk 5: Yes please, do they offer free wifi and parking Thank you.\nChunk 6: That is all the information I need at this time."}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=search. C2 domain=attraction; goal=request_info; requested_info+=address, phone; acceptance=selected_option. C3 intent=context_update. C4 domain=hotel; hotel_type+=hotel. C5 amenities+=parking, wifi; acceptance=selected_option. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=attraction, hotel; goal=search, request_info; amenities=parking, wifi; requested_info=address, phone; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Hi, I'm looking for some information about the Cambridge Corn Exchange.\nChunk 2: Yes, can I get the attraction type, the phone number, and the address please?\nChunk 3: This sounds like it would be a great place Thank you!\nChunk 4: I'm also looking for information on the Gonville Hotel.\nChunk 5: Yes please, do they offer free wifi and parking Thank you.\nChunk 6: That is all the information I need at this time.", "input_token_count": 78, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is search. Next, the topic is attraction; the goal is request info; requested information: address; acceptance: selected_option. Next, intent: context_update. Next, the topic is hotel; hotel type: hotel. Finally, amenities: parking; acceptance: selected_option.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is hotel. the goal is request info. requested information: address; acceptance: selected_option.; intent: context_update.; hotel type: hotel.; amenities: parking.", "trace": "C1 goal=search. C2 domain=attraction; goal=request_info; requested_info+=address, phone; acceptance=selected_option. C3 intent=context_update. C4 domain=hotel; hotel_type+=hotel. C5 amenities+=parking, wifi; acceptance=selected_option. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Hi, I'm looking for some information about the Cambridge Corn Exchange.", "streaming_reasoning": "Initially, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Yes, can I get the attraction type, the phone number, and the address please?", "streaming_reasoning": "As more information arrives, the topic is attraction; the goal is request info; requested information: address; acceptance: selected_option..", "trace": "domain=attraction; goal=request_info; requested_info+=address, phone; acceptance=selected_option."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "This sounds like it would be a great place Thank you!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm also looking for information on the Gonville Hotel.", "streaming_reasoning": "As more information arrives, the topic is hotel; hotel type: hotel..", "trace": "domain=hotel; hotel_type+=hotel."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes please, do they offer free wifi and parking Thank you.", "streaming_reasoning": "As more information arrives, amenities: parking; acceptance: selected_option..", "trace": "amenities+=parking, wifi; acceptance=selected_option."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "That is all the information I need at this time.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a attraction task with the goal of search. Key information: amenities is parking; requested information is address. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=attraction, hotel; goal=search, request_info; amenities=parking, wifi; requested_info=address, phone; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002983", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I've heard about Royal Spice, is it a very good restaurant?\nChunk 2: What is the price like?\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 11:15.\nChunk 5: Please make a booking.\nChunk 6: No.\nChunk 7: I am all set Thanks Goodbye.", "streaming_reasoning": "C1 domain=restaurant. C2 goal=request_info; requested_info+=price. C3 party_size+=6 people. C4 time+=6, 11:15; day+=monday. C5 goal=booking. C6 goal=modify_constraint. C7 intent=context_update.", "deep_reasoning": "Need domain=restaurant; goal=request_info, booking; party_size=6 people; requested_info=price; when=monday, 6, 11:15.", "answer": "I can help with that and include the price once I find the matching option.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I've heard about Royal Spice, is it a very good restaurant?\nChunk 2: What is the price like?\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 11:15.\nChunk 5: Please make a booking.\nChunk 6: No.\nChunk 7: I am all set Thanks Goodbye."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant. C2 goal=request_info; requested_info+=price. C3 party_size+=6 people. C4 time+=6, 11:15; day+=monday. C5 goal=booking. C6 goal=modify_constraint. C7 intent=context_update.\n\nDeep reasoning: Need domain=restaurant; goal=request_info, booking; party_size=6 people; requested_info=price; when=monday, 6, 11:15.\n\nAnswer: I can help with that and include the price once I find the matching option."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I've heard about Royal Spice, is it a very good restaurant?\nChunk 2: What is the price like?\nChunk 3: It is for 6 people.\nChunk 4: The time is monday, 6, 11:15.\nChunk 5: Please make a booking.\nChunk 6: No.\nChunk 7: I am all set Thanks Goodbye.", "input_token_count": 53, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant. Next, the goal is request info; requested information: price. Next, party size: 6 people. Next, time: 6; day: monday. Next, the goal is booking. Next, the goal is modify constraint. Finally, intent: context_update. In summary, The overall topic is restaurant.. the goal is modify constraint.. requested information: price.; party size: 6 people.; time: 6; day: monday.; intent: context_update..", "trace": "C1 domain=restaurant. C2 goal=request_info; requested_info+=price. C3 party_size+=6 people. C4 time+=6, 11:15; day+=monday. C5 goal=booking. C6 goal=modify_constraint. C7 intent=context_update.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I've heard about Royal Spice, is it a very good restaurant?", "streaming_reasoning": "Initially, the topic is restaurant..", "trace": "domain=restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "What is the price like?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: price..", "trace": "goal=request_info; requested_info+=price."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "It is for 6 people.", "streaming_reasoning": "As more information arrives, party size: 6 people..", "trace": "party_size+=6 people."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "The time is monday, 6, 11:15.", "streaming_reasoning": "As more information arrives, time: 6; day: monday..", "trace": "time+=6, 11:15; day+=monday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Please make a booking.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "No.", "streaming_reasoning": "As more information arrives, the goal is modify constraint..", "trace": "goal=modify_constraint."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "I am all set Thanks Goodbye.", "streaming_reasoning": "Finally, intent: context_update..", "trace": "intent=context_update."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of request info. Key information: party size is 6 people; requested information is price; timing is monday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "I can help with that and include the price once I find the matching option.", "deep_reasoning_trace": "Need domain=restaurant; goal=request_info, booking; party_size=6 people; requested_info=price; when=monday, 6, 11:15."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002984", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm are looking for a train.\nChunk 2: The train should leave on friday and should go to norwich.\nChunk 3: I will be leaving from Cambridge.\nChunk 4: I need to arrive by 11:15 Ok, thank you.\nChunk 5: Can you also give me the travel time?\nChunk 6: What is the train ID for the one you booked?\nChunk 7: No, that's all I need Thank you.", "streaming_reasoning": "C1 domain=train; goal=search. C2 day+=friday; destination+=norwich. C3 intent=context_update. C4 time+=11:15; destination+=arrive by 11:15 ok. C5 goal=request_info; requested_info+=travel_time. C6 goal=request_info. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train; goal=search, request_info; destination=norwich, arrive by 11:15 ok; requested_info=travel_time; when=friday, 11:15; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I'm are looking for a train.\nChunk 2: The train should leave on friday and should go to norwich.\nChunk 3: I will be leaving from Cambridge.\nChunk 4: I need to arrive by 11:15 Ok, thank you.\nChunk 5: Can you also give me the travel time?\nChunk 6: What is the train ID for the one you booked?\nChunk 7: No, that's all I need Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=train; goal=search. C2 day+=friday; destination+=norwich. C3 intent=context_update. C4 time+=11:15; destination+=arrive by 11:15 ok. C5 goal=request_info; requested_info+=travel_time. C6 goal=request_info. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train; goal=search, request_info; destination=norwich, arrive by 11:15 ok; requested_info=travel_time; when=friday, 11:15; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I'm are looking for a train.\nChunk 2: The train should leave on friday and should go to norwich.\nChunk 3: I will be leaving from Cambridge.\nChunk 4: I need to arrive by 11:15 Ok, thank you.\nChunk 5: Can you also give me the travel time?\nChunk 6: What is the train ID for the one you booked?\nChunk 7: No, that's all I need Thank you.", "input_token_count": 72, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is train; the goal is search. Next, day: friday; destination: norwich. Next, intent: context_update. Next, time: 11:15; destination: arrive by 11:15 ok. Next, the goal is request info; requested information: travel_time. Finally, the goal is request info.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is train. the goal is request info.. day: friday; destination: norwich., arrive by 11:15 ok.; intent: context_update.; time: 11:15; requested information: travel_time..", "trace": "C1 domain=train; goal=search. C2 day+=friday; destination+=norwich. C3 intent=context_update. C4 time+=11:15; destination+=arrive by 11:15 ok. C5 goal=request_info; requested_info+=travel_time. C6 goal=request_info. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I'm are looking for a train.", "streaming_reasoning": "Initially, the topic is train; the goal is search..", "trace": "domain=train; goal=search."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "The train should leave on friday and should go to norwich.", "streaming_reasoning": "As more information arrives, day: friday; destination: norwich..", "trace": "day+=friday; destination+=norwich."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I will be leaving from Cambridge.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I need to arrive by 11:15 Ok, thank you.", "streaming_reasoning": "As more information arrives, time: 11:15; destination: arrive by 11:15 ok..", "trace": "time+=11:15; destination+=arrive by 11:15 ok."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you also give me the travel time?", "streaming_reasoning": "As more information arrives, the goal is request info; requested information: travel_time..", "trace": "goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "What is the train ID for the one you booked?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No, that's all I need Thank you.", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of search. Key information: destination is norwich; requested information is travel_time; timing is friday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train; goal=search, request_info; destination=norwich, arrive by 11:15 ok; requested_info=travel_time; when=friday, 11:15; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_how_to_guidance_000622", "domain": "how_to_guidance", "source_dataset": "b-mc2/wikihow_lists", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Bypass Parental Controls on a Mac.\nChunk 2: Click the Apple icon in the menu bar in the upper-left corner.\nChunk 3: Click the Parental Controls icon.\nChunk 4: Click the lock icon in the lower-left corner of the Parental Controls window.\nChunk 5: Enter the admin username and password.\nChunk 6: Select a restricted account to the left.", "streaming_reasoning": "C1 task=bypass_parental_controls_on. C2 step=click_the_apple_icon. C3 [SKIP: repeated_information]. C4 step=click_the_lock_icon. C5 step=enter_the_admin_username. C6 step=select_a_restricted_account.", "deep_reasoning": "Procedure for Bypass Parental Controls on a Mac: Click the Apple icon in the menu bar in the, Click the lock icon in the lower-left corner of the, Enter the admin username and password, Select a restricted account to the left.", "answer": "For Bypass Parental Controls on a Mac, follow the steps in order: Click the Apple icon in the menu bar in the, Click the lock icon in the lower-left corner of the, Enter the admin username and password, Select a restricted account to the left.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Task: Bypass Parental Controls on a Mac.\nChunk 2: Click the Apple icon in the menu bar in the upper-left corner.\nChunk 3: Click the Parental Controls icon.\nChunk 4: Click the lock icon in the lower-left corner of the Parental Controls window.\nChunk 5: Enter the admin username and password.\nChunk 6: Select a restricted account to the left."}, {"role": "assistant", "content": "Streaming reasoning: C1 task=bypass_parental_controls_on. C2 step=click_the_apple_icon. C3 [SKIP: repeated_information]. C4 step=click_the_lock_icon. C5 step=enter_the_admin_username. C6 step=select_a_restricted_account.\n\nDeep reasoning: Procedure for Bypass Parental Controls on a Mac: Click the Apple icon in the menu bar in the, Click the lock icon in the lower-left corner of the, Enter the admin username and password, Select a restricted account to the left.\n\nAnswer: For Bypass Parental Controls on a Mac, follow the steps in order: Click the Apple icon in the menu bar in the, Click the lock icon in the lower-left corner of the, Enter the admin username and password, Select a restricted account to the left."}], "language": "en", "split": "eval", "quality_flags": [], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "information_extraction", "subcategory": "action_items", "intent_type": "instruction_following", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Task: Bypass Parental Controls on a Mac.\nChunk 2: Click the Apple icon in the menu bar in the upper-left corner.\nChunk 3: Click the Parental Controls icon.\nChunk 4: Click the lock icon in the lower-left corner of the Parental Controls window.\nChunk 5: Enter the admin username and password.\nChunk 6: Select a restricted account to the left.", "input_token_count": 62, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, task: bypass_parental_controls_on. Next, step: click_the_apple_icon. Next, step: click_the_lock_icon. Next, step: enter_the_admin_username. Finally, step: select_a_restricted_account.  Some chunks were skipped because they contained repeated_information. In summary, task: bypass_parental_controls_on.; step: click_the_apple_icon., click_the_lock_icon., enter_the_admin_username., select_a_restricted_account..", "trace": "C1 task=bypass_parental_controls_on. C2 step=click_the_apple_icon. C3 [SKIP: repeated_information]. C4 step=click_the_lock_icon. C5 step=enter_the_admin_username. C6 step=select_a_restricted_account.", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Task: Bypass Parental Controls on a Mac.", "streaming_reasoning": "Initially, task: bypass_parental_controls_on..", "trace": "task=bypass_parental_controls_on."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Click the Apple icon in the menu bar in the upper-left corner.", "streaming_reasoning": "As more information arrives, step: click_the_apple_icon..", "trace": "step=click_the_apple_icon."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Click the Parental Controls icon.", "streaming_reasoning": "The content at C3 was skipped (repeated_information).", "trace": "[SKIP: repeated_information]."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Click the lock icon in the lower-left corner of the Parental Controls window.", "streaming_reasoning": "As more information arrives, step: click_the_lock_icon..", "trace": "step=click_the_lock_icon."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Enter the admin username and password.", "streaming_reasoning": "As more information arrives, step: enter_the_admin_username..", "trace": "step=enter_the_admin_username."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Select a restricted account to the left.", "streaming_reasoning": "Finally, step: select_a_restricted_account..", "trace": "step=select_a_restricted_account."}]}, "output": {"deep_reasoning": "Procedure for Bypass Parental Controls on a Mac: Click the Apple icon in the menu bar in the, Click the lock icon in the lower-left corner of the, Enter the admin username and password, Select a restricted account to the left.", "answer": "For Bypass Parental Controls on a Mac, follow the steps in order: Click the Apple icon in the menu bar in the, Click the lock icon in the lower-left corner of the, Enter the admin username and password, Select a restricted account to the left."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": []}, "metadata": {"source_dataset": "b-mc2/wikihow_lists", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002985", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: It is for 5 people.\nChunk 3: The time is thursday, 19:00.\nChunk 4: Please make a booking Thank you.\nChunk 5: I also want to go to a museum.\nChunk 6: It can be in any area.\nChunk 7: Could you suggest one and give me some information about it, please?\nChunk 8: I also need a taxi between the two places.\nChunk 9: I need to arrive at the restaurant by the booking time Great!\nChunk 10: That is all I needed Thank you.", "streaming_reasoning": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 party_size+=5 people. C3 time+=19:00; day+=thursday. C4 goal=booking. C5 domain=attraction; destination+=go to a museum. C6 area+=any. C7 goal=request_info. C8 domain=taxi. C9 intent=context_update. C10 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant, attraction, taxi; goal=search, booking, recommendation, request_info; area=any; party_size=5 people; destination=find a restaurant, go to a museum; when=thursday, 19:00; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I want to find a restaurant.\nChunk 2: It is for 5 people.\nChunk 3: The time is thursday, 19:00.\nChunk 4: Please make a booking Thank you.\nChunk 5: I also want to go to a museum.\nChunk 6: It can be in any area.\nChunk 7: Could you suggest one and give me some information about it, please?\nChunk 8: I also need a taxi between the two places.\nChunk 9: I need to arrive at the restaurant by the booking time Great!\nChunk 10: That is all I needed Thank you."}, {"role": "assistant", "content": "Streaming reasoning: C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 party_size+=5 people. C3 time+=19:00; day+=thursday. C4 goal=booking. C5 domain=attraction; destination+=go to a museum. C6 area+=any. C7 goal=request_info. C8 domain=taxi. C9 intent=context_update. C10 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant, attraction, taxi; goal=search, booking, recommendation, request_info; area=any; party_size=5 people; destination=find a restaurant, go to a museum; when=thursday, 19:00; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I want to find a restaurant.\nChunk 2: It is for 5 people.\nChunk 3: The time is thursday, 19:00.\nChunk 4: Please make a booking Thank you.\nChunk 5: I also want to go to a museum.\nChunk 6: It can be in any area.\nChunk 7: Could you suggest one and give me some information about it, please?\nChunk 8: I also need a taxi between the two places.\nChunk 9: I need to arrive at the restaurant by the booking time Great!\nChunk 10: That is all I needed Thank you.", "input_token_count": 97, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant. Next, party size: 5 people. Next, time: 19:00; day: thursday. Next, the goal is booking. Next, the topic is attraction; destination: go to a museum. Next, area: any. Next, the goal is request info. Next, the topic is taxi. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is taxi.. the goal is request info.. destination: find a restaurant., go to a museum.; party size: 5 people.; time: 19:00; day: thursday.; area: any.; intent: context_update..", "trace": "C1 domain=restaurant; goal=search; destination+=find a restaurant. C2 party_size+=5 people. C3 time+=19:00; day+=thursday. C4 goal=booking. C5 domain=attraction; destination+=go to a museum. C6 area+=any. C7 goal=request_info. C8 domain=taxi. C9 intent=context_update. C10 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I want to find a restaurant.", "streaming_reasoning": "Initially, the topic is restaurant; the goal is search; destination: find a restaurant..", "trace": "domain=restaurant; goal=search; destination+=find a restaurant."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "It is for 5 people.", "streaming_reasoning": "As more information arrives, party size: 5 people..", "trace": "party_size+=5 people."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "The time is thursday, 19:00.", "streaming_reasoning": "As more information arrives, time: 19:00; day: thursday..", "trace": "time+=19:00; day+=thursday."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Please make a booking Thank you.", "streaming_reasoning": "As more information arrives, the goal is booking..", "trace": "goal=booking."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "I also want to go to a museum.", "streaming_reasoning": "As more information arrives, the topic is attraction; destination: go to a museum..", "trace": "domain=attraction; destination+=go to a museum."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "It can be in any area.", "streaming_reasoning": "As more information arrives, area: any..", "trace": "area+=any."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "Could you suggest one and give me some information about it, please?", "streaming_reasoning": "As more information arrives, the goal is request info..", "trace": "goal=request_info."}, {"checkpoint_id": "C8", "chunk_index": 7, "observed_text": "I also need a taxi between the two places.", "streaming_reasoning": "As more information arrives, the topic is taxi..", "trace": "domain=taxi."}, {"checkpoint_id": "C9", "chunk_index": 8, "observed_text": "I need to arrive at the restaurant by the booking time Great!", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C10", "chunk_index": 9, "observed_text": "That is all I needed Thank you.", "streaming_reasoning": "The content at C10 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of search. Key information: area is any; party size is 5 people; destination is find a restaurant; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant, attraction, taxi; goal=search, booking, recommendation, request_info; area=any; party_size=5 people; destination=find a restaurant, go to a museum; when=thursday, 19:00; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002986", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am open to suggestions on the location.\nChunk 2: Can you recommend an Italian restaurant in the centre as well?\nChunk 3: I am on a tight budget so would prefer something in the cheap price range That sounds perfect.\nChunk 4: Can you book me a table for 3 on Thursday at 18:45?\nChunk 5: Yes, can you try to book at 17:45?\nChunk 6: I think that is all I need, thank you Good bye.", "streaming_reasoning": "C1 destination+=suggestions on the location. C2 domain=restaurant; goal=recommendation; area+=centre; cuisine+=italian. C3 price+=cheap, affordable; acceptance=selected_option. C4 goal=booking; time+=3, 18:45; day+=thursday. C5 goal=confirm_booking; time+=17:45; goal=confirm_booking. C6 [SKIP: closing_only].", "deep_reasoning": "Need domain=restaurant; goal=recommendation, booking, confirm_booking; area=centre; food=italian; price=cheap, affordable; destination=suggestions on the location; when=thursday, 3, 18:45, 17:45; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: I am open to suggestions on the location.\nChunk 2: Can you recommend an Italian restaurant in the centre as well?\nChunk 3: I am on a tight budget so would prefer something in the cheap price range That sounds perfect.\nChunk 4: Can you book me a table for 3 on Thursday at 18:45?\nChunk 5: Yes, can you try to book at 17:45?\nChunk 6: I think that is all I need, thank you Good bye."}, {"role": "assistant", "content": "Streaming reasoning: C1 destination+=suggestions on the location. C2 domain=restaurant; goal=recommendation; area+=centre; cuisine+=italian. C3 price+=cheap, affordable; acceptance=selected_option. C4 goal=booking; time+=3, 18:45; day+=thursday. C5 goal=confirm_booking; time+=17:45; goal=confirm_booking. C6 [SKIP: closing_only].\n\nDeep reasoning: Need domain=restaurant; goal=recommendation, booking, confirm_booking; area=centre; food=italian; price=cheap, affordable; destination=suggestions on the location; when=thursday, 3, 18:45, 17:45; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: I am open to suggestions on the location.\nChunk 2: Can you recommend an Italian restaurant in the centre as well?\nChunk 3: I am on a tight budget so would prefer something in the cheap price range That sounds perfect.\nChunk 4: Can you book me a table for 3 on Thursday at 18:45?\nChunk 5: Yes, can you try to book at 17:45?\nChunk 6: I think that is all I need, thank you Good bye.", "input_token_count": 82, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, destination: suggestions on the location. Next, the topic is restaurant; the goal is recommendation; area: centre; cuisine: italian. Next, price: cheap; acceptance: selected_option. Next, the goal is booking; time: 3; day: thursday. Finally, the goal is confirm booking.; time: 17:45.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is restaurant. the goal is confirm booking.. destination: suggestions on the location.; area: centre; cuisine: italian.; price: cheap; acceptance: selected_option.; time: 3, 17:45; day: thursday..", "trace": "C1 destination+=suggestions on the location. C2 domain=restaurant; goal=recommendation; area+=centre; cuisine+=italian. C3 price+=cheap, affordable; acceptance=selected_option. C4 goal=booking; time+=3, 18:45; day+=thursday. C5 goal=confirm_booking; time+=17:45; goal=confirm_booking. C6 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "I am open to suggestions on the location.", "streaming_reasoning": "Initially, destination: suggestions on the location..", "trace": "destination+=suggestions on the location."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "Can you recommend an Italian restaurant in the centre as well?", "streaming_reasoning": "As more information arrives, the topic is restaurant; the goal is recommendation; area: centre; cuisine: italian..", "trace": "domain=restaurant; goal=recommendation; area+=centre; cuisine+=italian."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "I am on a tight budget so would prefer something in the cheap price range That sounds perfect.", "streaming_reasoning": "As more information arrives, price: cheap; acceptance: selected_option..", "trace": "price+=cheap, affordable; acceptance=selected_option."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "Can you book me a table for 3 on Thursday at 18:45?", "streaming_reasoning": "As more information arrives, the goal is booking; time: 3; day: thursday..", "trace": "goal=booking; time+=3, 18:45; day+=thursday."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Yes, can you try to book at 17:45?", "streaming_reasoning": "As more information arrives, the goal is confirm booking.; time: 17:45.", "trace": "goal=confirm_booking; time+=17:45; goal=confirm_booking."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "I think that is all I need, thank you Good bye.", "streaming_reasoning": "The content at C6 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a restaurant task with the goal of recommendation. Key information: area is centre; cuisine is italian; price is cheap; destination is suggestions on the location; timing is thursday. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=restaurant; goal=recommendation, booking, confirm_booking; area=centre; food=italian; price=cheap, affordable; destination=suggestions on the location; when=thursday, 3, 18:45, 17:45; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}
+{"id": "life_task_oriented_assistant_002987", "domain": "task_oriented_assistant", "source_dataset": "pietrolesci/multiwoz_all_versions", "instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes book the ticket please.\nChunk 2: On second thought, I don't need a ticket reserved.\nChunk 3: Could you tell me what the travel time will be on that train, though Excellent.\nChunk 4: I'm also looking to go to a museum on the west part of town That sounds wonderful.\nChunk 5: Can you give me the address, postcode, and phone number?\nChunk 6: Okay thank you very much.\nChunk 7: No that's everything I need Thank you!", "streaming_reasoning": "C1 goal=confirm_booking; goal=confirm_booking. C2 goal=search. C3 domain=train; goal=request_info; requested_info+=travel_time. C4 domain=attraction; area+=west; destination+=go to a museum on the west part of town t. C5 requested_info+=address, phone, postcode. C6 intent=context_update. C7 [SKIP: closing_only].", "deep_reasoning": "Need domain=train, attraction; goal=booking, confirm_booking, search, request_info; area=west; destination=go to a museum on the west part of town t; requested_info=travel_time, address, phone, postcode; closing_detected.", "answer": "You're welcome. Glad I could help; have a great day.", "messages": [{"role": "user", "content": "Instruction: Help the user complete a real-life task based on gradually revealed information.\n\nContext:\nChunk 1: Yes book the ticket please.\nChunk 2: On second thought, I don't need a ticket reserved.\nChunk 3: Could you tell me what the travel time will be on that train, though Excellent.\nChunk 4: I'm also looking to go to a museum on the west part of town That sounds wonderful.\nChunk 5: Can you give me the address, postcode, and phone number?\nChunk 6: Okay thank you very much.\nChunk 7: No that's everything I need Thank you!"}, {"role": "assistant", "content": "Streaming reasoning: C1 goal=confirm_booking; goal=confirm_booking. C2 goal=search. C3 domain=train; goal=request_info; requested_info+=travel_time. C4 domain=attraction; area+=west; destination+=go to a museum on the west part of town t. C5 requested_info+=address, phone, postcode. C6 intent=context_update. C7 [SKIP: closing_only].\n\nDeep reasoning: Need domain=train, attraction; goal=booking, confirm_booking, search, request_info; area=west; destination=go to a museum on the west part of town t; requested_info=travel_time, address, phone, postcode; closing_detected.\n\nAnswer: You're welcome. Glad I could help; have a great day."}], "language": "en", "split": "eval", "quality_flags": ["merged_fragments"], "version": "v0.4.1", "quality_score": 1.0, "is_high_quality": true, "modality": "text", "turn_type": "single_turn", "taxonomy": {"category": "daily_life", "subcategory": "constraints_extraction", "intent_type": "task_completion", "difficulty": "medium"}, "input": {"instruction": "Help the user complete a real-life task based on gradually revealed information.", "context": "Chunk 1: Yes book the ticket please.\nChunk 2: On second thought, I don't need a ticket reserved.\nChunk 3: Could you tell me what the travel time will be on that train, though Excellent.\nChunk 4: I'm also looking to go to a museum on the west part of town That sounds wonderful.\nChunk 5: Can you give me the address, postcode, and phone number?\nChunk 6: Okay thank you very much.\nChunk 7: No that's everything I need Thank you!", "input_token_count": 82, "length_bucket": "short"}, "streaming": {"streaming_reasoning": "Initially, the goal is confirm booking. Next, the goal is search. Next, the topic is train; the goal is request info; requested information: travel_time. Next, the topic is attraction; area: west; destination: go to a museum on the west part of town t. Next, requested information: address. Finally, intent: context_update.  Some chunks were skipped because they contained closing_only. In summary, The overall topic is attraction. the goal is request info. requested information: travel_time., address; area: west; destination: go to a museum on the west part of town t.; intent: context_update..", "trace": "C1 goal=confirm_booking; goal=confirm_booking. C2 goal=search. C3 domain=train; goal=request_info; requested_info+=travel_time. C4 domain=attraction; area+=west; destination+=go to a museum on the west part of town t. C5 requested_info+=address, phone, postcode. C6 intent=context_update. C7 [SKIP: closing_only].", "checkpoints": [{"checkpoint_id": "C1", "chunk_index": 0, "observed_text": "Yes book the ticket please.", "streaming_reasoning": "Initially, the goal is confirm booking..", "trace": "goal=confirm_booking; goal=confirm_booking."}, {"checkpoint_id": "C2", "chunk_index": 1, "observed_text": "On second thought, I don't need a ticket reserved.", "streaming_reasoning": "As more information arrives, the goal is search..", "trace": "goal=search."}, {"checkpoint_id": "C3", "chunk_index": 2, "observed_text": "Could you tell me what the travel time will be on that train, though Excellent.", "streaming_reasoning": "As more information arrives, the topic is train; the goal is request info; requested information: travel_time..", "trace": "domain=train; goal=request_info; requested_info+=travel_time."}, {"checkpoint_id": "C4", "chunk_index": 3, "observed_text": "I'm also looking to go to a museum on the west part of town That sounds wonderful.", "streaming_reasoning": "As more information arrives, the topic is attraction; area: west; destination: go to a museum on the west part of town t..", "trace": "domain=attraction; area+=west; destination+=go to a museum on the west part of town t."}, {"checkpoint_id": "C5", "chunk_index": 4, "observed_text": "Can you give me the address, postcode, and phone number?", "streaming_reasoning": "As more information arrives, requested information: address.", "trace": "requested_info+=address, phone, postcode."}, {"checkpoint_id": "C6", "chunk_index": 5, "observed_text": "Okay thank you very much.", "streaming_reasoning": "As more information arrives, intent: context_update..", "trace": "intent=context_update."}, {"checkpoint_id": "C7", "chunk_index": 6, "observed_text": "No that's everything I need Thank you!", "streaming_reasoning": "The content at C7 was skipped (closing_only).", "trace": "[SKIP: closing_only]."}]}, "output": {"deep_reasoning": "The user is working on a train task with the goal of booking. Key information: area is west; destination is go to a museum on the west part of town t; requested information is travel_time. Given the above, the assistant should answer the user's current request directly, using only the known constraints, and not ask about information that has already been provided.", "answer": "You're welcome. Glad I could help; have a great day.", "deep_reasoning_trace": "Need domain=train, attraction; goal=booking, confirm_booking, search, request_info; area=west; destination=go to a museum on the west part of town t; requested_info=travel_time, address, phone, postcode; closing_detected."}, "quality": {"is_high_quality": true, "reasoning_quality": "high", "single_turn_quality": "usable", "drop_reason": "", "quality_score": 1.0, "quality_flags": ["merged_fragments"]}, "metadata": {"source_dataset": "pietrolesci/multiwoz_all_versions", "original_version": "v0.4.1"}}