question stringlengths 20 376 | answer stringlengths 3 25 | task_config stringclasses 1
value | task_source stringclasses 1
value | prompt listlengths 2 2 | model_responses listlengths 0 0 | model_responses__eval_is_correct listlengths 0 0 | prompt_variant stringclasses 1
value | choices dict | answer_key stringclasses 5
values | answer_index int64 0 4 | id stringlengths 32 34 | model_responses__mutated_prompts listlengths 16 16 | model_responses__mutated_prompts__finish_reason_length_flags listlengths 16 16 | model_responses__mutated_prompts__length_partial_responses listlengths 16 16 | prompt__mutated_prompts__metadata dict | model_responses__mutated_prompts__metadata dict | model_responses__mutated_prompts__eval_is_correct listlengths 16 16 | model_responses__mutated_prompts__eval_extracted_answers listlengths 16 16 | model_responses__mutated_prompts__eval_extraction_metadata listlengths 16 16 | model_responses__mutated_prompts__eval_evaluation_metadata listlengths 16 16 | model_responses__mutated_prompts__internal_answers__eval_is_correct listlengths 16 16 | model_responses__mutated_prompts__internal_answers__eval_extracted_answers listlengths 16 16 | model_responses__mutated_prompts__internal_answers__eval_extraction_metadata listlengths 16 16 | model_responses__mutated_prompts__internal_answers__eval_evaluation_metadata listlengths 16 16 | model_responses__mutated_prompts__metrics dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
How is someone who loves their TV likely to feel about their remote? | attached | commonsenseQA | csqa | [
{
"content": "You like to solve problems by understanding the problem, writing a plan, executing the plan, then giving an answer. Write a plan that when reasoned over would solve the question then give your answer in \"<answer>\n(your answer)\n</answer>\". You always end with </answer>, you never ever end witho... | [] | [] | plan_and_execute | {
"label": [
"A",
"B",
"C",
"D",
"E"
],
"text": [
"attached",
"nostalgic",
"companionable",
"likely",
"close"
]
} | A | 0 | a771ea8c42519d651e2b1ab36a6187b7 | [
"First, I'll try to understand the problem better by writing out a plan and go really deep into detail about how I should solve this.\n1. Identify the key elements of the problem: The person loves their TV, so they must have strong feelings towards it. We need to determine what type of feeling these strong emotions... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {
"api_url": "http://127.0.0.1:41177",
"backend": "litellm",
"chat_template_applied": true,
"generation_params": {
"chat_template_applied": true,
"max_tokens": 4096,
"n": 16,
"repetition_penalty": 1.1,
"temperature": 0.7,
"top_k": 20,
"top_p": 0.8
},
"model_name": "hosted_vllm/Qw... | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
false,
false,
false,
false,
false,
false,
false,
true,
false,
false,
false,
false,
true,
false,
true,
false
] | [
"Attached",
"C",
"C",
"C",
null,
"B",
"C",
"A",
"C",
"BCD",
"nostalgic",
"C",
"A",
"C",
"A",
"C"
] | [
{
"extraction_type": "final",
"non_overlapping_spans": 1,
"original_span": "Attached",
"span_end": 1634,
"span_start": 1626,
"total_spans_found": 1
},
{
"extraction_type": "final",
"non_overlapping_spans": 1,
"original_span": "C",
"span_end": 1374,
"span_start": 1373,... | [
{
"evaluation_method": "legacy",
"extraction_result": null,
"legacy_result": false,
"reason": null
},
{
"evaluation_method": "legacy",
"extraction_result": null,
"legacy_result": false,
"reason": null
},
{
"evaluation_method": "legacy",
"extraction_result": null,
... | [
[
false
],
[
false
],
[
false
],
[
false
],
[],
[
false
],
[
false
],
[
true
],
[
false
],
[
false
],
[
false
],
[
false
],
[
true
],
[
false
],
[
true
],
[
false
]
] | [
[
"Attached"
],
[
"C"
],
[
"C"
],
[
"C"
],
[],
[
"B"
],
[
"C"
],
[
"A"
],
[
"C"
],
[
"BCD"
],
[
"nostalgic"
],
[
"C"
],
[
"A"
],
[
"C"
],
[
"A"
],
[
"C"
]
] | [
[
{
"confidence": 1,
"extraction_type": "internal",
"original_span": "Attached",
"pattern_used": "answer tag",
"position": 1626,
"span_end": 1634,
"span_start": 1626,
"span_text": "Attached"
}
],
[
{
"confidence": 1,
"extraction_type": "int... | [
[
{
"evaluation_method": "legacy",
"legacy_result": false
}
],
[
{
"evaluation_method": "legacy",
"legacy_result": false
}
],
[
{
"evaluation_method": "legacy",
"legacy_result": false
}
],
[
{
"evaluation_method": "legacy",
"leg... | {
"flips_by": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"flips_total": 0,
"num_correct": 3,
"pass_at_n": 1,
"percent_correct": 0.1875,
"skill_count": {
"answer_revision": [
0,
0,
0,
0,
0,
0,
... |
What was the reaction when the children were given ice cream? | enjoyed | commonsenseQA | csqa | [
{
"content": "You like to solve problems by understanding the problem, writing a plan, executing the plan, then giving an answer. Write a plan that when reasoned over would solve the question then give your answer in \"<answer>\n(your answer)\n</answer>\". You always end with </answer>, you never ever end witho... | [] | [] | plan_and_execute | {
"label": [
"A",
"B",
"C",
"D",
"E"
],
"text": [
"awesome",
"enjoyed",
"play chess",
"skip",
"sadness"
]
} | B | 1 | 5973770bb0e4b43fcaeaba19dd0de38e | [
"First, I'll try to understand the problem better by writing out a plan and go really deep into detail about how I should solve this.\nStep 1: Identify the key elements of the question.\n- The subject is children receiving ice cream.\n- We need to determine their reaction to the ice cream.\n\nStep 2: Consider possi... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {
"api_url": "http://127.0.0.1:41177",
"backend": "litellm",
"chat_template_applied": true,
"generation_params": {
"chat_template_applied": true,
"max_tokens": 4096,
"n": 16,
"repetition_penalty": 1.1,
"temperature": 0.7,
"top_k": 20,
"top_p": 0.8
},
"model_name": "hosted_vllm/Qw... | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
true,
true,
true,
true,
false,
true,
true,
true,
false,
false,
true,
false,
false,
true,
true,
true
] | [
"B",
"B - enjoyed",
"B",
"B - enjoyed",
"A",
"B",
"B",
"B",
"awesome",
"A",
"B",
"(A)",
"A",
"B",
"B - enjoyed",
"B"
] | [
{
"extraction_type": "final",
"non_overlapping_spans": 1,
"original_span": "B",
"span_end": 1126,
"span_start": 1125,
"total_spans_found": 1
},
{
"extraction_type": "final",
"non_overlapping_spans": 1,
"original_span": "B - enjoyed",
"span_end": 1113,
"span_start": 11... | [
{
"evaluation_method": "legacy",
"extraction_result": null,
"legacy_result": true,
"reason": null
},
{
"evaluation_method": "legacy",
"extraction_result": null,
"legacy_result": true,
"reason": null
},
{
"evaluation_method": "legacy",
"extraction_result": null,
"l... | [
[
true
],
[
true
],
[
true
],
[
true
],
[
false
],
[
true
],
[
true
],
[
true
],
[
false
],
[
false
],
[
true
],
[
false
],
[
false
],
[
true
],
[
true
],
[
true
]
] | [
[
"B"
],
[
"B - enjoyed"
],
[
"B"
],
[
"B - enjoyed"
],
[
"A"
],
[
"B"
],
[
"B"
],
[
"B"
],
[
"awesome"
],
[
"A"
],
[
"B"
],
[
"(A)"
],
[
"A"
],
[
"B"
],
[
"B - enjoyed"
],
[
"B"
]
] | [
[
{
"confidence": 1,
"extraction_type": "internal",
"original_span": "B",
"pattern_used": "answer tag",
"position": 1125,
"span_end": 1126,
"span_start": 1125,
"span_text": "B"
}
],
[
{
"confidence": 1,
"extraction_type": "internal",
... | [
[
{
"evaluation_method": "legacy",
"legacy_result": true
}
],
[
{
"evaluation_method": "legacy",
"legacy_result": true
}
],
[
{
"evaluation_method": "legacy",
"legacy_result": true
}
],
[
{
"evaluation_method": "legacy",
"legacy... | {
"flips_by": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"flips_total": 0,
"num_correct": 11,
"pass_at_n": 1,
"percent_correct": 0.6875,
"skill_count": {
"answer_revision": [
0,
0,
0,
0,
0,
0,
... |
What is something bad not likely to be to anyone? | beneficial | commonsenseQA | csqa | [
{
"content": "You like to solve problems by understanding the problem, writing a plan, executing the plan, then giving an answer. Write a plan that when reasoned over would solve the question then give your answer in \"<answer>\n(your answer)\n</answer>\". You always end with </answer>, you never ever end witho... | [] | [] | plan_and_execute | {
"label": [
"A",
"B",
"C",
"D",
"E"
],
"text": [
"profitable",
"beneficial",
"valued",
"competent",
"excellent"
]
} | B | 1 | 623037d32f3726a795fa8de66fb0bd19 | [
"**Plan**\n\n1. **Understand the Question**: The question asks what something bad is not likely to be to anyone.\n2. **Identify Key Concepts**: We need to identify what qualities or characteristics are associated with being good rather than bad.\n3. **Analyze Each Option**:\n - A) Profitable: Bad things can somet... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {
"api_url": "http://127.0.0.1:41177",
"backend": "litellm",
"chat_template_applied": true,
"generation_params": {
"chat_template_applied": true,
"max_tokens": 4096,
"n": 16,
"repetition_penalty": 1.1,
"temperature": 0.7,
"top_k": 20,
"top_p": 0.8
},
"model_name": "hosted_vllm/Qw... | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
true,
false,
true
] | [
"excellent",
"Excellence",
"C",
"C",
"competed",
"C",
"C",
"D",
null,
"E",
"C",
null,
"C",
"(B)",
"C",
"B"
] | [
{
"extraction_type": "final",
"non_overlapping_spans": 1,
"original_span": "excellent",
"span_end": 860,
"span_start": 851,
"total_spans_found": 1
},
{
"extraction_type": "final",
"non_overlapping_spans": 1,
"original_span": "Excellence",
"span_end": 1268,
"span_start... | [
{
"evaluation_method": "legacy",
"extraction_result": null,
"legacy_result": false,
"reason": null
},
{
"evaluation_method": "legacy",
"extraction_result": null,
"legacy_result": false,
"reason": null
},
{
"evaluation_method": "legacy",
"extraction_result": null,
... | [
[
false
],
[
false
],
[
false
],
[
false
],
[
false
],
[
false
],
[
false
],
[
false
],
[],
[
false
],
[
false
],
[],
[
false
],
[
true
],
[
false
],
[
true
]
] | [
[
"excellent"
],
[
"Excellence"
],
[
"C"
],
[
"C"
],
[
"competed"
],
[
"C"
],
[
"C"
],
[
"D"
],
[],
[
"E"
],
[
"C"
],
[],
[
"C"
],
[
"(B)"
],
[
"C"
],
[
"B"
]
] | [
[
{
"confidence": 1,
"extraction_type": "internal",
"original_span": "excellent",
"pattern_used": "answer tag",
"position": 851,
"span_end": 860,
"span_start": 851,
"span_text": "excellent"
}
],
[
{
"confidence": 1,
"extraction_type": "inte... | [
[
{
"evaluation_method": "legacy",
"legacy_result": false
}
],
[
{
"evaluation_method": "legacy",
"legacy_result": false
}
],
[
{
"evaluation_method": "legacy",
"legacy_result": false
}
],
[
{
"evaluation_method": "legacy",
"leg... | {
"flips_by": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"flips_total": 0,
"num_correct": 2,
"pass_at_n": 1,
"percent_correct": 0.125,
"skill_count": {
"answer_revision": [
0,
0,
0,
0,
0,
0,
... |
James found himself watching films all the time. He did it because he was too high strung and needed some what? | relaxation | commonsenseQA | csqa | [
{
"content": "You like to solve problems by understanding the problem, writing a plan, executing the plan, then giving an answer. Write a plan that when reasoned over would solve the question then give your answer in \"<answer>\n(your answer)\n</answer>\". You always end with </answer>, you never ever end witho... | [] | [] | plan_and_execute | {
"label": [
"A",
"B",
"C",
"D",
"E"
],
"text": [
"like",
"stupidity",
"relaxation",
"enjoyment",
"loved"
]
} | C | 2 | ac674e5c9a49b2d461ea46d40434f151 | [
"First, I'll try to understand the problem better by writing out a plan and go really deep into detail about how I should solve this.\n- James finds himself watching films excessively due to his high-strung nature.\n- His excessive film-watching is causing him discomfort or dissatisfaction.\n- To alleviate this iss... | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {
"api_url": "http://127.0.0.1:41177",
"backend": "litellm",
"chat_template_applied": true,
"generation_params": {
"chat_template_applied": true,
"max_tokens": 4096,
"n": 16,
"repetition_penalty": 1.1,
"temperature": 0.7,
"top_k": 20,
"top_p": 0.8
},
"model_name": "hosted_vllm/Qw... | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
true,
false,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
false,
true,
true,
true
] | [
"C",
null,
"C",
"C",
"C",
"C",
"C",
"C",
"C",
"C",
"C",
"C",
null,
"C",
"C",
"C"
] | [
{
"extraction_type": "final",
"non_overlapping_spans": 1,
"original_span": "C",
"span_end": 1413,
"span_start": 1412,
"total_spans_found": 1
},
{
"extraction_type": "final",
"non_overlapping_spans": null,
"original_span": null,
"span_end": null,
"span_start": null,
... | [
{
"evaluation_method": "legacy",
"extraction_result": null,
"legacy_result": true,
"reason": null
},
{
"evaluation_method": "response_processor",
"extraction_result": "{'extraction_type': 'final'}",
"legacy_result": null,
"reason": "no_extracted_answer"
},
{
"evaluation_m... | [
[
true
],
[],
[
true
],
[
true
],
[
true
],
[
true
],
[
true
],
[
true
],
[
true
],
[
true
],
[
true
],
[
true
],
[],
[
true
],
[
true
],
[
true
]
] | [
[
"C"
],
[],
[
"C"
],
[
"C"
],
[
"C"
],
[
"C"
],
[
"C"
],
[
"C"
],
[
"C"
],
[
"C"
],
[
"C"
],
[
"C"
],
[],
[
"C"
],
[
"C"
],
[
"C"
]
] | [
[
{
"confidence": 1,
"extraction_type": "internal",
"original_span": "C",
"pattern_used": "answer tag",
"position": 1412,
"span_end": 1413,
"span_start": 1412,
"span_text": "C"
}
],
[],
[
{
"confidence": 1,
"extraction_type": "internal",
... | [
[
{
"evaluation_method": "legacy",
"legacy_result": true
}
],
[],
[
{
"evaluation_method": "legacy",
"legacy_result": true
}
],
[
{
"evaluation_method": "legacy",
"legacy_result": true
}
],
[
{
"evaluation_method": "legacy",
"... | {
"flips_by": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"flips_total": 0,
"num_correct": 14,
"pass_at_n": 1,
"percent_correct": 0.875,
"skill_count": {
"answer_revision": [
0,
0,
0,
0,
0,
0,
... |
What would use an account book? | bank | commonsenseQA | csqa | [{"content":"You like to solve problems by understanding the problem, writing a plan, executing the (...TRUNCATED) | [] | [] | plan_and_execute | {"label":["A","B","C","D","E"],"text":["desk drawer","purse","bank","keep accounts","keep track of e(...TRUNCATED) | C | 2 | 14e9f1ab04ad31019e71dc3fd2c0ca50 | ["First, I'll try to understand the problem better by writing out a plan and go really deep into det(...TRUNCATED) | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {"api_url":"http://127.0.0.1:41177","backend":"litellm","chat_template_applied":true,"generation_par(...TRUNCATED) | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
true,
false,
false,
false,
true,
false
] | [
"D",
"D",
"D",
null,
"D",
null,
"D",
"D",
"D",
"none",
"C",
"D",
"D",
null,
"C",
null
] | [{"extraction_type":"final","non_overlapping_spans":1,"original_span":"D","span_end":1053,"span_star(...TRUNCATED) | [{"evaluation_method":"legacy","extraction_result":null,"legacy_result":false,"reason":null},{"evalu(...TRUNCATED) | [[false],[false],[false],[],[false],[],[false],[false],[false],[false],[true],[false],[false],[],[tr(...TRUNCATED) | [
[
"D"
],
[
"D"
],
[
"D"
],
[],
[
"D"
],
[],
[
"D"
],
[
"D"
],
[
"D"
],
[
"none"
],
[
"C"
],
[
"D"
],
[
"D"
],
[],
[
"C"
],
[]
] | [[{"confidence":1.0,"extraction_type":"internal","original_span":"D","pattern_used":"answer tag","po(...TRUNCATED) | [[{"evaluation_method":"legacy","legacy_result":false}],[{"evaluation_method":"legacy","legacy_resul(...TRUNCATED) | {"flips_by":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"flips_total":0,"num_correct":2,"pass_at_n":1,"percent(...TRUNCATED) |
When all the members drank the poison and died it was because everybody what? | believed | commonsenseQA | csqa | [{"content":"You like to solve problems by understanding the problem, writing a plan, executing the (...TRUNCATED) | [] | [] | plan_and_execute | {
"label": [
"A",
"B",
"C",
"D",
"E"
],
"text": [
"exist",
"cat",
"out of mind",
"believed",
"happy"
]
} | D | 3 | ab112c6be9806f2b5ee0b29868c43b44 | ["First, I'll try to understand the problem better by writing out a plan and go really deep into det(...TRUNCATED) | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {"api_url":"http://127.0.0.1:41177","backend":"litellm","chat_template_applied":true,"generation_par(...TRUNCATED) | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
false,
false,
false,
true,
false,
false,
false,
false,
false,
true,
false,
false,
false,
false,
false,
false
] | [
"C",
"E",
"C",
"D",
"C",
"E - happy",
"C",
"C",
"C",
"D - believed",
"out of mind",
"exist",
"C",
"E",
"C",
"cat"
] | [{"extraction_type":"final","non_overlapping_spans":1,"original_span":"C","span_end":1539,"span_star(...TRUNCATED) | [{"evaluation_method":"legacy","extraction_result":null,"legacy_result":false,"reason":null},{"evalu(...TRUNCATED) | [[false],[false],[false],[true],[false],[false],[false],[false],[false],[true],[false],[false],[fals(...TRUNCATED) | [["C"],["E"],["C"],["D"],["C"],["E - happy"],["C"],["C"],["C"],["D - believed"],["out of mind"],["ex(...TRUNCATED) | [[{"confidence":1.0,"extraction_type":"internal","original_span":"C","pattern_used":"answer tag","po(...TRUNCATED) | [[{"evaluation_method":"legacy","legacy_result":false}],[{"evaluation_method":"legacy","legacy_resul(...TRUNCATED) | {"flips_by":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"flips_total":0,"num_correct":2,"pass_at_n":1,"percent(...TRUNCATED) |
Where do humans go to be entertained and eat popcorn? | movie theatre | commonsenseQA | csqa | [{"content":"You like to solve problems by understanding the problem, writing a plan, executing the (...TRUNCATED) | [] | [] | plan_and_execute | {
"label": [
"A",
"B",
"C",
"D",
"E"
],
"text": [
"mall",
"country",
"movie theatre",
"park",
"university"
]
} | C | 2 | 53e8ac48325cd055d0de5e6eafdb88dd | ["First, I'll try to understand the problem better by writing out a plan and go really deep into det(...TRUNCATED) | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {"api_url":"http://127.0.0.1:41177","backend":"litellm","chat_template_applied":true,"generation_par(...TRUNCATED) | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
true,
false,
true,
true,
true,
true,
true,
true,
true,
true,
false,
true,
true,
true,
true,
true
] | ["C","Cinema/Movie Theater","C - movie theater","C","C","C","C","C","C","C",null,"C","C","C","C","C"(...TRUNCATED) | [{"extraction_type":"final","non_overlapping_spans":1,"original_span":"C","span_end":1351,"span_star(...TRUNCATED) | [{"evaluation_method":"legacy","extraction_result":null,"legacy_result":true,"reason":null},{"evalua(...TRUNCATED) | [[true],[false],[true],[true],[true],[true],[true],[true],[true],[true],[],[true],[true],[true],[tru(...TRUNCATED) | [["C"],["Cinema/Movie Theater"],["C - movie theater"],["C"],["C"],["C"],["C"],["C"],["C"],["C"],[],[(...TRUNCATED) | [[{"confidence":1.0,"extraction_type":"internal","original_span":"C","pattern_used":"answer tag","po(...TRUNCATED) | [[{"evaluation_method":"legacy","legacy_result":true}],[{"evaluation_method":"legacy","legacy_result(...TRUNCATED) | {"flips_by":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"flips_total":0,"num_correct":14,"pass_at_n":1,"percen(...TRUNCATED) |
The person knew the police were after him, so what did he do? | prepare to go | commonsenseQA | csqa | [{"content":"You like to solve problems by understanding the problem, writing a plan, executing the (...TRUNCATED) | [] | [] | plan_and_execute | {"label":["A","B","C","D","E"],"text":["the sun","catch cold","prepare to go","feel humiliated","hun(...TRUNCATED) | C | 2 | 17e5e2f42d600c5f5c4c38eb2cbd7314 | ["First, I'll try to understand the problem better by writing out a plan and go really deep into det(...TRUNCATED) | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {"api_url":"http://127.0.0.1:41177","backend":"litellm","chat_template_applied":true,"generation_par(...TRUNCATED) | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
false,
false,
true,
false,
true,
false,
true,
true,
true,
false,
true,
false,
true,
true,
true,
true
] | [
"E",
"E",
"C",
"E",
"C",
"none",
"C",
"C",
"C",
"E",
"C",
"E",
"C",
"C",
"C",
"C"
] | [{"extraction_type":"final","non_overlapping_spans":1,"original_span":"E","span_end":1005,"span_star(...TRUNCATED) | [{"evaluation_method":"legacy","extraction_result":null,"legacy_result":false,"reason":null},{"evalu(...TRUNCATED) | [[false],[false],[true],[false],[true],[false],[true],[true],[true],[false],[true],[false],[true],[t(...TRUNCATED) | [
[
"E"
],
[
"E"
],
[
"C"
],
[
"E"
],
[
"C"
],
[
"none"
],
[
"C"
],
[
"C"
],
[
"C"
],
[
"E"
],
[
"C"
],
[
"E"
],
[
"C"
],
[
"C"
],
[
"C"
],
[
"C"
]
] | [[{"confidence":1.0,"extraction_type":"internal","original_span":"E","pattern_used":"answer tag","po(...TRUNCATED) | [[{"evaluation_method":"legacy","legacy_result":false}],[{"evaluation_method":"legacy","legacy_resul(...TRUNCATED) | {"flips_by":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"flips_total":0,"num_correct":10,"pass_at_n":1,"percen(...TRUNCATED) |
"Joe needs a container cup to hold milk that he gets out of something. What might the milk come out(...TRUNCATED) | dispenser | commonsenseQA | csqa | [{"content":"You like to solve problems by understanding the problem, writing a plan, executing the (...TRUNCATED) | [] | [] | plan_and_execute | {"label":["A","B","C","D","E"],"text":["dispenser","cow","person's hand","kitchen cupboard","refridg(...TRUNCATED) | A | 0 | c30b487879eda928ada9c32ace89b7d5 | ["First, I'll try to understand the problem better by writing out a plan and go really deep into det(...TRUNCATED) | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {"api_url":"http://127.0.0.1:41177","backend":"litellm","chat_template_applied":true,"generation_par(...TRUNCATED) | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
true,
false,
false,
true,
false,
true,
false,
true,
true,
true,
false,
false,
true,
false,
false,
false
] | [
"A",
"dispenser, person's hand",
"E",
"A",
null,
"A",
"B",
"A",
"A",
"A",
"dispenser",
"C",
"A",
"C",
"E",
null
] | [{"extraction_type":"final","non_overlapping_spans":1,"original_span":"A","span_end":1331,"span_star(...TRUNCATED) | [{"evaluation_method":"legacy","extraction_result":null,"legacy_result":true,"reason":null},{"evalua(...TRUNCATED) | [[true],[false],[false],[true],[],[true],[false],[true],[true],[true],[false],[false],[true],[false](...TRUNCATED) | [["A"],["dispenser, person's hand"],["E"],["A"],[],["A"],["B"],["A"],["A"],["A"],["dispenser"],["C"](...TRUNCATED) | [[{"confidence":1.0,"extraction_type":"internal","original_span":"A","pattern_used":"answer tag","po(...TRUNCATED) | [[{"evaluation_method":"legacy","legacy_result":true}],[{"evaluation_method":"legacy","legacy_result(...TRUNCATED) | {"flips_by":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"flips_total":0,"num_correct":7,"pass_at_n":1,"percent(...TRUNCATED) |
A water spout was seen in the ocean off the coast of what? | florida | commonsenseQA | csqa | [{"content":"You like to solve problems by understanding the problem, writing a plan, executing the (...TRUNCATED) | [] | [] | plan_and_execute | {
"label": [
"A",
"B",
"C",
"D",
"E"
],
"text": [
"florida",
"basement",
"sink",
"beach",
"fountain"
]
} | A | 0 | e3b05b99436effba6ae8badb4639e14c | ["**High Level Plan:**\n\n1. **Understand the Problem:** The question asks us to identify where a wa(...TRUNCATED) | [
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | [
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
""
] | {"api_url":"http://127.0.0.1:41177","backend":"litellm","chat_template_applied":true,"generation_par(...TRUNCATED) | {
"backend": "litellm",
"model_name": "hosted_vllm/Qwen/Qwen2.5-1.5B-Instruct",
"n_responses": 16
} | [
false,
false,
false,
true,
false,
true,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false
] | ["Florida","Florida","Florida","(A) florida","Florida","(Florida)","(D) beach",null,"Florida","Flori(...TRUNCATED) | [{"extraction_type":"final","non_overlapping_spans":1,"original_span":"Florida","span_end":1572,"spa(...TRUNCATED) | [{"evaluation_method":"legacy","extraction_result":null,"legacy_result":false,"reason":null},{"evalu(...TRUNCATED) | [[false],[false],[false],[true],[false],[true],[false],[],[false],[false],[false],[false],[false],[f(...TRUNCATED) | [["Florida"],["Florida"],["Florida"],["(A) florida"],["Florida"],["(Florida)"],["(D) beach"],[],["Fl(...TRUNCATED) | [[{"confidence":1.0,"extraction_type":"internal","original_span":"Florida","pattern_used":"answer ta(...TRUNCATED) | [[{"evaluation_method":"legacy","legacy_result":false}],[{"evaluation_method":"legacy","legacy_resul(...TRUNCATED) | {"flips_by":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"flips_total":0,"num_correct":2,"pass_at_n":1,"percent(...TRUNCATED) |
End of preview. Expand in Data Studio
README.md exists but content is empty.
- Downloads last month
- 7