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You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) ... | where is the closest " dairy queen " ? | task260_spl_translation_zh_en | NIv2 | fs_opt | 0 | train |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) ... | which restaurants are on " main street " ? | task260_spl_translation_zh_en | NIv2 | fs_opt | 0 | train |
Teacher: The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* lo... | search for " burger king " . | task260_spl_translation_zh_en | NIv2 | fs_opt | 2 | train |
Given the task definition and input, reply with output. The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of ... | is there a restaurant in zipcode " 19101 " ? | task260_spl_translation_zh_en | NIv2 | zs_opt | 5 | train |
Teacher:The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* loo... | find reviews from " george " . | task260_spl_translation_zh_en | NIv2 | zs_opt | 6 | train |
The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for... | Output: search for " sushi joy " .
| task260_spl_translation_zh_en | NIv2 | fs_opt | 2 | train |
Detailed Instructions: The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. W... | what " mexican " restaurant has the most reviews ? | task260_spl_translation_zh_en | NIv2 | zs_opt | 8 | train |
The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for... | please tell me the location of " dave 's seafood shack " . | task260_spl_translation_zh_en | NIv2 | zs_opt | 0 | train |
Given the task definition and input, reply with output. The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of ... | where are the best " fast food " joints in my area . | task260_spl_translation_zh_en | NIv2 | zs_opt | 5 | test |
The provided file includes inquiries about restaurants in Chinese, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for... | find " italian " restaurants .
| task260_spl_translation_zh_en | NIv2 | fs_opt | 1 | validation |
Given the task definition and input, reply with output. In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision ... | non-overruling | task274_overruling_legal_classification | NIv2 | zs_opt | 5 | train |
Q: In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision by the same or higher ranking court which establishes... | non-overruling | task274_overruling_legal_classification | NIv2 | zs_opt | 7 | train |
In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision by the same or higher ranking court which establishes a ... | Solution: overruling | task274_overruling_legal_classification | NIv2 | fs_opt | 5 | train |
Definition: In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision by the same or higher ranking court which es... | overruling | task274_overruling_legal_classification | NIv2 | zs_opt | 2 | train |
In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision by the same or higher ranking court which establishes a ... | non-overruling | task274_overruling_legal_classification | NIv2 | fs_opt | 9 | train |
Definition: In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision by the same or higher ranking court which es... | non-overruling | task274_overruling_legal_classification | NIv2 | zs_opt | 2 | train |
Detailed Instructions: In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision by the same or higher ranking cou... | overruling | task274_overruling_legal_classification | NIv2 | zs_opt | 9 | train |
Q: In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision by the same or higher ranking court which establishes... | overruling | task274_overruling_legal_classification | NIv2 | zs_opt | 7 | train |
In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision by the same or higher ranking court which establishes a ... | Output: non-overruling
| task274_overruling_legal_classification | NIv2 | fs_opt | 2 | test |
Given the task definition and input, reply with output. In this task, you will be shown a sentence, and you should determine whether it is overruling or non-overruling. In law, an overruling sentence is a statement that nullifies a previous case decision as a precedent by a constitutionally valid statute or a decision ... | overruling | task274_overruling_legal_classification | NIv2 | zs_opt | 5 | validation |
In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.... | NUM
****
| task1168_brown_coarse_pos_tagging | NIv2 | fs_opt | 4 | train |
Definition: In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corp... | ADP | task1168_brown_coarse_pos_tagging | NIv2 | zs_opt | 2 | train |
Detailed Instructions: In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset o... | X | task1168_brown_coarse_pos_tagging | NIv2 | zs_opt | 8 | train |
Detailed Instructions: In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset o... | NOUN | task1168_brown_coarse_pos_tagging | NIv2 | zs_opt | 8 | train |
Definition: In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corp... | . | task1168_brown_coarse_pos_tagging | NIv2 | zs_opt | 2 | train |
TASK DEFINITION: In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this... | .
| task1168_brown_coarse_pos_tagging | NIv2 | fs_opt | 8 | train |
In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.... | VERB
| task1168_brown_coarse_pos_tagging | NIv2 | fs_opt | 1 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical pr... | ADP | task1168_brown_coarse_pos_tagging | NIv2 | zs_opt | 1 | train |
In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.... | ADP
| task1168_brown_coarse_pos_tagging | NIv2 | fs_opt | 1 | test |
Given the task definition and input, reply with output. In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of... | PRON | task1168_brown_coarse_pos_tagging | NIv2 | zs_opt | 5 | validation |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereo... | Anti-stereotype | task279_stereoset_classification_stereotype | NIv2 | fs_opt | 0 | train |
Instructions: In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not convey a ste... | Stereotype | task279_stereoset_classification_stereotype | NIv2 | zs_opt | 3 | train |
Detailed Instructions: In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not con... | Unrelated | task279_stereoset_classification_stereotype | NIv2 | zs_opt | 8 | train |
In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not convey a stereotype or ant... | Unrelated | task279_stereoset_classification_stereotype | NIv2 | zs_opt | 4 | train |
Detailed Instructions: In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not con... | Unrelated | task279_stereoset_classification_stereotype | NIv2 | zs_opt | 8 | train |
instruction:
In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not convey a ster... | Unrelated
| task279_stereoset_classification_stereotype | NIv2 | fs_opt | 9 | train |
Instructions: In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not convey a ste... | Unrelated | task279_stereoset_classification_stereotype | NIv2 | zs_opt | 3 | train |
In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not convey a stereotype or ant... | Stereotype
| task279_stereoset_classification_stereotype | NIv2 | fs_opt | 1 | train |
In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not convey a stereotype or ant... | Unrelated
| task279_stereoset_classification_stereotype | NIv2 | fs_opt | 1 | test |
Detailed Instructions: In this task, you are given a short passage that may convey stereotype, anti-stereotype, or is unrelated. A stereotype is an over-generalized belief about a particular group of people. An anti-stereotype is an idea that goes against a common stereotype. The passage is unrelated if it does not con... | Unrelated | task279_stereoset_classification_stereotype | NIv2 | fs_opt | 4 | validation |
Instructions: Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.
Input: Background info, I'm a sophomore i... | answerable | task503_scruples_anecdotes_isanswerable | NIv2 | zs_opt | 3 | train |
Teacher:Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.
Teacher: Now, understand the problem? Solve thi... | answerable | task503_scruples_anecdotes_isanswerable | NIv2 | zs_opt | 6 | train |
You will be given a definition of a task first, then some input of the task.
Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wro... | answerable | task503_scruples_anecdotes_isanswerable | NIv2 | zs_opt | 1 | train |
Detailed Instructions: Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.
Problem:I want to start this off... | answerable | task503_scruples_anecdotes_isanswerable | NIv2 | zs_opt | 8 | train |
Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.
[Q]: Due to uni/career/relationship, both my sister an... | answerable
| task503_scruples_anecdotes_isanswerable | NIv2 | fs_opt | 5 | train |
Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.
[EX Q]: Tell me ur opinions about it down in the comme... | answerable
| task503_scruples_anecdotes_isanswerable | NIv2 | fs_opt | 6 | train |
Given the task definition and input, reply with output. Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.... | answerable | task503_scruples_anecdotes_isanswerable | NIv2 | zs_opt | 5 | train |
Given the task definition and input, reply with output. Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.... | answerable | task503_scruples_anecdotes_isanswerable | NIv2 | zs_opt | 5 | train |
Teacher:Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.
Teacher: Now, understand the problem? Solve thi... | answerable | task503_scruples_anecdotes_isanswerable | NIv2 | zs_opt | 6 | test |
Given a real-life anecdote of a complex ethical situation, judge whether or not a specific person is wrong here. Answer 'not answerable' if more information is required and 'answerable' if all the information is sufficient to answer who is wrong in this situation.
Me and a friend of mine who's still in the closet (he ... | answerable | task503_scruples_anecdotes_isanswerable | NIv2 | zs_opt | 0 | validation |
I was once distinctly unsettled by a utility man who called to read the gas meter. We were living in an old house at the time and I was home alone with the youngest child (who was around six months old), balanced on my hip as I opened the door. The visitor looked genuine, dressed in the expected uniform. He was around ... | not enough information | quail_context_description_question_answer_text | P3 | fs_opt | 9 | train |
"If you can answer three questions," the dog said, "you can wear the magic shoes." Tommy looked up and down the deserted street. "Did you ... say something?" "That's right. Didn't you hear me?" It was a gruff voice, with just a trace of an English accent, and it was definitely coming out of the dog. "You're a dog." In ... | Looking stupid | quail_context_description_question_answer_text | P3 | zs_noopt | 7 | train |
WHITE HOUSE — U.S. President Donald Trump on Friday met for 80 minutes in the Oval Office with a general he described as the second most powerful man in North Korea. Afterward, Trump told reporters on the White House South Lawn that the June 12 summit in Singapore between him and North Korea's leader, Kim Jong Un, was ... | has developed a new device
------ | quail_context_description_question_answer_text | P3 | fs_opt | 5 | train |
Given the question: David Gauntlett makes a good point in his newest book (Making Media Studies: The Creativity Turn in Media and Communications Studies) and that is that traditional forms of media studies are no longer applicable. Gone are the days of massive institutions and production companies, gone are the traditi... | After his book was published | quail_context_description_question_answer_text | P3 | zs_noopt | 6 | train |
Answer the following question: If you visited the Getty Center in July or early August, you may have encountered a group of high school students wearing white lab coats with “Teen Lab” splattered across the back. You might have spotted them testing kinetic sculptures made from recycled materials, sketching in front of ... | Vera R. Campbell Foundation | quail_context_description_question_answer_text | P3 | zs_noopt | 5 | train |
Ques: U.S. President Donald Trump’s plan to impose tariffs of 25 percent on steel and 10 percent on aluminum has met criticism from his Republican allies in Congress, many of whom worry the measures could trigger a trade war that damages U.S. businesses. But the president does have supporters among some Senate Democrat... | after it's dry. | quail_context_description_question_answer_text | P3 | fs_opt | 7 | train |
The office smelled like money. Brand new carpet, somebody's expensive perfume still hanging in the air. The chairs in the waiting room are leather and the copy machine has a million attachments and there's pictures on the wall that I don't know what they're supposed to be. Made me ashamed of the shirt I was wearing, th... | ski scene | quail_context_description_question_answer_text | P3 | zs_opt | 7 | train |
Please answer the following question: Sondra Crench kicked a roach out of her way as she walked into her tiny apartment and sat down at her old laptop. It was after midnight. So, she figured her new friend, Jason, was already dead. And so were her hopes of landing a secretarial job in time to keep her apartment. Rent w... | To go home and look for work | quail_context_description_question_answer_text | P3 | zs_opt | 8 | train |
Yes, and I am not proud of it, but grief makes you do some really stupid things. My wife walked out of our 9 year marriage and into relationship on the same day with a (so-called) friend of mine that I had known for 25 years. I was completely blindsided and in shock. I was devastated, I was lost, and I was grieving ter... | Still has nuclear weapons | quail_context_description_question_answer_text | P3 | fs_opt | 8 | test |
Given the question: Roland felt his stomach knotting. Having ridden out of the city through the Saint-Denis Gate, he now was nearly home, and the hurt inside was cutting so deep that he thought it would drive him mad. He repeated again and again the pledge he had just made to Nicolette: I am your true troubadour, now a... | Nicolette | quail_context_description_question_answer_text | P3 | zs_opt | 6 | validation |
Detailed Instructions: Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buye... | rejected | task766_craigslist_bargains_classification | NIv2 | fs_opt | 4 | train |
Detailed Instructions: Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buye... | accepted | task766_craigslist_bargains_classification | NIv2 | zs_opt | 9 | train |
Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buyer seems likely to buy t... | rejected | task766_craigslist_bargains_classification | NIv2 | zs_opt | 0 | train |
Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buyer seems likely to buy t... | accepted | task766_craigslist_bargains_classification | NIv2 | zs_opt | 4 | train |
Q: Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buyer seems likely to bu... | rejected | task766_craigslist_bargains_classification | NIv2 | zs_opt | 7 | train |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two poss... | rejected | task766_craigslist_bargains_classification | NIv2 | fs_opt | 0 | train |
Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buyer seems likely to buy t... | accepted | task766_craigslist_bargains_classification | NIv2 | zs_opt | 0 | train |
instruction:
Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buyer seems li... | accepted
| task766_craigslist_bargains_classification | NIv2 | fs_opt | 9 | train |
Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buyer seems likely to buy t... | rejected
| task766_craigslist_bargains_classification | NIv2 | fs_opt | 1 | test |
Detailed Instructions: Given a text passage as input consisting of dialogues of negotiations between a seller and a buyer about the sale of an item, the task is to classify the text into one of the labels from the two possible outputs - 'accepted'/'rejected'. Select [accepted] if by the end of the conversation the buye... | rejected | task766_craigslist_bargains_classification | NIv2 | zs_opt | 9 | validation |
Detailed Instructions: The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (whereve... | Yes | task358_casino_classification_negotiation_uv_part | NIv2 | zs_opt | 9 | train |
Q: The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), output... | Yes | task358_casino_classification_negotiation_uv_part | NIv2 | zs_opt | 7 | train |
The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), output Ye... | No | task358_casino_classification_negotiation_uv_part | NIv2 | zs_opt | 0 | train |
The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), output Ye... | No
| task358_casino_classification_negotiation_uv_part | NIv2 | fs_opt | 6 | train |
The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), output Ye... | No
| task358_casino_classification_negotiation_uv_part | NIv2 | fs_opt | 0 | train |
Instructions: The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever availab... | Yes | task358_casino_classification_negotiation_uv_part | NIv2 | zs_opt | 3 | train |
The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), output Ye... | Solution: No | task358_casino_classification_negotiation_uv_part | NIv2 | fs_opt | 5 | train |
Teacher:The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), o... | No | task358_casino_classification_negotiation_uv_part | NIv2 | zs_opt | 6 | train |
The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (wherever available), output Ye... | No | task358_casino_classification_negotiation_uv_part | NIv2 | fs_opt | 9 | test |
Detailed Instructions: The input is taken from a negotiation between two participants who take the role of campsite neighbors and negotiate for Food, Water, and Firewood packages, based on their individual preferences and requirements. Given an utterance and recent dialogue context containing past 3 utterances (whereve... | Yes | task358_casino_classification_negotiation_uv_part | NIv2 | fs_opt | 4 | validation |
Detailed Instructions: In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
Q: Sentence: Th... | Hairdresser | task342_winomt_classification_profession_pro | NIv2 | zs_opt | 9 | train |
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
Input: Consider Input: Sentence: The ... | Output: Janitor
| task342_winomt_classification_profession_pro | NIv2 | fs_opt | 2 | train |
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
One example: Sentence: The carpenter h... | Clerk | task342_winomt_classification_profession_pro | NIv2 | fs_opt | 6 | train |
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
[EX Q]: Sentence: The receptionist he... | Analyst
| task342_winomt_classification_profession_pro | NIv2 | fs_opt | 6 | train |
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
[EX Q]: Sentence: The driver hit the ... | Chief
| task342_winomt_classification_profession_pro | NIv2 | fs_opt | 6 | train |
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
Sentence: The auditor caught the deve... | Developer | task342_winomt_classification_profession_pro | NIv2 | zs_opt | 0 | train |
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
Example Input: Sentence: The farmer d... | Assistant
| task342_winomt_classification_profession_pro | NIv2 | fs_opt | 3 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return... | Secretary | task342_winomt_classification_profession_pro | NIv2 | zs_opt | 1 | train |
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
Sentence: The laborer visited the cou... | Counselor | task342_winomt_classification_profession_pro | NIv2 | zs_opt | 0 | test |
In this task, you are given a sentence and a gender. The sentence mentions two professions: one's gender is unknown and the other's gender can be identified using the gendered pronouns that refer to them in the text. You are expected to return the profession with the given gender.
Example input: Sentence: The carpente... | Tailor | task342_winomt_classification_profession_pro | NIv2 | fs_opt | 3 | validation |
Definition: In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing re... | no_flight | task573_air_dialogue_classification | NIv2 | zs_opt | 2 | train |
instruction:
In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing r... | no_reservation
| task573_air_dialogue_classification | NIv2 | fs_opt | 9 | train |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following... | no_flight | task573_air_dialogue_classification | NIv2 | zs_opt | 1 | train |
In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing reservation, `... | book | task573_air_dialogue_classification | NIv2 | fs_opt | 6 | train |
Teacher:In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing reserv... | book | task573_air_dialogue_classification | NIv2 | zs_opt | 6 | train |
In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing reservation, `... | book | task573_air_dialogue_classification | NIv2 | zs_opt | 0 | train |
In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing reservation, `... | no_flight
| task573_air_dialogue_classification | NIv2 | fs_opt | 7 | train |
Instructions: In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing ... | book | task573_air_dialogue_classification | NIv2 | zs_opt | 3 | train |
In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing reservation, `... | no_flight | task573_air_dialogue_classification | NIv2 | fs_opt | 9 | test |
In this task, you are given a conversation between a flight agent and the customer. You are given 4 options and you need to select the goal of the conversation. It is provided as part of customer's context, which has to be one of the following: `book`: Make a new reservation, `cancel`: Cancel an existing reservation, `... | no_reservation
| task573_air_dialogue_classification | NIv2 | fs_opt | 7 | validation |
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