text string | labels string | task_name string | id string | category string | domain string | cluster_10 int64 | cluster_20 int64 | cluster_30 int64 | cluster_40 int64 |
|---|---|---|---|---|---|---|---|---|---|
Definition: In this task you will be given a list of numbers and you need to subtract every value in the list with the index it is at. The index of an elements shows its numerical order in the list(for example, in the list [7,10,4,5], the index of 7 is 1 and the index of 4 is 3) You should start the index at 1, so the... | [8, -1, 2] | task096_conala_list_index_subtraction | task096-aef0360d991c49bfb5b7d21e2ce32e60 | Program Execution | Code -> Repo -> Stack Overflow | 8 | 18 | 3 | 1 |
Definition: In this task, you are given concept set (with 3 to 5 concepts) that contain mentions of names of people, places, activities, or things. These concept sets reflect reasonable concept co-occurrences in everyday situations. All concepts given as input are separated by "#". Your job is to generate a sentence de... | a city leaves the station riding high above the traffic | task102_commongen_sentence_generation | task102-a6f570c601fd4784a01c7ccdb7b35901 | Data to Text | Captions -> Image Captions | 8 | 4 | 6 | 39 |
Definition: In this task, you're given a context passage, an answer, and a question. Your task is to classify whether the question for this answer is correct or not, based on the given context with commonsense reasoning about social situations. If its correct ,return "True" else "False".
Input: Context: Robin gave thei... | False | task384_socialiqa_question_classification | task384-12e7dc345e0045cd8645d0a054712980 | Question Understanding | Commonsense -> Concepts and Relations -> Social Commonsense | 5 | 19 | 16 | 24 |
Definition: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to choose whether the two sentences clearly agree (entailment)/disagree (contradiction) with each other, or if this cannot be determined (neutral). Your answer must be in the form of the numbers 0 (entailment), 1 (neutral... | 2 | task1612_sick_label_classification | task1612-32e0a5eb09924c5ca289e98a26a514bf | Textual Entailment | Captions -> Video Captions, Captions -> Image Captions | 0 | 8 | 2 | 29 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | How much was the settlement PG&E must pay? | task405_narrativeqa_question_generation | task405-5cdb0c7da99c4034a3fe8dfa23112578 | Question Generation | Books, Movies | 3 | 3 | 25 | 16 |
Definition: Given a premise, an initial context, an original ending, and a new ending, the task is to generate the counterfactual context that is aligned with the new ending. Each instance consists of a five-sentence story. The premise is the first sentence of a story, and the second sentence, which is the initial cont... | They play racing games a lot and it gets competitive. | task270_csrg_counterfactual_context_generation | task270-3a1af41c5e754ba7969dd8482d815743 | Story Composition | Story | 3 | 1 | 5 | 6 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Briscoe Center for American History | task303_record_incorrect_answer_generation | task303-206ae8624af74c84836554c6878a989b | Wrong Candidate Generation | News | 9 | 11 | 25 | 36 |
Definition: In this task, you are given a text which is the body of a document. You are given a question and options. Pick the correct number. Don't generate anything else apart from the numbers provided in options.
Input: Context: The Madagascar was a large British merchant ship built for the trade to India and China ... | 3 | task633_dbpedia_14_answer_generation | task633-98c1785b440f494fb8dba49e65ad759f | Text Categorization | Wikipedia | 4 | 19 | 10 | 26 |
Definition: In this task, you are given an input list. A list contains several comma-separated items written within brackets. You need to return the position of all the numerical elements in the given list in order. Assume the position of the 1st element to be 1. Return -1 if no numerical element is in the list.
Input:... | 1, 2, 3, 5, 7, 8, 9, 10, 12, 18, 19, 22, 24, 25, 26, 28, 31, 33, 35, 36, 38 | task507_position_of_all_numerical_elements_in_list | task507-adb4038445e5436d97b31eea84f260eb | Program Execution | Mathematics | 3 | 3 | 25 | 28 |
Definition: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to determine if the two sentences clearly agree/disagree with each other, or if this can't be determined. Indicate your answer as yes or no respectively.
Input: Sentence 1: Techniques and conventions that will come to see... | no | task199_mnli_classification | task199-204dd94fe7ed46f68602e99e3d99b989 | Textual Entailment | History, Fiction, Dialogue, Law, Government and Politics | 5 | 19 | 20 | 31 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Palm Beach County Sheriff's Office | task303_record_incorrect_answer_generation | task303-873fce94c2054b988c06b701615d20ef | Wrong Candidate Generation | News | 8 | 5 | 16 | 26 |
Definition: You are given a list of queries separated by new line. Your job is to answer with the query that is the most well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Input: What is the passcode to dr d computer in poptropica ?
What family do worms belong ?
The number of fo... | What is the highest basetball score ever ? | task675_google_wellformed_query_sentence_generation | task675-c5cbaaa9d20a47ecb2a9fc6ad28481bb | Text Quality Evaluation | Miscellaneous | 3 | 3 | 25 | 28 |
Definition: The input contains a debate topic, an argument on the topic and a keypoint, separated by "<sep>". Your task is to answer if the keypoint matches the argument and summarizes exactly what the argument means, in the context of the given topic.
Input: Topic: We should adopt libertarianism<sep>Argument: Libertar... | True | task1285_kpa_keypoint_matching | task1285-90a493f38c364e6a8dbe81c6d4c6dc16 | Text Matching | Reviews, Law, Dialogue, Government and Politics, Philosophy, World Religions | 2 | 15 | 14 | 22 |
Definition: In this task you will be given a list of integers. You should remove any integer that is not prime. A prime integer is an integer that is only divisible by '1' and itself. The output should be the list of prime numbers in the input list. If there are no primes in the input list an empty list ("[]") should b... | [733, 863, 499, 17, 809] | task366_synthetic_return_primes | task366-773fe2d93d53477bb9c1409053f18990 | Program Execution | Code, Mathematics | 6 | 13 | 17 | 9 |
Definition: You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answer to the qu... | Measuring the pH of a solution allows you to calculate the hydrogen ion concentration. | task045_miscellaneous_sentence_paraphrasing | task045-6df605f00d394107ae65d58569dcda97 | Paraphrasing | Natural Science | 8 | 17 | 23 | 25 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | Who is the first townsperson to die? | task405_narrativeqa_question_generation | task405-8aa73aa8de484104a9dae400f587406e | Question Generation | Books, Movies | 2 | 16 | 27 | 12 |
Definition: The input is a sentence. The sentence includes an emotion. The goal of the task is to classify the emotion in the sentence to one of the classes: 'fear', 'joy', 'anger', 'sadness'. The emotion mainly depends on the adverb within the sentence.
Input: The situation makes Frank feel fearful.
| fear | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | task1338-99fd2e64ae4b4908bde29b2abcdfdde3 | Sentiment Analysis | Commonsense, Dialogue, Narrative | 4 | 19 | 10 | 26 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | Who is the first to die on Prom Night? | task405_narrativeqa_question_generation | task405-9b9da9e9573f456bb3fd03a17c6d4303 | Question Generation | Books, Movies | 8 | 17 | 23 | 25 |
Definition: In this task you will be given a list of numbers and you need to subtract every value in the list with the index it is at. The index of an elements shows its numerical order in the list(for example, in the list [7,10,4,5], the index of 7 is 1 and the index of 4 is 3) You should start the index at 1, so the... | [-10, 7, -4, 5] | task096_conala_list_index_subtraction | task096-860cab016a45437199cf7f1db4a814e2 | Program Execution | Code -> Repo -> Stack Overflow | 6 | 13 | 17 | 9 |
Definition: In this task you will be given a text passage from a trivia quiz. You should choose the category this question belongs to from these categories: History, Science, Social Science, Fine Arts, Literature. You can only choose one category, so if in doubt, please choose the closest match.
Input: Kimberly Cornish... | Social Science | task521_trivia_question_classification | task521-d795900332a648eb941b256a7d435903 | Text Categorization | Art, Literature, History, Sociology, Natural Science | 0 | 14 | 0 | 4 |
Definition: In this task, you are given an article. Your task is to summarize the article in a sentence.
Input: However, that represented a fall, across all sports, of more than 10%, despite an increase in the number of tests carried out.
Athletics has been the subject of allegations of widespread doping.
And Wada has ... | Banned substances were found in more than 3,000 samples out of 283,304 tests carried out worldwide last year, World Anti-Doping Agency figures reveal. | task1290_xsum_summarization | task1290-db20827790f9400eba577ea786eb1a86 | Summarization | News | 8 | 18 | 15 | 1 |
Definition: The input contains a debate topic, an argument on the topic and a keypoint, separated by "<sep>". Your task is to answer if the keypoint matches the argument and summarizes exactly what the argument means, in the context of the given topic.
Input: Topic: We should legalize prostitution<sep>Argument: More pe... | True | task1285_kpa_keypoint_matching | task1285-1631390d6c9f451b9e6c580bb3024dec | Text Matching | Reviews, Law, Dialogue, Government and Politics, Philosophy, World Religions | 6 | 13 | 17 | 9 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | How does Sarah die? | task405_narrativeqa_question_generation | task405-2f3d1604a8bf419e9ca9abbb9e80399a | Question Generation | Books, Movies | 2 | 15 | 14 | 22 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: r... | select the row whose date record of all rows is 1st minimum . the opponent record of this row is cincinnati bengals . | task110_logic2text_sentence_generation | task110-ccc8552009f44b08960c644206669194 | Code to Text | Code -> Language -> SQL | 4 | 19 | 16 | 26 |
Definition: This task is about writing a correct answer for the reading comprehension task. Based on the information provided in a given passage, you should identify the shortest continuous text span from the passage that serves as an answer to the given question. Avoid answers that are incorrect or provides incomplete... | infectious disease | task075_squad1.1_answer_generation | task075-8ad668f9463a4c4bac289eafbbb861e2 | Question Answering | Wikipedia | 4 | 15 | 12 | 37 |
Definition: Given a paragraph about cooking, and a set of conversational questions and answers about the paragraph, say whether the passage contains sufficient information to answer the follow-up question. Say Yes if it is answerable; otherwise, say No. The paragraph has the prefix 'CONTEXT:'. Each conversation questio... | Yes | task1439_doqa_cooking_isanswerable | task1439-6d7a82b7d5bf408b85f8af4b2f0ac256 | Answerability Classification | Nutrition, Dialogue, Food | 8 | 18 | 24 | 0 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Rock Health | task303_record_incorrect_answer_generation | task303-b2e981a8e0934b1b921564f693409393 | Wrong Candidate Generation | News | 1 | 0 | 9 | 20 |
Definition: The given sentence contains a typo which could be one of the following four types: (1) swapped letters of a word e.g. 'niec' is a typo of the word 'nice'. (2) missing letter in a word e.g. 'nic' is a typo of the word 'nice'. (3) extra letter in a word e.g. 'nicce' is a typo of the word 'nice'. (4) replaced ... | esign | task088_identify_typo_verification | task088-b1dbadc220c64bd5aaf98fd0b966c6b0 | Spelling Error Detection | Commonsense -> Concepts and Relations | 8 | 4 | 6 | 39 |
Definition: In this task you are expected to fix an SQL query based on feedback. You will be given an SQL statement and an English description with what is wrong about that SQL statement. You must correct the SQL statement based off of the feedback. An SQL query works by selecting data from a table where certain condit... | SELECT T1.city FROM Addresses AS T1 JOIN Staff AS T2 ON T1.address_id = T2.staff_address_id WHERE T2.first_name = "Janessa" AND T2.last_name = "Sawayn" | task076_splash_correcting_sql_mistake | task076-6bf63ded20a8406f95babef08291b029 | Text to Code | SQL | 1 | 9 | 24 | 5 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Miami Dolphins | task303_record_incorrect_answer_generation | task303-954ac6521a9148c887193ccf848c8c25 | Wrong Candidate Generation | News | 5 | 19 | 20 | 31 |
Definition: In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You ha... | Yes | task1210_atomic_classification_madeupof | task1210-5e8491b49a3142749bd23d2fb9f4c851 | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Physical Commonsense, Commonsense -> Concepts and Relations -> Social Commonsense | 6 | 13 | 17 | 7 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Cornwall | task303_record_incorrect_answer_generation | task303-828c07cf047b4fbd8a2bba4e158d3d45 | Wrong Candidate Generation | News | 8 | 12 | 7 | 30 |
Definition: Given a sequence of actions to navigate an agent in its environment, provide the correct command in a limited form of natural language that matches the sequence of actions when executed. Commands are lowercase and encapsulate the logic of the sequence of actions. Actions are individual steps that serve as t... | look thrice and look left | task129_scan_long_text_generation_action_command_short | task129-71f01ac88ff143aba257b69e1fb385af | Code to Text | Computer Science -> Machine Learning | 3 | 3 | 25 | 16 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | What effect did the American Indian War have on Algren? | task405_narrativeqa_question_generation | task405-eb6b932ef7494a99b00e6e8e09c9e9fc | Question Generation | Books, Movies | 0 | 5 | 18 | 26 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Ted Cruz | task303_record_incorrect_answer_generation | task303-334481f3b8df40d0a3d8a7e686554f84 | Wrong Candidate Generation | News | 2 | 2 | 20 | 18 |
Definition: The given sentence contains a typo which could be one of the following four types: (1) swapped letters of a word e.g. 'niec' is a typo of the word 'nice'. (2) missing letter in a word e.g. 'nic' is a typo of the word 'nice'. (3) extra letter in a word e.g. 'nicce' is a typo of the word 'nice'. (4) replaced ... | istting | task088_identify_typo_verification | task088-15b2f9febc904f06a02e69b5f6b99768 | Spelling Error Detection | Commonsense -> Concepts and Relations | 0 | 5 | 18 | 15 |
Definition: Given a 'poster' sentence and a corresponding 'response' (often, from Facebook or Reddit)classify the sentiment of the given response into four categories: 1) Positive, 2) Negative, 3) Neutral, and 4) Mixed if it contains both positive and negative.
Input: Poster: Thank you Stone Mountain for such a moving ... | Positive | task823_peixian-rtgender_sentiment_analysis | task823-6ab183d7d1334c2a931cc6b528336a71 | Sentiment Analysis | Social Media | 0 | 8 | 29 | 26 |
Definition: In this task, you will be presented with a passage and have to answer a question based on your understanding of the events inferred from the passage. Try to find the best answer that is most likely to fill in "_". Note that the URLs in the text have been replaced with [Link].
Input: (CNN) Gov. Robert Bentle... | Rebekah Caldwell Mason | task339_record_answer_generation | task339-14914523e99a46bfa5d4e73c946ce49c | Question Answering | News | 0 | 19 | 16 | 26 |
Definition: In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event.... | Yes | task1197_atomic_classification_oreact | task1197-ad96a2ea002d42e5a45d3cc88aad5ded | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | 8 | 17 | 23 | 25 |
Definition: You are given a math word problem and you are supposed to only use subtraction on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Input: Context: Josh had 20 marbles in his collection. He gave 2 marbles to Jack.
Question: How many marbles... | 18 | task751_svamp_subtraction_question_answering | task751-7b82bd62ad2c4af7835a2a5fed0d56dd | Question Answering | Mathematics | 6 | 13 | 17 | 7 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | Who is the woman Alexander falls in love with while knighting for King Aruthur? | task405_narrativeqa_question_generation | task405-6eb9880e42fb4aedae89dc0cf743bd87 | Question Generation | Books, Movies | 6 | 13 | 17 | 9 |
Definition: Given reviews from Amazon, classify those review based on their content into two classes: Negative or Positive.
Input: I really liked the part when John Candy was at the firing range. This movie is one of Candy's greatest.
| Positive | task493_review_polarity_classification | task493-2c901320134847d3b6c1d130a9e769b8 | Sentiment Analysis | Reviews -> Electronics and Grocery | 0 | 14 | 0 | 29 |
Definition: Given a sequence of actions to navigate an agent in its environment, provide the correct command in a limited form of natural language that matches the sequence of actions when executed. Commands are lowercase and encapsulate the logic of the sequence of actions. Actions are individual steps that serve as t... | jump left and look opposite right | task129_scan_long_text_generation_action_command_short | task129-3ec92ab52c6b4e999668675d4a0e1bb0 | Code to Text | Computer Science -> Machine Learning | 6 | 13 | 17 | 8 |
Definition: In this task, you are given an article. Your task is to summarize the article in a sentence.
Input: Documents leaked by former US National Security Agency (NSA) contractor Edward Snowden in September have suggested that the NSA spied on Petrobras, Brazil's state oil giant.
The allegations caused uproar in B... | It was not quite the kind of attention Brazilian President Dilma Rousseff wanted to attract to her country's mining and oil riches. | task1290_xsum_summarization | task1290-4cb32077efb2446bbd0b524d30c78f6a | Summarization | News | 8 | 5 | 16 | 26 |
Definition: In this task, you are given concept set (with 3 to 5 concepts) that contain mentions of names of people, places, activities, or things. These concept sets reflect reasonable concept co-occurrences in everyday situations. All concepts given as input are separated by "#". Your job is to generate a sentence de... | helicopter coming in to land at an open day | task102_commongen_sentence_generation | task102-90bb09d5adfd403c8179ad4b0f2c1ef6 | Data to Text | Captions -> Image Captions | 8 | 18 | 11 | 5 |
Definition: In this task, you are given a text which is the body of a document. You are given a question and options. Pick the correct number. Don't generate anything else apart from the numbers provided in options.
Input: Context: Aneriophora is a little-known genus of hoverflies from South America.
Question: The docu... | 4 | task633_dbpedia_14_answer_generation | task633-b16ff88e2d2d4e89a602f8f1b4603189 | Text Categorization | Wikipedia | 2 | 16 | 14 | 22 |
Definition: In this task, you will be shown a short story with a beginning, two potential middles, and an ending. Your job is to choose the middle statement that makes the story coherent / plausible by writing "1" or "2" in the output. If both sentences are plausible, pick the one that makes most sense.
Input: Beginnin... | 2 | task069_abductivenli_classification | task069-4e78b787c49c4633b85bb42ef059e7e8 | Coherence Classification | Commonsense -> Stories | 5 | 19 | 20 | 31 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Melksham | task303_record_incorrect_answer_generation | task303-bcf35d30e3494f0096c8aa545734e781 | Wrong Candidate Generation | News | 8 | 12 | 7 | 33 |
Definition: Given a sequence of actions to navigate an agent in its environment, provide the correct command in a limited form of natural language that matches the sequence of actions when executed. Commands are lowercase and encapsulate the logic of the sequence of actions. Actions are individual steps that serve as t... | walk opposite right thrice after turn left twice | task129_scan_long_text_generation_action_command_short | task129-00115737282c41539657b1566b04f815 | Code to Text | Computer Science -> Machine Learning | 8 | 12 | 7 | 11 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Kaur | task303_record_incorrect_answer_generation | task303-ba8104b68a0546c4b777c56217625ac7 | Wrong Candidate Generation | News | 8 | 17 | 23 | 25 |
Definition: In this task, you are given triplets. Each triplet is in the form of [subject, predicate, object]. Your task is to generate proper sentence that utilizes these triples. The objective is to construct a sentence that (a) captures the facts specified in the triples and (b) is a well-formed sentence easily unde... | With high customer ratings, Zizzi's pub offers up Italian fare for the entire family. | task1409_dart_text_generation | task1409-fe82ea24baf44324b5d8db3152af9285 | Data to Text | Wikipedia | 8 | 17 | 23 | 25 |
Definition: In this task you are expected to fix an SQL query based on feedback. You will be given an SQL statement and an English description with what is wrong about that SQL statement. You must correct the SQL statement based off of the feedback. An SQL query works by selecting data from a table where certain condit... | SELECT district_name FROM district ORDER BY city_area ASC LIMIT 1 | task076_splash_correcting_sql_mistake | task076-211caa711808473399c73c90b01c77fa | Text to Code | SQL | 8 | 17 | 23 | 25 |
Definition: Given reviews from Amazon, classify those review based on their content into two classes: Negative or Positive.
Input: I find this book is in poor taste, notwithstanding the attempt to put a nice cover on it. Not authorship, but cut and paste out of the Bible. I did the same thing as a kid in CCD. But, make... | Negative | task493_review_polarity_classification | task493-4a71ba34d80245628805b6d9a61344f8 | Sentiment Analysis | Reviews -> Electronics and Grocery | 9 | 11 | 25 | 36 |
Definition: In this task, you are given product reviews about dvds. The goal is to classify the review as "POS" if the overall sentiment of the review is positive(the reviewer is satisfied) or as "NEG" if the overall sentiment of the review is negative(the reviewer is not satisfied).
Input: A Production of Peerless Qua... | POS | task477_cls_english_dvd_classification | task477-1dbf44c1abe04635a34da3dff8f6cbeb | Sentiment Analysis | Reviews -> Electronics and Grocery | 2 | 2 | 20 | 18 |
Definition: In this task, you're given a context passage, an answer, and a question. Your task is to classify whether the question for this answer is correct or not, based on the given context with commonsense reasoning about social situations. If its correct ,return "True" else "False".
Input: Context: Quinn hit a hom... | False | task384_socialiqa_question_classification | task384-90a73a851c894df48a14363f21640ad9 | Question Understanding | Commonsense -> Concepts and Relations -> Social Commonsense | 6 | 13 | 17 | 7 |
Definition: The input contains a debate topic, an argument on the topic and a keypoint, separated by "<sep>". Your task is to answer if the keypoint matches the argument and summarizes exactly what the argument means, in the context of the given topic.
Input: Topic: We should ban the use of child actors<sep>Argument: C... | True | task1285_kpa_keypoint_matching | task1285-15020efd7c82475d9869d28d76cd591c | Text Matching | Reviews, Law, Dialogue, Government and Politics, Philosophy, World Religions | 0 | 8 | 29 | 15 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | ABC | task303_record_incorrect_answer_generation | task303-a5670cf4d0104287885f12233a1b7df8 | Wrong Candidate Generation | News | 8 | 10 | 28 | 18 |
Definition: You are supposed to identify the category of a high-school level math question. There are five possible categories (1) algebra (2) arithmetic (3) measurement (4) numbers, and (5) probability. Use the following guidelines: (1) 'algebra' questions will typically contain letter variables and will ask you to fi... | algebra | task834_mathdataset_classification | task834-bcd4070a39c04bbd982f9b9d8c9e17c5 | Question Understanding | Mathematics | 0 | 1 | 5 | 19 |
Definition: In this task, you are given an input list. A list contains several comma-separated items written within brackets. You need to return the position of all the numerical elements in the given list in order. Assume the position of the 1st element to be 1. Return -1 if no numerical element is in the list.
Input:... | 2, 5, 8, 10, 11 | task507_position_of_all_numerical_elements_in_list | task507-db597712de37459b83eacff1a6f0d8f4 | Program Execution | Mathematics | 0 | 14 | 29 | 4 |
Definition: In this task, you need to answer the given multiple-choice question on the gain. Gain is the value by which to multiply the input. Classify your answers into 'a', 'b', 'c', 'd', and 'e'.
Input: Problem: a particular library has 150 books in a special collection , all of which were in the library at the begi... | e | task1419_mathqa_gain | task1419-4e258047e3ae4b829d2b11b0c084d4de | Question Answering | Mathematics | 1 | 7 | 1 | 27 |
Definition: Given reviews from Amazon, classify those review based on their content into two classes: Negative or Positive.
Input: Bought this camera for Christmas. Had her open it first so she could film the nights party & NO TAPES ARE INCLUDED! Of course all stores are closed Christmas day so the thing is USELESS unt... | Negative | task493_review_polarity_classification | task493-87548e6a74ca480b809965a35ccf0d70 | Sentiment Analysis | Reviews -> Electronics and Grocery | 5 | 19 | 20 | 31 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Washington | task303_record_incorrect_answer_generation | task303-443b39132a574580ba17f05298062b75 | Wrong Candidate Generation | News | 8 | 4 | 6 | 39 |
Definition: The input is a sentence. The sentence includes an emotion. The goal of the task is to classify the emotion in the sentence to one of the classes: 'fear', 'joy', 'anger', 'sadness'. The emotion mainly depends on the adverb within the sentence.
Input: I made my sister feel irritated.
| anger | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | task1338-2181181f9f39493a91a3ff90708f7a25 | Sentiment Analysis | Commonsense, Dialogue, Narrative | 8 | 12 | 7 | 33 |
Definition: Classify the given tweet into the three categories: (1) 'Hate Speech', (2) 'Offensive' and (3) 'Neither'. 'Hate Speech' is kind of a threating statement or sometimes include call for violence while 'offensive' statement just offensds someone. 'Neither' is when it doesn't fall into Hate Speech or Offensive c... | Offensive | task904_hate_speech_offensive_classification | task904-54fa071cdea14b8187f0b59837ea2c0a | Toxic Language Detection | Social Media -> Twitter | 6 | 13 | 17 | 7 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | CNN | task303_record_incorrect_answer_generation | task303-afc43eb2e64e4d0b805f74dd7cb15307 | Wrong Candidate Generation | News | 0 | 14 | 0 | 29 |
Definition: You are provided with an "Event", "Intent" and "XEmotion" (PersonX's reactions for the given "Event"). Indicate PersonY's reaction (person feels) at the end of this event. Provide one reaction for PersonY. If there's nothing that can be implied, respond as None
Input: Event:PersonX pulls PersonY's head back... | aroused | task924_event2mind_word_generation | task924-0b41f42bc36d4e1c9657da1a2b236177 | Misc. | Commonsense -> Concepts and Relations | 2 | 16 | 27 | 12 |
Definition: You are provided with an "Event", "Intent" and "XEmotion" (PersonX's reactions for the given "Event"). Indicate PersonY's reaction (person feels) at the end of this event. Provide one reaction for PersonY. If there's nothing that can be implied, respond as None
Input: Event:PersonX spends ___ in prison. Int... | sad | task924_event2mind_word_generation | task924-a6267a34b70f47be9a4116044cad22ac | Misc. | Commonsense -> Concepts and Relations | 8 | 10 | 28 | 18 |
Definition: In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Input: lNnkyCpWMhWV, whUnkyCptZWI
| nkyCp | task600_find_the_longest_common_substring_in_two_strings | task600-e265af9b6bd449d685f413ae7dd23cff | Program Execution | Mathematics | 0 | 14 | 0 | 4 |
Definition: Given a sequence of actions to navigate an agent in its environment, provide the correct command in a limited form of natural language that matches the sequence of actions when executed. Commands are lowercase and encapsulate the logic of the sequence of actions. Actions are individual steps that serve as t... | look opposite left twice and turn around right | task129_scan_long_text_generation_action_command_short | task129-00391d87adc44a13acc2e7790bf8b105 | Code to Text | Computer Science -> Machine Learning | 0 | 14 | 0 | 4 |
Definition: The input contains a debate topic, an argument on the topic and a keypoint, separated by "<sep>". Your task is to answer if the keypoint matches the argument and summarizes exactly what the argument means, in the context of the given topic.
Input: Topic: We should subsidize space exploration<sep>Argument: S... | False | task1285_kpa_keypoint_matching | task1285-c6412d93daac473a85b0782a32df93e9 | Text Matching | Reviews, Law, Dialogue, Government and Politics, Philosophy, World Religions | 0 | 8 | 29 | 15 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Parsons | task303_record_incorrect_answer_generation | task303-0434b53da83a478cba7584b1a867e530 | Wrong Candidate Generation | News | 2 | 16 | 14 | 22 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | Who becomes the Earl of Scroope? | task405_narrativeqa_question_generation | task405-6e63de339c1b404f9027f649660545f4 | Question Generation | Books, Movies | 8 | 18 | 11 | 5 |
Definition: In this task the focus is on physical knowledge about the world. Given the provided goal task in the input, describe a process that would lead to the asked outcome. This process often involves physical motions with objects, such as moving them, arranging them in a certain way, mixing them, shaking them, etc... | Set a pot of water to boiling. Hold the envelope over the steam. Carefully slip a butter knife under the seal peeling back the flap. Remove the contents. Reseal by firmly pressing into position. | task080_piqa_answer_generation | task080-ed5f91496572488cad8fa067416d4981 | Question Answering | Commonsense -> Concepts and Relations -> Physical Commonsense | 0 | 1 | 29 | 26 |
Definition: In this task, you will be shown a short story with a beginning, two potential middles, and an ending. Your job is to choose the middle statement that makes the story coherent / plausible by writing "1" or "2" in the output. If both sentences are plausible, pick the one that makes most sense.
Input: Beginnin... | 2 | task069_abductivenli_classification | task069-0437df6512cb4f20ba6324022c1ee990 | Coherence Classification | Commonsense -> Stories | 3 | 3 | 25 | 16 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | McCain Spaghetti Bolognese | task303_record_incorrect_answer_generation | task303-2cb4f45c656f418a987ac09ccdb7dd75 | Wrong Candidate Generation | News | 8 | 8 | 21 | 17 |
Definition: In this task you will be given a list of integers. You should remove any integer that is not prime. A prime integer is an integer that is only divisible by '1' and itself. The output should be the list of prime numbers in the input list. If there are no primes in the input list an empty list ("[]") should b... | [199] | task366_synthetic_return_primes | task366-f1ea5b5201a548d9b5b9ba6bd0b2bc42 | Program Execution | Code, Mathematics | 3 | 3 | 25 | 6 |
Definition: In this task, you are given an article. Your task is to summarize the article in a sentence.
Input: It is one of the hardest decisions any sportsman can make, because it is about stopping something you have devoted your life to.
Not just your adult life - university, and then a job - but your entire life, f... | Nico Rosberg's decision to retire from Formula 1 straight after winning the World Championship was bold, brave - and completely understandable. | task1290_xsum_summarization | task1290-62c7163d0ad54f7eb0a6cf64a07b0d27 | Summarization | News | 3 | 3 | 25 | 28 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | What captures Sheila? | task405_narrativeqa_question_generation | task405-022e67abf0af4b95a76f50501c2edef0 | Question Generation | Books, Movies | 8 | 8 | 21 | 17 |
Definition: In this task you will be given a list of integers. For every element in the list, if the element is positive you should multiply it by 2. If the element is negative you should multiply it by -3. The output should be a list of integers that is the result of applying that logic to the input list.
Note: A li... | [297, 15, 142, 78, 102, 80, 116, 166, 120, 84, 267] | task374_synthetic_pos_or_neg_calculation | task374-b772c8d91d7d4abd90e6e2b88a83fdcf | Program Execution | Code, Mathematics | 0 | 8 | 2 | 29 |
Definition: In this task, you are given a piece of an article. Your task is to generate a short summary of the text. Try to give the summary in just one sentence.
Input: Jeter said that he will retire after the 2014 season, according to a post on Facebook.
| Eni has won a license - 857 offshore Brazil. | task1355_sent_comp_summarization | task1355-cf31ca9f7f3a4e5b9ad45e618aa535a8 | Summarization | News | 9 | 11 | 25 | 6 |
Definition: In this task, you're given context and an answer. Your task is to generate the question for this answer based on the given context with commonsense reasoning about social situations..
Input: Context: Carson derived their powers from the consent form. They become very controlling.
Answer: pompous
| How would Carson feel afterwards? | task581_socialiqa_question_generation | task581-30479e7abe6d45c883cf8b52ff35b552 | Question Generation | Commonsense -> Concepts and Relations -> Social Commonsense | 0 | 8 | 2 | 13 |
Definition: In this task you will be given a list of integers. For every element in the list, if the element is positive you should multiply it by 2. If the element is negative you should multiply it by -3. The output should be a list of integers that is the result of applying that logic to the input list.
Note: A li... | [136, 231, 105, 162] | task374_synthetic_pos_or_neg_calculation | task374-5fc87f8e60044a1fba5fc23988e3995a | Program Execution | Code, Mathematics | 4 | 8 | 0 | 26 |
Definition: In this task, you're given context and an answer. Your task is to generate the question for this answer based on the given context with commonsense reasoning about social situations..
Input: Context: After Casey's first car broke down, she bought a car from a trusted friend.
Answer: save up the money to b... | What does Casey need to do before this? | task581_socialiqa_question_generation | task581-fa9a6fecfedf4e7582a939f4cc5eb048 | Question Generation | Commonsense -> Concepts and Relations -> Social Commonsense | 2 | 16 | 14 | 22 |
Definition: You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, th... | How did Sir Hugh and Archie Clavering die? | task405_narrativeqa_question_generation | task405-624a879a6ac0449193c65599ce85adb8 | Question Generation | Books, Movies | 6 | 13 | 17 | 7 |
Definition: You are given a list of integers and an integer target, return a list of a pair of numbers in any order such that they add up to target. If there is no such pair of numbers, then return an empty list
Input: [28, 32, 16, 19, 36, 8, 13, 38, 25, 1, 15, 42, 29, 49, 39, 31, 20, 35, 30, 37], target=43
| [42, 1] | task1087_two_number_sum | task1087-1721f9f58a7b4ba0bdd119b6ad111a0d | Program Execution | Mathematics | 0 | 5 | 18 | 26 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | FA of Ireland | task303_record_incorrect_answer_generation | task303-6249104ccd844cd286e966f2c02be309 | Wrong Candidate Generation | News | 3 | 3 | 25 | 16 |
Definition: You will be given a piece of text either about an everyday event, or a general statement. If the event seems a plausible event to you, or the general statement makes sense matches your commonsense, output 'True', otherwise output 'False'.
Input: Molly has been on a diet this summer and her friends noticed h... | False | task116_com2sense_commonsense_reasoning | task116-3cbb8baa17c54689a63dd17811f014aa | Commonsense Classification | Commonsense -> Concepts and Relations | 3 | 3 | 25 | 16 |
Definition: In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
Input: ahPbomjSH, rBbomynK
| bom | task600_find_the_longest_common_substring_in_two_strings | task600-68c3595f61de4d0b9ecf7345d376d7fd | Program Execution | Mathematics | 6 | 13 | 17 | 7 |
Definition: In this task, you will be presented with a passage, and you need to write an **implausible** answer to to fill in the place of "_". Your answer should be incorrect, but should not be out of context. Try using words that are related to the context of the passage, but are not the correct answer. Even though ... | Christian | task303_record_incorrect_answer_generation | task303-661b097ca93a49f798184e95cd4e99d0 | Wrong Candidate Generation | News | 2 | 16 | 14 | 22 |
Definition: The input is a sentence. The sentence includes an emotion. The goal of the task is to classify the emotion in the sentence to one of the classes: 'fear', 'joy', 'anger', 'sadness'. The emotion mainly depends on the adverb within the sentence.
Input: I made this girl feel annoyed.
| anger | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | task1338-51d4802260fe4f229abe0b9301712b67 | Sentiment Analysis | Commonsense, Dialogue, Narrative | 8 | 5 | 16 | 26 |
Definition: In this task, you are given an article. Your task is to summarize the article in a sentence.
Input: The expansion of the investigation meant no date could be given for when it would be concluded, South Yorkshire Police's chief constable said.
It comes after officers raided Sir Cliff's Berkshire home last Au... | A historical sex offence inquiry into singer Sir Cliff Richard has "increased significantly in size" and involves "more than one allegation", police say. | task1290_xsum_summarization | task1290-be1b8bb9c71d4b09bd82e246a7e6a799 | Summarization | News | 8 | 8 | 21 | 17 |
Definition: In this task the focus is on physical knowledge about the world. Given the provided goal task in the input, describe a process that would lead to the asked outcome. This process often involves physical motions with objects, such as moving them, arranging them in a certain way, mixing them, shaking them, etc... | Use chalkboard paint on the wood. | task080_piqa_answer_generation | task080-92567c36780747bbb817ddf95a04684e | Question Answering | Commonsense -> Concepts and Relations -> Physical Commonsense | 2 | 16 | 13 | 10 |
Definition: In this task, you're given context and an answer. Your task is to generate the question for this answer based on the given context with commonsense reasoning about social situations..
Input: Context: Riley has been sick and Cameron and his work is piling up at the office.
Answer: do their best
| What does Cameron need to do before this? | task581_socialiqa_question_generation | task581-1b257e6dbff24245b9fa10d3efdb80fa | Question Generation | Commonsense -> Concepts and Relations -> Social Commonsense | 8 | 17 | 23 | 25 |
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
Input: name[The Mill], eatType[pub... | A moderately price Indian pub in riverside is called The Mill. | task957_e2e_nlg_text_generation_generate | task957-6367bf5a6e4a4450bed50566bdf4e233 | Data to Text | Public Places -> Restaurants | 1 | 6 | 9 | 2 |
Definition: In this task you will be given a list of integers. You should remove any integer that is not prime. A prime integer is an integer that is only divisible by '1' and itself. The output should be the list of prime numbers in the input list. If there are no primes in the input list an empty list ("[]") should b... | [431, 691, 197, 193, 349, 379, 347, 571, 173, 43, 421, 983] | task366_synthetic_return_primes | task366-24edb31720784417ad1e59e706d48179 | Program Execution | Code, Mathematics | 2 | 16 | 13 | 10 |
Definition: The input contains a debate topic, an argument on the topic and a keypoint, separated by "<sep>". Your task is to answer if the keypoint matches the argument and summarizes exactly what the argument means, in the context of the given topic.
Input: Topic: We should introduce compulsory voting<sep>Argument: E... | False | task1285_kpa_keypoint_matching | task1285-fa011b4a8edd40f0ae9f2c4bc9f063b0 | Text Matching | Reviews, Law, Dialogue, Government and Politics, Philosophy, World Religions | 0 | 8 | 29 | 15 |
Definition: Given a premise, an initial context, an original ending, and a new ending, the task is to generate the counterfactual context that is aligned with the new ending. Each instance consists of a five-sentence story. The premise is the first sentence of a story, and the second sentence, which is the initial cont... | Three hours after leaving, the sea was still calm. | task270_csrg_counterfactual_context_generation | task270-95f948e1a2f14825bbcc52c286e1dd3e | Story Composition | Story | 8 | 18 | 15 | 1 |
Definition: You are given a question, its answer, and a sentence that supports the question, i.e., the answer to the question is inferable from the sentence. In this task, you need to paraphrase the given sentence so that the paraphrased sentence still supports the question i.e. you can still infer the answer to the qu... | Burning paper produces heat. | task045_miscellaneous_sentence_paraphrasing | task045-4b7d5d3dcf8d43c49f392b8d14c28c25 | Paraphrasing | Natural Science | 2 | 2 | 20 | 18 |
Definition: Given a sequence of actions to navigate an agent in its environment, provide the correct command in a limited form of natural language that matches the sequence of actions when executed. Commands are lowercase and encapsulate the logic of the sequence of actions. Actions are individual steps that serve as t... | jump after turn opposite right twice | task129_scan_long_text_generation_action_command_short | task129-f4144bb6aeef493993a308500cec6e91 | Code to Text | Computer Science -> Machine Learning | 2 | 2 | 20 | 18 |
Definition: In this task, you are given concept set (with 3 to 5 concepts) that contain mentions of names of people, places, activities, or things. These concept sets reflect reasonable concept co-occurrences in everyday situations. All concepts given as input are separated by "#". Your job is to generate a sentence de... | field of corn being harvested on an autumn day | task102_commongen_sentence_generation | task102-287feb2bea9240578b92e645e138f744 | Data to Text | Captions -> Image Captions | 8 | 10 | 28 | 18 |
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