inputs stringlengths 38 313k | targets stringlengths 0 4.86k | _template_idx int64 0 9 | _task_source stringclasses 1
value | _task_name stringlengths 19 85 | _template_type stringclasses 2
values | embedding listlengths 1.02k 1.02k |
|---|---|---|---|---|---|---|
Turn the given fact into a question by a simple rearrangement of words. This typically involves replacing some part of the given fact with a WH word. For example, replacing the subject of the provided fact with the word "what" can form a valid question. Don't be creative! You just need to rearrange the words to turn th... | What can help maintain pine forests?
| 5 | NIv2 | task040_qasc_question_generation | fs_opt | [
0.5300470590591431,
0.8616964221000671,
0.13277707993984222,
0.1491369605064392,
-0.2091154009103775,
-0.8532859086990356,
0.4375498592853546,
1.0662891864776611,
0.04569321125745773,
-0.27462178468704224,
-0.9596333503723145,
-0.19575092196464539,
-0.49135756492614746,
-0.2347668558359146... |
Classify the input text into either disfluent questions or proper questions. A disfluent question is a question that has some interruptions in it while framing. A proper question is the correct form of the question without any disfluency.
[EX Q]: In what battles were the Mongols battled no defeated by the Tran?
[EX A]... | disfluent
| 6 | NIv2 | task1623_disfl_qa_disfluent_question_classification | fs_opt | [
-0.023349184542894363,
0.3698003888130188,
-0.10279342532157898,
-0.26911020278930664,
-0.11834818124771118,
0.007110432256013155,
0.7642672657966614,
0.027334213256835938,
0.5079856514930725,
-0.0812789648771286,
-0.9041128158569336,
-1.3856123685836792,
-0.43232741951942444,
0.4446521997... |
In this task, you're given a review from Amazon's food products. Your task is to generate a rating for the product on a scale of 1-5 based on the review. The rating means 1: extremely poor, 2: poor, 3: neutral or mixed, 4: good, 5: extremely good.
Ex Input:
Love this soup. I have been eating this soup for a long tim... | 5
| 1 | NIv2 | task588_amazonfood_rating_classification | fs_opt | [
0.01581726036965847,
-0.42199110984802246,
0.12991556525230408,
0.051980674266815186,
0.22020867466926575,
-0.1065271720290184,
0.2754771113395691,
0.8896501064300537,
-0.4380510449409485,
0.3255175054073334,
0.08393760025501251,
-0.5183620452880859,
-0.9658291339874268,
-0.104554042220115... |
Definition: In this task, you're given two articles in the Thai language and the possible genre they belong to in the English language. Determine if the two articles share a positive sentiment on the given genre. Indicate your answer with Y for yes if they do and N for no if they don't. Genres available include: politi... | yes | 2 | NIv2 | task975_prachathai67k_same_genre_classification | zs_opt | [
0.04019618034362793,
-0.537541925907135,
0.1481662094593048,
0.057053036987781525,
0.7715511322021484,
-0.5561096668243408,
1.1052367687225342,
1.1250702142715454,
0.15507200360298157,
0.46654820442199707,
-0.2481183111667633,
0.4376823902130127,
-0.1985493302345276,
-0.2031983733177185,
... |
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.
Q: ['z', '5083', '... | 2, 8, 10, 12, 13, 14, 15, 16, 18, 20, 22, 23 | 4 | NIv2 | task507_position_of_all_numerical_elements_in_list | zs_opt | [
-0.21037641167640686,
0.5022914409637451,
-0.08433950692415237,
-0.10365040600299835,
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-0.025318775326013565,
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0.5210261940956116,
-0.38966649770736694,
0.13120806217193604,
-0.11763089895248413,
0.001994534861... |
Instructions: In this task, you are given a text from tweets. Your task is to classify given tweet text into two categories: 1) positive, and 2) negative based on its content.
Input: Making a really cute gift basket for shae! His last day
Output: | negative | 3 | NIv2 | task195_sentiment140_classification | zs_opt | [
-1.2880949974060059,
0.45250260829925537,
0.9550949335098267,
0.37577024102211,
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-0.7428916692733765,
-0.3342295289039612,
-0.13977962732315063,
-0.4727955162525177,
... |
Teacher:You are given a sentence in Galician. Your job is to translate the Galician sentence into Japanese.
Teacher: Now, understand the problem? Solve this instance: Pola contra, cando vostedes falan, empregan unha forma de telemetría non tan diferente do mando a distancia da súa televisión.
Student: | その代わりテレビに対してリモコンを使うのと似ていますが皆さんが話す時にはある種の遠隔測定法が使われています | 6 | NIv2 | task1239_ted_translation_gl_ja | zs_opt | [
-1.0138649940490723,
0.6109032034873962,
-0.150523379445076,
-0.5113731622695923,
-0.0034707053564488888,
-0.38392674922943115,
0.8215272426605225,
0.025484314188361168,
-0.11404133588075638,
-0.759114146232605,
-0.35665363073349,
0.07797810435295105,
-0.3834457993507385,
0.117016866803169... |
In this task, you're given the middle and ending of a three-part story. Your job is to complete the short story by writing a probable beginning of the story. Generated sentences must be short, have fewer than 10 words, and be simple as if narrating to a child. Avoid using any irrelevant extra information when creating ... | Joe was walking to school. | 3 | NIv2 | task072_abductivenli_answer_generation | fs_opt | [
-0.26486775279045105,
0.6923501491546631,
-0.27221375703811646,
-0.44701045751571655,
-0.38022059202194214,
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-0.2728303074836731,
-0.3701072335243225,
0.5857939720153809,
-0.025725577026605606,
-0.26066777110... |
Part 1. Definition
In this task, You are given an open-domain question that can be answered based on factual information. Your task is to provide \*short\* answer (in a few words only) for the given question. The short answer can be one or more entities or it can also be boolean \*yes\* or \*no\*.
Part 2. Example
when ... | Sean Patrick Astin | 7 | NIv2 | task582_naturalquestion_answer_generation | fs_opt | [
-0.042612504214048386,
0.5848788022994995,
0.24695107340812683,
-0.09559306502342224,
-0.13146613538265228,
-1.121894359588623,
0.9937400221824646,
0.3158113956451416,
-0.24105006456375122,
-0.543630838394165,
-0.4893583357334137,
-0.12059713155031204,
-0.7742190957069397,
-0.2549910247325... |
In this task, you are given a hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into two classes: political or non-political depending on the top... | non-political | 4 | NIv2 | task1491_bengali_political_hate_speech_binary_classification | zs_opt | [
-0.5378470420837402,
-0.2104077935218811,
0.3648165166378021,
0.6570520401000977,
-0.3972379267215729,
-0.49778175354003906,
-0.015866640955209732,
0.05840642750263214,
-0.6473298668861389,
0.026774099096655846,
-0.5165792107582092,
-0.3146815001964569,
-0.18342521786689758,
-0.49015286564... |
Given the task definition, example input & output, solve the new input case.
You are given a statement written in Hindi. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement. Output the word from the correct option .
Example: Statement: सिग्नेचर केल्विन क्... | इंडोनीशिया | 1 | NIv2 | task947_wiki_cloze_hi_multiple_choice_question_answering | fs_opt | [
0.3292708694934845,
0.5411232113838196,
-0.6273579001426697,
0.038170553743839264,
0.3191209137439728,
-0.7879934310913086,
-0.30271413922309875,
0.48594725131988525,
0.13269993662834167,
-0.3032218813896179,
0.26913467049598694,
0.07127940654754639,
-0.46876081824302673,
-0.18500800430774... |
Teacher:The input contains texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. Your task is to translate the given Yoruba sentence into the English language. Please bear in mind the ... | Sister Solovyev was also taken away by the police but in a separate vehicle from her husband. | 6 | NIv2 | task1620_menyo20k-mt_yo_en_translation | zs_opt | [
-0.476241797208786,
0.15970396995544434,
0.18134084343910217,
0.09722445905208588,
0.16291183233261108,
-0.31312453746795654,
0.0804087221622467,
0.6708622574806213,
0.18368008732795715,
-0.35865849256515503,
0.14142602682113647,
-0.04771573841571808,
-0.3834908902645111,
-0.09418945014476... |
instruction:
The input contains texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. Your task is to translate the given Yoruba sentence into the English language. Please bear in mind... | Whoever defames others defames himself or herself.
| 9 | NIv2 | task1620_menyo20k-mt_yo_en_translation | fs_opt | [
-0.19740800559520721,
0.346394807100296,
-0.09253391623497009,
0.1304708868265152,
0.25685352087020874,
-0.6200083494186401,
0.5086194276809692,
0.5063105821609497,
0.31299543380737305,
0.03571100905537605,
-0.37555521726608276,
0.2668493986129761,
-0.9514529705047607,
0.006736552342772484... |
In this task, you are given a sentence in Spanish and your task is to translate it into English. In translation, keep the numbers and capitalization (capitalize only the first word of each sentence and name).
Q: Bien está que hagamos todos, de mutuo consenso, un esfuerzo de racionalidad presupuestaria pero sea usted mu... | It is all very well for us, by mutual consensus, to make an effort in terms of budgetary rationalisation, but you must be very aware that the lack of resources, the absence of financial autonomy and the poor execution of the budget, continue to be urgent issues which must be resolved. | 4 | NIv2 | task531_europarl_es_en_translation | zs_opt | [
-0.24216386675834656,
1.0148048400878906,
0.6207863092422485,
-1.012892723083496,
-0.04424237832427025,
-0.7343604564666748,
0.9074236154556274,
0.7882426977157593,
-0.10968506336212158,
-0.005848322995007038,
-0.08665500581264496,
-0.016355400905013084,
-0.4261130690574646,
-0.12832576036... |
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 have to determ... | No
****
| 4 | NIv2 | task1215_atomic_classification_capableof | fs_opt | [
0.17339769005775452,
0.3788759112358093,
0.35316532850265503,
-0.004507146310061216,
-0.47497862577438354,
-0.9895254969596863,
1.1170613765716553,
0.520801305770874,
-0.2236310839653015,
-0.20551536977291107,
-0.5340385437011719,
-0.513160228729248,
-0.5421978235244751,
0.259835422039032,... |
Teacher: In this task, you are given a context tweet and an answer. Your job is to generate a question for the given answer based on the given tweet paragraph. Note that your question should be answerable based on the given tweet, and the answer to your question should be the given answer.
Teacher: Now, understand the ... | who is flying to meet with lebron's agent? | 2 | NIv2 | task240_tweetqa_question_generation | fs_opt | [
-0.03758269175887108,
0.5765556693077087,
0.04532512277364731,
-0.4233488142490387,
0.43642109632492065,
-0.14640963077545166,
-0.080392986536026,
-0.32163795828819275,
-0.40834346413612366,
-0.26923978328704834,
-0.15908057987689972,
-0.2803332209587097,
-0.05175727605819702,
-0.384100377... |
Definition: You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to label each of the continuous conversations done by one speaker with the emotion detected in that particular part. Your labels can be one among the following: 'No emotio... | No emotion,No emotion,No emotion,No emotion,No emotion,No emotion,happiness,happiness,No emotion,No emotion,No emotion,No emotion,happiness | 2 | NIv2 | task1532_daily_dialog_emotion_classification | zs_opt | [
-0.3433402180671692,
0.266232430934906,
-0.14443865418434143,
-0.4353518784046173,
-0.09293905645608902,
-0.5452952980995178,
0.6446834802627563,
-0.41541916131973267,
-0.03969584405422211,
-0.6174920797348022,
-0.18472205102443695,
-0.18262401223182678,
-0.16039489209651947,
0.63050830364... |
Q: 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.
The conversation with my brother was threatening.
A: | fear | 7 | NIv2 | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | zs_opt | [
-0.4140278995037079,
0.6261773705482483,
0.5616449117660522,
-0.9067062139511108,
-0.44927114248275757,
-0.39229151606559753,
1.049376130104065,
0.4812527298927307,
0.30817389488220215,
-0.7065945267677307,
-0.7876351475715637,
-0.6321954727172852,
-0.7482929825782776,
-0.34205105900764465... |
Given a sentence and two mentions from the text (arguments), indicate a phrase (a verb or noun phrase) that describes the relationship between the provided arguments.
[EX Q]: Sentence: 'They often see great works of God done with their eyes , but they do not eat thereof .', Argument/Subject 1: 'great', Argument/Subjec... | be suburb in
| 6 | NIv2 | task676_ollie_relationship_answer_generation | fs_opt | [
-0.29406899213790894,
0.08144664764404297,
0.6306192874908447,
-1.1455063819885254,
-0.17611253261566162,
-1.0682023763656616,
0.08803784847259521,
0.5774790048599243,
0.10693219304084778,
-0.5912623405456543,
0.3853095471858978,
-0.2727705240249634,
-0.43893957138061523,
-0.37813633680343... |
instruction:
Given a command in a limited form of natural language, provide the correct sequence of actions that executes the command to thus navigate an agent in its environment. A command can be broken down into many different actions. Actions are uppercase and are individual steps that serve as the building blocks f... | I_RUN I_RUN I_RUN I_RUN
| 9 | NIv2 | task126_scan_structured_text_generation_command_action_all | fs_opt | [
0.20409375429153442,
0.8021048307418823,
-0.49150100350379944,
0.29714125394821167,
-0.2675907015800476,
-0.36016222834587097,
-0.021641023457050323,
0.11650767922401428,
-0.223602294921875,
-0.012009527534246445,
-1.033479928970337,
0.058478906750679016,
-0.46278953552246094,
-0.070273861... |
In this task, you're given a dialogue between a customer and a flight booking agent with a gap in the conversation. Your job is to find the answer of the previous dialogue. Avoid using irrelevant extra information while creating the answer. The answer should be relevant to the question before the blank. If you fill the... | agent: May I know your connection limit? | 3 | NIv2 | task574_air_dialogue_sentence_generation | fs_opt | [
-0.0013213809579610825,
-0.10965927690267563,
-0.1445446014404297,
-0.6023107767105103,
0.6245121359825134,
-0.3435305953025818,
1.3215856552124023,
-0.24209779500961304,
-0.3427716791629791,
-0.04018303379416466,
0.1525181531906128,
-0.19825495779514313,
-0.43797242641448975,
0.2164968997... |
In this task you are given a tweet. You must judge whether the author of the tweet is sad or not. Label the instances as "Sad" or "Not sad" based on your judgment. You can get help from hashtags and emojis, but you should not judge only based on them, and should pay attention to tweet's text as well.
Q: @TouchPH The s... | Sad | 4 | NIv2 | task399_semeval_2018_task1_tweet_sadness_detection | zs_opt | [
-1.1369870901107788,
0.3790135681629181,
0.6623204946517944,
-0.3406871557235718,
-0.32408761978149414,
-0.5590542554855347,
0.5818636417388916,
0.4480336904525757,
0.5216124653816223,
0.9591766595840454,
-0.9807342290878296,
-0.039815668016672134,
-0.3729133605957031,
-0.2009652853012085,... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence in English, and your task is to translate it into Persian.
So it is, so it is, he thought, shutting his knife with a snap.
Output: | با خود گفت، همین طور است، همین طور است و چاقویش را با صدای تقی بست. | 1 | NIv2 | task661_mizan_en_fa_translation | zs_opt | [
-0.44413238763809204,
0.7556681632995605,
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-0.11997556686401367,
0.1359184831380844,
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0.7363395094871521,
0.44028520584106445,
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-0.31836968660354614,
0.34341681003570557,
-0.7493271231651306,
-0.00589626096189022... |
Given the task definition, example input & output, solve the new input case.
Given a review text from amazon and its polarity (either positive or negative). Generate answer "True" if given sentence and its polarity match, otherwise generate answer "False". A review is considered positive if the reviewer is satisfied wi... | False | 1 | NIv2 | task494_review_polarity_answer_generation | fs_opt | [
-0.1495991349220276,
-0.34601283073425293,
-0.06591515243053436,
0.23721952736377716,
0.5497258901596069,
-0.21577396988868713,
0.6022272706031799,
0.5673805475234985,
-0.06237155944108963,
-0.06398970633745193,
-0.6162344813346863,
0.37302660942077637,
-0.40120989084243774,
-0.79767996072... |
Given a paragraph, generate a claim that is supported by the given paragraph. 1) The claim must contain information from within the paragraph. 2) A sentence within the paragraph can be used as a claim. 3) The claim should not have contradictions within the paragraph. 4) The claim should be at most one sentence long.
E... | Climate fears lift Greens' chances of running Germany.
| 3 | NIv2 | task1368_healthfact_sentence_generation | fs_opt | [
0.5400360226631165,
0.3371773362159729,
-0.7183974981307983,
0.2476489245891571,
0.3693469762802124,
-0.5292410850524902,
0.4931284487247467,
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-0.2311900407075882,
0.3903837203979492,
-0.18788929283618927,
0.13512247800827026,
-0... |
We would like you to classify each of the following sets of argument pairs (discussing Gay Marriage) into either SIMILAR or NOT SIMILAR. A pair of arguments is considered SIMILAR if the arguments are about the same FACET (making the same argument), and is considered NOT SIMILAR if they do not have the same FACET. A FA... | Similar | 6 | NIv2 | task147_afs_argument_similarity_gay_marriage | fs_opt | [
-0.23044008016586304,
0.462388277053833,
-0.39466723799705505,
0.2782628536224365,
0.7398099899291992,
-0.41332778334617615,
0.985209584236145,
1.1204609870910645,
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-0.9983857870101929,
0.9656518697738647,
-0.8813124895095825,
-0.4084901809692383,
... |
In this task, you are given a sentence from the research paper and the category to which it belongs. Your task is to classify whether the given category is correct or not by providing "True" and "False", respectively. Here are the definitions for the categories: Background (Why is this problem important? What relevant ... | True
| 0 | NIv2 | task1164_coda19_section_correction_classification | fs_opt | [
-0.8608477115631104,
0.5405147671699524,
-0.45727187395095825,
0.3880336582660675,
-0.03629487007856369,
0.264117956161499,
0.2301691323518753,
1.4932072162628174,
0.1045801043510437,
-0.0032106025610119104,
-1.1913872957229614,
-0.11747066676616669,
-0.3301636874675751,
-0.075171634554862... |
In this task, you are given a sentence. You must judge whether a single noun or verb has been replaced with another word with the same part of speech. The inversion would result in the sentence sounding unnatural, So unnatural sentences will be considered changed. Label the instances as "Original" or "Changed" based on... | Solution: Changed | 5 | NIv2 | task515_senteval_odd_word_out | fs_opt | [
-0.6256709694862366,
1.1013519763946533,
0.3192545771598816,
-0.8071620464324951,
0.08085676282644272,
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0.6861593723297119,
0.3621698021888733,
0.4529198408126831,
-0.3445298373699188,
-0.5412558317184448,
-0.3928062319755554,
-1.0444148778915405,
0.10082117468118668,
... |
In this task, you are given a string with unique characters in it and you need to return the character from the string which has the maximum ASCII value. ASCII stands for American Standard Code For Information Interchange and It assigns a unique number to each character. The characters [a - z] have an ASCII range of 97... | w | 9 | NIv2 | task1148_maximum_ascii_value | fs_opt | [
0.08047384023666382,
0.10396499931812286,
-0.011519089341163635,
-0.30398839712142944,
-0.22863714396953583,
-0.7606624364852905,
0.6507237553596497,
-0.3047504425048828,
0.884448766708374,
0.1848198026418686,
-0.3253450095653534,
0.5792790651321411,
-0.26965898275375366,
0.339977324008941... |
This task is about identifying the subject of a given sentence. The subject of a sentence is the person, place, or thing that is performing the action of the sentence. The subject represents what or whom the sentence is about. Each sentence in this task is guaranteed to contain a single subject. The input is a sentence... | A Wizard of Mars | 0 | NIv2 | task1411_dart_subject_identification | zs_opt | [
-0.3354399800300598,
0.819398820400238,
-0.017655786126852036,
-0.867043137550354,
-0.17513611912727356,
0.38986289501190186,
0.7619272470474243,
-0.14649897813796997,
0.2933579981327057,
-0.36538487672805786,
-1.1205461025238037,
-0.4259123206138611,
-0.5532090067863464,
0.314544737339019... |
In this task you are given a sentence. You must judge whether there exist two consecutive words within the sentence with flipped orders, that is, whether the sentence will make sense and be correct if the order of two consecutive words changes. Label the instances as "Inversion" or "Original" based on your judgment.
Q:... | Inversion | 4 | NIv2 | task428_senteval_inversion | zs_opt | [
-0.8632532954216003,
0.6528277397155762,
0.606974184513092,
-0.1587030589580536,
-0.027169624343514442,
0.11518561840057373,
0.8318791389465332,
0.5414148569107056,
0.5107554793357849,
-0.2176322340965271,
-1.0592023134231567,
-0.5853710770606995,
-0.6683940887451172,
-0.060088105499744415... |
In this task, you are given a sentence and a question, you would be asked to create the answer which is contained in the sentence provided.
Example Input: Sentence: Iridescent green beetles, known as jewel beetles, change color because of the light-reflecting properties of the cells that make up this? Question: Irides... | solid
| 3 | NIv2 | task1555_scitail_answer_generation | fs_opt | [
-0.19162854552268982,
0.27956467866897583,
-0.10756225883960724,
-0.09347639977931976,
-0.13893550634384155,
-0.38561004400253296,
-0.12294115126132965,
1.275509238243103,
-0.30362561345100403,
0.2187047153711319,
-0.3967057168483734,
0.55960613489151,
-0.5613602995872498,
-0.0319709479808... |
Teacher: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 i... | CONJ | 6 | NIv2 | task1168_brown_coarse_pos_tagging | zs_opt | [
0.44059640169143677,
0.10519857704639435,
-0.09841702878475189,
0.13682422041893005,
-0.08919010311365128,
-0.9124100208282471,
0.7153950929641724,
0.7678549289703369,
-0.26594728231430054,
0.08815845847129822,
-0.44837117195129395,
0.08689704537391663,
-0.7752627730369568,
0.2545819878578... |
You are given a sentence in Galician. Your job is to translate the Galician sentence into Spanish.
[EX Q]: E tras facer isto catro ou cinco veces, nadou cara a min cunha mirada de desalento.
[EX A]: Y después de hacer esto 4 ó 5 veces nadó a mi lado con esta mirada abatida en su rostro.
[EX Q]: De feito, ten moito ta... | Si no nos satisfaces, es que tu inglés no es lo suficientemente bueno.
| 6 | NIv2 | task1240_ted_translation_gl_es | fs_opt | [
-0.7125504016876221,
0.975899338722229,
0.24766263365745544,
-0.6609717011451721,
0.09246616810560226,
-0.694433867931366,
0.7168439626693726,
0.8185158967971802,
-0.012100057676434517,
-0.8256881237030029,
-0.7268650531768799,
0.37131863832473755,
-0.4781686067581177,
0.5532376170158386,
... |
Given the task definition and input, reply with output. You will be given a context and a question in Spanish. Your job is to generate answers that are at least THREE words long.
The answers need to be context specific and can not be general knowledge or a random guess.
CONTEXT: Biografía del personaje y cronología
... | Batman Confidential número catorce | 5 | NIv2 | task1334_sqac_answer_generation | zs_opt | [
1.1055703163146973,
-0.05202791839838028,
-0.10960999131202698,
0.24455399811267853,
0.44451478123664856,
-0.4587984085083008,
0.6789634823799133,
0.5878924131393433,
0.12282334268093109,
0.19873513281345367,
-0.4537869989871979,
0.9616448879241943,
-0.6614437103271484,
0.05583438277244568... |
You are given a review about a place. You need to provide a rating from "1 star" to "5 stars" for this place.
Q: Huge fan of Tofu Hut when it comes to AYCE Korean BBQ. The one downside to this place is it's quite small. Only half the restaurant is dedicated to BBQ and the other half regular menu service. So with that ... | 4 stars | 4 | NIv2 | task1292_yelp_review_full_text_categorization | zs_opt | [
0.2544384002685547,
0.4456412196159363,
0.11992466449737549,
-0.10612615197896957,
0.8785226941108704,
-0.6766120791435242,
0.22005140781402588,
0.4505162239074707,
-0.17715007066726685,
0.6950914263725281,
0.6645575761795044,
-0.1319599449634552,
-0.6169818639755249,
0.4012134075164795,
... |
Definition: Given a sentence, an entity and its sentiment towards the entity, verify if it is the correct sentiment towards the entity. Answer should be yes or no. Note that URLs in the text have been replaced with [Link].
Input: Verify if the sentiment of the following document towards the entity Taylor Swift is Neutr... | yes | 2 | NIv2 | task422_persent_sentence_sentiment_verification | zs_opt | [
-0.8093392848968506,
-0.142537921667099,
0.43392759561538696,
0.3003470301628113,
0.6817961931228638,
-0.9304428100585938,
-0.2798767685890198,
0.2030109018087387,
0.28814974427223206,
0.6292531490325928,
0.4558715224266052,
-0.07048690319061279,
-0.4408266544342041,
-0.7513030171394348,
... |
You are given a sentence in English. Your job is to translate the English sentence into Persian.
[EX Q]: I showed that to you already, like we looked at the fact that despite a lot of screen time, those action gamers have a lot of very good vision, etc.
[EX A]: من این را پیش از این به شما نشان دادم ، مثل اینکه با وجود... | آنچه که این نشان می دهد ، آنچه که لحاظ تجربی نشان می دهد ، این است که تولید ناخالص داخلی حقیقت زندگی مردم را نشان نمیدهد.
| 6 | NIv2 | task1093_ted_translation_en_fa | fs_opt | [
-0.41333621740341187,
0.4357614517211914,
-0.7877441644668579,
-0.4002152681350708,
-0.8636325001716614,
-0.15299303829669952,
1.0714102983474731,
0.3867000341415405,
0.2328406572341919,
-0.43550950288772583,
0.0796610414981842,
0.7898298501968384,
-0.837221622467041,
-0.09900256246328354,... |
In this task, you are given a multiple-choice question and you have to pick the correct option. Answer with option indexes (i.e., "A", "B", "C", and "D").
Example: Deserts are in extremely dry environments, so liquids will naturally be (A) rainbow (B) plentiful (C) meager (D) talented
Example solution: C
Example explan... | Solution: D | 5 | NIv2 | task1286_openbookqa_question_answering | fs_opt | [
0.12086115032434464,
0.34552672505378723,
-0.26501789689064026,
-0.17286941409111023,
-0.086143359541893,
0.03210296481847763,
0.47818154096603394,
0.8304175138473511,
-0.0963490903377533,
0.2209501415491104,
-0.41271206736564636,
-0.6441071033477783,
-0.32414525747299194,
-0.2574197649955... |
Given the task definition and input, reply with output. Given a real-life anecdote of a complex ethical situation, identify who is wrong here. Classify each post into the following categories : AUTHOR (if the author of the post is wrong in the situation), OTHER (if any of the others mentioned in the paragraph is wrong)... | OTHER | 5 | NIv2 | task498_scruples_anecdotes_whoiswrong_classification | zs_opt | [
0.998808741569519,
-0.3043808937072754,
-0.4878581762313843,
-0.16957318782806396,
0.2692226767539978,
0.09959925711154938,
0.966038167476654,
0.9142019748687744,
0.30832117795944214,
-0.12938450276851654,
0.04421514645218849,
0.21232527494430542,
-0.8184189200401306,
0.2121182084083557,
... |
Given the task definition and input, reply with output. In this task, you will be given a short story. One sentence from the story is chosen. Consider the events that happen before that sentence, or are likely to have happened before it. Does any of them directly cause it, or simply make it possible? You should write y... | Fred had to take SAT test >Causes/Enables> he was finished his test within two hours | 5 | NIv2 | task614_glucose_cause_event_detection | zs_opt | [
-0.2853695750236511,
0.5799307823181152,
0.24947014451026917,
-0.11542221903800964,
-0.022513560950756073,
-0.6849237680435181,
-0.025682585313916206,
0.9959145784378052,
0.1548796147108078,
0.222744882106781,
-0.6185590028762817,
0.24366134405136108,
-0.2580864429473877,
-0.48845934867858... |
Evaluate the similarity between them and classify them into classes from 0-5 as follows:
0 : The two sentences are completely dissimilar.
1 : The two sentences are not equivalent, but are on the same topic.
2 : The two sentences are not equivalent, but share some details.
3 : The two sentences are roughly equivalent, b... | 3
****
| 4 | NIv2 | task1347_glue_sts-b_similarity_classification | fs_opt | [
-0.2742502987384796,
-0.02382948249578476,
-0.2797814607620239,
-0.06934095174074173,
0.5174246430397034,
-0.9024931788444519,
0.6134675741195679,
1.1800442934036255,
0.37702763080596924,
0.7592993378639221,
-0.38242587447166443,
-0.544402003288269,
-0.7296255826950073,
-0.3375188708305359... |
Detailed Instructions: You will be given a text in the Russian language, and you should classify the given input text to one of the emotion labels from this list of emotion labels- ['joy', 'sadness', 'surprise', 'fear', 'anger']. Make sure your output label (i) is strictly present in the given list of emotion labels. (... | joy | 9 | NIv2 | task1662_cedr_ru_classification | zs_opt | [
-0.5557563900947571,
-0.3313218355178833,
0.18834376335144043,
-0.3037286400794983,
-0.4922032356262207,
-0.3329610824584961,
0.5371407270431519,
0.9606439471244812,
0.10492420196533203,
-0.19189275801181793,
-0.6528729200363159,
0.060125187039375305,
0.16101425886154175,
0.364663451910018... |
You are given a sentence in Persian. Your job is to translate the Farsi sentence into Italian.
Example Input: یک عضو مصنوعی ، دیگر برای رفع نیاز به جایگزینی یک عضو از دست رفته ، ارائه نمی شد
Example Output: Una protesi ad un arto non rappresenta più il bisogno di rimpiazzare una perdita.
Example Input: بیشتر افراد ای... | Questi meccanismi lavorano a nostro grosso discapito.
| 3 | NIv2 | task1271_ted_translation_fa_it | fs_opt | [
-0.3480302691459656,
0.558207631111145,
-0.669021487236023,
0.47934553027153015,
-0.3779170513153076,
-0.14662815630435944,
0.655031144618988,
0.8300550580024719,
0.2487277388572693,
-0.09870459139347076,
-0.9344773292541504,
0.5713090896606445,
0.2978920042514801,
0.5684559941291809,
0.... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a text of article and corresponding title of an article. Your task is to generate label "yes" if headline (title) is right for article, otherwise generate "no".
Article: the coastal city of galveston , texas faces ... | yes | 1 | NIv2 | task289_gigaword_summarization | zs_opt | [
-0.8757885694503784,
0.5441334247589111,
0.4858282506465912,
0.11986112594604492,
0.41488349437713623,
-0.8067768812179565,
0.41487783193588257,
0.5059671401977539,
-0.35239237546920776,
0.449199914932251,
-0.24971535801887512,
-0.40846461057662964,
-0.6231774091720581,
0.27688366174697876... |
Your task is to generate the next utterance in a given dialogue. You will be given a few sentences describing the personality of the person who is making the dialogue, and a history of the dialogue after that. Each line in the history is said by one of the two participants in the conversation.
[Q]: Personality: I like... | Music is life... dancing to anything with a beat is the best.
| 5 | NIv2 | task1729_personachat_generate_next | fs_opt | [
-0.08156701177358627,
0.4371364712715149,
-0.8193267583847046,
0.5630649328231812,
-0.5495824813842773,
-0.4797223210334778,
0.6128947734832764,
0.2422555536031723,
-0.17922651767730713,
-0.4718285799026489,
0.040533971041440964,
0.5465477108955383,
-1.0014128684997559,
-0.0929195731878280... |
In this task you are given an anecdote, which recount a complex ethical situation. The question you are given is, has the author of the anecdote acted ethically? answer this question with "RIGHT" or "WRONG".
Let me give you an example: My boyfriend (well just call him M) and I are creators on Instagram (he is also on ... | RIGHT | 8 | NIv2 | task224_scruples_anecdotes_ethical_judgment | fs_opt | [
0.10275866836309433,
0.31756851077079773,
0.24033711850643158,
-0.13415348529815674,
0.27257683873176575,
-0.5667851567268372,
0.5459946990013123,
0.45487236976623535,
-0.3227059543132782,
-0.1203950047492981,
-0.3427717685699463,
0.7856475114822388,
-0.41613298654556274,
0.001096662599593... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
この新しい検出器を使うと腫瘍の外郭が見えるようになります
Output: | Ale dzięki naszemu nowemu detektorowi, zaczął wyłaniać się zarys guza. | 1 | NIv2 | task1097_ted_translation_ja_pl | zs_opt | [
0.11444617062807083,
0.5903176069259644,
-0.06441417336463928,
-0.026580315083265305,
0.001763002946972847,
-0.32850348949432373,
-0.10312087833881378,
0.21044163405895233,
0.792188823223114,
-0.11975792050361633,
-0.5426552295684814,
0.2518358528614044,
0.03871835768222809,
0.558347642421... |
Instructions: In this task, you will use your knowledge about language (and common sense) to determine what element the marked number refers to. The numbers are marked with two underlines around them, like: _ number _. Your answer should be chosen from the given text, and should not contain other words.
Input: A.J. Mul... | marker | 3 | NIv2 | task401_numeric_fused_head_reference | zs_opt | [
-0.06823479384183884,
0.8023087978363037,
-0.40152257680892944,
-0.20444676280021667,
0.12821902334690094,
-0.5552054643630981,
0.6532620787620544,
0.8316597938537598,
0.14354923367500305,
0.05315965414047241,
-0.21708965301513672,
0.20447894930839539,
-0.1413598209619522,
-0.1045150905847... |
This task is about translating a given French language sentence to English.
Q: Nous devons comprendre mais nous devons aussi commencer à gérer et protéger.
A: | We need to better understand, but we also need to start to manage and protect. | 4 | NIv2 | task1690_qed_amara_translation | zs_opt | [
-0.052377618849277496,
1.529369831085205,
0.9030176401138306,
-0.6375876665115356,
-0.4013120234012604,
-1.4669519662857056,
-0.050965145230293274,
0.15171165764331818,
0.6994171738624573,
-0.018993383273482323,
-0.2543952465057373,
-0.42532384395599365,
-1.2288570404052734,
0.346970677375... |
Detailed Instructions: Given an Amazon review, indicate whether it is a 'Positive Review' or 'Negative Review'.
Problem:When you want something, just go ahead and buy it rather than shopping for the cheapest. I bought this trying to save a few bucks and had to wait for it to arrive. I should have just gotten a new vi... | Negative Review | 8 | NIv2 | task1343_amazon_us_reviews_rating | zs_opt | [
0.320279985666275,
0.10246323049068451,
-0.19345393776893616,
-0.07516796141862869,
0.13705043494701385,
-0.31677699089050293,
0.6193242073059082,
0.41864368319511414,
0.2579490542411804,
0.6035789251327515,
0.33696505427360535,
0.005417257081717253,
-0.017376255244016647,
-0.3622666597366... |
Detailed Instructions: In this task, you will be presented with the directions of a recipe separated by "," and have to fill in the "___" which is a step that is missing from the recipe.
Problem:Cut cheese into cubes. Place in top of double boiler.,Cook over hot water, stirring frequently until melts. Place sausage, Bi... | Place in plastic bag. | 8 | NIv2 | task572_recipe_nlg_text_generation | zs_opt | [
0.5146958827972412,
0.5625185966491699,
-0.022944729775190353,
0.6133242249488831,
0.4032508134841919,
1.006521224975586,
1.0205367803573608,
0.3652822971343994,
-0.2462824285030365,
0.11395634710788727,
1.0100346803665161,
0.12912140786647797,
0.18966643512248993,
0.21202395856380463,
0... |
Detailed Instructions: In this task, you're given a passage, further information available on a particular linked term from the statement, and a question. Your job is to generate the answer to the question by using the information provided. If there is no clear answer obtainable, output 'none'.
Problem:Passage: This le... | Answer: 54 | 8 | NIv2 | task238_iirc_answer_from_passage_answer_generation | zs_opt | [
1.364610195159912,
0.2727492153644562,
-0.4298311471939087,
-0.5458964705467224,
0.08266592770814896,
-0.4521859288215637,
0.7646186351776123,
0.3393495976924896,
-0.004857679363340139,
0.024487685412168503,
-0.38296395540237427,
0.6102908849716187,
-0.679531991481781,
0.6866340041160583,
... |
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Ex Input:
System Reference: x is a restaurant in the x, riverside to locate... | 1
| 1 | NIv2 | task1284_hrngo_informativeness_classification | fs_opt | [
-0.3890753984451294,
0.381163626909256,
-0.6774490475654602,
-0.1216057687997818,
-0.8971716165542603,
-0.40633606910705566,
0.6542468667030334,
0.89350426197052,
0.22087380290031433,
-0.33755889534950256,
-0.03256046772003174,
-0.3184562921524048,
-0.41312840580940247,
0.00937986373901367... |
Instructions: In this task, you will be presented with a text and a pronoun. You should write an implausible answer to the question of what is the pronoun's reference. Even though there exist multiple wrong answers, we only need a single wrong answer. Position of the pronoun in the text is showed within two "_"s.
Input... | Avi Arad | 3 | NIv2 | task331_gap_incorrect_answer_generation | zs_opt | [
0.19327141344547272,
0.7879335284233093,
0.6435327529907227,
0.07011426985263824,
-0.2965414226055145,
0.6709516644477844,
0.7204481363296509,
-0.3058245778083801,
0.5850746035575867,
-0.8504236936569214,
-0.3127078115940094,
0.5610482692718506,
-0.6967973113059998,
-0.25818783044815063,
... |
Instructions: In this task, you're given a statement, further information available on a particular linked term from the statement, and a question. Your job is to generate the answer to the question by using the information provided. If there is no clear answer obtainable, output 'none'.
Input: Context: On the May 5 ep... | Answer: Mark Henry | 3 | NIv2 | task237_iirc_answer_from_subtext_answer_generation | zs_opt | [
0.29734086990356445,
0.22953981161117554,
-0.3916158080101013,
-0.1779562383890152,
-0.4711593687534332,
0.397519588470459,
0.6370172500610352,
0.09921462833881378,
0.757756233215332,
-0.16331708431243896,
-0.14552268385887146,
-0.003484579734504223,
-0.38411954045295715,
0.358491301536560... |
Turn the given fact into a question by a simple rearrangement of words. This typically involves replacing some part of the given fact with a WH word. For example, replacing the subject of the provided fact with the word "what" can form a valid question. Don't be creative! You just need to rearrange the words to turn th... | What decreases the melting point of liquid? | 4 | NIv2 | task040_qasc_question_generation | zs_opt | [
0.5306603908538818,
1.0674622058868408,
0.2410430908203125,
-0.15036916732788086,
-0.6386871933937073,
-0.7355024814605713,
0.5007463097572327,
0.5523896217346191,
0.3266647756099701,
-0.6313145756721497,
-1.4358725547790527,
-0.022890431806445122,
-0.6022845506668091,
0.2619142234325409,
... |
Q: 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 the buildi... | look around left after look opposite left twice | 7 | NIv2 | task127_scan_long_text_generation_action_command_all | zs_opt | [
0.4529948830604553,
0.8601458072662354,
-0.4477163553237915,
0.09677429497241974,
-0.0007366230711340904,
0.07245483994483948,
-0.05505892634391785,
0.7896872758865356,
-0.38151124119758606,
-0.1279076337814331,
-0.6100586652755737,
-0.34814706444740295,
-0.8101522922515869,
0.015983711928... |
Given a premise and two alternatives in Marathi, choose the alternative that is a more plausible cause or effect of the situation described by the premise. The premise is the 'विधान' field and the alternatives are the 'पर्याय A' and 'पर्याय B' fields The output should either be "पर्याय A" or "पर्याय B" based on your ju... | Output: पर्याय B
| 2 | NIv2 | task942_copa_mr_commonsense_reasoning | fs_opt | [
-0.08484802395105362,
0.17156699299812317,
-0.07860802114009857,
0.2235068380832672,
-1.0206148624420166,
-0.5369231104850769,
0.5124350190162659,
1.1571577787399292,
0.2688182592391968,
-0.17384880781173706,
-1.0492689609527588,
-0.31481045484542847,
-0.6727104783058167,
0.313512802124023... |
Teacher:Here are two questions (Question1 and Question2). If these questions have the same meaning and same answer, answer "Yes", otherwise "No".
Teacher: Now, understand the problem? Solve this instance: Question1: Do Asian men in general have less testosterone than men of other ethnicities?, Question2: Do gay men hav... | No | 6 | NIv2 | task1287_glue_qqp_paraphrasing | zs_opt | [
0.08258102834224701,
-0.4638545513153076,
0.20092181861400604,
-0.17163723707199097,
-0.23064082860946655,
-0.8245126605033875,
-0.13660062849521637,
0.8835623264312744,
0.23071111738681793,
-0.14255382120609283,
-0.7795473337173462,
-0.38963717222213745,
-0.5595518946647644,
-0.7594859600... |
instruction:
In this task, you are given a sentence in Persian, and your task is to translate it into English.
question:
تاثیر مباحثه بر اساس Tweet-tag.
answer:
(A Storify of the debate can be found here ).
question:
گزارشها حاکی از آن است که زنان، در برخی مناطق، از شرکت در رایگیری انتخابات جاری پاکستان، برای چهل ... | A man was beaten by members of the public in Kotodayo community in Ota in western Nigeria, on August 22, 2013, for allegedly being gay. This came in the wake of a bill passed in the Nigeria's House of Representative on May 30, 2013, which criminalises gay marriage, same-sex relationships and membership of a gay rights ... | 9 | NIv2 | task662_global_voices_fa_en_translation | fs_opt | [
-0.885144829750061,
0.40841037034988403,
0.5809270143508911,
0.3764986991882324,
-0.3518909215927124,
0.05077487230300903,
1.2468204498291016,
-0.19414719939231873,
-0.10733344405889511,
0.39196038246154785,
-0.15584909915924072,
0.706953227519989,
-0.4933297634124756,
0.16394278407096863,... |
Given the task definition and input, reply with output. This task is about creating an unanswerable question based on a given passage. Construct a question that looks relevant to the given context but is unanswerable. Following are a few suggestions about how to create unanswerable questions:
(i) create questions which... | Newman Thomas was Spectre's what? | 5 | NIv2 | task348_squad2.0_unanswerable_question_generation | zs_opt | [
0.30377209186553955,
0.7373622059822083,
-0.4299403727054596,
0.7738637924194336,
0.061059147119522095,
-0.285904198884964,
1.244156837463379,
0.1332569718360901,
0.2572380304336548,
-0.2405226230621338,
-0.10463699698448181,
0.09931372106075287,
-0.18138036131858826,
-0.005074756219983101... |
Given the task definition and input, reply with output. In this task, you're given an article and an answer. Your task is to generate the question for the answer based on the given article.
Article: Cassandra Feeley finds it hard to manage on her husband' s income. So this year she did something more than a hobby: She... | Why is vegetable gardening becoming increasingly popular? | 5 | NIv2 | task311_race_question_generation | zs_opt | [
0.06406030058860779,
0.6828022003173828,
-0.8788432478904724,
0.9177802801132202,
0.3219446539878845,
-0.48940807580947876,
0.44986146688461304,
1.153054118156433,
0.1362762451171875,
0.034629397094249725,
-0.7250255942344666,
0.44782283902168274,
-1.4865779876708984,
0.44810277223587036,
... |
Detailed Instructions: In this task, you're given a review from Amazon. Your task is to generate a rating for the product on a scale of 1-5 based on the review. The rating means 1: extremely poor, 2: poor, 3: neutral, 4: good, 5: extremely good.
Q: I am terribly disappointed at the lack of any care put into the manufac... | 1 | 9 | NIv2 | task1310_amazonreview_rating_classification | zs_opt | [
-0.17321087419986725,
-0.2997240126132965,
-0.4818173348903656,
-0.6075319051742554,
0.4451668858528137,
-0.5816398859024048,
0.5935608148574829,
0.35519278049468994,
-0.5961165428161621,
0.6622941493988037,
-0.2136780172586441,
0.28041213750839233,
-0.773582935333252,
0.24838024377822876,... |
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".
Q: Context: Cameron spent every Sunday afte... | True | 4 | NIv2 | task384_socialiqa_question_classification | zs_opt | [
0.07569880783557892,
-0.17684297263622284,
-0.38917821645736694,
-0.6044358015060425,
-0.10986527800559998,
-0.6952651739120483,
0.8098297119140625,
0.5714504718780518,
-0.027243515476584435,
0.20142172276973724,
-0.34801650047302246,
0.15271836519241333,
-0.7180160284042358,
-0.1441332548... |
In this task, you are given a pair of action statements. Your task is to check if you can conclusively identify which statement is less ethical or not. Answer: 'no' if one of the statements is less ethical, and 'yes' otherwise.
Let me give you an example: ACTION1: telling my friends sister that she probably won't get ... | no | 8 | NIv2 | task508_scruples_dilemmas_more_ethical_isidentifiable | fs_opt | [
-0.44116491079330444,
0.7022010087966919,
0.6572340726852417,
0.02401634305715561,
-0.09779335558414459,
-0.8237788081169128,
0.0186731219291687,
0.8325638175010681,
0.2488127201795578,
0.4750014543533325,
-0.2214723527431488,
-0.39074838161468506,
-0.8610432147979736,
-0.8290750980377197,... |
Detailed Instructions: Given a sentence in Dutch, generate a new Dutch sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable ... | Als je een examen wilt doen, moet je naar school gaan. | 9 | NIv2 | task409_mickey_nl_sentence_perturbation_generation | zs_opt | [
-0.19495385885238647,
0.6152207851409912,
0.6414420008659363,
-0.9083783626556396,
-0.028908193111419678,
-0.45878469944000244,
-0.11470847576856613,
0.5570300817489624,
-0.1482231616973877,
-0.432977557182312,
-0.20900455117225647,
0.4311865568161011,
-0.5901434421539307,
0.15356375277042... |
In this task, you're given a statement, the genre to which that statement belongs, and a label indicating if the statement should be agreed with (entailment), disagreed with (contradiction), or neither (neutral). Your job is to write a sentence that describes the genre that follows the tone with respect to the statemen... | Solution: Over the time period in the original sentence, she has gone to school, worked in her field, moved to her own place, and will start her next degree soon. | 5 | NIv2 | task203_mnli_sentence_generation | fs_opt | [
-0.3979816138744354,
0.036966726183891296,
0.23793376982212067,
0.24646970629692078,
0.3995676636695862,
-0.58903568983078,
-0.9880701303482056,
0.4161571264266968,
0.09170897305011749,
-0.05746760591864586,
0.02599690854549408,
-0.5863879323005676,
-0.06723141670227051,
-0.164830818772315... |
Instructions: You are given a sentence in English. Your job is to translate the English sentence into Persian.
Input: The answer to this question, I think, is an answer you've already heard in some of the talks, and I dare say you will hear again: namely, that our brains were evolved for a very different world than the... | پاسخ این سوال را البته شما در بعضی از سخنرانی های قبلی شنیدید و فکر کنم در آینده هم آن را باز خواهید شنید: و آن اینکه مغز ما برای زندگی در دنیایی تکامل یافته که خیلی با این دنیایی که ما امروز در آن زندگی می کنیم متفاوت است. | 3 | NIv2 | task1093_ted_translation_en_fa | zs_opt | [
-0.06819798052310944,
0.5412721633911133,
-0.13740161061286926,
0.4520995318889618,
-0.39316391944885254,
-1.3317543268203735,
-0.19423848390579224,
0.4429222047328949,
0.7100052833557129,
-0.22793811559677124,
-0.7799623012542725,
0.09594135731458664,
-1.2419040203094482,
0.57719647884368... |
In this task, you are given a country name and you need to return the continent to which the country belongs.
Example input: Aruba
Example output: North America
Example explanation: North America is the continent to which the country Aruba belongs.
Q: Togo
A: | Africa | 3 | NIv2 | task1321_country_continent | fs_opt | [
1.2297890186309814,
0.44750162959098816,
0.04084083065390587,
0.13811272382736206,
-0.13287866115570068,
-0.6987504363059998,
0.7598651647567749,
0.09488117694854736,
-1.1057275533676147,
-0.1459675431251526,
-0.5130007863044739,
0.03240801393985748,
-0.667811930179596,
-0.3461282253265381... |
Part 1. Definition
In this task, your goal is to judge a correct answer to a given question based on an associated paragraph and decide if it is a good correct answer or not. A good correct answer is one that correctly and completely answers the question. A bad correct answer addresses the question only partially or in... | Yes. | 7 | NIv2 | task056_multirc_classify_correct_answer | fs_opt | [
0.2875998318195343,
-0.35200023651123047,
-0.49090516567230225,
0.40647804737091064,
0.2824222445487976,
-0.3179764151573181,
0.6489795446395874,
1.0568974018096924,
0.7169645428657532,
0.1298409104347229,
-0.8358677625656128,
0.25477027893066406,
-0.5398443937301636,
-0.34942036867141724,... |
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
Input: Consider Input: とても名誉なことですありがとう
Output: لقد كان شرفاً حقاً. شكراً لكم.
Input: Consider Input: すべてが対称的になってる
Output: والمنحوتة لها شكل متناسق
Input: Consider Input: デザインにも色々な種類があります
| Output: لأن هنالك أنواع مختلفة من التصاميم.
| 2 | NIv2 | task1224_ted_translation_ja_ar | fs_opt | [
-0.37393510341644287,
0.2814847230911255,
0.003476268146187067,
-0.36640897393226624,
-0.14069825410842896,
-0.4241505265235901,
0.3182569742202759,
-0.5165722370147705,
0.9176335334777832,
-0.7162426114082336,
-0.8320146799087524,
0.7012038230895996,
-0.806636393070221,
-0.028749242424964... |
You are given a science question (easy-level) and four answer options (associated with "A", "B", "C", "D"). Your task is to find the correct answer based on scientific facts, knowledge, and reasoning. Do not generate anything else apart from one of the following characters: 'A', 'B, 'C', 'D'. There is only one correct ... | B | 8 | NIv2 | task228_arc_answer_generation_easy | fs_opt | [
0.8792223930358887,
-0.07846639305353165,
-0.6963026523590088,
0.3999776840209961,
0.06882523000240326,
-0.9817584156990051,
0.826979398727417,
0.6666314005851746,
-0.3369995653629303,
-0.37631940841674805,
-0.5400725603103638,
0.5911235809326172,
-0.48141273856163025,
0.22570258378982544,... |
Q: You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Italian.
Não havia redes sociais.
A: | Non c'erano i social. | 7 | NIv2 | task1280_ted_translation_pt_it | zs_opt | [
0.09567850828170776,
1.0123941898345947,
0.030258329585194588,
-0.6734781861305237,
-0.44319480657577515,
-0.048109885305166245,
0.5189424157142639,
0.8511950373649597,
0.4940067231655121,
-0.6574693322181702,
0.01528887078166008,
0.08181139826774597,
-0.06106723099946976,
0.14274296164512... |
Q: In this task, you need to count the number of words in a sentence that start with the given letter. Answer with numbers and not words.
Sentence: 'a plate of potatoes carrots and meat with a side of broccoli'. How many words start with the letter 'o' in the sentence.
A: | 2 | 7 | NIv2 | task162_count_words_starting_with_letter | zs_opt | [
0.07616111636161804,
0.9514697790145874,
-0.5298935770988464,
0.00618024030700326,
-0.3595117926597595,
-0.14412829279899597,
0.4160066843032837,
0.031739555299282074,
0.5948929786682129,
-1.0686519145965576,
-0.046677667647600174,
-0.37743061780929565,
-0.17151693999767303,
-0.27241456508... |
Definition: Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probabili... | Sie würden Essen hacken, weil Sie Abendessen machen wollen. | 2 | NIv2 | task416_mickey_de_sentence_perturbation_generation | zs_opt | [
-0.4858207106590271,
0.6714453101158142,
0.3083205819129944,
-0.2577343285083771,
-0.35221680998802185,
0.20586135983467102,
0.8146439790725708,
0.45910170674324036,
0.5689971446990967,
-0.5775654315948486,
-0.8309082984924316,
0.02954510599374771,
-1.125669240951538,
0.4994892477989197,
... |
Given the task definition and input, reply with output. Given a part of privacy policy text, identify the type of personal information which is collected, used, tracked or retained. The type of information should be present inside the given policy text, answer as 'Not Specified' otherwise
The site collects your IP add... | IP address and device IDs | 5 | NIv2 | task684_online_privacy_policy_text_information_type_generation | zs_opt | [
-0.8031308650970459,
0.11895930767059326,
-0.6258556842803955,
0.039613887667655945,
-0.9083643555641174,
-0.5860795378684998,
-0.10629861056804657,
0.08721964061260223,
0.1514642834663391,
0.7220485210418701,
-0.5107688903808594,
0.02976354956626892,
-0.6130404472351074,
-0.77708792686462... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a set of context paragraphs, some supporting facts and an answer of a question. Your task is to generate question for given answer based on set of context paragraphs, supporting facts and an answer.
Context_1 : Up ... | Eric Steelbergs film Up in the Air starred which celebrity playing the role of Ryan Bingham? | 1 | NIv2 | task191_hotpotqa_question_generation | zs_opt | [
0.4917278289794922,
0.5759763717651367,
-0.7648566961288452,
0.08667567372322083,
0.4797704517841339,
0.04999135807156563,
0.4721106290817261,
0.9558571577072144,
-0.9345756769180298,
0.1919456124305725,
-0.1620451807975769,
0.3660659193992615,
-1.1411349773406982,
0.2226121723651886,
0.... |
A text is given in Hindi. Translate it from the Hindi language to the Marathi language. The translation must not omit or add information to the original sentence.
[Q]: रेल्वे क्षेत्रात क्षमता आणि उपलब्धतेत लक्षणीय वाढ झाली आहे.
[A]: इसी तरह रेल क्षेत्र में महत्वपूर्ण प्रगति हुई है।
[Q]: मला विश्वास आहे की, माझ्या या... | गुरू रामानंद के शिष्य थे सो जाति कैसे मानते।
| 5 | NIv2 | task1082_pib_translation_marathi_hindi | fs_opt | [
0.2489619255065918,
0.4489862024784088,
0.21920494735240936,
-0.38668403029441833,
-0.37569937109947205,
-0.5774192810058594,
0.5260379314422607,
0.48100438714027405,
-0.1011805534362793,
-0.9700625538825989,
-0.4926906228065491,
-0.06504522264003754,
-0.05879425257444382,
-0.0409936457872... |
In this task you are given a sentence with one coordinating conjunction (for, and, nor, but, or, yet, and so). You must judge whether the order of two coordinated clausal conjoints have been inverted or not. Inversion would result in the sentence sounding unnatural. Label the instances as "Original" or "Inversion" base... | Original | 0 | NIv2 | task516_senteval_conjoints_inversion | zs_opt | [
-0.3946225643157959,
0.7812395095825195,
0.23912829160690308,
-0.0974486842751503,
0.1259271800518036,
-0.420742928981781,
0.5515448451042175,
0.7100808024406433,
0.12782803177833557,
0.15965242683887482,
-0.5587318539619446,
-0.40030497312545776,
-0.802464485168457,
-0.18481400609016418,
... |
Given the task definition and input, reply with output. Given a sentence in the Filipino, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Ayon sa mga balita, ang UN ay nag iisip "na ialis ang mga tagapagmasid mula sa lugar."
| 報告によると、国連は「監視員をその場から移動」させようとしている。 | 5 | NIv2 | task1119_alt_fil_ja_translation | zs_opt | [
0.0430479571223259,
0.3117825388908386,
-0.31649190187454224,
0.06576355546712875,
-0.11246703565120697,
-0.09663985669612885,
0.24251523613929749,
0.39603427052497864,
-0.5501917600631714,
0.020439891144633293,
-1.1515883207321167,
0.19869601726531982,
-0.49113425612449646,
0.418008089065... |
Teacher: You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Teacher: Now, understand the problem? If you are still confused, se... | 1 | 2 | NIv2 | task1284_hrngo_informativeness_classification | fs_opt | [
-0.84657883644104,
0.2534221410751343,
-0.3628108501434326,
0.008884105831384659,
-0.25882986187934875,
-0.9255438446998596,
1.3264756202697754,
0.5524924993515015,
0.09523393213748932,
-0.22853323817253113,
-0.01969796046614647,
-0.8293253183364868,
-0.3211776316165924,
-0.048802215605974... |
In this task, you are given two strings A,B. Find the longer of the two lists, convert it to lowercase, and return all the unique alphabets used in it. The two input strings are never equal.
KZrWTrOOXVVPgtnzfABhzzGU, azdhEHXVVPgtnzlL | a, b, f, g, h, k, n, o, p, r, t, u, v, w, x, z | 0 | NIv2 | task756_find_longert_substring_and_return_all_unique_alphabets_in_it | zs_opt | [
0.004751656670123339,
1.4431401491165161,
0.21447627246379852,
-0.37147846817970276,
0.10272496193647385,
0.385453999042511,
1.315373420715332,
-0.6918495893478394,
-0.4542301297187805,
-0.27395862340927124,
-0.6552810668945312,
-0.44787195324897766,
0.11982810497283936,
-0.134011209011077... |
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 | 2 | NIv2 | task1197_atomic_classification_oreact | zs_opt | [
0.12300100177526474,
0.09847718477249146,
0.3912178575992584,
-0.029573772102594376,
-0.21465438604354858,
-0.9081827402114868,
0.997704267501831,
0.46973180770874023,
-0.44540858268737793,
-0.4794795513153076,
-0.29405176639556885,
-0.09906492382287979,
-0.6796528100967407,
0.379993736743... |
You are given a sentence in Italian. Your job is to translate the Italian sentence into English.
--------
Question: Scorrerò le altre slide in modo che vediate i paesi più in fondo.
Answer: I'm going to whip through the other slides just so you can see some of the lower-lying countries.
Question: Devono lavorare ins... | As you wave your hand across the map, the name of the piece of real estate — the building or the cemetery — is revealed.
| 7 | NIv2 | task1247_ted_translation_it_en | fs_opt | [
-0.441947340965271,
0.5890424251556396,
-0.2197733074426651,
-0.08788809180259705,
-0.29065701365470886,
-0.34861573576927185,
0.13108667731285095,
0.6677039265632629,
-0.23251177370548248,
0.01701560616493225,
-0.20992375910282135,
0.8878357410430908,
-0.5811684131622314,
0.37424278259277... |
TASK DEFINITION: In this task you are given a small conversation between two persons and 4 options on how the conversation should continue. Your job is to choose the most reasonable option. The conversation and the options are separated by a newline character. Each dialogue in the conversation are separated by a comma.... | B
| 8 | NIv2 | task611_mutual_multi_turn_dialogue | fs_opt | [
0.39331814646720886,
0.15613406896591187,
-0.4221148192882538,
-0.3445102572441101,
0.6600909233093262,
-0.04306991025805473,
0.7161687612533569,
0.6270701289176941,
0.2574930191040039,
-0.17756034433841705,
-0.44324159622192383,
0.4863617420196533,
0.050411321222782135,
0.5329304337501526... |
Q: Given a sentence in the Japanese and Lao language. Your task is check if the Lao sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Japanese: しかし最優先されるのは、考え方や旧態依然とした政府の政策を変えることであるとリズバーマンは強調した。
Lao: ຍິ່ງໄປກວ່ານັ້ນ ຜູ້ດູແລບໍ່ໄດ້ອະນຸມັດໃຫ້ ຄະນະ... | No | 7 | NIv2 | task1126_alt_ja_lo_answer_generation | zs_opt | [
-1.034986972808838,
0.30746227502822876,
0.33495503664016724,
0.11603689938783646,
-0.5556992292404175,
-0.6182500720024109,
0.5519917011260986,
0.9407674074172974,
-0.8075547814369202,
-0.5737739205360413,
-0.16720500588417053,
-0.050789035856723785,
-0.44365596771240234,
1.04688763618469... |
Instructions: 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 ... | measurement | 3 | NIv2 | task834_mathdataset_classification | zs_opt | [
0.00548900943249464,
0.20737117528915405,
-0.042530931532382965,
-0.13748228549957275,
-0.24626439809799194,
-0.2362576723098755,
0.21941319108009338,
-0.023220481351017952,
0.21405896544456482,
-0.6034762859344482,
-0.8840256929397583,
0.23307068645954132,
-0.33269351720809937,
0.16543188... |
Teacher: In this task, you're given a context, a sentence, and a character. The sentence describes an action or job of the given character. Also, the context provides more information about the sentence or the character. Your task is to write the character's motivation by doing a specific job, which is given in the se... | None | 2 | NIv2 | task294_storycommonsense_motiv_text_generation | fs_opt | [
-0.26451626420021057,
0.48238301277160645,
-0.09176290780305862,
-0.5802483558654785,
-0.009206379763782024,
-0.2925655245780945,
0.3004566729068756,
0.4028612971305847,
0.20139339566230774,
0.49354854226112366,
0.1007978543639183,
-0.4042377769947052,
-0.17988544702529907,
-0.023524165153... |
Detailed Instructions: You're given a fill-in-the-blank question where the answer is PersonX. You need to minimally change the given question so that the answer flips to PersonY. This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "sympathetic" to "stern"). You... | PersonX disliked craft beer more than normal beer unlike PersonY because _ had a refined palette. | 8 | NIv2 | task035_winogrande_question_modification_person | zs_opt | [
1.0172008275985718,
0.2983560562133789,
-0.3266853094100952,
0.2700554132461548,
0.38191351294517517,
-0.8618179559707642,
1.4180163145065308,
0.6431616544723511,
-0.05140746384859085,
-0.4640296399593353,
-0.08035995066165924,
-0.14416244626045227,
-0.7086818218231201,
0.3230828046798706,... |
In this task, you're given a context, a question, and three options. Your task is to find the correct answer to the question using the given context and options. Also, you may need to use commonsense reasoning about social situations to answer the questions. Classify your answers into 'A', 'B', and 'C'.
One example: Co... | B | 6 | NIv2 | task580_socialiqa_answer_generation | fs_opt | [
0.6697439551353455,
0.07142730057239532,
-0.027910996228456497,
0.06912249326705933,
0.23640364408493042,
-0.25551706552505493,
1.2745667695999146,
0.8029441833496094,
0.1515960395336151,
0.1955677568912506,
-0.22896243631839752,
-0.3468719720840454,
0.32259705662727356,
-0.425751537084579... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Ex Input:
Sentence 1: You can see the copper plates giving land rights to a Jewish community on... | 6
| 1 | NIv2 | task198_mnli_domain_classification | fs_opt | [
-0.5390270352363586,
0.23193390667438507,
0.06392639130353928,
-0.2849259078502655,
-0.0732293576002121,
0.1192421168088913,
0.35138195753097534,
1.2728986740112305,
0.012089389376342297,
0.024434469640254974,
-0.13344158232212067,
0.22492200136184692,
-0.5577831864356995,
-0.5692356824874... |
Teacher: You will be given a trivia clue, and the category it belongs to. You should answer with the best answer that belongs in the category and is described by the clue. For simplicity, answers should be in all lower cased letters.
Teacher: Now, understand the problem? If you are still confused, see the following exa... | chocolate | 2 | NIv2 | task307_jeopardy_answer_generation_final | fs_opt | [
-0.1938929259777069,
0.6127465963363647,
-0.40113258361816406,
0.07227484881877899,
0.3674749732017517,
-0.7520041465759277,
0.003321719588711858,
0.43728065490722656,
0.5049800872802734,
0.2372877597808838,
0.18633417785167694,
0.025083350017666817,
-0.5700773000717163,
-0.501452863216400... |
In this task, you're given a context, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both context and link information to create the q... | How long did William D. Swenson serve in the army?
| 3 | NIv2 | task235_iirc_question_from_subtext_answer_generation | fs_opt | [
0.1421821415424347,
0.3975248634815216,
-0.7480824589729309,
-0.2824253439903259,
0.040242116898298264,
-0.7885959148406982,
0.330776184797287,
1.0121757984161377,
0.12709395587444305,
-0.041349925100803375,
-0.44569727778434753,
0.3100540339946747,
-0.24045684933662415,
-0.242324471473693... |
Instructions: In this task, you are given an input list A. You need to convert all the alphabets in the list with a number representing their position in the English alphabet. E.g., replace A by 1, B by 2, a by 1, b by 2, and so on.
Input: ['5859', '4891', '2471', '6299', '6291', '3993', 'q', 'j', 'Y', '8919', 'U', '52... | 5859, 4891, 2471, 6299, 6291, 3993, 17, 10, 25, 8919, 21, 525, 8423 | 3 | NIv2 | task622_replace_alphabets_in_a_list_by_their_position_in_english_alphabet | zs_opt | [
-0.40662264823913574,
0.2327989935874939,
0.06902707368135452,
-0.48254209756851196,
0.19759653508663177,
-0.18650484085083008,
-0.5350921750068665,
0.0162989292293787,
0.07930891215801239,
-0.29191291332244873,
-0.12245030701160431,
0.0264142956584692,
0.22149966657161713,
-0.613178193569... |
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 one French sentence. The major part of the sentences talk about health-related topics, but some of the them describe an organization and its activities. Your job is to tra... | The clinical presentation is variable. | 0 | NIv2 | task1397_europa_ecdc_tm_fr_en_translation | fs_opt | [
-1.3263733386993408,
0.6301806569099426,
0.3456032872200012,
-0.41275811195373535,
0.19643822312355042,
-0.028876371681690216,
0.6107995510101318,
0.026208922266960144,
0.44756510853767395,
-0.2389129102230072,
0.04022869095206261,
0.2829938530921936,
-0.49865803122520447,
0.60961371660232... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given an input list A. You need to find all the elements of the list that are numbers in the same order as they appear in the list A.
['J', 'T', 'P', '8425', '5103', 'g', '4209', 'F', 'R', '3871', '3179', 'P', '9427', 'M... | 8425, 5103, 4209, 3871, 3179, 9427, 5385, 9695, 2445 | 1 | NIv2 | task497_extract_all_numbers_from_list_in_order | zs_opt | [
-0.013886874541640282,
0.16008374094963074,
-0.6763556003570557,
0.05739075690507889,
0.5085046291351318,
0.24666108191013336,
0.20410557091236115,
-0.3455635905265808,
-0.5556058287620544,
0.314461350440979,
-1.072584629058838,
-0.5623347759246826,
0.26672378182411194,
-0.0559036992490291... |
You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Farsi.
Q: Estudamos os olivais sagrados, ou florestas sagradas em redor de antigos templos.
A: | بیشه های مقدس را بررسی می کنیم ، یا جنگل های مقدس اطراف معابد را. | 4 | NIv2 | task1282_ted_translation_pt_fa | zs_opt | [
-0.43419039249420166,
1.0474282503128052,
-0.5229150056838989,
-0.5544195175170898,
-0.7822313904762268,
-0.8176383972167969,
0.5819724798202515,
-0.13720703125,
0.5686786770820618,
-0.13057172298431396,
-0.8743090629577637,
-0.19927248358726501,
-0.004128742031753063,
0.37163805961608887,... |
Given a story, answer the question about the story. The question is the last sentence in the input. The story has one of the three following scenarios: the first is when the individual's belief matches reality, the second is when the individual's belief does not match reality, and the third is when an individual has a ... | green_bucket | 8 | NIv2 | task152_tomqa_find_location_easy_noise | fs_opt | [
0.18299347162246704,
-0.4886015057563782,
-0.551720380783081,
-0.1350487470626831,
-0.5593608617782593,
-0.8064282536506653,
0.3998391032218933,
0.6311455965042114,
-0.3261428475379944,
-0.19125284254550934,
-0.25721296668052673,
0.6659591197967529,
-0.14565174281597137,
0.0547128543257713... |
Teacher:In this task, given 2 input sentences, you must classify the relation between them. If the second sentence has a similar meaning to that of the first sentence then the output is ' B_entails_A', if the second sentence has the opposite meaning to the first sentence then it is classified as ' B_contradicts_A'. If ... | B_entails_A | 6 | NIv2 | task1615_sick_tclassify_b_relation_a | zs_opt | [
-0.9354608654975891,
0.22185875475406647,
0.6549248695373535,
0.018836786970496178,
-0.1592186689376831,
-0.3780074715614319,
-0.4812183678150177,
0.9458119869232178,
-0.44019871950149536,
-0.1143442913889885,
-0.773187518119812,
-0.5971273183822632,
0.30027127265930176,
-0.441768229007720... |
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