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 |
|---|---|---|---|---|---|---|
Detailed Instructions: 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. E... | Marshalltown | 8 | NIv2 | task303_record_incorrect_answer_generation | zs_opt | [
-0.19938398897647858,
0.6192587614059448,
-0.15208163857460022,
0.35589802265167236,
0.038927532732486725,
-0.26910510659217834,
1.3907561302185059,
0.9235614538192749,
-0.40556904673576355,
0.44663554430007935,
-0.1157405823469162,
0.9559472799301147,
-0.5047892928123474,
0.06796598434448... |
Teacher:A text is given in Marathi. Translate it from the Marathi language to the Tamil language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? Solve this instance: त्याला रंगरंगोटी केली जात आहे. कोणी भाज्यांचे रंगकाम करत आहेत, कोणी कागदाचे तुकडे चीटकवत... | இந்தக் காலகட்டத்தில் சமுதாயத்தில் நேசம், சுமூகம் பற்றிய செய்தி பரப்பப்படுவதோடு, மக்கள் மனங்களில் ஒரு புதிய உற்சாகம், புதிய எதிர்பார்ப்பு, ஒரு புதிய நம்பிக்கை ஆகியவற்றைத் தட்டி எழுப்புகிறது. | 6 | NIv2 | task1083_pib_translation_marathi_tamil | zs_opt | [
-0.19370022416114807,
0.5135692358016968,
0.027223657816648483,
-0.18299493193626404,
-0.16782045364379883,
-0.9316521883010864,
0.25647294521331787,
1.056199073791504,
-0.6688950061798096,
-0.17556175589561462,
-0.11875884979963303,
0.16072580218315125,
-0.40243643522262573,
-0.2819820940... |
Teacher:In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Teacher: Now, understand the problem? Solve this instance: Tw... | yes | 6 | NIv2 | task196_sentiment140_answer_generation | zs_opt | [
-1.5993423461914062,
0.18937009572982788,
0.6831746697425842,
0.4547525644302368,
0.5500266551971436,
-1.0148130655288696,
-0.3850381374359131,
0.23817592859268188,
0.13743555545806885,
0.5274059176445007,
-0.1457056850194931,
-0.6425110101699829,
-0.6002985239028931,
-0.5964078903198242,
... |
Instructions: In this task, you are given a sentence in English, and your task is to translate it into Persian.
Input: but he didnt count on her will to live .
Output: | اما اون حساب نکرده بود که اون زنده ميمونه . | 3 | NIv2 | task658_tep_en_fa_translation | zs_opt | [
-0.25207483768463135,
1.2848882675170898,
-0.08391483128070831,
0.05964384227991104,
-0.3810614347457886,
0.20881935954093933,
0.7295350432395935,
0.5524656772613525,
-0.2782214879989624,
0.5745657682418823,
-0.2376679629087448,
0.34464409947395325,
-0.30160754919052124,
-0.141201496124267... |
instruction:
In this task, you will be presented with a question and you have to answer the question based on your knowledge. Your answers should be as short as possible.
question:
What is the name of the title whose developers departed from MicroProse ?
answer:
Civilization V
question:
How many top division appearan... | 56.3 years
| 9 | NIv2 | task344_hybridqa_answer_generation | fs_opt | [
-0.4052976667881012,
-0.33966949582099915,
0.19423821568489075,
-0.24887880682945251,
0.3559008240699768,
-0.4220207929611206,
0.5626869201660156,
-0.5074831247329712,
0.3487895131111145,
-0.3896693289279938,
0.14017511904239655,
-0.5065988898277283,
-1.2526531219482422,
0.31843101978302,
... |
You are given a statement written in Tamil. 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 .
Q: Statement: ஊ தாண்ட் <MASK>வின் பண்டானோ என்ற இடத்தில் பிறந்தார். தனது 14வது வயதில் தனது தந்தையை இழந்தார். ரங்கூன் ... | பர்மா | 4 | NIv2 | task953_wiki_cloze_ta_multiple_choice_question_answering | zs_opt | [
0.7905070781707764,
0.6544715166091919,
-0.9185886979103088,
0.26470881700515747,
-0.11584366858005524,
-0.657029926776886,
-0.31683340668678284,
0.6431988477706909,
-0.10229016095399857,
0.46263638138771057,
-0.2717762589454651,
0.5028523206710815,
-0.6124335527420044,
-0.126888245344162,... |
In this task, you are given two sets, and you need to count the number of elements at the intersection of two given sets. A Set is shown by two curly braces and comma-separated numbers inside, like {1, 2, 3}. The intersection of two given sets is the largest set which contains all the elements that are common to both ... | 5 | 4 | NIv2 | task243_count_elements_in_set_intersection | zs_opt | [
0.3227509558200836,
0.14459973573684692,
-0.8386408090591431,
-0.13456416130065918,
-0.027421679347753525,
-0.16441850364208221,
0.588201642036438,
0.48241034150123596,
-0.06386803090572357,
-0.303297758102417,
-0.9730105400085449,
-0.007622208446264267,
0.28411903977394104,
0.004105615429... |
Teacher:In this task, you will be given a short story. One sentence from the story is chosen. Consider the likely emotions of the participants in the sentence and those affected by it. Is any of these emotions caused by the sentence? You should write your answer in the form " A >Causes> B". Try to use phrases and sente... | They go shopping >Causes> They feel(s) happy | 6 | NIv2 | task749_glucose_reverse_cause_emotion_detection | zs_opt | [
-0.320243239402771,
0.017847903072834015,
-0.0320127010345459,
0.04325341433286667,
0.2621847987174988,
-0.8764983415603638,
0.14119508862495422,
0.7122675180435181,
0.05144943669438362,
0.5173128843307495,
0.028767451643943787,
0.5308641791343689,
-0.12743932008743286,
-0.424022376537323,... |
Given the task definition and input, reply with output. Generate an appropriate title for the given text. The generated title must be short and include the main topic of the text. The preferred titles are under fifteen words.
Anthony ZurcherNorth America reporter@awzurcheron Twitter Most of the top-tier Republican can... | Will the Paris attacks shake up the US presidential race? | 5 | NIv2 | task1356_xlsum_title_generation | zs_opt | [
0.1932850480079651,
0.5162850618362427,
-0.2132510244846344,
0.15060794353485107,
-0.16578234732151031,
-0.07125227898359299,
0.9878730773925781,
0.9819526076316833,
-0.03829248994588852,
0.8895562291145325,
0.1818220615386963,
0.8492946028709412,
-0.2258356660604477,
0.14902058243751526,
... |
Q: The input is a tweet which can be classified as Hate Speech, Offensive or Normal. Given such a tweet, output the class the tweet belongs to. Hate Speech will contain threatening language towards the community targeted. Offensive language will contain abusive or discriminatory language towards the community targeted.... | Normal | 7 | NIv2 | task1502_hatexplain_classification | zs_opt | [
-0.4116305112838745,
1.0156571865081787,
0.5449853539466858,
0.36034348607063293,
-0.10331152379512787,
-1.0737428665161133,
-0.17310166358947754,
0.8688926696777344,
0.6542527079582214,
0.2083481252193451,
-0.1865186244249344,
0.04692932590842247,
-0.425108402967453,
-0.5147207379341125,
... |
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 alphabetical elements in the given list in order. Assume the position of the 1st element to be 1. Return -1 if no alphabetical element is in the list.
Example: ['2... | Solution: 4, 14, 15, 16, 18, 19, 20, 22, 23, 24, 26, 27, 29, 30, 31 | 5 | NIv2 | task506_position_of_all_alphabetical_elements_in_list | fs_opt | [
0.137305349111557,
0.31710460782051086,
-0.14966844022274017,
-0.5142040252685547,
0.3220292925834656,
-0.3731808066368103,
0.9100715517997742,
0.29259228706359863,
-0.37210220098495483,
0.29969191551208496,
-0.6194285154342651,
-0.253815233707428,
0.13914261758327484,
-0.16787506639957428... |
Q: In this task, you are given a sentence in Persian, and your task is to translate it into English.
بله، برای این بود که طحال ایشان آسیب دیده بود و باعث شده بود که اِشتهایشان را از دست بدهند
A: | yes, that's why it injured the spleen and made him lose his appetite... | 7 | NIv2 | task659_tep_fa_en_translation | zs_opt | [
-0.0166865773499012,
0.8082022666931152,
-0.44254839420318604,
-0.16921672224998474,
0.09564263373613358,
0.006332383491098881,
0.18848171830177307,
0.007972616702318192,
0.13064934313297272,
-0.6559546589851379,
0.24854525923728943,
0.4502599537372589,
-0.14762789011001587,
0.468275189399... |
You will be given a definition of a task first, then some input of the task.
This task is about translating a given French language sentence to English.
Nous avions donc beaucoup de choses à régler.
Output: | So we really had a lot to deal with. | 1 | NIv2 | task1690_qed_amara_translation | zs_opt | [
0.09227684140205383,
1.0955469608306885,
0.4633108973503113,
-0.3064030408859253,
0.13728533685207367,
-0.6540645360946655,
0.2614988088607788,
0.3540445566177368,
0.6803985238075256,
0.475106418132782,
-0.06916622072458267,
0.01233822014182806,
-0.31794166564941406,
-0.20251771807670593,
... |
Detailed Instructions: You are given two sentences(Sentence1 and Sentence2). Answer "Yes" if these sentences are a paraphrase of one another, otherwise answer "No".
See one example below:
Problem: Sentence1: While it was being called mandatory , Dupont said authorities were not forcing people from their homes ., Senten... | Yes | 4 | NIv2 | task1288_glue_mrpc_paraphrasing | fs_opt | [
-0.7179644107818604,
0.5413736701011658,
0.5596696138381958,
-0.4147678017616272,
0.03628191351890564,
-1.191992163658142,
0.8293534517288208,
0.5012767910957336,
-0.13318496942520142,
0.03246065974235535,
-0.8912227153778076,
-0.12887223064899445,
-0.5795679092407227,
-0.20337626338005066... |
Instructions: 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.
Input: Sentence: 'When the founder of Patagonia outdoor wear , Yvon Chouinard , got " sick and tired " of fancy plastic packaging , his fir... | be founder of | 3 | NIv2 | task676_ollie_relationship_answer_generation | zs_opt | [
-0.6466835737228394,
-0.33535218238830566,
-0.7766711711883545,
-0.1468951553106308,
-0.6678382158279419,
-0.9256441593170166,
-0.2854394316673279,
0.4617202579975128,
0.019865242764353752,
0.1677817404270172,
-0.4651836156845093,
0.498174786567688,
-1.2993710041046143,
-0.2609504163265228... |
You will be given a definition of a task first, then some input of the task.
Given a context passage, generate a question from the passage such that its answer is shortest continous span from the passage.
Peter availed himself of savage tortures while investigating the incident. Many suspects were whipped to death wit... | What happened first: Peter I ordered another investigation or members were removed from Moscow? | 1 | NIv2 | task470_mrqa_question_generation | zs_opt | [
0.533738911151886,
0.9603479504585266,
-0.6574338674545288,
0.02234625071287155,
0.12161752581596375,
-0.27912217378616333,
-0.42977601289749146,
0.6094167232513428,
0.5710143446922302,
0.21429365873336792,
-0.3980637788772583,
0.278764545917511,
-0.17525909841060638,
0.12747140228748322,
... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given two entities as input, classify as "yes" if second entity is the part of the first entity. Otherwise classify them as "no". These are entities of meronym In linguistics, meronymy is a semantic ... | no | 0 | NIv2 | task472_haspart_classification | fs_opt | [
-0.5656125545501709,
0.17500978708267212,
0.5274909734725952,
0.10131005942821503,
0.041832149028778076,
-0.8269948363304138,
0.31230658292770386,
0.47208574414253235,
0.36286216974258423,
-0.4900137186050415,
-0.27451154589653015,
-0.0831441655755043,
-0.3699396848678589,
0.25313866138458... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task you are given a 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 i... | Original | 0 | NIv2 | task428_senteval_inversion | fs_opt | [
-0.09851796925067902,
0.398933470249176,
0.7288612127304077,
0.09161433577537537,
-0.02670011669397354,
-0.24377471208572388,
1.1283377408981323,
0.30302608013153076,
0.4081405997276306,
-0.3420675992965698,
-0.7424910664558411,
-0.5255918502807617,
-0.3855799436569214,
0.09130144119262695... |
Given the task definition and input, reply with output. 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... | Answer: none | 5 | NIv2 | task238_iirc_answer_from_passage_answer_generation | zs_opt | [
-0.0006784799043089151,
0.383797824382782,
-0.626163125038147,
0.8333789706230164,
0.020550349727272987,
0.15958286821842194,
0.3943807780742645,
0.8160364627838135,
-0.019528083503246307,
0.2702101767063141,
-0.14417381584644318,
0.7286720275878906,
-0.25453251600265503,
-0.05014424771070... |
Teacher:In this task you will be given a passage and a yes/no question based on the passage. You should answer the question using the information from the passage.
Teacher: Now, understand the problem? Solve this instance: passage: Since each location on the board can be either empty, black, or white, there are a total... | Yes | 6 | NIv2 | task380_boolq_yes_no_question | zs_opt | [
0.371884822845459,
0.48812752962112427,
-0.5446697473526001,
-0.4808424413204193,
0.08727909624576569,
0.04292857274413109,
-0.033040910959243774,
0.628369927406311,
0.05839576572179794,
-0.12825077772140503,
-0.5297654867172241,
0.43177658319473267,
-0.2590699791908264,
-0.076426878571510... |
Teacher: 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 the... | American | 2 | NIv2 | task303_record_incorrect_answer_generation | fs_opt | [
-0.09417036175727844,
0.4917146861553192,
-0.23271164298057556,
0.24974875152111053,
0.15809081494808197,
-0.16265657544136047,
0.1972058117389679,
0.8722788095474243,
-0.554369330406189,
0.6146419048309326,
0.3006710410118103,
0.3186703026294708,
-0.7303444147109985,
0.30695104598999023,
... |
Instructions: In this task, you are given a premise sentence. Your task is to write a new sentence by substituting the subject and object (i.e., the input's subject should be output's object and vice versa.). The generated sentence must be fluent and shouldn't change the voice (i.e., passive or active) of the input.
In... | The scientist mentioned the lawyer . | 3 | NIv2 | task1364_hans_answer_generation | zs_opt | [
-0.4466080963611603,
0.8437767028808594,
0.11469004303216934,
-0.4929794669151306,
0.02981642819941044,
-0.15401095151901245,
0.2622423768043518,
0.3754366338253021,
0.5149528384208679,
-0.7754918336868286,
-1.0234850645065308,
-0.30165183544158936,
-0.5759221911430359,
-0.1975827515125274... |
Teacher:A text is given in Panjabi. Translate it from the Panjabi language to the Telugu language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? Solve this instance: o ਰੂਪੇ ਕਾਰਡ ਉੱਤੇ ਚਲਣ ਵਾਲਾ ਇੰਟਰ ਓਪਰੇਬਲ ਟ੍ਰਾਂਸਪੋਰਟ ਕਾਰਡ ਅਤੇ ਇਹ ਧਾਰਕ ਨੂੰ ਬੱਸ ਵਿੱਚ ਯਾਤਰਾ ਕਰ... | రూపే కార్డు ద్వారా చలామణి అయ్యే అన్ని రవాణా వ్యవస్థలకు పనికి వచ్చే కార్డు ద్వారా బస్సు ప్రయాణం, టోల్ పన్ను, పార్కింగ్ చార్జీలు, చిల్లర దుకాణాలలో కొనుగోళ్ళు చేయవచ్చు | 6 | NIv2 | task1065_pib_translation_punjabi_telugu | zs_opt | [
0.13512182235717773,
0.48175543546676636,
0.24016115069389343,
0.2950829267501831,
0.0455159917473793,
-0.676122784614563,
0.9823830127716064,
0.8733211159706116,
0.035945676267147064,
0.30134278535842896,
0.13367530703544617,
-0.45827460289001465,
0.11322331428527832,
-0.5742132663726807,... |
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), EVERYBODY (if everyone mentioned is wrong) and NOBODY ... | Output: NOBODY
| 2 | NIv2 | task498_scruples_anecdotes_whoiswrong_classification | fs_opt | [
0.6907134652137756,
-0.5638300776481628,
0.0076837968081235886,
-0.05192316696047783,
0.33961379528045654,
-0.16844616830348969,
0.9384298920631409,
0.9567528367042542,
0.33373409509658813,
0.2547686696052551,
-0.03612102195620537,
0.7719037532806396,
-0.5810549259185791,
-0.01605360582470... |
In this task, you're given a review from Amazon and 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. Your task is to generate whether the rating matches the review or not. Answer with "True" if the sentence belongs to that... | True
| 3 | NIv2 | task1311_amazonreview_rating_classification | fs_opt | [
0.05273372679948807,
0.2789562940597534,
-0.29798877239227295,
-0.30823540687561035,
0.15782086551189423,
-0.8768899440765381,
0.8905549645423889,
0.8833571076393127,
-0.34499669075012207,
0.29423606395721436,
0.052493467926979065,
-0.273199200630188,
-0.3351566791534424,
0.08653574436903,... |
You will be given a definition of a task first, then some input of the task.
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.
Put a rack in the middle of the oven and preheat the oven to 350 degrees F. Bu... | Line the bottom of each with a round of parchment paper, and then butter the paper. | 1 | NIv2 | task572_recipe_nlg_text_generation | zs_opt | [
0.8321682810783386,
0.6632312536239624,
-0.16569583117961884,
0.13295018672943115,
0.1535455286502838,
0.7012740969657898,
-0.17953458428382874,
1.0934927463531494,
-0.9422487020492554,
-0.22562973201274872,
0.8154903054237366,
-0.00943443737924099,
0.09543981403112411,
-0.1751930266618728... |
Definition: In this task, you are given an abstract of article. Your task is to generate label "True" if abstract is structured, otherwise generate "False". A structured abstract is composed of a topic sentence (or key sentence), relevant supporting sentences, and a closing (or transition) sentence. This structure is k... | False | 2 | NIv2 | task1589_scifact_classification | zs_opt | [
0.04953037202358246,
-0.28955405950546265,
-0.14472439885139465,
-0.31938010454177856,
-0.21482008695602417,
-0.43640992045402527,
0.47048288583755493,
0.9434563517570496,
0.3622856140136719,
0.2484205663204193,
-0.49754369258880615,
0.02372826263308525,
-0.4194578230381012,
0.669481754302... |
In this task, you are given an input list. A list contains several comma-separated items written within brackets. You need to return the count of all the alphabetical elements in the given list. Return 0 if no alphabetical element in the list
['f', '539', '6505', '1763', '5033', 'e', '291', '9133', 'G', 'I', '8085', '... | 15 | 0 | NIv2 | task504_count_all_alphabetical_elements_in_list | zs_opt | [
0.1205589771270752,
0.5192433595657349,
0.0898781269788742,
-0.46049031615257263,
0.2910754680633545,
-0.4666433334350586,
0.5120807886123657,
-0.13153846561908722,
-0.6567070484161377,
0.3252056837081909,
-0.9861962199211121,
0.2562447190284729,
-0.022729188203811646,
-0.44842594861984253... |
Detailed Instructions: You are given a set of queries separated by '
', and your job is to find out the query which is not a well-formed or well-structured query in terms of grammar, punctuations, or spelling errors.
Problem:How many different nail polish brands are there ?
How can you make your own wigi board ?
How do... | How can you make your own wigi board ? | 8 | NIv2 | task674_google_wellformed_query_sentence_generation | zs_opt | [
-0.2710516154766083,
0.25178879499435425,
-0.2801346182823181,
-0.3798362612724304,
-0.21955926716327667,
-0.3681747317314148,
0.3635576665401459,
-0.36898621916770935,
-0.28501927852630615,
-0.18490266799926758,
-0.20107519626617432,
-0.08682593703269958,
-0.08799974620342255,
-0.11569448... |
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 _. There are several possible answers, you'll need to choose the proper one. Carefully read the given text, pay specia... | OTHER | 6 | NIv2 | task304_numeric_fused_head_resolution | fs_opt | [
-0.04964267835021019,
0.4806777238845825,
-0.6982302069664001,
0.37364742159843445,
-0.2810668349266052,
-0.07481282204389572,
1.1521787643432617,
0.6206135749816895,
0.05961235612630844,
0.012873532250523567,
-0.7053731679916382,
0.15157821774482727,
-0.32221242785453796,
0.09626822173595... |
Given an entity as input, output another entity which is part of the input entity. These are entities of meronym. In linguistics, meronymy is a semantic relation between a meronym denoting a part and a holonym denoting a whole. In simpler terms, a meronym (i.e., output entity) is in a part-of relationship with its holo... | bacteria | 4 | NIv2 | task471_haspart_answer_generation | zs_opt | [
-0.7379013299942017,
0.8530836701393127,
0.28106218576431274,
-0.3465327024459839,
-0.7236900925636292,
-0.2486574649810791,
0.11998039484024048,
0.600632905960083,
1.0868871212005615,
-0.5641950368881226,
-0.6718533039093018,
1.1840755939483643,
-0.07315200567245483,
-0.09380041062831879,... |
You will be given a definition of a task first, then some input of the task.
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., Person... | No | 1 | NIv2 | task1197_atomic_classification_oreact | zs_opt | [
0.21150216460227966,
0.19190597534179688,
0.6536028981208801,
-0.3221641182899475,
-0.14697624742984772,
-0.7485671043395996,
1.1478883028030396,
0.5058006048202515,
-0.8271331787109375,
-0.2720417380332947,
0.11099227517843246,
-0.2652909755706787,
-0.6640024185180664,
0.4785825312137604,... |
In this task, you are given a sentence in the Bulgarian language. Your task is to convert it to Greek language.
One example is below.
Q: Възможно е да имат и епизоди на депресия.
A: Ενδέχεται επίσης να εµφανίσουν επεισόδια κατάθλιψης.
Rationale: The translate is accurate from Bulgarian to Greek
Q: Арипипразол е лекарс... | Η αριπιπραζόλη είναι το επικρατέστερο μόριο φαρμακευτικού προϊόντος στη συστηματική κυκλοφορία. | 9 | NIv2 | task765_emea_bg_el_translation | fs_opt | [
-0.38398268818855286,
0.10690732300281525,
0.271705687046051,
-0.8876938223838806,
-0.4536468982696533,
-1.0449780225753784,
1.8008970022201538,
0.3830159902572632,
0.64610356092453,
-0.254077672958374,
-0.6334174871444702,
0.9196970462799072,
-0.9464495182037354,
0.5138726234436035,
0.7... |
Definition: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Polish.
Input: אני פשוט אוהב ג 'פרדי ותמיד אהבתי.
Output: | Po prostu od zawsze kocham Jeopardy. | 2 | NIv2 | task1112_ted_translation_he_pl | zs_opt | [
-0.8047246932983398,
0.43336954712867737,
-0.6414307951927185,
-0.04123383387923241,
-0.035398729145526886,
-0.9087556600570679,
0.677186131477356,
-0.8964071273803711,
0.7616294622421265,
-0.7800604701042175,
-0.9607714414596558,
-0.4679562449455261,
-0.41088032722473145,
0.57817590236663... |
Detailed Instructions: 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 ev... | Yes | 4 | NIv2 | task1214_atomic_classification_xwant | fs_opt | [
0.5553924441337585,
0.09096983075141907,
-0.0010441495105624199,
0.00279040914028883,
-0.6378840208053589,
-0.6899518966674805,
1.4126536846160889,
0.5663598775863647,
-0.6627572774887085,
-0.39815476536750793,
-0.3752809166908264,
-0.30501365661621094,
-0.995853066444397,
0.30333766341209... |
The task is about translation from Telugu to English. While performing the translation you must preserve the original meaning. Do not include any words which are only limited to your native place.
లేదా మీరు కొనసాగించేందుకు కావలెను కొన్ని వ్యక్తిగత ఆసక్తులను. | Or when you wanted to pursue some personal interests. | 0 | NIv2 | task1324_open_subtitles_te_en_translation | zs_opt | [
0.07758361101150513,
1.0705451965332031,
0.7204077839851379,
0.5179173946380615,
0.1349995732307434,
-0.6355747580528259,
0.6878879070281982,
-0.33626529574394226,
-0.18162524700164795,
-0.6424269080162048,
-0.1332525610923767,
0.2533981502056122,
-1.0047110319137573,
0.45227229595184326,
... |
Q: In this task, you are given a sentence in the Gujarati language and a corresponding English translation of the Gujarati sentence. Your task is to generate a label "Yes" if the translation is correct, otherwise generate label "No".
Gujarati: વાદળી આકાશમાં વિમાન દ્વારા ઉડાન ભરેલી છે.
English: A skier standing in the... | No | 7 | NIv2 | task440_eng_guj_parallel_corpus_gu-en_classification | zs_opt | [
-1.3487739562988281,
0.21210461854934692,
0.3252158761024475,
-0.47368383407592773,
0.08905239403247833,
-0.6051802635192871,
0.33877894282341003,
0.38894549012184143,
0.08507449924945831,
-0.40751397609710693,
-0.222732812166214,
0.15054315328598022,
-0.474774569272995,
0.2376099675893783... |
In this task, you are given a sentence in the Bulgarian language and corresponding English translation of this sentence. Here, your job is to generate label "yes" if translation is right, otherwise generate label "no".
Bulgarian: Какво е направила Комисията, за да обясни на потребителите, че по-голямата част от нашата... | no | 0 | NIv2 | task273_europarl_classification | zs_opt | [
-0.19182522594928741,
0.5393842458724976,
0.6190510988235474,
0.10169821232557297,
-0.016884323209524155,
-0.5801266431808472,
0.42671799659729004,
0.4896911084651947,
-0.3583667278289795,
0.11313822120428085,
-0.16954658925533295,
0.6912156939506531,
-0.6523647308349609,
0.236393883824348... |
Q: In this task, the input is a set of dialogues between a user and an assistant. You need to find the dialogue that is basically a response given to a question or an aspect of the user.
Cool! What can you tell me about the history?
Sure, I would love that!
Unfortunately I have no information on the culture at this... | There are only 578 Jews in Serbia. | 7 | NIv2 | task576_curiosity_dialogs_answer_generation | zs_opt | [
0.06490106880664825,
1.1659448146820068,
-0.6955391764640808,
0.3546525239944458,
-0.36916330456733704,
-0.08572480827569962,
1.233961820602417,
-0.11654264479875565,
0.6929541230201721,
-0.3782915472984314,
0.03707841783761978,
0.0029654509853571653,
-0.6301622986793518,
-0.01454632449895... |
Definition: Given a sentence in English language, translate the sentence to Somali language keeping the meaning of the original sentence intact
Input: English sentence: 12:13 And David said to Nathan, “I have sinned against the Lord.” And Nathan said to David: “The Lord has also taken away your sin . You shall not die ... | 12:13 Markaasaa Daa'uud wuxuu Naataan, "Waan ku dembaabay Rabbiga." Markaasaa Naataan wuxuu Daa'uud ku yidhi: "Rabbiga ayaa sidoo kale qaaday dembigiinnii. | 2 | NIv2 | task446_opus_paracrawl_en_so_translation | zs_opt | [
0.44756513833999634,
0.5468022227287292,
0.1735517978668213,
-0.8335516452789307,
-0.6703063249588013,
-1.174926519393921,
0.9167828559875488,
0.3754992187023163,
0.34023725986480713,
0.6232244968414307,
0.3134830892086029,
0.7795381546020508,
-1.9265093803405762,
-0.22628077864646912,
0... |
In this task, you are given two natural language statements with similar wording. You must choose the statement that makes less sense based on common sense knowledge. A '
' separates the statements. Use "first" or "second" to indicate which sentence makes less sense.
Q: Jeff gave his girlfriend a lose.
Jeff gave his gi... | first | 4 | NIv2 | task291_semeval_2020_task4_commonsense_validation | zs_opt | [
-0.5211652517318726,
0.3121297359466553,
-0.3063313663005829,
-0.5387114882469177,
0.13260680437088013,
-0.41227400302886963,
0.3354482054710388,
0.5286375284194946,
0.5382095575332642,
-0.03314615786075592,
-0.6480313539505005,
-0.45549076795578003,
-0.774548351764679,
-0.3370796144008636... |
You are given a statement written in Oriya. 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 .
Q: Statement: <MASK> - ମରାଠୀ ଭାଷାରେ " ଭାବାର୍ଥ ରାମାୟଣ " ୧୬ ଶ ଶତାବ୍ଦୀରେ ଏକନାଥଙ୍କଦ୍ୱାରା ରଚିତ ହେଇଥିଲା । ୧୨ ଶ ଶତାବ୍ଦୀ ମରା... | ମହାରାଷ୍ଟ୍ର | 4 | NIv2 | task951_wiki_cloze_or_multiple_choice_question_answering | zs_opt | [
1.1055322885513306,
1.1826223134994507,
0.03937289118766785,
-0.30860042572021484,
-0.8586899042129517,
-0.703957200050354,
0.47076737880706787,
0.4949224293231964,
0.5790568590164185,
-0.1990639567375183,
-0.44002580642700195,
-0.0007852917769923806,
-0.014143165200948715,
-0.288288325071... |
Instructions: Given a sentence in the Indonesian(Bahasa variant), provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Input: Anggota PCS "menderita kondisi kerja yang tertekan hanya menghasilkan penyakit dan stres tinggi" menurut se... | PCSメンバーは組合によると「単に高レベルのストレスと病の結果の弾圧的な労働条件に苦し」み、大変な労働環境の証拠として、昨年の4月以降にジョブセンタープラスのコールセンターを去った2779名のスタッフ--公衆の電話を受けている37のジョブセンタープラスオフィスの労働力約20％にあたる--について指摘する。 | 3 | NIv2 | task1116_alt_id_ja_translation | zs_opt | [
-0.21027341485023499,
0.5902208089828491,
-1.12418532371521,
-0.3531420826911926,
0.20977166295051575,
-0.5364440679550171,
0.47407999634742737,
-0.11047559976577759,
0.5006136894226074,
-0.09420014917850494,
-0.6556001901626587,
0.4286210238933563,
-0.46764007210731506,
0.3174911141395569... |
In this task, you're given a question, along with a context passage which has extra information available on certain terms mentioned in it. Your job is to determine which sentence(s) from the passage can be used to search for further information needed to answer the question.
Q: Question: Who was named in Minnesota's b... | He was named to the Pavek Museum of Broadcasting's Minnesota Broadcasting Hall of Fame in 2005, and in 2007 he was inducted into the Bay Area Radio Hall of Fame | 4 | NIv2 | task234_iirc_passage_line_answer_generation | zs_opt | [
0.9110035300254822,
0.19986498355865479,
-0.7178401947021484,
0.2793031632900238,
0.9703273773193359,
-0.009926560334861279,
0.1896999180316925,
0.5979633331298828,
0.05641061067581177,
0.0856490358710289,
-0.16785158216953278,
0.17651930451393127,
-1.1178581714630127,
0.417031466960907,
... |
Part 1. Definition
You are given a sentence in Italian. Your job is to translate the Italian sentence into Arabic.
Part 2. Example
Penso che abbastanza presto vedrete pazienti curati con le cellule staminali derivanti dal proprio grasso o adipe.
Answer: وأعتقد أنه في القريب سوف ترى المرضى يعالجون بواسطة خلاياهم الجذعية... | لقد قدت هذه السيارة برفقة مرشد من الشركة سائق سيارات سباق محترف وقدنا حول الوديان في لوس أنجلوس وعلى طريق ساحل المحيط الهادىء السريع | 7 | NIv2 | task1250_ted_translation_it_ar | fs_opt | [
-0.3460080325603485,
0.31236720085144043,
-0.2766895294189453,
-0.8402463793754578,
-0.31037870049476624,
-0.24798372387886047,
0.7840811014175415,
0.42696717381477356,
0.3493877351284027,
-0.26896435022354126,
-0.5176505446434021,
0.25467923283576965,
-0.5881342887878418,
0.32197582721710... |
Instructions: In this task, you are given two lists A,B. Find the longest common subsequence in the lists A and B.
Input: ['W', 9115, 6349, 3857, 8999, 'm', 'p', '9581', 'J', 'J', '3951', 'F', 'x', '3793', 'U', 'a', 5165, 'w', 9853, 's', 'Y'], ['t', 'l', 7927, 3483, '9581', 'J', 'J', '3951', 'F', 'x', '3793', 'A', 7459... | 9581, J, J, 3951, F, x, 3793 | 3 | NIv2 | task605_find_the_longest_common_subsequence_in_two_lists | zs_opt | [
-0.5288962125778198,
-0.22701874375343323,
-0.5125226974487305,
-0.7474696636199951,
-0.38834142684936523,
0.6349035501480103,
-0.3708556294441223,
0.054344162344932556,
-0.4128665328025818,
-0.11935308575630188,
-1.1040699481964111,
0.1819162666797638,
0.5418457984924316,
0.10653434693813... |
Q: In this task, you are given a sentence in the Hindi language and your task is to convert it into the English language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
प्रधान मंत्री के कार्यालय के एक संदेशवाहक, माइकल रयान की पहचान एक गुप्तचर ... | Michael Ryan, a messenger at the office of the prime minister, has been identified as the mole who leaked confidential papers to Telecom. | 7 | NIv2 | task433_alt_hi_en_translation | zs_opt | [
-1.0238966941833496,
0.3276771903038025,
0.7110929489135742,
-0.9888434410095215,
0.5774579048156738,
0.2243281602859497,
0.19313620030879974,
0.0681825578212738,
0.1419065147638321,
-0.08480783551931381,
-0.16600753366947174,
0.15471595525741577,
-0.6699550151824951,
0.2877727150917053,
... |
Definition: In this task, you are given a sentence in the English language and your task is to convert it into the Hindi language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
Input: "He's disgraced himself, he's an embarrassment to the Clay... | उन्होंने कहा, "वह खुद बदनाम हैं, वह क्लेटन काउंटी पुलिस विभाग के लिए एक शर्मिंदगी है, एक अधिकारी के रूप में उनकी विश्वसनीयता और अखंडता चली गई है और मेरे पास उनके लिए कुछ नहीं है," उन्होंने घोषणा की। | 2 | NIv2 | task432_alt_en_hi_translation | zs_opt | [
-0.25280606746673584,
0.3376607894897461,
0.6622186899185181,
-0.1511114090681076,
0.17865954339504242,
-0.23728099465370178,
0.4236745834350586,
0.10646720230579376,
0.12515485286712646,
-0.5019321441650391,
-0.9603943824768066,
0.11054477095603943,
-0.5644597411155701,
0.3578572273254394... |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Arabic.
Input: Consider Input: Però penso che ci sia innocenza in questi animali.
Output: لكنني نوع من ال — هناك براءة في هذه الحيوانات.
Input: Consider Input: Così l'istante è importante. Non fermatevi!
Output: أذاً النشاط جيد... | Output: هذا هو ذلك التلميذ ، ديفيد برادويل ، الذي يظهر في هذه الصورة وهو متعجباً ما إن كان هذا الشيء سيعمل.
| 2 | NIv2 | task1250_ted_translation_it_ar | fs_opt | [
-0.81877601146698,
0.3898699879646301,
-0.5040697455406189,
-0.3370884954929352,
-0.7448267936706543,
-0.09722264856100082,
0.7054589986801147,
0.7294217348098755,
0.18372198939323425,
-0.4587612748146057,
-0.8537995219230652,
0.4215596318244934,
-0.5586478114128113,
-0.08628508448600769,
... |
Given the task definition and input, reply with output. Given a sentence in the Japanese and Thai language. Your task is check if the Filipino sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Japanese: 情報不足が問題で、超党派での調査では、実際より少なすぎる報告とデータ収集不足の裏付... | No | 5 | NIv2 | task1129_alt_ja_th_answer_generation | zs_opt | [
-1.2398293018341064,
-0.7109021544456482,
0.12857268750667572,
0.20229391753673553,
0.07573533058166504,
-0.6458547115325928,
0.6907845139503479,
0.5768252015113831,
-0.5739923119544983,
-0.23767322301864624,
-0.03213845565915108,
0.548509955406189,
-0.3360446095466614,
0.9675346612930298,... |
instruction:
In this task you will be given a list of integers. A list contains numbers separated by a comma. You need to round every integer to the closest power of 2. A power of 2 is a number in the form '2^n', it is a number that is the result of multiplying by 2 n times. The following are all powers of 2, '2, 4, 8,... | [256, 512, 1024, 1024, 16, 32, 2, 128, 2048, 4096, 4096, 8, 64, 2, 256, 1024]
| 9 | NIv2 | task1444_round_power_of_two | fs_opt | [
0.31935030221939087,
0.7737258076667786,
-0.49528568983078003,
0.06952527910470963,
-0.07324863970279694,
-0.08737276494503021,
1.017655372619629,
0.5194156169891357,
-0.5769432783126831,
0.26905834674835205,
-0.7283886671066284,
0.4862358570098877,
-0.25989919900894165,
-0.166283681988716... |
Instructions: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Japanese.
Input: هذا المنظر من النهر الشرقي ، يطل على تلال مارري عند المكان الذي يوجد فيه مبنى الأمم المتحدة اليوم.
Output: | イーストリバーからの眺めマリーヒルを見上げています現在国連本部がある場所です | 3 | NIv2 | task1231_ted_translation_ar_ja | zs_opt | [
0.7848939895629883,
0.139584481716156,
-0.6212267279624939,
-0.3686394691467285,
-0.11468541622161865,
-0.4067980647087097,
0.3617231249809265,
-0.1438741832971573,
0.3323040306568146,
-0.7523781061172485,
-0.3465721607208252,
-0.3695206046104431,
-0.3954695463180542,
0.48764628171920776,
... |
Definition: In this task, you are given an input list A. You need to extract and sort the unique digits used in the list in ascending order. Return -1 if there is no digit in the list.
Input: ['u', 'g', 'y', 'w', 'p', '123', 'v', '181', 'b', 'a', '475', '131', 'u', 'g', '49']
Output: | 1, 2, 3, 4, 5, 7, 8, 9 | 2 | NIv2 | task637_extract_and_sort_unique_digits_in_a_list | zs_opt | [
-0.1479344367980957,
-0.5440858006477356,
-0.5397348403930664,
-0.6134423017501831,
0.3472691774368286,
0.5808930397033691,
0.8137568235397339,
-0.0997220128774643,
0.005394710693508387,
0.4087831377983093,
-0.9231870174407959,
-0.1835610270500183,
-0.3853280544281006,
-0.19219453632831573... |
In this task you are given a list of numbers and you need to find the average of each two consecutive values. The average of two numbers a and b is calculated as: (a + b) /2. The output should be a list of the averages of each two consecutive values. A list is presented with two brackets and comma-separated values, lik... | [26.0, 37.5, 40.5, 69.0, -1.0, -71.0, -56.5, -7.0, -16.0, -52.5, -30.0, -4.0, 7.5]
****
| 4 | NIv2 | task124_conala_pair_averages | fs_opt | [
-0.6680160164833069,
0.3773680329322815,
-0.7378981113433838,
-0.46795332431793213,
-0.04029060900211334,
0.4477544128894806,
0.66749107837677,
0.5954792499542236,
-0.07174105197191238,
-0.5140445828437805,
-0.8994185328483582,
-0.20958974957466125,
0.08341138809919357,
0.1586553156375885,... |
Detailed Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Polish.
Problem:תראו, מה שאנו עושים כיום, זה לכפות על אנשים ללמוד מתמטיקה.
Solution: | Zwróćcie uwagę, to co teraz robimy jest zmuszaniem ludzi do nauki matematyki. | 8 | NIv2 | task1112_ted_translation_he_pl | zs_opt | [
-0.3325296640396118,
1.1267385482788086,
-0.01498685497790575,
-0.6633915305137634,
-0.29481562972068787,
-0.1675877869129181,
0.859694242477417,
0.0724770575761795,
0.6600555181503296,
-0.33515986800193787,
-0.8612192869186401,
-0.047845467925071716,
0.11715459078550339,
0.177667677402496... |
The task is to generate text based of an event. For the given event, there will be a person who does the action in the event (usually PersonX). Your task is to write that persons emotional reaction to the event, i.e. how that person feels after doing the action.
--------
Question: PersonX does not want to go to bed
An... | irritated
| 7 | NIv2 | task1595_event2mind_text_generation_1 | fs_opt | [
-0.007743778172880411,
0.8875887989997864,
0.18583901226520538,
-0.832298994064331,
-0.7005968689918518,
-0.4188932478427887,
1.3122966289520264,
0.34954947233200073,
0.12884321808815002,
-0.6812213063240051,
-0.13910570740699768,
0.2907361388206482,
-0.8229652047157288,
0.2023119032382965... |
Part 1. Definition
A text is given in Bengali. Translate it from the Bengali language to the Hindi language. The translation must not omit or add information to the original sentence.
Part 2. Example
ইংরেজিতেও সবাই বলেন – পেসিমিজ্ম লীড্স টু উইক্নেস্, অপ্টিমিজ্ম টু পাওয়ার।
Answer: हर किसी ने अंग्रेजी में भी कहा -... | उनके स्वास्थ्य और सुरक्षा पर असर न हो। इसलिए स्वच्छ भारत मिशन के तहत पांच करोड़ से ज्यादा शौचालय बनवाए गए हैं। | 7 | NIv2 | task1009_pib_translation_bengali_hindi | fs_opt | [
-0.25053346157073975,
0.448111355304718,
0.1612904667854309,
-0.08295392990112305,
-0.18608805537223816,
-0.9877642393112183,
0.8319162130355835,
0.28471851348876953,
-0.09346833825111389,
-0.3484874367713928,
-1.0189357995986938,
0.41013506054878235,
-0.45432770252227783,
-0.0055553675629... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
You will be given a text in Russian language which contain different emotion labels from the list - ['joy', ' sadness', 'surprise', 'fear', 'anger']. You need to output the incorrect emotion label, w... | sadness | 0 | NIv2 | task1663_cedr_ru_incorrect_classification | fs_opt | [
-0.739917516708374,
0.10446338355541229,
0.1630483716726303,
-0.51413893699646,
-0.603685736656189,
-0.06147667393088341,
0.4379313588142395,
0.5803290605545044,
-0.22468802332878113,
-0.3405570089817047,
-0.4648757874965668,
-0.2501823902130127,
-0.1757626235485077,
0.36048802733421326,
... |
Detailed Instructions: In this task, you are given a sentence in the English language and your task is to convert it into the Japanese language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
Problem:Each of the ten plaintiffs is a child who w... | １０人の原告それぞれは、フィリピン人の母親のもとに生まれた子であり、後に日本人の父親に認知された。 | 8 | NIv2 | task435_alt_en_ja_translation | zs_opt | [
-0.06401093304157257,
0.12375667691230774,
-0.028167597949504852,
-0.47340112924575806,
-0.16960006952285767,
0.22669032216072083,
1.07780122756958,
0.5929767489433289,
0.16169142723083496,
-0.4061356782913208,
-0.24435372650623322,
0.3178388476371765,
-1.1424074172973633,
0.10576325654983... |
Generate a correct and concise answer for the question based on the words in the context.
Input: Consider Input: Context : Karl Helge Hampus Hellekant, later Karl Svensson (born January 30, 1976 in Danderyd, Stockholm County) is a Swedish neo-Nazi who was sentenced to 11 years of prison for the murder of syndicalist u... | Output: P.J. Ramster
| 2 | NIv2 | task1327_qa_zre_answer_generation_from_question | fs_opt | [
-0.2108987271785736,
0.7668313980102539,
-0.5201531648635864,
-0.0783577710390091,
-0.033778127282857895,
0.6631064414978027,
0.09571290761232376,
-0.3252703547477722,
-0.7337597012519836,
0.6625335216522217,
0.22712954878807068,
0.32662343978881836,
-0.36607760190963745,
-0.21502858400344... |
You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Polish.
[Q]: E despeja 18 mil toneladas de dióxido de carbono na atmosfera.
[A]: a do powietrza dostaje się 18 tysięcy ton dwutlenku węgla.
[Q]: Esta é a base do meu trabalho.
[A]: To podstawa naszej pracy.
[Q]: Esqueci t... | Pominąłem metryki, motywację, komitety, middle offices i interfejsy.
| 5 | NIv2 | task1281_ted_translation_pt_pl | fs_opt | [
-0.6560038328170776,
0.896066427230835,
-0.49616026878356934,
-0.8956692218780518,
-0.6142569780349731,
-1.0825881958007812,
0.9307287931442261,
0.44872161746025085,
0.19350695610046387,
-0.3570883572101593,
-0.7729051113128662,
0.30204305052757263,
-0.4223034381866455,
0.10226739943027496... |
Definition: Given a phrase describing the relationship between two words, extract the words and the lexical relationship between them. The relation has to be of the type 'MemberOf', 'MadeOf', 'Synonym', 'Entails', 'HasA', 'HasProperty', 'PartOf', 'Antonym' or 'IsA'. The output should have the format: word1 relation wor... | bend PartOf road | 2 | NIv2 | task1510_evalution_relation_extraction | zs_opt | [
0.10997510701417923,
0.8799258470535278,
0.36077040433883667,
-0.5799669623374939,
-0.5224666595458984,
-0.575941264629364,
0.849768340587616,
0.06697531044483185,
0.3661530613899231,
-0.5074731707572937,
-1.0548019409179688,
-0.03032747283577919,
-0.5812683701515198,
0.1808314472436905,
... |
Teacher:Given the prompt and a response, classify the them to "yes" if response is "yes, and" type. Otherwise classify it as "no". "Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that line... | no | 6 | NIv2 | task361_spolin_yesand_prompt_response_classification | zs_opt | [
0.0031454579439014196,
0.3411688804626465,
0.579494833946228,
0.05884968489408493,
0.3260209560394287,
-0.9170230627059937,
-0.02605915069580078,
0.8479568958282471,
-0.06406508386135101,
-0.1402522474527359,
-0.3326471447944641,
-0.36548760533332825,
-0.2125462293624878,
0.134147346019744... |
In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: sexual-explicit and non-sexual-explicit. A comment is considered sexual-explicit if it explicitly portrays sexual matters.
Comment: Nitwityahoo is a war criminal and baby killer - HE SHOULD BE... | Sexual-explicit | 0 | NIv2 | task323_jigsaw_classification_sexually_explicit | zs_opt | [
-1.223459005355835,
0.5917412042617798,
1.0067410469055176,
0.43776220083236694,
-0.11678705364465714,
-0.31748151779174805,
0.25529393553733826,
0.11177012324333191,
0.27009961009025574,
0.9043291211128235,
0.48456236720085144,
-0.27090901136398315,
-0.694462776184082,
-0.2815553843975067... |
Teacher: In this task, you are given a context, a subject, a relation, and many options. Based on the context, from the options select the object entity that has the given relation with the subject. Answer with text (not indexes).
Teacher: Now, understand the problem? If you are still confused, see the following exampl... | prime minister of india | 2 | NIv2 | task1296_wiki_hop_question_answering | fs_opt | [
0.26914268732070923,
0.5071694254875183,
-0.745435357093811,
-0.40309253334999084,
0.4892784357070923,
0.1946142017841339,
0.5324892997741699,
0.8215187788009644,
-0.24383603036403656,
0.018248572945594788,
-0.019957825541496277,
0.9516878128051758,
-0.5674198865890503,
0.49421563744544983... |
Given the task definition and input, reply with output. This is a paraphrasing task. In this task, you're given a sentence and your task is to generate another sentence which express same meaning as the input using different words.
if you have any last words , my lord , now 's the time .
| if you have any last words , sir ... | 5 | NIv2 | task177_para-nmt_paraphrasing | zs_opt | [
-0.3870915472507477,
1.0844223499298096,
0.6201478242874146,
0.015087390318512917,
-0.44036293029785156,
-0.1966044157743454,
0.6366369724273682,
-0.017394648864865303,
0.3807944655418396,
-0.41670429706573486,
-0.5329846143722534,
0.2117234170436859,
-0.25327956676483154,
0.19413644075393... |
Teacher: You are given a sentence in Italian. Your job is to translate the Italian sentence into Galician.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Tra di esse, si annovera il piccolo sistema in arabo detto al-jebr.
Solution: Isto inclúe un sistema en árabe chamado al-... | Isto sucede porque estamos constantemente liberando microbios. | 2 | NIv2 | task1252_ted_translation_it_gl | fs_opt | [
-0.1704794466495514,
0.9131010174751282,
-0.200901061296463,
-0.029976222664117813,
-0.2636023759841919,
-1.3293970823287964,
0.2996896803379059,
0.8297715187072754,
-0.9566155672073364,
0.016723288223147392,
0.02520669996738434,
0.1078297421336174,
-0.8976858258247375,
0.24888594448566437... |
Detailed Instructions: In this task, you are given a sentence in the Gujarati language and a corresponding English translation of the Gujarati sentence. Your task is to generate a label "Yes" if the translation is correct, otherwise generate label "No".
Q: Gujarati: કેમેરા સામે પેસ્ટ્રીઝ ધરાવતા કેટલાક લોકો.
English: ... | Yes | 9 | NIv2 | task440_eng_guj_parallel_corpus_gu-en_classification | zs_opt | [
-0.8058730959892273,
0.47270670533180237,
0.22749896347522736,
0.2133081555366516,
-0.32059967517852783,
-0.8962483406066895,
0.1450297087430954,
0.24996019899845123,
-0.09087652713060379,
-0.48144760727882385,
-0.3153102397918701,
0.2343592345714569,
-0.4010698199272156,
0.579049468040466... |
Detailed Instructions: You are given a statement written in Oriya. 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 .
Problem:Statement: ସାଧାରଣତଃ ପଖାଳ ଗରମ ଭାତରେ ପାଣି ମିଶାଇ କେଇ ଘଣ୍ଟାରୁ ଆରମ୍ଭ କରି ରାତିଏ ଯାଏ ରଖାଯାଇଥ... | ପଶ୍ଚିମବଙ୍ଗ | 8 | NIv2 | task951_wiki_cloze_or_multiple_choice_question_answering | zs_opt | [
0.15146909654140472,
1.4075758457183838,
0.03274722024798393,
0.18984796106815338,
-0.048660773783922195,
-0.585464358329773,
0.3993658423423767,
0.05846623703837395,
0.19251644611358643,
-0.15598689019680023,
-0.3351220190525055,
-0.13915932178497314,
-0.011627502739429474,
-0.57163000106... |
Q: Given a scientific question, generate an incorrect answer to the given question. The incorrect answer should be a plausible alternative to the correct answer. The answer should be some other item belonging to the same category as the correct answer but should be incorrect.
What are surface currents mainly caused by?... | lightning | 7 | NIv2 | task592_sciq_incorrect_answer_generation | zs_opt | [
-0.46198806166648865,
1.2645506858825684,
-0.5038771629333496,
-1.223013162612915,
-0.03080150857567787,
-0.435161828994751,
-0.4371381998062134,
0.6598372459411621,
0.03167463839054108,
0.07327787578105927,
-0.08717551827430725,
0.13642612099647522,
-1.0384553670883179,
-0.317544579505920... |
In this task you will break down a question into the basic steps required to answer it.
A question decomposition is a numbered list of operations that must be performed to answer the original question. Imagine explaining your question to a friendly droid by listing each action it should take in order for the question ... | #1 return poland
#2 return people of #1
#3 return language of #2 | 4 | NIv2 | task176_break_decompose_questions | zs_opt | [
1.0521451234817505,
0.05336112901568413,
-0.5785428285598755,
0.6127290725708008,
0.13531601428985596,
-0.3917514383792877,
1.316776990890503,
-0.26490047574043274,
-0.35733088850975037,
0.4380261301994324,
-0.5581907033920288,
0.1523568332195282,
-0.08877915889024734,
0.6256650686264038,
... |
Given the task definition, example input & output, solve the new input case.
A text is given in Bengali. Translate it from the Bengali language to the Marathi language. The translation must not omit or add information to the original sentence.
Example: স্তন্যপান সম্পর্কে অভিভাবকদের সচেতন ও উৎসাহদানে গুরুত্ব বিশ্ব স্তন্... | आपल्या भाषणाचा समारोप करतांना सर्वांसाठी समान संधी आणि विकासाप्रती आपल्या कटिबद्धतेचा पुनरुच्चार करताना ‘सबका साथ, सबका विकास’ हा नवीन भारतासाठी पुढे जाण्याचा मार्ग आहे अशी टिप्पणी त्यांनी केली. | 1 | NIv2 | task1061_pib_translation_bengali_marathi | fs_opt | [
-0.4868347942829132,
0.7117254734039307,
-0.3216627836227417,
0.03970469906926155,
-0.6651167273521423,
-0.4645112156867981,
0.4915940761566162,
0.8115172982215881,
0.3715241551399231,
-0.44645416736602783,
-0.572596549987793,
0.26131224632263184,
0.06727512180805206,
-0.007265768945217133... |
You will be given a definition of a task first, then some input of the task.
You are given a math word problem and you are supposed to make use of mathematical concepts like probability, combinatorics, linear equations, sequences/series, or simple operators like addition, subtraction, division, or multiplication to ans... | Option C | 1 | NIv2 | task750_aqua_multiple_choice_answering | zs_opt | [
0.40645039081573486,
0.16619938611984253,
-0.24167734384536743,
-0.33592718839645386,
0.04187735542654991,
0.052998386323451996,
0.6792206168174744,
1.1104223728179932,
-0.1323990523815155,
-0.2406613528728485,
-0.5111207962036133,
-0.4628969430923462,
-0.15186533331871033,
-0.307677626609... |
In this task, you have to generate the title of the recipe given its required ingredients and directions.
Q: ingredients: '2 c. light brown sugar', '1 c. white sugar', '1 c. milk', '1 Tbsp. white Karo', '2 Tbsp. margarine', '3 c. pecans', '1 tsp. vanilla',<sep> directions: 'Put all of the ingredients except margarine... | Slow Cooker White Bean Chicken Chili
****
| 4 | NIv2 | task569_recipe_nlg_text_generation | fs_opt | [
0.7984769940376282,
0.22380217909812927,
-0.6557397246360779,
0.09669595211744308,
0.10809572786092758,
0.13516820967197418,
0.9138461351394653,
1.1250641345977783,
-0.41845348477363586,
-0.03597458451986313,
0.18632389605045319,
-0.19757911562919617,
-0.3006435036659241,
0.506611943244934... |
instruction:
In this task, you are given a sentence that is either in the Yoruba language or the English language. Your task is to identify the language of the input sentence. Input sentences should be in Yoruba or English language and also it cannot have two languages at a time.
question:
I understand
answer:
English
... | English
| 9 | NIv2 | task1621_menyo20k-mt_en_yo_language_identification | fs_opt | [
0.330095112323761,
-0.2038644552230835,
0.3743624687194824,
0.05403467267751694,
0.14037790894508362,
-0.5573632717132568,
-0.07196445763111115,
0.5605500340461731,
-0.06645327806472778,
-0.13599419593811035,
0.1619797796010971,
0.25015032291412354,
-0.5764620304107666,
0.34910306334495544... |
Detailed Instructions: In this task, you will be shown an extract from a movie plot and a question. You need to provide the correct answer for it. Short answers containing words that are present in the passage are preferred.
See one example below:
Problem: Twenty-year-old Will Hunting of South Boston is a self-taught, ... | Answer: Artful dodger | 4 | NIv2 | task194_duorc_answer_generation | fs_opt | [
0.5882917642593384,
0.38791581988334656,
-0.344671368598938,
-0.7333822846412659,
0.0033153186086565256,
-0.19933612644672394,
0.5485342144966125,
0.6019037961959839,
0.2649875283241272,
-0.06940488517284393,
-0.10878393054008484,
0.37986311316490173,
-0.7240062355995178,
-0.18032464385032... |
Detailed Instructions: In this task, you're given the title of a story consisting of five sentences, numbered 1 through 5. Your job is to determine which two sentences need to be swapped sentences in order to make a story that makes complete sense and is befittingly titled. Indicate your answer using the numbers of the... | 41 | 4 | NIv2 | task218_rocstories_swap_order_answer_generation | fs_opt | [
0.22292399406433105,
0.22247126698493958,
-0.5212583541870117,
0.04936278983950615,
0.047878749668598175,
-0.5659667253494263,
0.3511545956134796,
0.8483074307441711,
-0.11261402070522308,
0.2772147059440613,
-1.0204761028289795,
0.021964769810438156,
-0.9988855123519897,
0.015001483261585... |
Given two entities as input, classify as "yes" if second entity is the part of the first entity. Otherwise classify them as "no". These are entities of meronym In linguistics, meronymy is a semantic relation between a meronym denoting a part and a holonym denoting a whole. In simpler terms, a meronym (i.e., second enti... | yes | 0 | NIv2 | task472_haspart_classification | zs_opt | [
-0.7975159883499146,
0.27915793657302856,
0.8522327542304993,
-0.07942362129688263,
-0.3791998028755188,
-0.6489932537078857,
-0.02216506004333496,
0.5284479260444641,
0.6525486707687378,
-0.6229310631752014,
-0.4384559392929077,
-0.2776705324649811,
-0.5863025784492493,
0.2790553569793701... |
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... | political
****
| 4 | NIv2 | task1491_bengali_political_hate_speech_binary_classification | fs_opt | [
-0.4129024147987366,
-0.29528677463531494,
0.48551398515701294,
0.41311976313591003,
-0.14045250415802002,
-0.13347893953323364,
-0.04842096194624901,
0.2033267766237259,
0.09633082151412964,
0.082810178399086,
-0.2255244255065918,
-0.07421034574508667,
0.006936406716704369,
-0.29999756813... |
Detailed Instructions: Here are two questions (Question1 and Question2). If these questions have the same meaning and same answer, answer "Yes", otherwise "No".
Problem:Question1: What is the best stock to invest in 2016 and why?, Question2: What are the best stocks to invest in 2012?
Solution: | No | 8 | NIv2 | task1287_glue_qqp_paraphrasing | zs_opt | [
-0.8516429662704468,
0.3398667573928833,
0.27269232273101807,
0.5362139344215393,
0.07299202680587769,
-0.11407463252544403,
0.31352919340133667,
0.616798996925354,
0.3839789927005768,
0.17382770776748657,
-0.03641030192375183,
0.46505051851272583,
-0.32584843039512634,
-0.2307780832052230... |
Detailed Instructions: You will be given three sentences. Read them, then identify a noun phrase (person, place, or thing) or event that is shared between all three sentences. As the output, write the span of the text corresponding to that phrase in each sentence. Keep the order of the sentences, that is, your answer s... | 1: two Australian drug smugglers -- members of the `` Bali Nine 2: Andrew Chan and Myuran Sukumaran 3: Two Australian drug traffickers on death row in Indonesia | 8 | NIv2 | task281_points_of_correspondence | zs_opt | [
0.1292508840560913,
-0.054070375859737396,
-0.2737233638763428,
-1.0812057256698608,
0.08212736248970032,
0.3415268659591675,
0.37562084197998047,
0.35372114181518555,
-0.26028457283973694,
0.4698728919029236,
-0.47987937927246094,
0.1734289824962616,
-0.9745840430259705,
-0.07031704485416... |
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 : Guy Ritchie's Gamekeeper is a comic book series from Virgin Comics and film dire... | Which building was build for the Minnesota National Guard in 19351936, that began to host the Minneapolis Lakers in 1959?
| 0 | NIv2 | task191_hotpotqa_question_generation | fs_opt | [
0.07256294786930084,
0.24651245772838593,
-0.6035308837890625,
-0.18287943303585052,
0.5085893869400024,
0.07125074416399002,
0.17705994844436646,
1.1433689594268799,
-0.18332543969154358,
0.30019670724868774,
-0.3060442805290222,
0.09966901689767838,
-0.9928335547447205,
0.175170153379440... |
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 incoherent / implausible by indicating 1 or 2 in the output. If both sentences are plausible, pick the one that makes less sense.
Q: Beginning: Mary has b... | 2 | 4 | NIv2 | task070_abductivenli_incorrect_classification | zs_opt | [
-0.15010564029216766,
0.22957921028137207,
-0.22950509190559387,
0.06929279863834381,
-0.3874383568763733,
-0.6287970542907715,
-0.1245749369263649,
1.154579520225525,
0.07506537437438965,
0.3506414294242859,
-0.43847236037254333,
-0.40714704990386963,
-0.3001544773578644,
-0.3471843898296... |
Part 1. 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.
Part 2. Example
... | Social Science | 7 | NIv2 | task521_trivia_question_classification | fs_opt | [
0.4417104423046112,
0.6294598579406738,
0.06780095398426056,
0.5180229544639587,
0.28014397621154785,
-0.3502168357372284,
0.6185766458511353,
0.5401341915130615,
0.4034608006477356,
-0.08556509017944336,
-0.6726067066192627,
0.470637708902359,
-0.949374794960022,
-0.329336017370224,
0.7... |
Part 1. Definition
Given an open-ended topic (movie name, a persons name, an event, sports, etc) generate a simple trivia-type question.
Part 2. Example
1968 winter olympics
Answer: Which Frenchman won the Alpine triple-crown at the 1968 Winter Olympics?
Explanation: Both these questions ask a specific fact as the answ... | Ceres is the Roman counterpart of which Greek goddess? | 7 | NIv2 | task897_freebase_qa_topic_question_generation | fs_opt | [
0.3701310455799103,
0.5111428499221802,
-0.6822654604911804,
0.0011685688514262438,
0.016115128993988037,
0.3544660806655884,
1.034787654876709,
-0.13781118392944336,
0.1717282235622406,
-0.8540456295013428,
-1.1624820232391357,
0.17176687717437744,
-0.8737019300460815,
-0.1587220728397369... |
In this task, you are given a post in English from online platforms. You are expected to identify whether the post is hateful against immigrants and women. A hateful post expresses hate or encourages violence towards a person or a group. If a post is hateful but not towards immigrants and women, it should be labeled as... | Non-hateful
| 6 | NIv2 | task333_hateeval_classification_hate_en | fs_opt | [
-0.12076450139284134,
0.324196457862854,
0.4484916925430298,
0.49749279022216797,
0.3825247883796692,
-0.6423361301422119,
0.3700324296951294,
0.858220636844635,
0.21510109305381775,
0.86412113904953,
0.057275980710983276,
0.0603940449655056,
0.02555299550294876,
-0.9795160293579102,
-0.... |
You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Hebrew.
Input: Consider Input: ¿Y cuántas veces creen que han estado en la cárcel antes?
Output: וכמה פעמים, לדעתכם, הם שהו קודם בכלא?
Input: Consider Input: En cambio, nuestro rey nos impuso la democracia incluyéndola en la Con... | Output: והצילה 1,500 ילדות מכריתה.
| 2 | NIv2 | task1229_ted_translation_es_he | fs_opt | [
-0.6547873020172119,
0.7583637237548828,
0.1965533345937729,
-0.0021830955520272255,
-0.535415530204773,
-0.4781668782234192,
0.441164493560791,
0.7833845019340515,
0.5617426633834839,
-0.31731873750686646,
-0.6085916757583618,
0.07658575475215912,
-0.7459837198257446,
-0.39710429310798645... |
In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: toxic and non-toxic. Toxicity is defiend as anything that is rude, disrespectful, or unreasonable that would make someone want to leave a converation.
One example is below.
Q: Comment: i am jus... | Toxic | 9 | NIv2 | task327_jigsaw_classification_toxic | fs_opt | [
-0.4259757995605469,
0.7785420417785645,
0.7914476990699768,
-0.2067742645740509,
-0.12281651049852371,
-0.949596643447876,
0.9173988699913025,
0.41081565618515015,
0.5645942687988281,
0.7962955236434937,
-0.029744133353233337,
-0.14297693967819214,
-1.0656955242156982,
-0.7309939861297607... |
In this task you will be given two dialogues. You need to determine if both dialogues have the same underlying emotion. The possible emotions are happy, sad, angry, or other. If they do output 'yes', if not output 'no'.
Q: Dialogue 1: 'u r going to send haha of my car if you really want to see ok '. Dialogue 2: 'do yo... | yes | 4 | NIv2 | task518_emo_different_dialogue_emotions | zs_opt | [
-0.847065269947052,
0.04605986177921295,
0.7049578428268433,
-0.24896591901779175,
-0.5829674005508423,
0.07814590632915497,
1.2366867065429688,
-0.011568120680749416,
0.1922677755355835,
-0.3698192536830902,
-0.10836997628211975,
-0.8734220266342163,
0.011110714636743069,
0.34943264722824... |
Detailed Instructions: Given a sentence in the Japanese and Indonesian(Bahasa variant) language. Your task is check if the Bahasa Indonesia sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Problem:Japanese: HMCSトロントとカナダの沿岸警備隊船ピエール・ラディソンは、ハドソン海峡... | Yes | 8 | NIv2 | task1117_alt_ja_id_answer_generation | zs_opt | [
-0.2799898087978363,
0.015618785284459591,
-0.10950438678264618,
-0.24297377467155457,
0.45375221967697144,
-1.0004216432571411,
0.3683508634567261,
-0.2728555202484131,
0.24365893006324768,
-0.30002814531326294,
-0.29701822996139526,
-0.5672029852867126,
-0.6588262915611267,
0.06193565577... |
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..
[EX Q]: Context: Even though Sydney had only just graduate from medical school, Sydney prevented the virus from spreading and saved the... | Why did Austin do this?
| 6 | NIv2 | task581_socialiqa_question_generation | fs_opt | [
-0.5780307054519653,
0.7971823215484619,
0.24639204144477844,
-1.3052141666412354,
0.7530622482299805,
-0.9308251142501831,
-0.46620965003967285,
0.8912173509597778,
0.9344452619552612,
0.0374448262155056,
-0.18138012290000916,
0.49259811639785767,
-1.0243635177612305,
0.07846233248710632,... |
Detailed Instructions: In this task you are given a sentence. You must judge whether the main verb of the sentence is in present or past tense. Label the instances as "Present" or "Past" based on your judgment. If there is no verb in the given text, answer "Present".
Q: Once again he toyed with the idea of calling this... | Past | 9 | NIv2 | task429_senteval_tense | zs_opt | [
-0.40449953079223633,
0.41994011402130127,
0.47058624029159546,
0.010238701477646828,
0.07864353060722351,
-0.13472089171409607,
0.9061563014984131,
1.0546985864639282,
0.026417162269353867,
-0.11304971575737,
-0.47121164202690125,
-0.11528447270393372,
-0.11113877594470978,
-0.08857560902... |
Given a sentence in the Japanese, provide an equivalent translation in Filipino that retains the same meaning through the translation. In translation, keep numbers as it is.
Example input: フランスのパリ、パルク・デ・プランスで行われた2007年ラグビーワールドカップのプールCで、イタリアは31対5でポルトガルを下した。
Example output: អ៊ីតាលីបានឈ្នះលើព័រទុយហ្គាល់ 31-5 ក្នុងប៉ូលCនៃព... | ក្រុមកំហឹងអ្នកជំទាស់ប្រហែលជា600នាក់-ខ្លះរាយការមកថារាប់ពាន់នាក់ -បានប្រមូលផ្តុំគ្នានៅទីលានខាងក្រៅវិមានប្រធានាធិបតី។ | 3 | NIv2 | task1121_alt_ja_khm_translation | fs_opt | [
-0.15939711034297943,
0.7262500524520874,
-0.704573929309845,
0.26947903633117676,
-0.21480655670166016,
-0.9784379005432129,
-0.12215256690979004,
0.14766493439674377,
0.08582761138677597,
-0.6917576789855957,
-0.8855043649673462,
0.722093939781189,
-0.6801038384437561,
0.7376588582992554... |
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.
[Q]: Ayon sa nagpapatakbo ng makina, aabutin ng mga ilang Linggo upang ganap na mapigil ito.
[A]: トレーラーの操縦者によると、栓を締めるのに何週間も掛かる可能性がある。
[Q]: "Ina... | 7歳の生徒がテディベアに、アラブ世界で最も一般的な名前のひとつであるムハンマドという名を付けるのを許したために昨日逮捕されたイギリスの教師、ジリアン・ギボンズの死刑を求めるために、約600人の怒ったスーダンデモ隊がナイフや棒で武装し、金曜日の祈りの後でハルツーム殉教者広場に集まった。
| 5 | NIv2 | task1119_alt_fil_ja_translation | fs_opt | [
-0.027502574026584625,
-0.09785667061805725,
-0.3111981749534607,
-0.30849629640579224,
-0.13040968775749207,
-0.7072810530662537,
0.7785084247589111,
0.3592246472835541,
0.044772692024707794,
0.10722130537033081,
-0.3783743381500244,
0.5940175652503967,
-0.4300422966480255,
0.535227715969... |
Teacher:Given a sentence, generate a most likely context or previous statement. The previous statement should be relevant to the given statement.
Teacher: Now, understand the problem? Solve this instance: Someone gives a dissatisfied look.
Student: | Someone pulls at the hair on the back of her head. | 6 | NIv2 | task455_swag_context_generation | zs_opt | [
0.15085825324058533,
0.7938469052314758,
-0.040977753698825836,
-0.6677713394165039,
-0.3234604597091675,
-0.31596773862838745,
-0.016645710915327072,
0.7597146034240723,
0.5396099090576172,
0.028725624084472656,
0.04869266599416733,
-0.29915696382522583,
-0.9406851530075073,
-0.0754429474... |
You will be given a definition of a task first, then some input of the task.
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 i... | colse | 1 | NIv2 | task088_identify_typo_verification | zs_opt | [
-0.4330417811870575,
0.6271559000015259,
-0.08066828548908234,
0.41489267349243164,
0.5460138320922852,
-0.7882132530212402,
0.7383915185928345,
0.2959165573120117,
-0.1284404695034027,
0.3438005745410919,
-0.24244317412376404,
-0.31501463055610657,
-0.5640363693237305,
-0.4981748163700104... |
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Spanish.
One example: それは個人の内面で起こる闘い悪 ､ 罪 ､ 誘惑 ､ 欲望 ､ 貪欲に対する苦闘ですそれは個人の内面で起こる闘い悪 ､ 罪 ､ 誘惑 ､ 欲望 ､ 貪欲に対する苦闘です
Solution is here: Es una lucha interna, una lucha en contra del vicio, el pecado, la tentación, el deseo, la avaricia.
Expl... | Eso es lo que realmente hace de este, un descubrimiento increíble. | 6 | NIv2 | task1223_ted_translation_ja_es | fs_opt | [
-0.39262792468070984,
0.5071422457695007,
-0.42097702622413635,
-0.24782896041870117,
-0.8496805429458618,
-0.2819030284881592,
0.08158014714717865,
0.48414865136146545,
0.29938334226608276,
-0.6424683928489685,
-0.6247891187667847,
-0.21911022067070007,
-1.1591798067092896,
-0.34138107299... |
You are asked to create a question containing a blank (_), based on the given context word. Your question must contain two related but different objects; for example "trophy" and "suitcase". The expected answer to your question must be one of the objects present in the sentence. The expected answer must not be associat... | The judge didn't think that the span of the created sculpture was as accurate as the statue as the _ was 10 feet long.
| 3 | NIv2 | task031_winogrande_question_generation_object | fs_opt | [
0.8785825967788696,
0.6615925431251526,
0.19459331035614014,
0.2945345342159271,
0.5905653238296509,
-0.7095433473587036,
0.5718522071838379,
1.241076946258545,
-0.32271814346313477,
-0.7178689241409302,
-0.24364572763442993,
0.2631247639656067,
-0.1744757890701294,
-0.001163780689239502,
... |
Q: 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 corre... | C | 7 | NIv2 | task228_arc_answer_generation_easy | zs_opt | [
0.013232242316007614,
0.6923319697380066,
-0.6937016844749451,
-1.0870285034179688,
-0.8868237733840942,
-0.2540421187877655,
0.24589984118938446,
0.3614940047264099,
0.052943482995033264,
-0.3023785650730133,
-0.5821347236633301,
-0.4527136981487274,
0.2205558717250824,
-0.425043493509292... |
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.
--------
Question: good thing i didnt get my new glasses today, i just founf a coupon for 100 dollars off :O yay im excited.
Answer: positive
Question: Th... | positive
| 7 | NIv2 | task195_sentiment140_classification | fs_opt | [
-1.2316523790359497,
-0.04347161576151848,
0.8461425304412842,
0.64508056640625,
-0.15012958645820618,
-1.0028624534606934,
-0.026431608945131302,
0.922869861125946,
0.5471638441085815,
0.8223349452018738,
-0.3719474673271179,
-0.35555464029312134,
-0.535369873046875,
-0.7599469423294067,
... |
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