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 |
|---|---|---|---|---|---|---|
Given the task definition and input, reply with output. 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 listi... | #1 return cylinders
#2 return number of #1 | 5 | NIv2 | task176_break_decompose_questions | zs_opt | [
0.5606527328491211,
-0.21138930320739746,
-0.7521671056747437,
0.6881461143493652,
0.2003631889820099,
-0.26879459619522095,
1.1293439865112305,
0.0982215404510498,
-0.1885259747505188,
0.39503681659698486,
-0.7216552495956421,
0.0018253520829603076,
0.11367550492286682,
0.387634813785553,... |
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 are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. If the conversation begins with a question, label it '1' otherwise '0'.
Pe... | 0 | 0 | NIv2 | task1534_daily_dialog_question_classification | fs_opt | [
0.464287132024765,
0.33470654487609863,
-0.21786493062973022,
0.396087110042572,
0.3567200303077698,
0.02336738631129265,
0.22834816575050354,
0.3493932783603668,
-0.005714942701160908,
0.09576709568500519,
-0.46753162145614624,
-0.48429393768310547,
0.028493167832493782,
-0.28187775611877... |
In this task, you are given a sentence from the Quran in English, and your task is to translate it into Persian.
Ex Input:
Truly they will eat thereof and fill their bellies therewith.
Ex Output:
پس این منکران لجوج حتما از آن میخورند و شکمها را از آن پر میکنند.
Ex Input:
Say: Who hath forbidden the beautiful (gi... | آیا به قرآن [عمیقا] نمیاندیشند؟ چنانچه از سوی غیر خدا بود، همانا در آن اختلاف و ناهمگونی بسیاری مییافتند.
| 1 | NIv2 | task656_quran_en_fa_translation | fs_opt | [
-0.8005205988883972,
0.9230487942695618,
-0.16279897093772888,
-0.19980579614639282,
-1.004744052886963,
-0.06046966463327408,
0.4850500822067261,
0.6572180986404419,
0.10907553881406784,
-0.028010107576847076,
-1.0775957107543945,
0.8738123774528503,
-0.6015348434448242,
0.228778406977653... |
In this task, you are given a sentence. You are expected to recognize the name of gene or protein. Although there might be several correct answers, you need to write one of them.
Q: Further , cells cotransfected with a UF promoter - luciferase ( - 1935UF - Luc ) reporter gene and the BTEB expression vector had 2 - fol... | UF promoter | 4 | NIv2 | task1481_gene_extraction_bc2gm_dataset | zs_opt | [
-1.3761112689971924,
-0.022650647908449173,
-0.8653943538665771,
-0.186685711145401,
-0.5220019817352295,
0.4315875470638275,
0.05095665156841278,
0.5111236572265625,
0.030298713594675064,
-0.4268956482410431,
-0.6337723135948181,
0.6171094179153442,
-0.6266433596611023,
0.3063334822654724... |
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statement... | eq { hop { nth_argmax { all_rows ; number ; 2 } ; language } ; yiddish } | 2 | NIv2 | task210_logic2text_structured_text_generation | zs_opt | [
0.33616942167282104,
-0.013663173653185368,
-0.4006793797016144,
0.44293856620788574,
0.16666293144226074,
-0.4410746097564697,
0.6525849103927612,
0.451775461435318,
0.29042017459869385,
-0.20237982273101807,
-0.3322438895702362,
-0.16418467462062836,
-0.2981055676937103,
0.65538817644119... |
Detailed Instructions: The provided files include famous book titles and sentences in the English language, and we ask you to translate those to the Portuguese Language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and form of each sentence i... | "Gostaria de ter isto explicado", disse a Tartaruga Falsa. | 9 | NIv2 | task1647_opus_books_en-pt_translation | zs_opt | [
-0.34275880455970764,
0.4717266261577606,
0.026485618203878403,
-0.564608633518219,
-0.277239590883255,
-1.188644528388977,
0.5105631351470947,
-0.07386152446269989,
-0.2640177607536316,
-0.2364671230316162,
-0.08935929834842682,
0.17641977965831757,
-1.456563949584961,
0.0876246765255928,... |
Part 1. Definition
In this task, you need to reverse the order of words in the given sentence.
Part 2. Example
Sentence: luggage surrounds a vehicle in an underground parking area
Answer: area parking underground an in vehicle a surrounds luggage
Explanation: This is a correct answer, as it correctly reverses the order... | chairs stacked of lot a near beach a on walking dog a and man a | 7 | NIv2 | task376_reverse_order_of_words | fs_opt | [
0.09712004661560059,
0.47174209356307983,
-0.7669121026992798,
-0.10483723878860474,
-0.12445910274982452,
0.1409423053264618,
0.4175255298614502,
0.39125609397888184,
0.7977579832077026,
-0.3902548551559448,
-0.659770131111145,
0.1903747022151947,
-0.012651771306991577,
-0.202430263161659... |
Detailed Instructions: In this task, you are given a premise, a hypothesis, and an update. The premise sentence describes a real-world situation and is always assumed to be true. The hypothesis sentence describes an assumption or inference that you might make about that situation having read the premise. The update pro... | weakener | 8 | NIv2 | task936_defeasible_nli_snli_classification | zs_opt | [
-0.08114328980445862,
-0.16095581650733948,
-0.16430965065956116,
-0.1498246192932129,
-0.0873522236943245,
0.046699464321136475,
1.1168146133422852,
1.210284948348999,
0.46075427532196045,
-0.17407342791557312,
-1.035072922706604,
-0.405978798866272,
-0.7725239396095276,
0.174211502075195... |
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... | spine | 4 | NIv2 | task471_haspart_answer_generation | zs_opt | [
-0.8721315860748291,
0.7239362597465515,
0.04246314615011215,
-0.47592538595199585,
-0.3813523054122925,
-0.33183595538139343,
-0.36818963289260864,
0.43999338150024414,
0.6136068105697632,
-0.7241374254226685,
-0.1595459133386612,
0.10325765609741211,
-0.14134573936462402,
0.0827496945858... |
You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Japanese.
Example input: A ideia é muito, muito simples.
Example output: このアイデアはとてもシンプルで
Example explanation: The Portugese sentence is correctly translated into Japanese, because the meaning is preserved.
Q: Qual é o tipo de... | どんな方法を使いますか ？ | 3 | NIv2 | task1275_ted_translation_pt_ja | fs_opt | [
-0.568122148513794,
0.5802382230758667,
0.06645594537258148,
-0.5606395602226257,
-0.010666468180716038,
-0.9179282188415527,
0.3367490768432617,
0.3279532790184021,
0.27973803877830505,
-0.6530731916427612,
-1.0035943984985352,
0.03297191113233566,
-0.34831130504608154,
0.330127090215683,... |
Detailed Instructions: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, t... | Sentence 1: Betty has started fixing her eyebrows with makeup rather than wax, because the _ is too difficult.
Answer1: wax.
Sentence 2: Betty has started fixing her eyebrows with makeup rather than wax, because the _ is easier.
Answer2: makeup. | 8 | NIv2 | task029_winogrande_full_object | zs_opt | [
0.5260745286941528,
0.2903462052345276,
0.08972875773906708,
-0.38158661127090454,
0.6929289102554321,
-0.5411445498466492,
0.41020599007606506,
1.1176682710647583,
-0.6866936683654785,
-0.15424126386642456,
-0.3534548580646515,
-0.14263349771499634,
-0.555878758430481,
-0.1008825153112411... |
Teacher:In this task, you will be shown a short story with a beginning, two potential middles, and an ending. Your job is to choose the middle statement that makes the story coherent / plausible by writing "1" or "2" in the output. If both sentences are plausible, pick the one that makes most sense.
Teacher: Now, under... | 1 | 6 | NIv2 | task069_abductivenli_classification | zs_opt | [
-0.5033408403396606,
0.6778831481933594,
0.1762208789587021,
-0.2349587380886078,
-0.33275729417800903,
-0.015648212283849716,
0.3036571741104126,
0.6363165378570557,
-0.30468690395355225,
0.140452042222023,
0.20285260677337646,
0.07283962517976761,
-0.37522879242897034,
-0.793830513954162... |
Teacher:A text is given in Hindi. Translate it from the Hindi language to the Urdu language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? Solve this instance: سنگیت ناٹک اکیڈیمی ویب مہم ‘سانجھی۔ مجھ میں کلاکار ’ کےدوسرے مرحلے کاآغاز کرے گی
Student: | संगीत नाटक अकादमी वेब अभियान सांझी-मुझ में कलाकार के दूसरे चरण की शुरूआत करेगी | 6 | NIv2 | task1054_pib_translation_urdu_hindi | zs_opt | [
-0.7323886156082153,
0.3433580994606018,
-0.3426620364189148,
-0.2775306701660156,
-0.5397276282310486,
-0.049162305891513824,
0.4952002167701721,
-0.1530303657054901,
-0.07825998961925507,
-0.9305484294891357,
0.04100193828344345,
-0.43908408284187317,
-0.5067701935768127,
-0.054194793105... |
Q: This task is about generating an incorrect answer to a question given the question and a true statement related to the question. The answer must be related to the question, but incorrectly answer it given the context.
Fact: lightning can cause a forest fire. Question: In a forest without anyone around, a fire may be... | a bird | 7 | NIv2 | task1400_obqa_incorrect_answer_generation | zs_opt | [
0.2673053741455078,
1.2915599346160889,
-0.2531590461730957,
-1.0982513427734375,
-0.9528601765632629,
-1.1309348344802856,
0.7708157300949097,
1.4240751266479492,
-0.1376882642507553,
-0.8177700638771057,
-0.697184681892395,
-0.5832059383392334,
-1.1531721353530884,
-0.5011592507362366,
... |
Q: In this task, you are given Wikipedia articles on a range of topics, we ask you to write a question based on the content of the articles that can be answered in a binary manner i.e. True or False.
Banknotes of the pound sterling -- Not since 1945 has there been bigger notes than £50 issued for general circulation by... | can you get a £100 pound note | 7 | NIv2 | task1660_super_glue_question_generation | zs_opt | [
0.0003707828000187874,
0.004919972270727158,
-0.5006808638572693,
0.07314546406269073,
-0.13549400866031647,
-1.2234245538711548,
0.9332039952278137,
0.31530606746673584,
0.3376707136631012,
-0.4046560525894165,
-0.10623742640018463,
0.4844891428947449,
-0.5031013488769531,
-0.075856208801... |
Detailed Instructions: You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Galician.
Problem:Y la mayoría de ellos, salvo SCRIPT y Cha0, no presentaban habilidad social real en el mundo exterior; sólo en la Web.
Solution: | E a maioría, salvo SCRIPT e Cha0, non demostraron habilidades sociais no mundo exterior, só na Web. | 8 | NIv2 | task1100_ted_translation_es_gl | zs_opt | [
-1.1488964557647705,
1.679703712463379,
-0.14928609132766724,
-1.0786540508270264,
-0.2979852259159088,
-0.6807314157485962,
-0.022716529667377472,
1.3341195583343506,
-0.6265254020690918,
-0.678709864616394,
-0.697604238986969,
0.20260357856750488,
-0.9185981750488281,
-0.3988711535930633... |
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: No one wants to... | Not sad | 4 | NIv2 | task399_semeval_2018_task1_tweet_sadness_detection | zs_opt | [
-1.4363994598388672,
0.23257297277450562,
0.33010804653167725,
0.008828620426356792,
-0.17800204455852509,
-0.29504072666168213,
1.0364000797271729,
-0.08027538657188416,
0.7189251780509949,
0.4993056356906891,
-0.2590031921863556,
0.01951982080936432,
0.12016236782073975,
0.03778033703565... |
Given the task definition and input, reply with output. In this task, find the most appropriate number to replace the blank (indicated with _ ) and express it in words.
Malaria is the leading killer, responsible for _ in five child deaths.
| one | 5 | NIv2 | task672_nummersense | zs_opt | [
0.8839646577835083,
0.39649754762649536,
-0.46605613827705383,
-0.6441973447799683,
-0.24296914041042328,
0.2122049182653427,
0.008635872974991798,
0.5240845680236816,
0.10690389573574066,
0.008914452977478504,
-0.42712923884391785,
0.5099694728851318,
-0.5278235673904419,
0.73582297563552... |
Detailed Instructions: Given a document and an entity the task is to select the author's sentiment towards the entity. Sentiments can be Positive, Neutral and Negative. Select Positive if the article expresses a positive view towards the given entity or praises its quality or skills. Select Neutral if the document expr... | Positive | 8 | NIv2 | task420_persent_document_sentiment_classification | zs_opt | [
0.4951138496398926,
0.3289130926132202,
0.3288230299949646,
-0.2620547413825989,
-0.22559261322021484,
-0.5913562178611755,
0.8323913812637329,
0.4666147232055664,
0.6453099846839905,
0.7328863143920898,
0.0561412051320076,
1.5434386730194092,
-1.0242373943328857,
-0.05083072930574417,
0... |
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 there exist ... | Melbourne
| 1 | NIv2 | task303_record_incorrect_answer_generation | fs_opt | [
0.6615833044052124,
0.11217549443244934,
-0.19994047284126282,
-0.4306436777114868,
0.6060779094696045,
0.07670280337333679,
0.45591026544570923,
0.894896388053894,
-0.2313709557056427,
-0.13251063227653503,
-0.04498923569917679,
1.3234272003173828,
-0.596572756767273,
0.03039843589067459,... |
In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.
[EX Q]: name[Midsummer House], food[Chinese],... | The Waterman is a pub that sells Japanese food and is located in riverside and has a customer rating of 3 out of 5.
| 6 | NIv2 | task957_e2e_nlg_text_generation_generate | fs_opt | [
-0.6703203916549683,
0.2718665599822998,
-0.7117003798484802,
-0.3390495181083679,
0.14389102160930634,
-0.16381138563156128,
-0.3529219627380371,
0.270505428314209,
-0.5177133083343506,
-0.20725031197071075,
0.818700909614563,
-0.23733070492744446,
-0.9255540370941162,
-0.1188844889402389... |
In this task, you're given reviews from Amazon's food products and a summary of that review. Your task is to classify whether the given summary matches the original review. Generate "True" if the given review and its summary match, otherwise generate "False".
Reviews: Cute but way way way to big they don't know how to... | False | 0 | NIv2 | task1309_amazonreview_summary_classification | zs_opt | [
-0.48443830013275146,
0.3899573087692261,
-0.0606217235326767,
-0.5363287925720215,
-0.12440791726112366,
-0.4653360843658447,
0.4124250113964081,
0.5151443481445312,
-0.7383877038955688,
0.5699177384376526,
-0.45124924182891846,
-0.0026310270186513662,
-0.7870921492576599,
-0.026962466537... |
In this task, you will be shown an English sentence. You need to classify the sentence as either a representation of an anaphor number agreement or as an incorrect representation. An anaphor is an expression whose interpretation depends upon another expression. Anaphor number agreement is a restriction where a phrase a... | Output: good
| 2 | NIv2 | task1560_blimp_binary_classification | fs_opt | [
0.5335599184036255,
0.494448721408844,
-0.1667596995830536,
-0.5947294235229492,
-0.40726855397224426,
-0.8316686153411865,
0.6452149152755737,
0.20654676854610443,
0.46649008989334106,
-0.33518558740615845,
-0.31691062450408936,
0.03617270290851593,
-0.5879850387573242,
-0.154669642448425... |
Part 1. Definition
You are given a paragraph (Passage), a question (Question) and two answer options (Option1 and Option2). Your task is to find the correct answer (and return the string of the correct option, not option1/2) for the given question from the given options and based on the given passage. Answer of the que... | backyard | 7 | NIv2 | task164_mcscript_question_answering_text | fs_opt | [
0.7770607471466064,
0.7491600513458252,
-0.07709510624408722,
0.23761305212974548,
-0.09508538246154785,
-0.09818127006292343,
1.2109241485595703,
0.6677979826927185,
-0.0348990336060524,
-0.25333839654922485,
-0.45193061232566833,
-0.11432607471942902,
-0.5978983044624329,
0.1003676205873... |
Given a negotiation between two participants, answer 'Yes' if both participants agree to the deal, otherwise answer 'No'.
Example input: THEM: i need the hats and the ball YOU: i can give you one hat and the ball. i want 2 books and 1 hat THEM: i have to have both hats and the ball or both hats and a book to make a ... | Yes | 3 | NIv2 | task1384_deal_or_no_dialog_classification | fs_opt | [
0.6670328378677368,
0.5173442959785461,
0.1960284411907196,
0.7099664211273193,
0.4210042357444763,
-0.8176860213279724,
0.39380016922950745,
0.10763116180896759,
0.24400001764297485,
-0.2877665162086487,
-0.09370554983615875,
-0.03463678061962128,
-0.6504557728767395,
-0.20772424340248108... |
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\*.
Example input: when are hops added to t... | September 19, 2018 | 3 | NIv2 | task582_naturalquestion_answer_generation | fs_opt | [
-0.7277411222457886,
0.3150150179862976,
0.5525777339935303,
0.4732673466205597,
-0.6312118172645569,
-0.9942117929458618,
0.4763100743293762,
-0.12840571999549866,
-0.3881177008152008,
0.09286722540855408,
-0.16689527034759521,
0.15393607318401337,
-0.15429875254631042,
0.0098244678229093... |
Instructions: In this task, you need to count the number of words in a sentence that contain the given letter
Input: Sentence: 'a home office looks well equipped and often used'. How many words contain the letter 'r' in the sentence.
Output: | 0 | 3 | NIv2 | task161_count_words_containing_letter | zs_opt | [
-0.043952275067567825,
1.2991539239883423,
-0.059030428528785706,
0.3477376103401184,
-0.12780630588531494,
0.7726609110832214,
0.005670913495123386,
0.4884044826030731,
0.32488495111465454,
-0.5566538572311401,
-0.4994265139102936,
-0.5960360765457153,
-0.8703867793083191,
0.0829480662941... |
Detailed Instructions: In this task, given a sentence in the English language, your task is to convert it into the Lao (Laotian) language.
Problem:Before the success of his first film, Corneau attempted to make a documentary about New York and an adaptation of a novel.
Solution: | ກ່ອນຄວາມສໍາເລັດຈາກຮູບເງົາເລື່ອງທໍາອິດຂອງລາວ ຄໍໂນ ມີຄວາມຕັ້ງໃຈຈະສ້າງສາລະຄະດີກ່ຽວກັບ ນິວຢອກ ແລະ ການດັດແປງນາວະນິຍາຍ. | 8 | NIv2 | task554_alt_translation_en_la | zs_opt | [
0.4889103174209595,
0.7061249017715454,
-0.11593417078256607,
-0.5474449992179871,
-0.05386221408843994,
0.47415345907211304,
-0.03061078116297722,
0.5564149618148804,
-0.7011057138442993,
-0.2853474020957947,
0.09967456758022308,
-0.5513253211975098,
-1.2340936660766602,
-0.16508065164089... |
You are given a sentence in English. Your job is to translate the English sentence into Arabic.
One example: (Applause) However there is a political battle in our country.
Solution is here: (تصفيق) ومع ذلك هناك معارك سياسية في بلدنا.
Explanation: The English sentence is correctly translated into Arabic, because the mea... | ظننت أنها النهاية. | 6 | NIv2 | task1220_ted_translation_en_ar | fs_opt | [
0.031575530767440796,
0.42218971252441406,
0.3913722336292267,
-0.8134886026382446,
0.10750096291303635,
-0.5817646980285645,
1.004056692123413,
0.030097976326942444,
0.155399888753891,
0.3676568865776062,
-0.7182436585426331,
-0.048569079488515854,
-1.1126203536987305,
0.15255437791347504... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Generate a question which can yield the answer mentioned in the input. Generated question must be answered by the answer provided in input, without using any extra knowledge.
Context : Isaac Nicola ... | Where did Stephen Nissenbaum study or work? | 0 | NIv2 | task1326_qa_zre_question_generation_from_answer | fs_opt | [
0.4726521074771881,
-0.3114941716194153,
-0.3574889302253723,
-0.19012890756130219,
0.524581789970398,
-0.21863119304180145,
0.4528976082801819,
0.4833518862724304,
0.2004074901342392,
0.46602246165275574,
0.5702095031738281,
0.7369065880775452,
-1.2846968173980713,
0.13070160150527954,
... |
In this task you will be given a list of integers. You should find the minimum absolute difference between 2 integers in the list. The absolute difference is the absolute value of one integer subtracted by another. The output should be a single integer which is the smallest possible absolute distance.
Q: [30, 21, -39, ... | 3 | 4 | NIv2 | task1445_closest_integers | zs_opt | [
-0.9010360240936279,
0.8150302171707153,
0.3014356195926666,
-0.7819238901138306,
-0.4445844888687134,
-0.36133041977882385,
1.034260869026184,
0.06202895939350128,
0.6653573513031006,
-0.013319961726665497,
-0.18820220232009888,
-0.2053017020225525,
-0.5245500802993774,
-0.066373877227306... |
Detailed Instructions: Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
See one example below:
Problem: អ៊ីតាលីបានឈ្នះលើព័រទុយហ្គាល់ 31-5 ក្នុងប៉ូលCនៃពីធីប្រកួតពានរង្វាន់ពិភពលោកនៃកីឡាបាល់ឱបឆ... | 最初の世代のXboxコンソールも、プレイステーション２の２年後に発売されたために似たような売れ行きだった。 | 4 | NIv2 | task1122_alt_khm_ja_translation | fs_opt | [
0.6524456739425659,
0.2678820788860321,
-0.698125958442688,
0.31074851751327515,
-0.19425833225250244,
-0.5151146650314331,
-0.0323539599776268,
0.31707075238227844,
-0.10994326323270798,
-0.6354585886001587,
-0.701429009437561,
0.48249581456184387,
-0.5110688209533691,
0.33400171995162964... |
Teacher: In this task, you're given a pair of sentences, sentence 1 and sentence 2, that neither agree with nor contradict each other. Your job is to alter sentence 2 so that the pair clearly agree with each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid usin... | A young man is about to hit the ball during a baseball game. | 2 | NIv2 | task188_snli_neutral_to_entailment_text_modification | fs_opt | [
0.02377992868423462,
0.1865539699792862,
0.059364695101976395,
-0.22788715362548828,
0.6055648326873779,
-0.8143587112426758,
-0.5744935274124146,
0.4748157262802124,
0.05265782028436661,
-0.3061746060848236,
-0.550850510597229,
0.2562735676765442,
-0.712110161781311,
-0.5840770602226257,
... |
You will be given a definition of a task first, then some input of the task.
In this task, you are given a statement spoken by a politician in natural language. Your task is to generate the subject of the discussion for the given statement. The subject generated is not necessarily a part of the given input. Your answer... | candidates-biography | 1 | NIv2 | task613_politifact_text_generation | zs_opt | [
0.2829762399196625,
0.43677765130996704,
0.027415376156568527,
0.10414539277553558,
-0.16302810609340668,
0.08258606493473053,
1.3226863145828247,
-0.21399201452732086,
0.3741932511329651,
0.08480652421712875,
0.32505732774734497,
0.35283705592155457,
-0.8920965194702148,
0.249616414308547... |
In this task you will be given a list of numbers. A list is shown by two brackets and comma-separated numbers inside, like: [1,2,3]. You should remove all of the even numbers from the list. If every number in the input list is even an empty list should be returned. Zero should be counted as an even number.
Example inp... | [15] | 3 | NIv2 | task205_remove_even_elements | fs_opt | [
-0.3755171597003937,
0.06120260804891586,
-0.6832842826843262,
-0.5165402889251709,
0.4635542631149292,
-0.1689724326133728,
0.9610416889190674,
0.1956944763660431,
-0.6908841133117676,
0.14433544874191284,
-0.7222133874893188,
0.3407436013221741,
-0.08388940244913101,
-0.8103319406509399,... |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Ex Input:
חברת השוקולדים הדנית "" אנטון ברג "" פתחה את מה שנקרא "" חנות נדיבה "" בקופנהאגן.
Ex Output:
L'azienda danese di cioccolato, Anthon Berg, ha aperto un cosiddetto "" negozio generoso "" a Copenaghen.
Ex Input:
אף... | Teheran non era interessato.
| 1 | NIv2 | task1111_ted_translation_he_it | fs_opt | [
-0.589878499507904,
0.41186976432800293,
-0.20044973492622375,
-0.43281349539756775,
-1.1719226837158203,
0.010721791535615921,
0.17342239618301392,
0.16450653970241547,
0.08887334167957306,
-1.019720435142517,
-0.43887680768966675,
0.8433212041854858,
-1.104685664176941,
-0.05315785482525... |
In this task, you're given the title of a story consisting of five sentences, numbered 1 through 5. Your job is to arrange the sentences in order to make a story that makes complete sense and is apt for the title. Indicate your answer using the number of the sentences in order, such as '34152'.
[EX Q]: Title: Firefigh... | 12543
| 6 | NIv2 | task217_rocstories_ordering_answer_generation | fs_opt | [
0.4102042019367218,
-0.08102263510227203,
-0.18331557512283325,
-0.9715451002120972,
0.6958923935890198,
-0.3075127601623535,
0.5556528568267822,
0.937567412853241,
-0.26840758323669434,
-0.03424583375453949,
-0.8601980209350586,
-0.23064158856868744,
-0.3856411576271057,
-0.10072272270917... |
Part 1. Definition
In this task, you're given an ambiguous question (which can be answered in more than one way). Your task is to write a question that clarifies the given question in such a way that the generated question has one unique answer.
Part 2. Example
Lucifer how many episodes are in season 3?
Answer: How man... | Where is the 2017 US darts masters being held in las vegas? | 7 | NIv2 | task670_ambigqa_question_generation | fs_opt | [
-0.011270989663898945,
-0.23207780718803406,
-0.350709468126297,
-0.4855847954750061,
-0.1451795995235443,
0.4874473512172699,
0.39187347888946533,
-0.38316911458969116,
-0.19733133912086487,
-0.43276944756507874,
-0.5423833727836609,
0.7103792428970337,
-1.4129791259765625,
0.315468579530... |
TASK DEFINITION: In this task, you will be shown a conversation. You need to write a question with three choices for the conversation. Your question should be answerable based on the conversation and only have one correct answer. Note that you don't need to answer your question. "W" and "M" in the conversations stand f... | What does the woman imply? (A) Their team played very badly. (B) Football is-her favorite pastime. (C) The game has been canceled.
| 8 | NIv2 | task246_dream_question_generation | fs_opt | [
0.6115540862083435,
0.36620381474494934,
-0.4154272675514221,
-0.20976388454437256,
0.6648972630500793,
0.2561015188694,
1.1433080434799194,
0.9832419753074646,
0.19073905050754547,
-0.2124772071838379,
0.17584455013275146,
0.42041662335395813,
0.5205950736999512,
0.18532642722129822,
0.... |
Definition: You will be given a piece of text either about an everyday event, or a general statement. If the event seems a plausible event to you, or the general statement makes sense matches your commonsense, output 'True', otherwise output 'False'.
Input: Daniel had a bus to catch in 10 minutes so he heated his soup ... | True | 2 | NIv2 | task116_com2sense_commonsense_reasoning | zs_opt | [
-0.3611791133880615,
0.18221306800842285,
0.03023357130587101,
0.09033133089542389,
-0.520582377910614,
-0.33263084292411804,
0.8183934688568115,
0.31691646575927734,
0.008879533968865871,
0.20838062465190887,
-0.9468224048614502,
0.06061909347772598,
-0.030432602390646935,
-0.028840389102... |
Definition: In this task, you are given two sets, and a question. You need to find whether an element is 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 th... | Yes | 2 | NIv2 | task245_check_presence_in_set_intersection | zs_opt | [
0.20148861408233643,
-0.14842326939105988,
-0.5257756114006042,
-0.12524130940437317,
-0.0009887011256068945,
-0.00979758519679308,
0.7489299774169922,
0.40565094351768494,
-0.029531551524996758,
0.07276815921068192,
-0.4872244596481323,
0.29240328073501587,
0.30068355798721313,
-0.2889924... |
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... | Yes | 8 | NIv2 | task1202_atomic_classification_xneed | fs_opt | [
1.0307250022888184,
0.18404817581176758,
-0.012660285457968712,
0.17991387844085693,
-0.4681248664855957,
-1.031153917312622,
1.3551652431488037,
0.6827051043510437,
-0.7521359920501709,
-0.30027347803115845,
-0.553134024143219,
-0.12071588635444641,
-0.7562446594238281,
0.1417919099330902... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in English. Your job is to translate the English sentence into Galician.
It impacts: the spread of disease, the storage of food and medicine and the quality of life.
Output: | [e ten un impacto:] [na propagación de enfermidades] [no almacenamento de comida e medicinas] [e na calidade de vida] | 1 | NIv2 | task1090_ted_translation_en_gl | zs_opt | [
-0.2202843427658081,
0.3752329647541046,
0.042617909610271454,
-0.5145227909088135,
-0.22941330075263977,
-0.8285383582115173,
-0.4561726748943329,
0.926276445388794,
-0.7854935526847839,
-0.14627522230148315,
-0.4057139456272125,
0.5603882670402527,
-0.940962553024292,
0.04552462324500084... |
In this task, you are given two statements. The task is to output whether a given textual premise, i.e. Statement 2, entails or implies a given scientific fact, i.e. Statement 1. The output should be 'entails' if Statement 2 supports Statement 1 and should be 'neutral' otherwise.
Sentence 1: Cytoplasm and cell wall pa... | neutral | 0 | NIv2 | task1554_scitail_classification | zs_opt | [
-0.17850443720817566,
0.365328848361969,
-0.4573840796947479,
0.11247393488883972,
-0.5665935277938843,
-0.8690935373306274,
-0.22548697888851166,
0.7655988335609436,
0.3065114915370941,
-0.27648213505744934,
-0.41598811745643616,
-0.2514207363128662,
-0.38632214069366455,
-0.0500047802925... |
Q: In this task, you are given a sentence in the Japanese 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).
投票は、彼の措置案を「常識である」としたミッシェル・オバマによるスピーチによって支えられた大統領による、何週間にもわたるキャンペーンの後に行わ... | The vote followed weeks of campaigning by the President, who was supported by a speech by Michelle Obama describing his proposed measures as "common sense." | 7 | NIv2 | task436_alt_ja_en_translation | zs_opt | [
-0.2965937852859497,
0.4700869917869568,
0.9300019145011902,
-0.5034472942352295,
0.09654465317726135,
-0.7789415121078491,
0.816744327545166,
0.43025636672973633,
0.3581545650959015,
-0.31617239117622375,
-0.42456215620040894,
0.05987728014588356,
-0.3173878490924835,
-0.3445863723754883,... |
Given the task definition, example input & output, solve the new input case.
You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Polish.
Example: لذا نعلم أنها ستكون ناجحة. ولكن علينا مراقبتها
Output: Poradzi sobie, ale trzeba na nią uważać.
The Arabic sentence is correctly translated ... | Czyli statek to nie była nowość. | 1 | NIv2 | task1107_ted_translation_ar_pl | fs_opt | [
-0.06972882151603699,
0.786497950553894,
0.03398286551237106,
-0.5868727564811707,
0.03223418444395065,
0.5561903715133667,
1.0137629508972168,
-0.30536895990371704,
0.24325509369373322,
0.27628305554389954,
-0.4903726875782013,
0.002730295527726412,
-0.2908143401145935,
0.0088502019643783... |
Part 1. Definition
In this task, you're shown a three-part story, with a beginning, middle, and ending. Your job is to slightly modify the middle part, so that the whole story becomes unlikely, improbable, or inconsistent. Generated sentences must minimally alter the given middle, with at most 4 new words added/existin... | Will didnt work very hard. | 7 | NIv2 | task068_abductivenli_incorrect_answer_generation | fs_opt | [
0.2457345873117447,
0.42240840196609497,
-0.22499403357505798,
0.19204097986221313,
0.16626083850860596,
0.18619288504123688,
0.3461031913757324,
0.3892018795013428,
-0.2558315396308899,
-0.45460671186447144,
-0.3006283640861511,
0.127466082572937,
-0.4662182927131653,
-0.6507746577262878,... |
Teacher: This task is about classifying the sentiment of tweets in the Arabic language as POSITIVE or NEGATIVE. A positive (negative) sentiment indicates that the expressed opinion in the sentence is positive (negative). The input is a sentence is a sentence in Arabic and the output is the classified sentiment.
Teacher... | POSITIVE | 2 | NIv2 | task1414_ajgt_twitter_ar_classification | fs_opt | [
-0.6869261860847473,
-0.7113521099090576,
0.9437282085418701,
-0.575425386428833,
0.24150685966014862,
-0.912254810333252,
0.7451921701431274,
0.5518736839294434,
0.2441227287054062,
0.30912259221076965,
-0.5107074975967407,
-0.04163689911365509,
-0.6892056465148926,
-0.2172771841287613,
... |
In this task, you're given passages that contain mentions of names of people, places, or things. Some of these mentions refer to the same person, place, or thing. Your job is to write questions that evaluate one's understanding of such references. Good questions are expected to link pronouns (she, her, him, his, their,... | What word is omitted on the version around the base of Nelson's Column? | 8 | NIv2 | task001_quoref_question_generation | fs_opt | [
0.3926582634449005,
0.02048533409833908,
-0.3089630603790283,
-0.04167851433157921,
0.8730007410049438,
-0.8560384511947632,
0.8767701983451843,
0.8369337916374207,
-0.4111919403076172,
0.0879434272646904,
-0.14463138580322266,
0.40688785910606384,
-0.3163641691207886,
0.13454046845436096,... |
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_envelope | 0 | NIv2 | task152_tomqa_find_location_easy_noise | zs_opt | [
-0.31580036878585815,
-0.0693008303642273,
-0.144871324300766,
-0.3157648742198944,
-0.5892003178596497,
0.12104802578687668,
0.48957115411758423,
0.5573673248291016,
0.2329990565776825,
-0.5689007043838501,
-0.5566996335983276,
0.8779666423797607,
0.30351394414901733,
-0.1521299183368683,... |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Spanish.
Example input: אבל התחלנו לממש את הרעיון של ללמד כל ילד בנפרד.
Example output: Pero comenzamos con la idea de un niño por vez.
Example explanation: The Hebrew sentence is correctly translated into Spanish, because the meanin... | (Risas) Terminó la semana y mi traductora volvió, como le había pedido, Terminó la semana y mi traductora volvió, como le había pedido, para poder agradecer formalmente a Hyun Sook y a su abuela. | 3 | NIv2 | task1236_ted_translation_he_es | fs_opt | [
-0.6615222692489624,
0.6187472343444824,
0.3405492901802063,
-0.31210267543792725,
-0.8020026683807373,
-0.1718253642320633,
0.6660209894180298,
0.3247183561325073,
0.842130184173584,
-0.6670432686805725,
-0.05502064526081085,
0.6562842130661011,
-1.0166645050048828,
0.4242762625217438,
... |
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".
Example Input: Article: zimbabweans on friday awaited details of a power-sharing deal to end a political crisis after tortuous tal... | yes
| 3 | NIv2 | task289_gigaword_summarization | fs_opt | [
-0.37445348501205444,
0.06400128453969955,
0.1288129985332489,
0.3810230493545532,
0.0715692937374115,
-0.33733320236206055,
0.792659342288971,
0.2885258197784424,
-0.023214496672153473,
0.00024203769862651825,
-0.43596792221069336,
0.1715233325958252,
-0.32204198837280273,
-0.122165255248... |
Q: Write a question from the passage such that it identifies a character (a person or a thing) in the passage.
Happened to me while visiting Chicago a few weeks ago. A young couple with a baby in a pram boarded a crowded bus. The bus driver would not pull out of the stop until the pram was secured in the wheelchair cho... | Who was angry as the bus rode on? | 7 | NIv2 | task886_quail_question_generation | zs_opt | [
0.5236742496490479,
-0.17609825730323792,
-0.598418653011322,
0.14529183506965637,
-0.034443199634552,
-0.32217150926589966,
0.37379190325737,
0.918704628944397,
0.5381884574890137,
0.1781843602657318,
-0.18013297021389008,
0.24110206961631775,
-0.0710231363773346,
0.03064751625061035,
-... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Read the given sentence and if it is a general advice then indicate via "yes". Otherwise indicate via "no". advice is basically offering suggestions about the best course of action to someone. advice... | no | 0 | NIv2 | task115_help_advice_classification | fs_opt | [
0.0909201055765152,
0.440181702375412,
-0.07844952493906021,
0.4310176968574524,
0.5369974374771118,
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0.8283461332321167,
0.9809296131134033,
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-0.4198839068412781,
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... |
Given the task definition and input, reply with output. Given a text passage as input comprising of dialogue of negotiations between a seller and a buyer about the sale of an item, your task is to classify the item being sold into exactly one of these categories: 'housing', 'furniture', 'bike', 'phone', 'car', 'electro... | car | 5 | NIv2 | task767_craigslist_bargains_classification | zs_opt | [
-1.2314637899398804,
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-0.16276821494102478,
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... |
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... | The weather varies a lot from day to day; cold one day, warm the next.
****
| 4 | NIv2 | task203_mnli_sentence_generation | fs_opt | [
-1.155179738998413,
0.4911970794200897,
-0.611986517906189,
0.006080586463212967,
0.283128947019577,
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-0.3067741394042969,
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0.3234095275402069,
-0.5324208736419678,
-0.0031605535186827183,... |
Teacher:You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Portugese.
Teacher: Now, understand the problem? Solve this instance: 車椅子は色を塗って遊ぶためのオブジェとなりました
Student: | A cadeira de rodas tornou-se um objeto para pintar e brincar. | 6 | NIv2 | task1099_ted_translation_ja_pt | zs_opt | [
-0.0757441446185112,
0.36389243602752686,
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-0.5587533116340637,
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0.35461223125457764,
-0.015151661820709705,
0.20900842547416687,
-0.27121105790138... |
Teacher:In this task, answer 'Yes' if the frequency of the given word in the two sentences is equal, else answer 'No'.
Teacher: Now, understand the problem? Solve this instance: Sentence1: 'a white truck travelling on a street pass homes', Sentence2: 'people sitting at tables with computers and papers on it in front of... | No | 6 | NIv2 | task159_check_frequency_of_words_in_sentence_pair | zs_opt | [
-0.16661494970321655,
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-0.47807979583740234,
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-0.0038952380418777466,
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0.3049444854259491,
-0.14074298739... |
In this task, you need to answer 'Yes' if the given word is the longest word (in terms of number of letters) in the given sentence, else answer 'No'. Note that there could be multiple longest words in a sentence as they can have the same length that is the largest across all words in that sentence.
Q: Sentence: 'a chil... | Yes | 4 | NIv2 | task114_is_the_given_word_longest | zs_opt | [
-0.1652437299489975,
0.558578610420227,
-0.3078419864177704,
-0.6794490814208984,
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-0.09340490400791168,
-0.181508690118789... |
Given the task definition and input, reply with output. In this task, you're given a story (which contains five sentences only). Your task is to find all the characters which are available in the given story.
Sentence1: Sampson was a strong and ferocious Rottweiler. Sentence2: One day, a neighbor girl jumped the fence... | Neighbor girl, Sampson | 5 | NIv2 | task292_storycommonsense_character_text_generation | zs_opt | [
-0.39543598890304565,
0.452827125787735,
0.560844898223877,
-0.20972943305969238,
-0.08023305237293243,
-0.7467450499534607,
-0.12007743120193481,
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-0.025388594716787338,
-0.5406991243362427,
0.16615739464759827,
-0.30309921503067017,
-0.48922413587570... |
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.
--------
Question: ఆ మీ కోసం.
Answer: And that's for you.
Question: మీరు సంస్థ తన కుటుంబం ఇవ్వాలని ఏమి పరిగణనలోకి లేదు?
... | Yeah, figure out where the asshole is.
| 7 | NIv2 | task1324_open_subtitles_te_en_translation | fs_opt | [
-0.6461849808692932,
0.8032473921775818,
0.7180064916610718,
0.23570238053798676,
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-1.0256948471069336,
0.40396055579185486... |
Instructions: You are given a sentence in English. Your job is to translate the English sentence into Spanish.
Input: Remember fire?
Output: | ¿Recuerdan el fuego? | 3 | NIv2 | task1219_ted_translation_en_es | zs_opt | [
-0.8450171947479248,
0.8205078840255737,
-0.42172741889953613,
-0.7597354054450989,
-0.25048398971557617,
-1.568374514579773,
1.1310997009277344,
1.341177225112915,
-0.37828874588012695,
-0.8250143527984619,
-0.005291490349918604,
-0.30180811882019043,
-1.105432391166687,
0.444983720779418... |
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'.
--------
Questi... | A
| 7 | NIv2 | task580_socialiqa_answer_generation | fs_opt | [
0.34744173288345337,
0.3690701723098755,
-0.3891223073005676,
-0.09660546481609344,
-0.06404764950275421,
-0.17689180374145508,
0.5608295798301697,
0.4353903830051422,
-0.2091803103685379,
0.24934035539627075,
-0.0784248411655426,
0.31186363101005554,
-0.27759748697280884,
-0.5307906866073... |
You will be given a definition of a task first, then some input of the task.
Read the given text and if it has abusive content then indicate via "yes". Otherwise indicate via"no".
We consider the content to be abusive if it contains any of the following instances: (1) Identity Directed Abuse (e.g., Content which conta... | no | 1 | NIv2 | task108_contextualabusedetection_classification | zs_opt | [
-0.42985057830810547,
0.5835422277450562,
0.22401636838912964,
-0.11891555786132812,
-0.32135653495788574,
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1.552947998046875,
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0.2902587056159973,
-0.3281840980052948,
-0.15117736160755157,
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-0.535040497779846... |
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: પૃષ્ઠભૂમિમાં લાલ ધાબળો ધરાવતી સાયકલ હેઠળ બેસીને એક બિ... | Yes | 9 | NIv2 | task440_eng_guj_parallel_corpus_gu-en_classification | zs_opt | [
-0.607746958732605,
0.23500211536884308,
-0.051128238439559937,
0.4654165804386139,
0.08576327562332153,
-0.9950231313705444,
0.3547271490097046,
0.4034324884414673,
0.12580589950084686,
-0.21437937021255493,
-0.08212574571371078,
0.5025762319564819,
-0.33817803859710693,
0.595357894897460... |
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: இந்தி மொழியில் அமைந்த தொடரானது தமிழ், தெலுங்கு, மராத்தி ஆகிய மொழிகளுக்கு மொழி மாற்றம் செய்யப்பட்டுள்ளத... | 2012 | 4 | NIv2 | task953_wiki_cloze_ta_multiple_choice_question_answering | zs_opt | [
0.36784881353378296,
-0.1230495348572731,
0.5024358630180359,
0.42119497060775757,
0.11923409253358841,
-0.10641320049762726,
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0.5030715465545654,
-0.49536222219467163,
-0.05733247473835945,
0.029668666422367096,
0.42402100563049316,
-0.2977416515350342,
0.0013287486508... |
In this task, you are given a sentence in the Bulgarian language. Here, your job is to convert bulgarian sentence into the english language.
Q: Освобождаването от отговорност във връзка с изпълнението на бюджета на Европейски полицейски колеж за финансовата 2006 г. (
A: | 2006 discharge: European Police College ( | 4 | NIv2 | task271_europarl_translation | zs_opt | [
-0.1302388608455658,
0.4190528988838196,
0.4651242792606354,
-0.3464197516441345,
-0.2129148542881012,
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0.17140008509159088,
0.5461804270744324,
-0.5817548036575317,
0.36418774724006653,
... |
Instructions: The task is to write a full sentence or two using all of the information given. The sentence(s) will be a brief review of a restaurant. Use all of the information provided.
Input: name[xname], price[less than £20], location[city centre], familyFriendly[yes], near[xnear]
Output: | xname is located near xnear in the city centre. Their prices are less than £20 and they are family-friendly. | 3 | NIv2 | task1598_nyc_long_text_generation | zs_opt | [
-0.7352375984191895,
0.9412755370140076,
-0.6709854006767273,
-0.2939291298389435,
-0.2571200728416443,
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0.938421368598938,
-0.09190376102924347,
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0.5329359769821167,
0.1504291296005249,
-1.0226373672485352,
-0.21673250198364258,
... |
Teacher: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 .
Teacher: Now, understand the problem? Solve this instance: Statement: रवींद्रनाथ रामपॉल (Ravindranath Rampau... | वेस्टइंडीज | 6 | NIv2 | task947_wiki_cloze_hi_multiple_choice_question_answering | zs_opt | [
0.21603728830814362,
0.5719980597496033,
0.26143401861190796,
0.22365808486938477,
-0.0667385533452034,
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-0.57445454597473... |
Q: 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".
Japanese: アメリカ合衆国へ移るとすぐに、彼は1988年のNBAドラフトの第3巡でアトランタホークスに獲得された。
Bahasa Indo... | Yes | 7 | NIv2 | task1117_alt_ja_id_answer_generation | zs_opt | [
0.29340291023254395,
-0.5238989591598511,
0.1699322909116745,
0.6438360214233398,
0.5786875486373901,
-0.854175865650177,
0.6751968264579773,
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-0.08696568012237549,
-0.2637607455253601,
0.5096360445022583,
-0.5742126703262329,
0.10297486186027527,... |
Detailed Instructions: In this task, you are given Twitter posts. Your task is to label the post's emotion (as expressed by the user) as sadness, joy, love, anger, fear, or surprise.
Problem:i was gay that i began to feel disturbed and embarrassed
Solution: | sadness | 8 | NIv2 | task512_twitter_emotion_classification | zs_opt | [
-0.6395227313041687,
-0.18574613332748413,
0.7070711851119995,
-0.23531033098697662,
0.0009604815859347582,
-1.0594232082366943,
0.29384374618530273,
0.4435880780220032,
0.3576781451702118,
0.1002044826745987,
-0.46749579906463623,
-0.17831134796142578,
-0.7285754680633545,
-0.204896241426... |
Detailed Instructions: In this task, you're given an ambiguous question (which can be answered in more than one way). Your task is to provide one question which clarifies the input question and it has one unique answer, and also provide an answer to the generated question. Generated question and answer should be separa... | Who sang the 1955 song let it be me?
Gilbert Bécaud | 9 | NIv2 | task671_ambigqa_text_generation | zs_opt | [
-0.26197439432144165,
1.1030590534210205,
-0.7499735355377197,
-0.29436564445495605,
-0.11427047848701477,
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0.6635684370994568,
0.32068055868148804,
-0.21662931144237518,
-0.44349122047424316,
-1.0348868370056152,
-0.06010427325963974,
-0.2956473231315613,
-0.376992583... |
Teacher:This task is to translate a news commentary given in Dutch language into Portuguese language. Translate the input statement into the output language while preserving the numberical values, special characters and proper nouns and context of the commentary done.
Teacher: Now, understand the problem? Solve this i... | Por exemplo, o Presidente dos EUA, Barack Obama, salientou repetidamente a necessidade de aumentar a percentagem de jovens Americanos com graus universitários. | 6 | NIv2 | task1375_newscomm_translation | zs_opt | [
-0.4083058834075928,
0.579693615436554,
0.24024054408073425,
-0.31559938192367554,
-0.07563234120607376,
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0.33460572361946106,
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0.39921674132347107,
-0.2527283728122711,
0.8083736300468445,
-0.18265490233898163,
-0.5309880971908569,... |
In this task, you are given two sentences in the English language and your task is to classify them into one of their discourse types. A discourse type is an indicator to classify the given two sentences on the basis of a co-text as well as a relevant context. There are 13 discourse types in total which are 'SINGLE_S_C... | SINGLE_CONN_START
| 5 | NIv2 | task564_discofuse_classification | fs_opt | [
0.3943924009799957,
0.4589047431945801,
0.10226891934871674,
0.4604266881942749,
-0.7073451280593872,
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0.46925032138824463,
0.9704846143722534,
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0.10903918743133545,
0.06472466886043549,
-0.18802732229232788,
-0.3328093886375427,
-0.377135723829269... |
In this task, you need to count the number of words in a sentence that end with the given letter. Answer with numbers and not words.
Input: Consider Input: Sentence: 'teddy bear in front of a holly covered object'. How many words end with the letter 't' in the sentence.
Output: 2
Input: Consider Input: Sentence: 'a... | Output: 1
| 2 | NIv2 | task163_count_words_ending_with_letter | fs_opt | [
-0.09896831214427948,
0.8434057235717773,
-0.4796385169029236,
0.4994445741176605,
0.1515699028968811,
-0.6965365409851074,
-0.8468784093856812,
0.5080691576004028,
0.2205566167831421,
-0.17709198594093323,
-0.5827573537826538,
0.20897531509399414,
0.028530828654766083,
-0.1035412922501564... |
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 emotion', 'surpris... | happiness,happiness,happiness,happiness,happiness,happiness,happiness,happiness
| 3 | NIv2 | task1532_daily_dialog_emotion_classification | fs_opt | [
0.3505416512489319,
-0.23053862154483795,
-0.2580162584781647,
0.208294078707695,
0.1658594012260437,
-0.1825152039527893,
0.9307321310043335,
0.4229431450366974,
-0.39756011962890625,
-0.14809641242027283,
-0.014079713262617588,
-0.2433425784111023,
-0.5170481204986572,
0.3958688378334045... |
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: No opera smells of the sea quite like Britten's Peter Grimes. The music makes us constantly aware of the sea's immensity, it's potential for threat, and the play of light on it... | Which of the following can best describe the sailor's work in the first act? | 0 | NIv2 | task311_race_question_generation | zs_opt | [
0.887293815612793,
1.2281228303909302,
-0.6411969065666199,
-0.039280325174331665,
0.295571893453598,
-0.852677583694458,
0.2811131179332733,
0.7882418632507324,
0.1645030677318573,
0.323935866355896,
-0.20722165703773499,
0.657791018486023,
-0.5466792583465576,
0.4082947075366974,
-0.09... |
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 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).
... | Due to suffering from prostate cancer, he was granted a compassionate release from Scottish prison two days later. | 1 | NIv2 | task433_alt_hi_en_translation | zs_opt | [
-0.1802501082420349,
0.38358020782470703,
0.3301379680633545,
-0.31556421518325806,
0.041139326989650726,
-0.1275908350944519,
0.2602936625480652,
0.5024527311325073,
0.015221599489450455,
-0.3078886866569519,
-0.49186578392982483,
0.35988742113113403,
-0.030727330595254898,
0.250667333602... |
Given a fact, create a question that can be answered using the fact. Construct the question such that it is unambiguous, has a unique answer and the answer can be given using the fact.
Ex Input:
Fact: An example of combining two substances is pouring one substance into the other substance
Ex Output:
An example of com... | A landfill?
| 1 | NIv2 | task1398_obqa_question_generation | fs_opt | [
0.0694747269153595,
0.8619939684867859,
-0.29511457681655884,
0.29997721314430237,
-0.3795012831687927,
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0.4445178806781769,
1.0081886053085327,
-0.4594578146934509,
-0.012424971908330917,
-1.3668441772460938,
0.6918562054634094,
-0.43455180525779724,
-0.484734535217285... |
Definition: Given a post that is a real-life anecdote of a complex ethical situation and a question asks if AUTHOR, NOBODY, EVERYBODY, or OTHER is wrong in the situation. Answer the question and classify your answers into yes or no.
Input: Is NOBODY wrong in the post ? POST : My boyfriend suggested I posted here about ... | no | 2 | NIv2 | task502_scruples_anecdotes_whoiswrong_verification | zs_opt | [
0.1896287202835083,
-0.4623746871948242,
0.06661781668663025,
-0.07851085811853409,
0.4103458523750305,
-0.18257743120193481,
0.9753057360649109,
0.8047158122062683,
-0.03314263001084328,
-0.1343940794467926,
-0.20440196990966797,
0.2562571167945862,
-0.6435839533805847,
-0.298190921545028... |
You are given a sentence in Polish. Your job is to translate the Polish sentence into English.
Input: Consider Input: Pink: Oto sierżant Stephan Pink.
Output: (Video) Stephen Pink: This is Sergeant Stephen Pink.
Input: Consider Input: Wszystko o czym wam opowiedziałam zostało odkryte przez kogoś z tego zdjęcia.
Ou... | Output: And there's 55 trillion links between all the Web pages of the world.
| 2 | NIv2 | task1256_ted_translation_pl_en | fs_opt | [
-0.918800950050354,
0.44914984703063965,
-0.40482863783836365,
-0.2856767475605011,
-0.1109103113412857,
-0.8672425746917725,
0.7339004278182983,
0.19121822714805603,
0.7807859778404236,
0.06395615637302399,
0.1966629922389984,
1.199191927909851,
-1.0520823001861572,
0.03342023491859436,
... |
In this task, you will be presented with a question in Persian. Based on the knowledge you need to answer the question, classify the question into "math_and_logic", "literature", or "common_knowledge".
Ex Input:
جزایر لانگرهانس در کجا قرار دارد؟
Ex Output:
common_knowledge
Ex Input:
رابطه ناخن با انگشت مثل رابطه :
... | literature
| 1 | NIv2 | task474_parsinlu_mc_classification | fs_opt | [
-0.5687179565429688,
0.8602216243743896,
0.028932029381394386,
-0.4573903977870941,
-0.31406450271606445,
-0.27374428510665894,
0.4943056106567383,
-0.4854182004928589,
0.046648479998111725,
-0.8719695806503296,
-0.33492058515548706,
0.5361330509185791,
-0.32969218492507935,
0.125555098056... |
Detailed Instructions: In this task, you are given a string with duplicate characters ocurring in the string. You need to return the character which is ocurring with the maximum frequency. In case of a tie, return the character with the least ascii value.
See one example below:
Problem: mvwduljootadondrwbrledodqnmfqtxa... | f | 4 | NIv2 | task1188_count_max_freq_char | fs_opt | [
-0.27657216787338257,
0.31028005480766296,
-0.010721927508711815,
-0.15862584114074707,
0.14348694682121277,
0.1921612173318863,
1.1416056156158447,
0.21674790978431702,
0.015531702898442745,
0.07929275184869766,
-0.6641364097595215,
-0.26330679655075073,
-0.16424039006233215,
-0.016590729... |
Provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e tagset of this corpus is -
'.': Period symbol is used f... | ADV | 0 | NIv2 | task1167_penn_treebank_coarse_pos_tagging | zs_opt | [
0.21549901366233826,
0.07404200732707977,
-0.1308724284172058,
0.0064833080396056175,
-0.24863716959953308,
-0.5242359042167664,
0.6550970077514648,
0.612149715423584,
-0.3151445984840393,
-0.10349724441766739,
-0.7992703318595886,
-0.035646647214889526,
-0.6050465703010559,
0.253778517246... |
Teacher: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.
Teacher: Now, understand the problem? Solve this instance: アレクサンドル・ロマイア、グルジア安全保障会議長は「サアカシュヴィリ大統領はグルジアの軍隊がツヒンヴァリから撤退して、ロシアからの爆撃に反応するのを止めること... | លោកអាឡិចសាន់ដ្រឺ ឡូម៉ៃអា ប្រធានក្រុមប្រឹក្សាសនិ្តសុខនៃប្រទេសចូចា បាននិយាយថាការស្នើរបស់លោកប្រធានាធិបតី សាកាស្វីលី គឺថាក្រុមសម្ព័នជនជាតិចូចានឹងដកថយពីទីក្រុងជឺហ៊ីវ៉ាលី ព្រមទាំងឈប់ប្រតិកម្មទៅនឹងការទំលាក់គ្រាប់បែករបស់ ប្រទេសរូស៊ី។ | 6 | NIv2 | task1121_alt_ja_khm_translation | zs_opt | [
-0.5168641805648804,
0.30294549465179443,
0.0038723163306713104,
-0.6195917129516602,
0.07391899079084396,
-1.1700944900512695,
1.127524733543396,
0.24735116958618164,
-0.502687394618988,
-0.15148299932479858,
-0.7683402299880981,
0.44460660219192505,
-0.9717598557472229,
0.098408646881580... |
Given a category and a set of five words, find the word from the set that does not belong (i.e. is the least relevant) with the other words in the category. Words are separated by commas.
Q: Category: aesthetic characteristic
Words: flaxen, well, size, ghostly, fair
A: | well | 4 | NIv2 | task141_odd-man-out_classification_category | zs_opt | [
-0.2859553098678589,
0.6443514823913574,
0.41685548424720764,
-0.586424708366394,
-0.31328392028808594,
-0.3133291006088257,
-0.031791575253009796,
-0.23424553871154785,
-0.28870633244514465,
-0.3978152275085449,
-0.588452160358429,
1.0979653596878052,
-0.5621639490127563,
-0.0363135486841... |
Detailed Instructions: In this task, you are given a sentence containing a particular emotion. You must classify the sentence into one of the six emotions: 'joy', 'love', 'anger', 'fear', or 'surprise'.
Problem:i cannot even begin to express in words the depth of sorrow that i feel having not posted any of my ludicrous... | surprise | 8 | NIv2 | task875_emotion_classification | zs_opt | [
0.09093638509511948,
0.20384259521961212,
1.0071041584014893,
-0.48882466554641724,
-0.2557021975517273,
-0.5076441764831543,
0.4565548896789551,
0.6039998531341553,
0.13968852162361145,
-0.794965386390686,
-0.40637150406837463,
-0.21494629979133606,
-1.2509020566940308,
0.0321651808917522... |
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.
One example is below.
Q: The first two were found unreliable and the prosecution case rested mainly on the evidence of the remaining five approvers .
A: पहले दो क... | उस गुरुभाई को पाठ पढ़ाते हुए और गुरुदेव की प्रत्येक वस्तु के प्रति प्रेम दर्शाते हुए उनके बिस्तर के पास रक्त कफ आदि से भरी थूकदानी उठाकर फेकते थे। | 9 | NIv2 | task425_hindienglish_corpora_en_hi_translation | fs_opt | [
-0.07430751621723175,
0.4677177369594574,
0.5389605760574341,
-0.19477586448192596,
0.09522107243537903,
-0.7659165859222412,
0.08805431425571442,
0.2609395980834961,
-0.18828518688678741,
-0.5174862146377563,
-0.5787286758422852,
-0.04444392770528793,
-0.4210347533226013,
0.21113985776901... |
Teacher:In this task, you are given a question and a context passage. You have to answer the question based on the given passage.
Teacher: Now, understand the problem? Solve this instance: What are the elements so necessary?, Context: Interspersed repeats mainly come from transposable elements (TEs), but they also incl... | TEs are an important driving force on genome evolution of higher eukaryotes | 6 | NIv2 | task1295_adversarial_qa_question_answering | zs_opt | [
0.052295006811618805,
-0.2008761316537857,
-0.42667436599731445,
-0.04336073622107506,
-0.24421267211437225,
-0.7551063895225525,
0.11406359821557999,
0.9382253885269165,
-0.40528804063796997,
0.5753183364868164,
-0.25670185685157776,
0.024454185739159584,
-0.6110727787017822,
0.2546361088... |
TASK DEFINITION: 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".
PROBLEM: Japanese: ベルルスコーニが襲撃されたのはこれだけではなく、数年前には男が三脚で彼を襲い、額を切ったことがある。
Lao: ນີ້ບໍ່ແມ່ນພຽງແຕ່ການໂ... | No
| 8 | NIv2 | task1126_alt_ja_lo_answer_generation | fs_opt | [
0.14323690533638,
-0.931001603603363,
-0.3258160948753357,
0.282551109790802,
1.0524351596832275,
-0.2820447087287903,
1.0920941829681396,
0.5538465976715088,
-0.27668526768684387,
0.028615614399313927,
-0.25262215733528137,
0.9010443091392517,
-0.44637030363082886,
0.3723159432411194,
0... |
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 | [
0.5826730728149414,
0.11241307854652405,
0.03826873004436493,
0.035623081028461456,
-0.5910885334014893,
-0.8783047199249268,
1.3963727951049805,
0.5158807039260864,
-0.8447592258453369,
-0.27220872044563293,
-0.3611027002334595,
-0.19930507242679596,
-0.9040082693099976,
0.222304224967956... |
Definition: 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 com... | 1 | 2 | NIv2 | task243_count_elements_in_set_intersection | zs_opt | [
0.4703703224658966,
0.09664179384708405,
-0.8960138559341431,
-0.08940224349498749,
-0.06150171905755997,
0.2000102698802948,
0.30853521823883057,
0.12443488836288452,
0.10335418581962585,
-0.09104380011558533,
-0.9440064430236816,
0.1393142193555832,
0.2691457271575928,
0.1593165844678878... |
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.
Ang lalaki ay kinilala na isang espiya na Ruso at namumuhay na mayroong huwad na pangalan... | 男はロシアのスパイと確認され、偽名で生活していた。 | 5 | NIv2 | task1119_alt_fil_ja_translation | zs_opt | [
-0.35934996604919434,
0.5713647603988647,
0.28617772459983826,
-0.6524642109870911,
-0.08846636116504669,
-0.010617701336741447,
0.9799566864967346,
-0.28143179416656494,
0.3142857253551483,
-0.523475170135498,
-0.969109058380127,
0.6731368899345398,
-1.302445888519287,
0.08782191574573517... |
Detailed Instructions: A text is given in Malayalam. Translate it from the Malayalam language to the Tamil language. The translation must not omit or add information to the original sentence.
Q: സമഗ്രമായ പ്രാഥമിക പരിരക്ഷയും പ്രതിരോധ ആരോഗ്യ സേവനവും ലഭ്യമാക്കുന്നതിനായി 1. 5 ലക്ഷം ആരോഗ്യ-ക്ഷേമകേന്ദ്രങ്ങള് ആരംഭിച്ചു.
A: | ஒட்டுமொத்த ஆரம்ப சிகிச்சை மற்றும் நோய் தடுப்பு சேவைகளை வழங்குவதற்காக ஒன்றரை லட்சம் சுகாதார மற்றும் நலவாழ்வு மையங்கள் அமைக்கப்பட்டு வருகின்றன. | 9 | NIv2 | task999_pib_translation_malayalam_tamil | zs_opt | [
1.0167216062545776,
0.3426986634731293,
0.07501576840877533,
-0.2230546474456787,
-0.1873103231191635,
-0.504982590675354,
0.4865022897720337,
0.21334892511367798,
-0.03613144904375076,
-0.38234686851501465,
-0.27982097864151,
0.06250396370887756,
-0.9669531583786011,
0.7112377285957336,
... |
Given a 'poster' sentence and a corresponding 'response' (often, from Facebook or Reddit)classify the sentiment of the given response into four categories: 1) Positive, 2) Negative, 3) Neutral, and 4) Mixed if it contains both positive and negative.
Poster: Glad to be back in studio for #SpecialReport with Bret Baier ... | Positive
| 0 | NIv2 | task823_peixian-rtgender_sentiment_analysis | fs_opt | [
0.09323673695325851,
-0.6440458297729492,
-0.11496375501155853,
0.12953351438045502,
0.16940566897392273,
-0.6737799048423767,
0.7654153108596802,
0.25458478927612305,
0.02725566178560257,
0.16593292355537415,
-0.11104432493448257,
0.3937278985977173,
0.21975937485694885,
0.223979473114013... |
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 an Amazon customer review, write a title for the review. The preferred titles are under fifteen words.
I was very surprised at the high quality of the stitching, the sturdiness of the handles ... | Work properly | 0 | NIv2 | task1342_amazon_us_reviews_title | fs_opt | [
0.08262002468109131,
0.07906509935855865,
-0.5079303979873657,
-0.042961809784173965,
0.4803309142589569,
-0.5050438642501831,
0.9274415373802185,
0.08513661473989487,
0.5959799885749817,
0.576513409614563,
0.0666237324476242,
0.054207295179367065,
-0.2847057282924652,
-0.31459686160087585... |
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 are given a sentence in Arabic. Your job is to translate the Arabic sentence into Hebrew.
ويمكن اعادة تكرار هذه العملية على طول الشريط لكي نطبق شريط الحمض النووي فنشكل ما يشبه المستطيلات
Solutio... | ויצרנו פרוייקט שקראנו לו אתגר CyArk 500 — וזה לשמר דיגיטלית 500 אתרי מורשת עולמיים בחמש שנים. | 0 | NIv2 | task1233_ted_translation_ar_he | fs_opt | [
-0.3701055645942688,
0.5130705833435059,
0.29996737837791443,
0.027139578014612198,
-0.3876935839653015,
0.448164701461792,
1.0387868881225586,
0.31028467416763306,
0.9016477465629578,
-0.1339718997478485,
-0.6071485877037048,
0.06277123093605042,
-0.637721836566925,
0.552882194519043,
0... |
Definition: In medical studies, the efficacy of medical treatments (called interventions) is evaluated within a group of study participants. You will be given a sentence of a study report in which your task is to list the phrases that describe the intervention(s) of the study. You should list the phrase in the same ord... | not found | 2 | NIv2 | task180_intervention_extraction | zs_opt | [
0.3423027992248535,
0.1615152508020401,
-0.8259335160255432,
-0.5574862957000732,
0.6029242277145386,
-0.3160005807876587,
0.14387264847755432,
0.5135660171508789,
0.37384724617004395,
0.8445672988891602,
-0.8086403608322144,
-0.5414060950279236,
0.5714852809906006,
0.04285009205341339,
... |
Teacher:Answer the question from the given passage. Your answer should be directly extracted from the passage, and it should be a single entity, name, or number, not a sentence.
Teacher: Now, understand the problem? Solve this instance: Passage: There were 158,349 households, of which 68,511 (43.3%) had children under ... | 1,388 | 6 | NIv2 | task1608_xquad_en_answer_generation | zs_opt | [
0.224911630153656,
0.14805559813976288,
-0.32725709676742554,
-0.45560526847839355,
-0.032916292548179626,
0.273705393075943,
0.8015523552894592,
0.48304957151412964,
0.07559503614902496,
-0.5727462768554688,
-1.0142688751220703,
0.6252328157424927,
-0.6836316585540771,
-0.9197054505348206... |
Instructions: In this task, you are to Translate German text to English
Input: Solche unterirdischen Hohlraeume, z.
Output: | Such underground cavities, z. | 3 | NIv2 | task841_para_pdt_de_en_translation | zs_opt | [
0.18842895328998566,
1.0755151510238647,
0.1720617115497589,
0.27530503273010254,
-0.14322885870933533,
0.28416556119918823,
0.4779243469238281,
0.07242491096258163,
-0.4449918866157532,
-0.22545471787452698,
-0.002171359956264496,
0.13957522809505463,
-0.9817438125610352,
-0.3230522274971... |
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