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 are given a sentence and a category word that defines the relation between the input sentence and the output to be generated. Your job is to generate another sentence that satisfies the relation specified by the category. If the category is specified as entailment, then the outp... | A man is putting vegetables into a pot | 9 | NIv2 | task1613_sick_given_category_generate_sentence | zs_opt | [
-0.37836259603500366,
0.7507465481758118,
0.19532008469104767,
-0.15291708707809448,
-0.17192012071609497,
-0.6245215535163879,
0.2698013186454773,
0.27471810579299927,
0.2710895538330078,
-0.5026160478591919,
-0.45656105875968933,
-0.2709740102291107,
-0.4225643575191498,
0.17622527480125... |
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 The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ).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... | No | 9 | NIv2 | task1209_atomic_classification_objectuse | zs_opt | [
0.3200860619544983,
0.5210665464401245,
0.2568405270576477,
-0.0864618718624115,
-0.4900359511375427,
-1.2677838802337646,
1.1440227031707764,
0.600111722946167,
-0.44575992226600647,
-0.46147215366363525,
-0.619219183921814,
-0.26319557428359985,
-0.5850521326065063,
0.12117766588926315,
... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Q: Sentence 1: Fear we shall be too late anyway. Sentence 2: Concerned that we will reach too e... | 6
****
| 4 | NIv2 | task198_mnli_domain_classification | fs_opt | [
-0.03659524396061897,
0.21129067242145538,
0.3828429579734802,
-0.35946154594421387,
-0.14581707119941711,
-0.13488981127738953,
0.2540851831436157,
1.0814486742019653,
-0.6485311388969421,
0.12587660551071167,
-0.6255176067352295,
-0.0031644878908991814,
-0.4992291033267975,
-0.5606191158... |
In this task, you are given a question and answer options for that question. Using this information, you have to classify each text into different topics: medicine, nursery, psychology, chemistry, pharmacology, biology.
Example: Question: A distension is defined as:
Options: <0> Soft tissue injury. <1> Forced moveme... | Solution: pharmacology | 5 | NIv2 | task1434_head_qa_classification | fs_opt | [
0.6392436027526855,
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-0.1652931571006775,
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0.1918487548828125,
-0.6492075324058533,
0.5699067115783691,
0.7283790111541748,
0.49348947405815125,
0.32573461532592773,
-0.0629890039563179,
0.009751155972480774,
-0.05413663387298584,
0.4409569501876831... |
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 in the Portuguese Langua... | Eu devo somente olhar para cima e dizer 'Quem sou eu então? | 0 | NIv2 | task1647_opus_books_en-pt_translation | zs_opt | [
-0.11525645107030869,
0.7054998278617859,
-0.04132536053657532,
-0.20999039709568024,
-0.7987819910049438,
-0.6882503032684326,
0.32547223567962646,
0.3614174723625183,
0.15680456161499023,
-0.353769451379776,
-0.24015605449676514,
0.30601146817207336,
-1.669576644897461,
0.043935373425483... |
Given the task definition, example input & output, solve the new input case.
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 | task1198_atomic_classification_owant | fs_opt | [
0.22137485444545746,
-0.05593345686793327,
0.3411611020565033,
0.32463690638542175,
-0.07138268649578094,
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0.6481596827507019,
0.7988622188568115,
-0.8063218593597412,
-0.19991815090179443,
-0.1586742401123047,
-0.4056149125099182,
-0.535741925239563,
-0.295048624277114... |
Teacher: In this task, you're given a review from Amazon and category of the product based on the review given by the user and your task is classify whether the given category match the review. Generate "True" if given review and its category match, otherwise generate "False".
Teacher: Now, understand the problem? If y... | False | 2 | NIv2 | task1308_amazonreview_category_classification | fs_opt | [
-0.3428325951099396,
0.1610633283853531,
-0.2994491457939148,
-0.05731801688671112,
0.16764022409915924,
-0.2447817623615265,
0.5279425382614136,
1.0214531421661377,
0.03025589883327484,
0.48940855264663696,
0.43891799449920654,
0.026945237070322037,
-0.42397457361221313,
0.392006784677505... |
Teacher: 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.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Sox - 4 is important for very early B - ... | G protein-coupled receptor | 2 | NIv2 | task1482_gene_extraction_chemprot_dataset | fs_opt | [
-0.2336839735507965,
0.1322515308856964,
-0.42523887753486633,
-0.5347233414649963,
0.43774348497390747,
-0.75941401720047,
-0.14307299256324768,
0.8202143907546997,
0.11016619205474854,
-0.4094178378582001,
-0.4455302953720093,
-0.21488332748413086,
-0.665717363357544,
-0.6021360158920288... |
Given the task definition, example input & output, solve the new input case.
In this task, you're given a question, a context passage, and four options which are terms from the passage. After reading a passage, you will get a brief understanding of the terms. Your job is to determine by searching and reading further in... | a | 1 | NIv2 | task231_iirc_link_classification | fs_opt | [
0.30136939883232117,
0.7587202191352844,
-1.0116033554077148,
-0.08510652184486389,
0.36813488602638245,
-0.5503250956535339,
1.355698823928833,
0.8062504529953003,
0.2843376100063324,
0.6428064703941345,
-0.1249164417386055,
-0.11226602643728256,
-0.34376847743988037,
-0.12853777408599854... |
A text is given in Tamil. Translate it from the Tamil language to the Malayalam language. The translation must not omit or add information to the original sentence.
Example: இளவயது பெண்களைச் சந்திக்கும் வாய்ப்பு எனக்குக் கிட்டியது, அவர்களில் சில பெண்கள் இமயமலைப் பகுதியில் பிறந்தவர்கள்
Example solution: എനിക്ക് യുവതികളെ... | Solution: ഇതിനു പുറമേ, ദേശീയപാതകളുടെയും പാലങ്ങളുടെയും നഗര ഗതാഗത | 5 | NIv2 | task1000_pib_translation_tamil_malayalam | fs_opt | [
0.11844239383935928,
0.5079372525215149,
-0.19528168439865112,
-0.038052748888731,
-0.11932143568992615,
-1.2532143592834473,
0.184184730052948,
0.9840177893638611,
-0.2050342708826065,
0.07947161048650742,
-0.5127786993980408,
0.38009852170944214,
-0.6660593748092651,
-0.03456591069698334... |
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... | NOUN | 0 | NIv2 | task1167_penn_treebank_coarse_pos_tagging | zs_opt | [
0.29423993825912476,
0.2352617383003235,
-0.21564537286758423,
0.0486002154648304,
-0.18205946683883667,
-0.4600161612033844,
0.617866039276123,
0.44477975368499756,
-0.0075920275412499905,
-0.1003640666604042,
-0.6650607585906982,
0.2064337432384491,
-0.4371938705444336,
0.359074056148529... |
In this task, you will be presented with a question in Dutch language, and you have to write the named entities from the question if present. B denotes the first item of a phrase and an I any non-initial word. Here is the list of terms used: person names (PER), organizations (ORG), locations (LOC) and miscellaneous nam... | None
| 0 | NIv2 | task1544_conll2002_named_entity_recognition_answer_generation | fs_opt | [
-0.14766332507133484,
0.29658401012420654,
0.08648243546485901,
-0.08006133139133453,
-0.3111483156681061,
-0.399907648563385,
1.135632038116455,
0.3593396544456482,
0.6114439368247986,
-0.09520433843135834,
-0.6004952192306519,
0.30746620893478394,
-0.4675895869731903,
-0.2511291801929474... |
Instructions: 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... | Non-hateful | 3 | NIv2 | task333_hateeval_classification_hate_en | zs_opt | [
-0.785602331161499,
0.2034078985452652,
0.5860286951065063,
1.1489500999450684,
-0.18274052441120148,
-1.2269935607910156,
0.6130449771881104,
0.8989385366439819,
0.5417309999465942,
0.5509743094444275,
0.37694764137268066,
0.47378668189048767,
-0.4914427399635315,
-0.34082451462745667,
... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given a sentence in the Japanese and Filipino language. Your task is check if the Filipino sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise gene... | No | 0 | NIv2 | task1120_alt_ja_fil_answer_generation | fs_opt | [
0.19560319185256958,
-0.34113365411758423,
-0.3776494562625885,
0.40771955251693726,
0.5281978845596313,
-0.233302503824234,
0.403110533952713,
0.22869272530078888,
-1.2455012798309326,
-0.43383365869522095,
0.09721013158559799,
0.9789782166481018,
-0.054667726159095764,
0.7135733366012573... |
In this task, you need to answer the given multiple-choice question on the physics. Classify your answers into 'a', 'b', 'c', 'd', and 'e'.
Q: Problem: kathleen can paint a room in 2 hours , and anthony can paint an identical room in 7 hours . how many hours would it take kathleen and anthony to paint both rooms if th... | c
****
| 4 | NIv2 | task1422_mathqa_physics | fs_opt | [
0.7231175303459167,
1.032002568244934,
0.06764968484640121,
-0.4592219889163971,
-0.23374561965465546,
-0.3382444381713867,
-0.028842194005846977,
0.5801564455032349,
-0.2710284888744354,
0.04863392934203148,
-0.0808231309056282,
0.732241153717041,
-0.026294369250535965,
-0.285781025886535... |
Detailed Instructions: A text is given in Hindi. Translate it from the Hindi language to the Telugu language. The translation must not omit or add information to the original sentence.
See one example below:
Problem: ఈ పోర్టల్ ను 2019-20 ఆర్థిక సంవత్సరానికి ఎన్జిఒ లు మరియు రాష్ట్రాలు ఆన్లైన్ లో దరఖాస్తులను దాఖల... | सरकार का मुख्य प्रयास यह है कि स्वायशासी निकायों की समीक्षा की जाए और उन्हें युक्तिसंगत बनाया जाए, ताकि उनके कामकाज, प्रभाव और कार्यकुशलता में सुधार हो, वित्तीय और मानव संसाधनों का उचित इस्तेमाल हो, मौजूदा निति में उनकी प्रासंगिकता एवं प्रशासन में इजीफा हो और उनकी निगरानी उचित तरीके से हो सके। | 4 | NIv2 | task1046_pib_translation_telugu_hindi | fs_opt | [
-0.6119765043258667,
-0.09062537550926208,
0.20254763960838318,
0.5246491432189941,
-0.025998573750257492,
-0.8899044990539551,
-0.007338033057749271,
0.897182285785675,
-0.6372029781341553,
0.6448723673820496,
-0.7183775305747986,
-0.015100883319973946,
-0.4066568613052368,
0.045677885413... |
You are given a math word problem and you are supposed to apply a single mathematical operator like addition, subtraction, multiplication, or division on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Q: after going down the falls he then went to rock ... | 400 | 4 | NIv2 | task864_asdiv_singleop_question_answering | zs_opt | [
-0.08374933153390884,
1.1595391035079956,
0.012422065250575542,
-0.6780931949615479,
-0.014935174956917763,
-0.21932661533355713,
0.8611962795257568,
0.5775192379951477,
-0.23068538308143616,
-0.04381004348397255,
-0.30142292380332947,
0.3392147421836853,
-0.7826863527297974,
0.37270441651... |
Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it bei... | Wenn Sie ein Unternehmen eröffnen wollen, dann sollten Sie einen Geschäftsplan machen. | 6 | NIv2 | task416_mickey_de_sentence_perturbation_generation | fs_opt | [
-0.4511376619338989,
0.22307100892066956,
0.16469258069992065,
0.022860677912831306,
0.08412929624319077,
-1.1202962398529053,
0.443576455116272,
1.1302461624145508,
0.1342887580394745,
0.45673811435699463,
-0.05194661766290665,
-0.18142136931419373,
-1.1239145994186401,
-0.053726423531770... |
In this task, you will be shown a conversation and a question. You need to answer the question and choose the correct option based on the conversation. "W" and "M" in the conversations stand for "woman" and "man".
W: I wonder if you could sell me the Psychology textbooks. You took the course last semester, didn't you?... | (C) Doctor and patient.
| 0 | NIv2 | task247_dream_answer_generation | fs_opt | [
0.4905843138694763,
-0.2886713147163391,
-0.7787703275680542,
-0.25618934631347656,
0.3401818871498108,
-0.643322765827179,
0.6342458724975586,
0.4310867488384247,
0.21034587919712067,
-0.27649205923080444,
-0.31032365560531616,
-0.11269687861204147,
-0.2757071852684021,
0.3727495074272156... |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Japanese.
Example input: Mio padre è medico. Ed è stato un grande vantaggio per noi. Si è occupato di lei in modo fantastico.
Example output: 父が医師だったので父に担当してもらえるという大きな利点がありました父は母に見事な治療を施しました
Example explanation: The Italian sentenc... | ９月に発売の予定です | 3 | NIv2 | task1248_ted_translation_it_ja | fs_opt | [
-0.437015175819397,
0.31949958205223083,
-0.5659023523330688,
-0.3137941360473633,
-0.64359050989151,
-0.6220067739486694,
0.5648372769355774,
0.8855313658714294,
0.33462053537368774,
-0.4207336902618408,
-0.5119448304176331,
0.6933112144470215,
-0.4202725887298584,
-0.04820618778467178,
... |
Q: You are given a statement written in Marathi. 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 .
Statement: इस्रायल फुटबॉल संघ (हिब्रू: נבחרת ישראל בכדורגל; फिफा संकेत: ISR) हा पश्चिम आशियामधील <MASK> देशाचा ... | इस्रायल | 7 | NIv2 | task950_wiki_cloze_mr_multiple_choice_question_answering | zs_opt | [
0.9425086379051208,
0.3377177119255066,
-0.3850443959236145,
0.4759094715118408,
0.026941906660795212,
0.17209920287132263,
0.7128231525421143,
0.38279110193252563,
0.48014551401138306,
-0.06277508288621902,
-0.598236620426178,
0.3384634554386139,
-0.4625285863876343,
-0.4377531111240387,
... |
Definition: A question is presented to you in this task, and your job is to write a potentially correct answer.
Input: what airport do you fly into maui?
Output: | Kahului Airport | 2 | NIv2 | task1412_web_questions_question_answering | zs_opt | [
0.19484171271324158,
0.837166428565979,
-0.8294775485992432,
-0.8590442538261414,
-0.49200814962387085,
0.2568981647491455,
-0.20722176134586334,
0.5746443271636963,
0.13370761275291443,
0.22898352146148682,
-0.9544298648834229,
-0.39931049942970276,
-0.07892891764640808,
-0.08437714725732... |
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Hebrew.
Q: 言うつもりでした「かくかくしかじかの男が来たら私が言ったことは間違いだったと伝えてくれ
A: | הייתי מוכן לומר לו, "" שמע, אם מישהו אשר נראה כך וכך יגיע מחר בבקשה תאמר לו שזו הייתה טעות. | 4 | NIv2 | task1225_ted_translation_ja_he | zs_opt | [
0.7239893674850464,
0.5957013964653015,
0.3747560679912567,
-0.2913137674331665,
0.14837124943733215,
-1.0993077754974365,
0.05024225637316704,
-0.6590670347213745,
0.5150356292724609,
-0.2766250669956207,
-0.7355467081069946,
0.0371144637465477,
-1.3635001182556152,
-0.06906301528215408,
... |
Detailed Instructions: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to classify the command into one of these seven categories: (1) majority, (2) unique, (3) superlative, (4) count, (5) comparative, (6) aggregation, and (7) ordinal.
He... | comparative | 8 | NIv2 | task212_logic2text_classification | zs_opt | [
0.1841028332710266,
-0.3291614055633545,
-0.26446300745010376,
0.2894977331161499,
0.4881483316421509,
-0.5137954950332642,
0.8299391269683838,
0.6363481879234314,
0.3579480051994324,
0.04636983573436737,
0.017542563378810883,
-0.01488875225186348,
0.026884233579039574,
0.5212142467498779,... |
Detailed Instructions: In this task, you're given a review from Amazon. Your task is to generate a rating for the product on a scale of 1-5 based on the review. The rating means 1: extremely poor, 2: poor, 3: neutral, 4: good, 5: extremely good.
Problem:Shelf came in warped and one of the arms was longer than the other... | 2 | 8 | NIv2 | task1310_amazonreview_rating_classification | zs_opt | [
-0.06577953696250916,
-0.4768821597099304,
-0.14876596629619598,
-0.23576170206069946,
0.6564594507217407,
0.07354630529880524,
0.5060269832611084,
0.9934902191162109,
-0.34488290548324585,
0.8611679077148438,
-0.38845452666282654,
-0.2522548735141754,
-0.7640196084976196,
0.03578935563564... |
Given a sentence in Italian, generate a new Italian sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it b... | Output: Lì hai i tuoi documenti come uno o patente di guida.
| 2 | NIv2 | task408_mickey_it_sentence_perturbation_generation | fs_opt | [
0.1766456663608551,
0.5871503949165344,
-0.5928603410720825,
0.5853444933891296,
-0.6631143093109131,
-1.2073122262954712,
0.6613364815711975,
1.1981383562088013,
-0.4461662769317627,
0.05320246145129204,
-0.8588384389877319,
0.8516130447387695,
-0.3768995702266693,
0.07249743491411209,
... |
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... | No | 4 | NIv2 | task1206_atomic_classification_isbefore | fs_opt | [
0.37482309341430664,
0.29394495487213135,
0.08983013033866882,
-0.04996403679251671,
-0.5306928157806396,
-0.9085016250610352,
1.1262696981430054,
0.584731936454773,
-0.6047614812850952,
-0.35067296028137207,
-0.35781508684158325,
-0.6749234795570374,
-0.7677056193351746,
0.079559646546840... |
Given the task definition and input, reply with output. In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ).... | No | 5 | NIv2 | task1199_atomic_classification_xattr | zs_opt | [
0.008393201977014542,
0.15670707821846008,
0.6631504893302917,
-0.12449054419994354,
-0.3886217474937439,
-0.8562558889389038,
0.6763056516647339,
0.8254095315933228,
-0.5278923511505127,
-0.3160104751586914,
-0.5284342765808105,
-0.7368927001953125,
-0.7407335042953491,
-0.034540094435214... |
Teacher: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Polish.
Teacher: Now, understand the problem? If you are still confused, see the following example:
全て肋骨の間から行うのです
Solution: Wszystko jest robione pomiędzy żebrami.
Reason: The Japanese sentence is correctly translated int... | Cudownie opowiadający o innym świecie, równoległym do tego, w którym żyjemy. | 2 | NIv2 | task1097_ted_translation_ja_pl | fs_opt | [
0.6675823330879211,
0.9130958318710327,
-0.020701143890619278,
-0.08306145668029785,
-0.15408383309841156,
-0.4133392572402954,
0.6413740515708923,
-0.336251825094223,
-0.07570773363113403,
-0.4818313717842102,
-0.27804121375083923,
0.6319869756698608,
-0.8676936030387878,
0.44190540909767... |
Detailed Instructions: In this task, you are given a passage and a question regarding that passage. You must determine whether or not the question is answerable from the given passage. If a question is answerable, output should be 'True', otherwise 'False'. You must not consider any other information that is not provid... | True | 9 | NIv2 | task349_squad2.0_answerable_unanswerable_question_classification | zs_opt | [
0.10730262100696564,
0.2705478072166443,
0.05545322969555855,
-0.33937186002731323,
-1.0580825805664062,
-0.7610361576080322,
0.459363728761673,
0.23851343989372253,
0.0818413719534874,
-0.03933154419064522,
-0.028933163732290268,
0.0366278812289238,
-0.4204772710800171,
-0.573484182357788... |
Teacher:You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Hebrew.
Teacher: Now, understand the problem? Solve this instance: Ainda estamos longe de melhorarmos pessoas. O nosso objetivo é apenas assegurarmos que teremos uma hipótese de sobreviver o suficiente para conseguir i... | יש לנו עוד דרך ארוכה עד שנגיע לשיפור בני אדם. המטרה שלנו היא רק לוודא שיש לנו סיכוי לשרוד מספיק זמן כדי שאולי נעשה זאת. תודה רבה לכם. | 6 | NIv2 | task1278_ted_translation_pt_he | zs_opt | [
-0.2657231092453003,
0.5922535061836243,
0.47331300377845764,
-0.8888673782348633,
-0.2230253964662552,
-0.5666046142578125,
0.8062753081321716,
0.061640359461307526,
0.1726047545671463,
0.03342381864786148,
-0.3635929822921753,
-0.04905431717634201,
-1.0818785429000854,
-0.160408288240432... |
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.
Ex Input:
Article: The silent young woman in bed number six is called Jasmine. So am I, but names are only superficial things, floats on the surface of the water, and we share deeper co... | Why did Sen. McCain make a phone call to the writer?
| 1 | NIv2 | task311_race_question_generation | fs_opt | [
0.8203822374343872,
0.06283842027187347,
-0.5990381240844727,
-0.9565141201019287,
0.5944076776504517,
-0.7495430111885071,
1.3097498416900635,
0.8771235942840576,
0.4903191328048706,
0.4025402069091797,
0.11461904644966125,
0.27873629331588745,
-0.7348461151123047,
0.22079676389694214,
... |
Teacher:You are given a sentence in Persian. Your job is to translate the Farsi sentence into Galician.
Teacher: Now, understand the problem? Solve this instance: اتاق هایی که به صورت طبیعی هوا تهویه می شد را بررسي كرديم ، در آن اتاق ها بیمارستان به ما اجازه داد که تهویه مکانیکی هوا را در بخشي از ساختمان خاموش ... | Tamén habitacións ventiladas de forma natural, donde se nos permitiu apagar os sistemas de ventilación mecánica nunha zona do edificio e abrir an fiestras que xa non se empregaban, pero que se fixeron útiles para o noso estudo. | 6 | NIv2 | task1270_ted_translation_fa_gl | zs_opt | [
-0.3489798903465271,
0.904850959777832,
-0.31487828493118286,
-0.9568092823028564,
-0.28225573897361755,
-1.3904650211334229,
0.1671813428401947,
0.655664324760437,
0.0018264326499775052,
0.3066742718219757,
0.05942583084106445,
0.30987852811813354,
-0.6218094229698181,
0.01279815658926963... |
Teacher: You are given a paragraph, a question and some answer options (associated with "A", "B", "C", "D", etc.) You need to list all the correct answer options with their associated letters (e.g. "A" can be a valid answer). Note that sometimes, more than one option can answer the question correctly and completely. In... | B, C, D. | 2 | NIv2 | task058_multirc_question_answering | fs_opt | [
0.5592149496078491,
-0.24100084602832794,
-0.5901025533676147,
0.16010892391204834,
-0.15937046706676483,
-1.1825854778289795,
0.6803174018859863,
1.0823272466659546,
0.4375758469104767,
0.3411899507045746,
-0.9260386228561401,
0.48650985956192017,
-0.5885758399963379,
-0.05422582477331161... |
Given a document, an entity and its sentiment towards the entity, verify if it is the correct sentiment towards the entity. Answer should be yes or no. Note that URLs in the text have been replaced with [Link].
Input: Consider Input: Verify if the sentiment of the following document towards the entity Nick Fitzgerald ... | Output: no
| 2 | NIv2 | task423_persent_document_sentiment_verification | fs_opt | [
-0.02021717093884945,
0.24884594976902008,
-0.41726481914520264,
0.09832490980625153,
0.1025986447930336,
-0.4692326784133911,
1.0607950687408447,
0.4106646776199341,
-0.06654626876115799,
0.8017590045928955,
0.09362722188234329,
0.03252556174993515,
-0.35047000646591187,
0.066795550286769... |
Instructions: This task is to translate a news commentary statement given in German language into Spanish 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.
Input: Bis zu 60 % des alten Waldbest... | Durante los años de guerra puede que se talara hasta el 60 por ciento de los bosques antiguos de Nangahar, la segunda provincia por la cantidad de opio producido. | 3 | NIv2 | task1373_newscomm_translation | zs_opt | [
-0.5828061103820801,
0.5597727298736572,
-0.2659548223018646,
-0.80709308385849,
-0.6245330572128296,
-0.40671008825302124,
0.7284164428710938,
1.559464454650879,
0.25547152757644653,
-0.006398140452802181,
-0.7531694173812866,
-0.496303528547287,
-0.836679220199585,
0.1287495195865631,
... |
Instructions: You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into English.
Input: Isso significa, que numa população em que a malária diminuiu, e onde há poucas pessoas que ainda têm o parasita, os cães podem encontrar essas pessoas, podemos tratá-las com medicamentos anti-malá... | That means that in a population where malaria has gone down all the way, and there's few people remaining with parasites, that the dogs can find these people, we can treat them with anti-malarial drugs, and give the final blow to malaria. | 3 | NIv2 | task1274_ted_translation_pt_en | zs_opt | [
-0.9982823729515076,
0.5790001749992371,
-0.5415270328521729,
-0.23164890706539154,
-0.2537412643432617,
-1.4842212200164795,
-0.47517091035842896,
1.1077520847320557,
0.26061803102493286,
0.4180833101272583,
-0.6985235214233398,
0.41103100776672363,
0.07217216491699219,
0.0479144155979156... |
Q: Given an adjective, generate its antonym. An antonym of a word is a word opposite in meaning to it.
incorrigible
A: | corrigible | 7 | NIv2 | task1508_wordnet_antonyms | zs_opt | [
0.24770262837409973,
1.862672209739685,
0.8177064657211304,
-0.15270762145519257,
-0.801182746887207,
-0.9291667938232422,
-0.35058167576789856,
0.3061169683933258,
0.5315215587615967,
-0.31898555159568787,
-0.7637276649475098,
-0.29685503244400024,
-1.1520354747772217,
0.1694657802581787,... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the... | The man is smoking a pipe. | 4 | NIv2 | task187_snli_entailment_to_contradiction_text_modification | zs_opt | [
-0.16300010681152344,
0.8408603072166443,
0.5567746162414551,
-0.805574893951416,
0.2259928435087204,
-0.939601480960846,
0.3027244210243225,
0.5429954528808594,
0.2729640603065491,
-0.44007569551467896,
-1.5323114395141602,
-1.3586864471435547,
-0.7409521341323853,
-0.38966310024261475,
... |
Detailed Instructions: You are given a sentence from a conversation between a human and a virtual assistant. Your task is to classify the sentence into one of the following five action categories - INFORM, INFORM_INTENT, OFFER, REQUEST, REQUEST_ALTS. If the sentence is about informing something, generate 'INFORM'. If i... | OFFER | 4 | NIv2 | task880_schema_guided_dstc8_classification | fs_opt | [
0.35631227493286133,
0.19628828763961792,
-0.028636833652853966,
0.5765420794487,
-0.04780545458197594,
0.10268858820199966,
-0.018276935443282127,
0.7528150081634521,
0.5403830409049988,
-0.07530194520950317,
-0.37334153056144714,
-0.7414143085479736,
-0.4581664502620697,
0.41814538836479... |
Generate a correct and concise answer for the question based on the words in the context.
--------
Question: Context : The Master Gunfighter is mainly a remake of the 1969 Japanese film Goyokin, although the story revolves around a true incident in the early 1800s involving massacred Indians that occurred in the vicini... | National Premier Soccer League
| 7 | NIv2 | task1327_qa_zre_answer_generation_from_question | fs_opt | [
-0.4582749307155609,
-0.3023808002471924,
-0.40838733315467834,
-0.4416646957397461,
0.6010100841522217,
0.35634344816207886,
0.23629701137542725,
0.37442830204963684,
-0.25481027364730835,
0.017976775765419006,
-0.17412161827087402,
0.17657022178173065,
-0.9798357486724854,
-0.19147729873... |
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 will be presented with a passage and have to answer a question based on your understanding of the events inferred from the passage. Among the entities, try to find the best entity t... | (C) | 0 | NIv2 | task302_record_classification | fs_opt | [
0.15687209367752075,
0.3071158230304718,
-0.31646111607551575,
-0.29062169790267944,
0.28698641061782837,
0.14035676419734955,
0.49575749039649963,
0.9398312568664551,
-0.6294274926185608,
0.9362747669219971,
0.40979868173599243,
0.5805925130844116,
-0.7710330486297607,
0.5111662149429321,... |
instruction:
Given a premise, an initial context, an original ending, and a new ending, the task is to generate the counterfactual context that is aligned with the new ending. Each instance consists of a five-sentence story. The premise is the first sentence of a story, and the second sentence, which is the initial con... | He was devastated by all the exhibits and artifacts.
| 9 | NIv2 | task270_csrg_counterfactual_context_generation | fs_opt | [
0.1328248828649521,
0.30555009841918945,
0.08008863031864166,
0.14637888967990875,
0.05934169143438339,
-0.8675063848495483,
-0.1172194555401802,
0.9504668712615967,
-0.13249413669109344,
0.13260826468467712,
-0.298021137714386,
-0.1274292916059494,
-0.1274758279323578,
-0.0283932909369468... |
Teacher: In this task, you're given a short article. Your job is to classify the article based on its category. Use the following classification labels, 0. World, 1. Sports, 2. Business, 3. Science or Technical. Label the text "0" if it contains information related to world. Label the text "1" if it contains informatio... | 2 | 2 | NIv2 | task1541_agnews_classification | fs_opt | [
-0.8177614212036133,
0.35040283203125,
0.034047793596982956,
0.10317026078701019,
0.2215227633714676,
-0.21392038464546204,
-0.42247557640075684,
0.97272789478302,
0.0042957100085914135,
0.08856722712516785,
-0.31360071897506714,
0.11104842275381088,
0.06301771104335785,
-0.525543153285980... |
In this task, you are given a sentence from the research paper and the category to which it belongs. Your task is to classify whether the given category is correct or not by providing "True" and "False", respectively. Here are the definitions for the categories: Background (Why is this problem important? What relevant ... | True
| 0 | NIv2 | task1164_coda19_section_correction_classification | fs_opt | [
-0.22848837077617645,
-0.02969641238451004,
-0.1526460200548172,
-0.07761810719966888,
0.14935609698295593,
0.06976398825645447,
-0.2847384214401245,
1.0822248458862305,
0.09340521693229675,
0.00937455054372549,
-1.3351821899414062,
-0.16477498412132263,
-0.01488574780523777,
-0.0293406732... |
instruction:
In this task, you're given the middle and ending of a three-part story. Your job is to complete the short story by writing a probable beginning of the story. Generated sentences must be short, have fewer than 10 words, and be simple as if narrating to a child. Avoid using any irrelevant extra information w... | Roger was 80 years old.
| 9 | NIv2 | task072_abductivenli_answer_generation | fs_opt | [
-0.07099268585443497,
0.5021893382072449,
-0.2970007061958313,
-0.6206349730491638,
-0.580359697341919,
-0.13659659028053284,
0.6547258496284485,
0.592923641204834,
-0.4964561462402344,
0.0697052925825119,
-0.5815201997756958,
-0.13437509536743164,
-0.2752513885498047,
-0.14511069655418396... |
Detailed Instructions: 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".
Q: Article: indian shares ended flat tuesday , rebounding from intra-day lows on hopes the us federal reserv... | no | 9 | NIv2 | task289_gigaword_summarization | zs_opt | [
-0.7709815502166748,
0.20135153830051422,
0.19417044520378113,
0.27504420280456543,
-0.21243612468242645,
-0.29616019129753113,
0.12220282852649689,
0.7520527839660645,
-0.5208663940429688,
-0.15672287344932556,
-0.33030056953430176,
0.20524033904075623,
-0.44987809658050537,
0.19867447018... |
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... | Output: OTHER
| 2 | NIv2 | task304_numeric_fused_head_resolution | fs_opt | [
-0.09867457300424576,
0.6128212213516235,
-0.3915005922317505,
0.4351387917995453,
-0.060400985181331635,
-0.018176227807998657,
1.2664412260055542,
0.775864839553833,
-0.12894800305366516,
0.1118922010064125,
-0.2670443654060364,
0.37172332406044006,
-0.4986345171928406,
-0.12116526812314... |
In this task, you are given a sentence and a profession that is mentioned in the sentence. The gender of the person with the given profession can be identified using the gendered pronouns that refer to them in the text. You are expected to identify the gender. Select from female and male.
Q: Sentence: The guard went t... | Male | 4 | NIv2 | task341_winomt_classification_gender_anti | zs_opt | [
-1.0443460941314697,
0.8915337324142456,
-0.41794663667678833,
-1.1530401706695557,
0.10377741605043411,
-0.49311932921409607,
-0.21753838658332825,
0.6051912307739258,
1.0728785991668701,
0.3733254373073578,
-1.1537646055221558,
-0.03954571485519409,
-0.8330621123313904,
-0.22718663513660... |
In this task, you are given two phrases: Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determ... | No | 0 | NIv2 | task1214_atomic_classification_xwant | zs_opt | [
0.05611114203929901,
0.4248267710208893,
0.4205174744129181,
-0.48526477813720703,
-0.5019132494926453,
-0.7484602332115173,
1.357617974281311,
0.11949752271175385,
-0.5400476455688477,
-0.606772780418396,
-0.4935661256313324,
-0.4115489423274994,
-0.8430567979812622,
0.3959192931652069,
... |
In this task, you will use your knowledge about language (and common sense) to determine what element the marked number refers to. The numbers are marked with two underlines around them, like: _ number _. Your answer should be chosen from the given text, and should not contain other words.
Let me give you an example: ... | story | 8 | NIv2 | task401_numeric_fused_head_reference | fs_opt | [
-0.3216586709022522,
0.08767369389533997,
-1.1069235801696777,
-0.16722789406776428,
-0.2553725838661194,
-0.7007195949554443,
0.8652578592300415,
0.8609750270843506,
-0.41039198637008667,
0.031356051564216614,
-0.37252116203308105,
-0.11013132333755493,
-0.17536649107933044,
-0.1885710954... |
Teacher:In this task you will be given a list of integers. For every element in the list, if the element is even you should divide by 4, if the element is odd you should multiply by 4 then add 2. The output should be a list of numbers that is the result of applying that logic to the input list. You should not round any... | [166, 25.0, -2.0, -138, 318, -6.5, -24.5, -34, -9.5, -210] | 6 | NIv2 | task368_synthetic_even_or_odd_calculation | zs_opt | [
-0.5781386494636536,
0.5029156804084778,
-0.1699720025062561,
-0.41665932536125183,
0.004771511536091566,
0.24742208421230316,
1.156783103942871,
0.4155780076980591,
-0.33724743127822876,
0.24868595600128174,
-0.38011646270751953,
-0.8919561505317688,
-0.32222220301628113,
-0.5457196235656... |
Teacher:In this task, you are given a text of the article. Your task is to generate a headline (title) for this article.
Teacher: Now, understand the problem? Solve this instance: hurricane dean plowed into the caribbean coast of mexico on tuesday as a roaring category # hurricane , lashing ancient mayan ruins and head... | eye of roaring hurricane dean strikes mexico s yucatan peninsula | 6 | NIv2 | task288_gigaword_summarization | zs_opt | [
-0.03212997317314148,
-0.1714719831943512,
-0.2937019467353821,
-0.9953651428222656,
-0.6370878219604492,
-0.21000486612319946,
-0.1988438069820404,
0.82566899061203,
-0.065645232796669,
0.020854691043496132,
-0.024659115821123123,
-0.588290810585022,
-0.1906784623861313,
-0.41074046492576... |
In this task, given a sentence in the Burmese Language, your task is to convert it into the English language.
One example: အသက် ၂၇ နှစ် အရွယ် ဂျေဆွန် မက်ကေ ၏ မိခင် ဘိုနီ မက်ကေ က " သူတို့ အလုပ်လုပ်တဲ့ နည်းလမ်း ကို အရာများစွာ ပြောင်းလဲလိုက်မှာ ကို သင် မယုံဘူး ဆိုတာ ကျွန်မ အသေအချာ ယုံကြည်ပါတယ် ၊ ဒါပေမယ့် သူတို့ လုပ်ဆောင်ခ... | Massa became the first Brazilian to win on home soil since Ayrton Senna in 1993. | 6 | NIv2 | task538_alt_translation_bu_en | fs_opt | [
0.03322621062397957,
0.01814054697751999,
-0.274028480052948,
-0.977484405040741,
0.34931105375289917,
-0.8262097835540771,
0.6362920999526978,
0.13224747776985168,
0.5779699087142944,
0.31249433755874634,
-0.30934181809425354,
0.6246878504753113,
-0.7775092124938965,
-0.329511821269989,
... |
This task is to identify the language of a sentence correctly by classifying if it is English or Telugu
Such: 0523-66 46 74 | English | 0 | NIv2 | task1618_cc_alligned_classify_tel_eng | zs_opt | [
-0.4626040458679199,
0.1934792399406433,
0.91643887758255,
-0.18427708745002747,
-0.18789377808570862,
-0.30707669258117676,
0.19272565841674805,
-0.18631285429000854,
-0.2021082192659378,
-0.4014679789543152,
-0.24938632547855377,
-0.14723894000053406,
-0.6527470350265503,
-0.037032518535... |
Definition: You are given a sentence in Polish. Your job is to translate the Polish sentence into Arabic.
Input: To rezultat wykorzystania szybszych komputerów do budowy jeszcze szybszych.
Output: | هذا نتيجة الكمبيوترات الأسرع المستخدمة في صنع كمبيوترات أسرع منها. | 2 | NIv2 | task1259_ted_translation_pl_ar | zs_opt | [
-0.6862690448760986,
0.9326786994934082,
-0.3344917595386505,
-0.31337159872055054,
-0.40131789445877075,
0.5118669271469116,
1.21122407913208,
-0.19253738224506378,
0.9315903186798096,
0.045955874025821686,
-0.7799689769744873,
0.2164393961429596,
-0.035777874290943146,
0.4821985960006714... |
Detailed Instructions: You will be given a person's personality, and a history of a conversation this person has had. You will be given four candidate sentences to complete the conversation, based on the context. Choose one and answer with the text.
Problem:Personality: I work as a bartender.
I used to be in the marine... | Hey... how are you doing tonight? | 8 | NIv2 | task1730_personachat_choose_next | zs_opt | [
-0.7067984938621521,
0.7683397531509399,
-0.12292619049549103,
-0.18110699951648712,
-0.08430668711662292,
0.3514191508293152,
0.7369232177734375,
-0.20459860563278198,
0.5464434027671814,
-0.1490887850522995,
0.020365800708532333,
-0.7600433826446533,
0.03564741462469101,
-0.3208363652229... |
Detailed Instructions: You will be given a person's personality, and a history of a conversation this person has had. You will be given four candidate sentences to complete the conversation, based on the context. Choose one and answer with the text.
Q: Personality: I like to play tennis.
My favorite food is a burger.
I... | My current obsession is hamilton the musical. Seen it? | 9 | NIv2 | task1730_personachat_choose_next | zs_opt | [
-0.39576035737991333,
0.3098450303077698,
-0.44886669516563416,
0.12251688539981842,
0.0710148885846138,
0.05965452268719673,
0.5148318409919739,
-0.05365728586912155,
-0.0423739068210125,
-0.2674490213394165,
0.06095489114522934,
-0.10999925434589386,
-0.048038605600595474,
-0.40158435702... |
Q: Given a sequence of actions to navigate an agent in its environment, provide the correct command in a limited form of natural language that matches the sequence of actions when executed. Commands are lowercase and encapsulate the logic of the sequence of actions. Actions are individual steps that serve as the buildi... | look around left after run thrice | 7 | NIv2 | task127_scan_long_text_generation_action_command_all | zs_opt | [
0.381813645362854,
0.9416161775588989,
-0.4730730950832367,
0.05804441124200821,
-0.1637800633907318,
0.20408995449543,
-0.09800499677658081,
0.6602135896682739,
-0.4237176775932312,
-0.25629737973213196,
-0.787001371383667,
-0.4055641293525696,
-0.8170775175094604,
-0.0205240361392498,
... |
In this task, you are given a summary for US Congressional and California state bill, your task is to generate a Title for this bill. The preferred titles are under forty words and mention the purpose of the bill.
[EX Q]: Congressional Pay for Performance Act - Suspends basic pay adjustments for Members of Congress, a... | To amend title 38, United States Code, to improve the outreach activities of the Department of Veterans Affairs, and for other purposes.
| 6 | NIv2 | task1659_title_generation | fs_opt | [
-0.12295927852392197,
0.02605520188808441,
-0.47592470049858093,
-0.018620971590280533,
-0.0001151177566498518,
-0.20432505011558533,
1.1827409267425537,
0.9346975684165955,
0.17987050116062164,
0.3147483468055725,
0.2843989431858063,
0.08036375790834427,
-0.23551513254642487,
0.0101209273... |
Given a sentence in the Japanese, provide an equivalent translation in Lao 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: ອິຕາລີໄດ້ເສຍໃຫ້ປ໊ອກຕຸຍການ 31 ຕໍ່ 5 ໃນພູລ C ຂອງ ການແຂ... | ນີ້ແມ່ນລະດູທຳອິດຂອງ ເພຣັຊລີ່ ໃນນາມເປັນຜູ້ຈັດການ ແລະ ລາວໄດ້ຖືກຖາມເຖິງ ປະສົບການຂອງລາວໃນບົດບາດດັ່ງກ່າວ:"ຂ້ອຍມັກມັນ." | 3 | NIv2 | task1124_alt_ja_lo_translation | fs_opt | [
-0.7184544801712036,
0.5479987263679504,
-0.7559217214584351,
0.2484656125307083,
-0.03448980301618576,
-0.2892489731311798,
0.27734899520874023,
0.17663681507110596,
0.10133291780948639,
-0.7859888076782227,
-1.3146955966949463,
0.8358427286148071,
-0.5351512432098389,
0.9665525555610657,... |
In this task, you are given a multiple-choice question and you have to pick the correct option. Answer with option indexes (i.e., "A", "B", "C", and "D").
A lack of water has a direct connection on the amount of available (A) shelters (B) sustenance (C) rainy days (D) mates
B
In a decade spring occurs (A) three times... | A
| 0 | NIv2 | task1286_openbookqa_question_answering | fs_opt | [
0.40609002113342285,
0.4378788471221924,
-0.8865485191345215,
-0.19995510578155518,
-0.6108225584030151,
-0.7353523969650269,
0.595424234867096,
0.6562033891677856,
-0.6441283822059631,
0.4893679618835449,
-0.4530302882194519,
-0.1369543820619583,
-0.3144778907299042,
-0.43787264823913574,... |
Definition: Given a comment text in Tamil, classify the comment into one of these categories (i) Hope speech, if it contains encouraging, positive or supportive contents about equality, diversity or inclusion, (ii) Not Hope Speech or (iii) Not in Expected Language, if the text is not Tamil.
Input: Apps ah ban pannatha ... | Not Hope Speech | 2 | NIv2 | task680_hope_edi_tamil_text_classification | zs_opt | [
0.026856135576963425,
0.3179234266281128,
0.39564669132232666,
0.5506109595298767,
-0.11391642689704895,
-1.0662001371383667,
-0.17699995636940002,
1.0345109701156616,
-0.8863434791564941,
0.4913219213485718,
-0.6131962537765503,
0.17631199955940247,
-0.2054131031036377,
-0.550790071487426... |
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.
One example is below.
Q: Comment: President lied under oath about cons... | Sexual-explicit | 9 | NIv2 | task323_jigsaw_classification_sexually_explicit | fs_opt | [
-1.2039926052093506,
0.07263197004795074,
0.3537217974662781,
0.20886215567588806,
0.0005554939853027463,
-0.4162403345108032,
-0.2390909045934677,
0.5183340907096863,
0.003850498702377081,
0.6704656481742859,
0.3875153064727783,
-0.1264403611421585,
-0.15968888998031616,
-1.03084409236907... |
Craft one incorrect answer. In doing so, try to use words from the context as much as possible, or by using similar words used in the correct answer. DO NOT craft nonsensical or off-topic incorrect answers, such that the incorrect answers can be directly excluded without reasoning according to the context. Try to make ... | I might have used a camera to make the blouse . | 9 | NIv2 | task025_cosmosqa_incorrect_answer_generation | fs_opt | [
0.3887770175933838,
0.8508691191673279,
-0.5489290952682495,
1.5025722980499268,
0.5363215804100037,
-1.0738167762756348,
0.43376559019088745,
1.002829670906067,
-0.5483750104904175,
-0.011655470356345177,
-0.4915025234222412,
-0.1948988139629364,
-0.11740262061357498,
0.018190570175647736... |
Instructions: 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... | True | 3 | NIv2 | task1589_scifact_classification | zs_opt | [
0.4561285376548767,
0.6772709488868713,
-0.7347943186759949,
-0.31887534260749817,
0.26089978218078613,
-1.0132217407226562,
1.3584012985229492,
0.5701478123664856,
0.3530305027961731,
0.06735462695360184,
-0.0735655128955841,
0.9464995861053467,
-0.37740182876586914,
0.19552013278007507,
... |
Given a sentence in Chinese, provide an equivalent paraphrased version from the original that retains the same meaning.
One example is below.
Q: 1975年的NBA赛季 - 76赛季是全美篮球协会的第30个赛季。
A: 1975-76赛季的全国篮球协会是NBA的第30个赛季。
Rationale: The paraphrase of the original sentence in Chinese is correct and accurate because even though se... | 当Patrick Logan到达Wisteria Lane时，他跑过Nick。 | 9 | NIv2 | task775_pawsx_chinese_text_modification | fs_opt | [
-0.07539358735084534,
-0.6357123255729675,
-0.47379741072654724,
0.36839473247528076,
0.2776404917240143,
-0.5829386711120605,
-0.1264209747314453,
0.26128146052360535,
0.5323619246482849,
0.42247435450553894,
0.003380731213837862,
0.5929794907569885,
-0.1360149085521698,
0.308590859174728... |
Detailed Instructions: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into English.
See one example below:
Problem: (تصفيق) ومع ذلك هناك معارك سياسية في بلدنا.
Solution: (Applause) However there is a political battle in our country.
Explanation: The Arabic sentence is correctly transla... | This is Allan Okrainec from Toronto. | 4 | NIv2 | task1230_ted_translation_ar_en | fs_opt | [
0.5515910983085632,
0.8687875270843506,
0.63904869556427,
-0.7418894171714783,
0.04771339148283005,
-0.39042675495147705,
0.7499439120292664,
-0.46273043751716614,
0.3207421898841858,
-0.1097128763794899,
-0.5297377705574036,
-0.03719255328178406,
-0.9332677125930786,
0.25564044713974,
0... |
In this task, you're given a statement, further information available on a particular linked term from the statement, and a question. Your job is to generate the answer to the question by using the information provided. If there is no clear answer obtainable, output 'none'.
Q: Context: In 1965 Link Information: Dino Pa... | Answer: 48 | 4 | NIv2 | task237_iirc_answer_from_subtext_answer_generation | zs_opt | [
0.8649322986602783,
-0.008521772921085358,
-0.058558136224746704,
-0.5321490168571472,
-0.37688472867012024,
-0.04374562203884125,
0.06540293991565704,
0.43622392416000366,
0.18624192476272583,
-0.16760654747486115,
-0.28774964809417725,
0.3216794729232788,
-1.4107756614685059,
-0.15545922... |
You are given an open-domain question from an open movie database. Your task is to provide an answer to that question. Try to only include the answer. Do not put it in a sentence.
Q: what movies are about pop art?
A: | The Party, Barbarella, Pierrot le Fou, Head, Our Man Flint, The Young Girls of Rochefort, Modesty Blaise, Chelsea Girls | 4 | NIv2 | task615_moviesqa_answer_generation | zs_opt | [
-0.9753646850585938,
0.6911199688911438,
-0.24180394411087036,
0.5224536061286926,
-0.7803226113319397,
0.9341627359390259,
0.3839590549468994,
-0.35888105630874634,
0.15808847546577454,
-0.5800270438194275,
0.08149982988834381,
-0.07342483103275299,
-0.1724601686000824,
-0.001910706749185... |
Detailed Instructions: In this task, you will be given a set of steps that are required to answer a specific question. Your job is to generate that question. Each given step refers to either an entity (known or unknown), a propery of an entity or a query operation (count, group, union, etc.) Knowing those operations an... | For each bed type, find the average room price. | 4 | NIv2 | task184_break_generate_question | fs_opt | [
0.8142622113227844,
0.07693953812122345,
-0.7772946953773499,
0.29994314908981323,
0.15492749214172363,
-0.4731232821941376,
0.797661304473877,
0.4083036184310913,
-0.5230015516281128,
0.5164457559585571,
-0.30768316984176636,
0.5971219539642334,
-0.14703720808029175,
0.1837698519229889,
... |
Q: In this task, you are given a sentence in Persian, and your task is to translate it into English.
آن حالت متانت و وقاری که من در آن حالت این بوسهها را تحمل میکردم
A: | and the gravity and quiescence with which I underwent it, | 7 | NIv2 | task660_mizan_fa_en_translation | zs_opt | [
0.6079672574996948,
0.8682922124862671,
-0.13291162252426147,
-0.33867231011390686,
-0.6268734931945801,
-0.39086687564849854,
0.5561939477920532,
-0.01605135202407837,
1.09381103515625,
-0.45620280504226685,
-0.03304098919034004,
1.08391535282135,
0.16038763523101807,
0.3919365108013153,
... |
This task is about creating an unanswerable question based on a given passage. Construct a question that looks relevant to the given context but is unanswerable. Following are a few suggestions about how to create unanswerable questions:
(i) create questions which require satisfying a constraint that is not mentioned i... | In what year was the Student Committee for Admission of Negroes established? | 4 | NIv2 | task348_squad2.0_unanswerable_question_generation | zs_opt | [
0.11097374558448792,
-0.02902773953974247,
-0.22858993709087372,
-0.07616761326789856,
0.18189358711242676,
0.5730377435684204,
0.30597248673439026,
0.994563102722168,
0.6786630153656006,
0.5324894189834595,
0.4115656912326813,
-0.1654999554157257,
-0.10398843139410019,
-0.0246122442185878... |
Teacher:You are given a passage. You need to construct a question about the information present in the passage. Construct a question in such a way that (i) it is unambiguous, (ii) its answer is the whole paragraph. Avoid creating questions that can be answered correctly without actually understanding the paragraph.
Tea... | Is it possible to verify a russian passport with the passport number if i'm in canada? | 6 | NIv2 | task1594_yahoo_answers_topics_question_generation | zs_opt | [
0.6819244027137756,
0.37103742361068726,
0.11403834074735641,
-0.7080326080322266,
-0.25224757194519043,
-0.12374665588140488,
1.4503787755966187,
0.4816489815711975,
-0.06225544214248657,
0.24176183342933655,
-0.38407957553863525,
-0.23679682612419128,
-0.8717716336250305,
0.0056221187114... |
You are given a passage. You need to construct a question about the information present in the passage. Construct a question in such a way that (i) it is unambiguous, (ii) its answer is the whole paragraph. Avoid creating questions that can be answered correctly without actually understanding the paragraph.
On Everest... | What are the steps required to edit, publish and distribute a book?
| 0 | NIv2 | task1594_yahoo_answers_topics_question_generation | fs_opt | [
0.3901559114456177,
0.13539204001426697,
0.12895125150680542,
0.3259912431240082,
0.255681574344635,
-0.2812035381793976,
0.9404886960983276,
-0.3027559518814087,
0.21952471137046814,
-0.3488278388977051,
-0.5599031448364258,
0.35723036527633667,
-1.2937272787094116,
-0.025852102786302567,... |
Teacher: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 provides additiona... | strengthener | 6 | NIv2 | task936_defeasible_nli_snli_classification | zs_opt | [
0.07639598846435547,
-0.028947604820132256,
-0.26203322410583496,
-0.09216796606779099,
-0.17038094997406006,
-1.0281414985656738,
0.7745734453201294,
1.4331791400909424,
0.7566843032836914,
-0.35125404596328735,
-0.7505083084106445,
0.06633520126342773,
-0.32844632863998413,
-0.1697686612... |
Instructions: In this task, you need to reverse the order of words in the given sentence.
Input: Sentence: a black bear calmly swimming in the water
Output: | water the in swimming calmly bear black a | 3 | NIv2 | task376_reverse_order_of_words | zs_opt | [
0.35097208619117737,
1.3387911319732666,
-1.3875621557235718,
-0.5430796146392822,
-0.6259350776672363,
0.10473541915416718,
-0.14987300336360931,
-0.16080394387245178,
0.31903791427612305,
0.19707752764225006,
-0.13135603070259094,
0.03406214341521263,
-0.6103827953338623,
-0.636367738246... |
Detailed Instructions: 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".
See one example below:
Problem: Japanese: 詳細は昨日UTC17時30分、英国議会でイギリスのルス・ケリー運輸大臣によって伝えられた。
L... | Yes | 4 | NIv2 | task1126_alt_ja_lo_answer_generation | fs_opt | [
-0.7179691791534424,
-0.14863279461860657,
-0.3954465985298157,
0.15503829717636108,
-0.14973638951778412,
-0.40412193536758423,
0.3522549271583557,
0.6155478954315186,
-0.4588692784309387,
-0.07821078598499298,
0.22404882311820984,
0.8221275210380554,
-0.26882922649383545,
0.8815830349922... |
You will be given a definition of a task first, then some input of the task.
In this task, you will be presented with an English sentence, and you have to translate it into Arabic.
Sam, if I get too close to --
Output: | سام , اذا قمت بالاقتراب كثيرا من | 1 | NIv2 | task651_opus100_en_ar_translation | zs_opt | [
-0.18669652938842773,
0.16723522543907166,
0.3684939444065094,
-0.6946647763252258,
-0.36604511737823486,
-0.19764533638954163,
0.34976524114608765,
0.23517611622810364,
-0.21826651692390442,
0.7884887456893921,
-0.18266327679157257,
0.5186000466346741,
-0.5016664266586304,
-0.461154460906... |
Teacher:In this task, you are given a context and four options. Each option is a suggested ending for the context. You should read the context and pick the best ending for the context. Please answer with "A", "B", "C", and "D".
Teacher: Now, understand the problem? Solve this instance: [header] How to weld underwater ... | C | 6 | NIv2 | task1389_hellaswag_completion | zs_opt | [
-0.15388652682304382,
0.3234195113182068,
-1.2496908903121948,
-0.5465509295463562,
0.39372438192367554,
-0.8272655010223389,
0.8474162817001343,
0.944510281085968,
0.28696775436401367,
0.28314268589019775,
0.76982581615448,
0.48819413781166077,
0.26480385661125183,
0.152328759431839,
-0... |
In this task, you are presented with a term, a question, and a yes/no answer. For context, the term is associated with a short description. Write the simple facts one needs to know in order to answer the given question. The facts should be easily found on the web (e.g. mentioned in a Wikipedia page)
Example Input: Ter... | Fact1: The Spanish-American War lasted from April 21, 1898 to August 13, 1898. Fact2: William McKinley was President of the United States from March 4, 1897 to September 14, 1901. Fact3: William McKinley died from gun related injuries after an assassination attempt. Fact4: Abraham Lincoln died shortly after being shot ... | 3 | NIv2 | task169_strategyqa_sentence_generation | fs_opt | [
0.7215620875358582,
0.2195223867893219,
-0.20889125764369965,
0.04521922767162323,
-0.170008584856987,
-1.2608082294464111,
0.214647114276886,
0.8884650468826294,
-0.21272732317447662,
0.6353780627250671,
-0.48608648777008057,
-0.028292972594499588,
-0.3110871911048889,
-0.4742886126041412... |
You are shown a conversation between a user and system. Identify who has spoken the indicated sentence based on the conversation.
Sentence1: Are there any places in the south section of town the has to do with multiple sports? Sentence2: Do you have in attractions in a type of park in the south? Sentence3: Okay. Have ... | Answer: (B) System | 0 | NIv2 | task638_multi_woz_classification | zs_opt | [
0.07751793414354324,
0.6240451335906982,
-0.9284963607788086,
-0.670026421546936,
-0.12268178164958954,
-0.9096192121505737,
0.2854611873626709,
0.7322158217430115,
0.21636857092380524,
-0.41213324666023254,
-0.6736952066421509,
-0.1732625663280487,
0.05278060585260391,
-0.3512459695339203... |
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to choose whether the two sentences clearly agree (entailment)/disagree (contradiction) with each other, or if this cannot be determined (neutral). Your answer must be in the form of the numbers 0 (entailment), 1 (neutral), or 2(cont... | 2 | 0 | NIv2 | task1612_sick_label_classification | zs_opt | [
-0.7109867334365845,
0.6757116913795471,
0.7375078201293945,
-0.7056550979614258,
0.2519514560699463,
-0.6124677062034607,
0.6489764451980591,
0.12019877135753632,
0.37298858165740967,
-0.13132509589195251,
-0.8003908395767212,
-0.42663514614105225,
-0.3306463956832886,
-0.2228787541389465... |
Detailed Instructions: In this task you will be given a list of numbers. You should remove any number that is not an integer (whole number). If every number is not an whole number then an empty list ("[]") should be returned. Otherwise, answer with the list of whole numbers separated by comma inside brackets.
Q: [-30.4... | [-99, -86, 13] | 9 | NIv2 | task367_synthetic_remove_floats | zs_opt | [
-0.3802911937236786,
0.4853717088699341,
-0.2997438311576843,
-0.9636252522468567,
-0.04300263524055481,
-0.6608675718307495,
1.1070445775985718,
-0.0713481456041336,
-0.15564848482608795,
0.40413570404052734,
-0.5269888639450073,
0.655937910079956,
0.05515437573194504,
0.08979343622922897... |
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 event. You... | Yes | 3 | NIv2 | task1203_atomic_classification_xreact | zs_opt | [
0.028610944747924805,
0.15527167916297913,
0.547272264957428,
-0.37279561161994934,
-0.3231457471847534,
-1.3829345703125,
1.235475778579712,
0.28181755542755127,
-0.2772054374217987,
-0.8082605600357056,
-0.3893943428993225,
-0.27226153016090393,
-0.7934869527816772,
0.40968456864356995,
... |
instruction:
You are given a sentence in Persian. Your job is to translate the Farsi sentence into Galician.
question:
یکی از دوستانم این رو اینطوری توصیف میکنه که که فکر میکنم یک تعریف بسیار عالی هست
answer:
Un amigo meu describiuno como estar na propia verdade dun, e paréceme un xeito moi fermoso de dicilo.
questio... | Eu reúno, en certa medida, esas condicións a partir da miña doenza cando era cativa.
| 9 | NIv2 | task1270_ted_translation_fa_gl | fs_opt | [
-0.6880766749382019,
0.7650827169418335,
0.0645008534193039,
-0.725737452507019,
-0.7515610456466675,
-0.4691419005393982,
1.0775277614593506,
0.4766196608543396,
0.312036395072937,
-0.45339176058769226,
-0.6911654472351074,
0.7784442901611328,
-0.9082441329956055,
0.6878113746643066,
0.... |
In this task, you are given a sentence from the research paper and your task is to classify the given sentence into the following categories: Background (Why is this problem important? What relevant works have been created before? What is still missing in the previous works? What are the high-level research questions? ... | purpose
| 6 | NIv2 | task1163_coda19_section_classification | fs_opt | [
0.28485679626464844,
-0.35943716764450073,
-0.2029028832912445,
-0.37470221519470215,
0.5220620632171631,
0.06887917220592499,
0.7723004817962646,
0.9922943115234375,
-0.08132533729076385,
0.13572490215301514,
-0.3717808127403259,
0.5948612689971924,
-0.11583662778139114,
0.312047958374023... |
Q: This task is to translate a news commentary given in Italian language into Zhuang 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.
Una seconda ragione è il fatto che l’Onu ha inserito l’eli... | 第二个原因是联合国将根除长期贫困列入了其可持续发展目标。这意味着我们决定将贫困线画在哪里可能不但会影响世界银行的使命，也会影响联合国及世界全体国家的发展日程。显然，在我们计算数字时，肩负着特殊的艰巨任务。 | 7 | NIv2 | task1376_newscomm_translation | zs_opt | [
-0.5950772762298584,
0.7834600210189819,
-0.49265867471694946,
-0.2950800061225891,
-0.08824638277292252,
-0.7245663404464722,
0.2924692928791046,
0.4622846841812134,
-0.12653106451034546,
0.2378358393907547,
-0.49000534415245056,
0.4430065155029297,
-0.1909291297197342,
0.0265653431415557... |
Definition: You are given a sentence in Galician. Your job is to translate the Galician sentence into Spanish.
Input: Tede en conta que levamos dado 230 premios.
Output: | Recuerden, hemos dado 230 premios. | 2 | NIv2 | task1240_ted_translation_gl_es | zs_opt | [
-0.9232301712036133,
0.7744813561439514,
-0.169653058052063,
-1.0507878065109253,
-0.5181875824928284,
-1.1465065479278564,
0.3662509620189667,
0.5993283987045288,
-0.2285640984773636,
-0.5357911586761475,
-0.626404345035553,
0.41159284114837646,
-1.0377545356750488,
0.4948926568031311,
... |
You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into English.
Q: Também podemos ver nesta filmagem dois elementos importantes.
A: | In this clip you can see two other important elements. | 4 | NIv2 | task1274_ted_translation_pt_en | zs_opt | [
0.013667885214090347,
1.2219468355178833,
-0.20487618446350098,
0.05624030530452728,
-0.4879322648048401,
0.21328942477703094,
-0.03611469268798828,
1.316561222076416,
0.25845420360565186,
0.07622544467449188,
0.056869424879550934,
-1.099161982536316,
0.08734487742185593,
0.729325771331787... |
In this task, you will be presented with a passage and have to answer a question based on your understanding of the events inferred from the passage. Among the entities, try to find the best entity that is most likely to fill in "_" and classify the answers based on options.
Q: Washington (CNN) -- Just two months afte... | (A)
****
| 4 | NIv2 | task302_record_classification | fs_opt | [
-0.23671270906925201,
-0.07757347822189331,
-0.5543317794799805,
-0.06868845224380493,
0.6584690809249878,
-0.09142467379570007,
0.6477857828140259,
1.0544685125350952,
-0.23639358580112457,
0.16923129558563232,
-0.19101575016975403,
0.8497682809829712,
-0.6956902146339417,
0.6293157339096... |
In this task, you will be given sentences in which your task is to recognize the name of the drug or medicine. Drugs are substances that change a person's mental or physical state. They can affect how your brain works, how you feel and behave, your understanding, and your senses. Although there might be several correct... | tamoxifen | 8 | NIv2 | task1447_drug_extraction_ade | fs_opt | [
0.6657457947731018,
0.37148067355155945,
-0.20408207178115845,
-0.7763887643814087,
-0.3525465130805969,
-1.336004376411438,
0.896011233329773,
0.5499931573867798,
0.9316768646240234,
-0.5085358619689941,
-0.9544519782066345,
-0.2772808372974396,
-0.8092848062515259,
-0.15622714161872864,
... |
Given the task definition and input, reply with output. In this task, you are given one english sentence. The major part of the sentences talk about health-related topics, but some of the them describe an organization and its activities. Your job is to translate the given sentences into German.
A general risk assessme... | Es wurde eine allgemeine Risikobewertung für vektorübertragene Krankheiten in Europa durchgeführt, deren Ergebnisse demnächst veröffentlicht werden. | 5 | NIv2 | task1396_europa_ecdc_tm_en_de_translation | zs_opt | [
-0.10695208609104156,
0.7844635248184204,
0.16222801804542542,
-0.1698024868965149,
-0.16165047883987427,
0.23622018098831177,
0.3138619363307953,
0.4800226092338562,
0.2196573168039322,
-0.2626471519470215,
0.17516419291496277,
0.9319788217544556,
-0.39786529541015625,
-0.0226666405797004... |
This task involves annotating the answer type to a given question that involve some kind of complex reasoning (including numerical reasoning). Note that the questions require looking at more than one part of the passage to answer. There are 3 possible answer types (i) spans, (ii) numbers and (iii) dates. If the answer ... | span
| 5 | NIv2 | task027_drop_answer_type_generation | fs_opt | [
0.6878666877746582,
0.2680162787437439,
-0.8140168190002441,
0.17328794300556183,
0.26009565591812134,
0.06981038302183151,
1.0282418727874756,
0.6095457077026367,
-0.23786669969558716,
-0.04531990736722946,
-0.13855679333209991,
0.8202266693115234,
-0.8432111740112305,
0.0737825483083725,... |
In this task, you are given a question. You have to answer the question based on your information.
[EX Q]: Yeo Jin-goo was in what movie that had a toal of 1,066,765 admissions across South Korea?
[EX A]: Sad Movie
[EX Q]: How many people are employed by the laboratory across from McKenzie, Maryland?
[EX A]: some 1,0... | the San Francisco 49ers
| 6 | NIv2 | task1293_kilt_tasks_hotpotqa_question_answering | fs_opt | [
-0.6546800136566162,
-0.1512373983860016,
-0.2232055962085724,
-0.20658951997756958,
0.16288350522518158,
-0.08639603853225708,
0.029911139979958534,
-0.39974477887153625,
-0.3028671145439148,
-0.012846192345023155,
-0.1235746443271637,
-0.92116779088974,
-0.06372158974409103,
0.1691114604... |
From the given sentence, extract the phrase (often noun or verb) that carries the given relationship. The generated phrase should be present in the sentence.
Ex Input:
Given Relationship: 'be language of', Sentence: 'In the Greek New Testament , the Greek language is not as much influenced by figures of speech as the ... | Presented
| 1 | NIv2 | task678_ollie_actual_relationship_answer_generation | fs_opt | [
-0.02874448522925377,
0.3206077814102173,
-0.06548360735177994,
-0.26693078875541687,
0.09660645574331284,
-1.0002541542053223,
0.5753632187843323,
0.46120452880859375,
0.08092745393514633,
0.21218156814575195,
0.18270443379878998,
0.4181152582168579,
-1.1378101110458374,
0.048377826809883... |
A text is given in Bengali. Translate it from the Bengali language to the Panjabi language. The translation must not omit or add information to the original sentence.
ਗਰੀਬਾਂ ਨੂੰ ਸਸਤੀ ਦਵਾਈ ਲਈ ਭਾਰਤੀ ਜਨ ਔਸ਼ਧੀ ਪ੍ਰਾਜੈਕਟ ਸ਼ੁਰੂ ਕੀਤਾ ਗਿਆ ਹੈ। 500 ਤੋਂ ਜ਼ਿਆਦਾ ਦਵਾਈਆਂ ਨੂੰ ਘੱਟ ਕਰਕੇ ਉਨ੍ਹਾਂ ਨੂੰ essential ਦਵਾਈਆਂ ਦੀ ਲਿਸਟ ਵਿੱਚ ਰੱਖਿਆ ਗਿਆ... | সম্প্রতি, ডিজিটাল ক্যান্সার নার্ভ সেন্টার-ও কাজ শুরু করে দিয়েছে। | 0 | NIv2 | task1026_pib_translation_punjabi_bengali | zs_opt | [
-0.33226585388183594,
0.7208185195922852,
0.10752184689044952,
-0.2874634861946106,
-0.4722769856452942,
-0.5723204016685486,
1.1244972944259644,
0.333646297454834,
0.11527042835950851,
-0.36216217279434204,
-1.5380427837371826,
-0.15133580565452576,
-0.0780290812253952,
0.2105957716703415... |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Galician.
One example: Tra di esse, si annovera il piccolo sistema in arabo detto al-jebr.
Solution is here: Isto inclúe un sistema en árabe chamado al-jebra.
Explanation: The Italian sentence is correctly translated into Galician, ... | A primeira cousa evidente era que estaba perfectamente corda e lúcida e que era intelixente, pero estaba moi asustada e perplexa, porque estivera a ver cousas. | 6 | NIv2 | task1252_ted_translation_it_gl | fs_opt | [
-0.03806362301111221,
1.215397834777832,
-0.11470302939414978,
-0.1322537511587143,
-0.2925882339477539,
-1.192652940750122,
0.7506427764892578,
0.3988674581050873,
-1.0270771980285645,
-0.007776491343975067,
-0.49645477533340454,
-0.24414855241775513,
-0.9978632926940918,
0.34328857064247... |
You will be given a definition of a task first, then some input of the task.
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.
total of all entries must not exceed % d
Output: | the sum of the items must not exceed % d | 1 | NIv2 | task177_para-nmt_paraphrasing | zs_opt | [
-0.36687445640563965,
0.8447989225387573,
-0.15672853589057922,
-0.10049927234649658,
-0.14627009630203247,
0.38767069578170776,
0.7433900833129883,
0.6399050951004028,
-0.18361970782279968,
-0.06345207989215851,
-1.177621603012085,
-0.5434188842773438,
-0.13938522338867188,
-0.18460007011... |
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".
Tweet: @justineungaro - You and me both! She is one big FML, I say.... | yes | 0 | NIv2 | task196_sentiment140_answer_generation | zs_opt | [
-1.1397128105163574,
-0.505691647529602,
-0.22162802517414093,
0.0688982829451561,
-0.054204583168029785,
-1.1072345972061157,
0.3694673180580139,
-0.2530958354473114,
0.15488287806510925,
0.2709646224975586,
0.01163011696189642,
-0.6716829538345337,
-0.1084851622581482,
-0.286876559257507... |
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