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 |
|---|---|---|---|---|---|---|
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.
Input: Consider Input: Question: When administering oxygen therapy to a patient admitted to the eme... | Output: chemistry
| 2 | NIv2 | task1434_head_qa_classification | fs_opt | [
-0.18171179294586182,
-0.1529940664768219,
-0.2601992189884186,
-0.40168681740760803,
0.14358632266521454,
-0.37927788496017456,
0.1489819437265396,
1.1594529151916504,
0.02599167264997959,
0.35688403248786926,
-0.8559802174568176,
-0.6932628750801086,
0.33009016513824463,
-0.0474113225936... |
Given the task definition, example input & output, solve the new input case.
In this task you will be given a list of integers. You should round each integer to the nearest tens place. That means you should round the number to the nearest multiple of 10.
Example: [-83, 53, -48, 8]
Output: [-80, 50, -50, 10]
The output ... | [510, 140, 290, -720, -250, -530, 480] | 1 | NIv2 | task373_synthetic_round_tens_place | fs_opt | [
-0.3942500352859497,
0.5186704397201538,
-0.4756176471710205,
0.1473027765750885,
0.30342745780944824,
-0.1096508651971817,
0.44420862197875977,
0.7212376594543457,
-0.09008203446865082,
0.3573869466781616,
-0.24607187509536743,
-0.32136720418930054,
-0.11943279206752777,
0.188164219260215... |
Generate an overlapping word between the given two sentences. When you find the overlapping words, they don't have to match exactly, e.g., "survival" and "survive" are valid overlapping words. Little words like "the" or "of" don't count! You must generate significant words which are not the stop words.
--------
Questio... | cause
| 7 | NIv2 | task039_qasc_find_overlapping_words | fs_opt | [
-0.06407828629016876,
0.8086497783660889,
0.34862077236175537,
-0.69859778881073,
0.39240556955337524,
-0.8892210721969604,
0.8808974027633667,
0.8067420125007629,
0.47194865345954895,
-0.25632989406585693,
-0.37044602632522583,
-0.24173212051391602,
-1.0003728866577148,
0.2177525162696838... |
Instructions: Given a trivia question, classify broad topical category from this list: 'theater', 'geology', 'book', 'tv', 'astronomy', 'aviation', 'military', 'government', 'boxing', 'projects', 'metropolitan_transit', 'law', 'venture_capital', 'broadcast', 'biology', 'people', 'influence', 'baseball', 'spaceflight', ... | user | 3 | NIv2 | task900_freebase_qa_category_classification | zs_opt | [
-0.1301523894071579,
0.32719454169273376,
-0.14679807424545288,
-0.014965216629207134,
0.2198317050933838,
-0.21581435203552246,
0.1607285439968109,
0.5919228792190552,
-0.36028438806533813,
-0.012309659272432327,
-0.04436613246798515,
-0.26624009013175964,
-0.01804688572883606,
-0.4756576... |
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: I bought it for my Android phone, and it never con... | True | 0 | NIv2 | task1309_amazonreview_summary_classification | zs_opt | [
-0.583523154258728,
0.06374678015708923,
0.17724429070949554,
-0.9108469486236572,
0.0340912900865078,
-0.09920045733451843,
0.8965145349502563,
0.40965837240219116,
-0.44830501079559326,
0.7572015523910522,
-0.39253008365631104,
-0.6692409515380859,
-0.40968644618988037,
-0.06941635161638... |
Teacher: Given a phrase describing the relationship between two words, extract the words and the lexical relationship between them. The relation has to be of the type 'MemberOf', 'MadeOf', 'Synonym', 'Entails', 'HasA', 'HasProperty', 'PartOf', 'Antonym' or 'IsA'. The output should have the format: word1 relation word2.... | aid Synonym help | 2 | NIv2 | task1510_evalution_relation_extraction | fs_opt | [
0.8056195974349976,
0.8020375967025757,
0.25291138887405396,
-0.4617077112197876,
-0.15511265397071838,
-0.8729962110519409,
0.3686440587043762,
0.6028532385826111,
0.3692993223667145,
-0.37127235531806946,
-0.4892579913139343,
0.08835861086845398,
-0.6400152444839478,
-0.12652146816253662... |
Teacher:You are given a sentence in Persian. Your job is to translate the Farsi sentence into Portugese.
Teacher: Now, understand the problem? Solve this instance: مثل یک کودک نوپای مست می مانید.
Student: | É como se fôssemos um bebé bêbedo. | 6 | NIv2 | task1273_ted_translation_fa_pt | zs_opt | [
-0.7659906148910522,
0.5974990725517273,
-0.3120778203010559,
-0.7591527700424194,
-0.8621425628662109,
0.4247128963470459,
0.8641526699066162,
0.7305961847305298,
0.7985433340072632,
-0.49887800216674805,
-0.23530760407447815,
0.2227332890033722,
-0.471870481967926,
0.021677697077393532,
... |
The input is a sentence. The sentence includes an emotion. The goal of the task is to classify the emotion in the sentence to one of the classes: 'fear', 'joy', 'anger', 'sadness'. The emotion mainly depends on the adverb within the sentence.
Q: My mother found herself in an annoying situation.
A: anger
****
Q: Roger... | anger
****
| 4 | NIv2 | task1338_peixian_equity_evaluation_corpus_sentiment_classifier | fs_opt | [
-0.6139198541641235,
0.13961803913116455,
0.4250968098640442,
-1.0264973640441895,
-0.2840587794780731,
0.12987399101257324,
0.8210340738296509,
0.5961934328079224,
0.3203343152999878,
-0.19906720519065857,
-0.48531800508499146,
-0.6340319514274597,
-0.5972023010253906,
-0.0657483562827110... |
Teacher:In this task you will be given a list of numbers and you need to find the mean (average) of that list. The mean of a list can be found by summing every number in the list then dividing the result by the size of that list. The output should be rounded to 3 decimal places.
Teacher: Now, understand the problem? So... | 23.829 | 6 | NIv2 | task094_conala_calculate_mean | zs_opt | [
-0.608301043510437,
-0.06741951406002045,
-0.9583005905151367,
-1.373846173286438,
0.2642916738986969,
0.12888893485069275,
0.2550944983959198,
0.37242838740348816,
-0.46056824922561646,
-0.0773899257183075,
-0.9951367378234863,
0.41367021203041077,
-1.1620464324951172,
0.00116866989992558... |
In this task, you're given a passage, further information available on a particular linked term from the statement, and an answer term. Your job is to generate a question that can use the information provided to obtain the given answer. You should use the information on both passage and link information to create the q... | How old were the two students who committed suicide in July of 1994?
| 0 | NIv2 | task236_iirc_question_from_passage_answer_generation | fs_opt | [
0.39688605070114136,
0.04732218384742737,
-1.1057766675949097,
-0.01570240966975689,
0.38222286105155945,
0.16870048642158508,
1.2754607200622559,
0.791890025138855,
-0.12872314453125,
0.3861756920814514,
0.20542314648628235,
0.6316496729850769,
-0.0799676775932312,
0.511814534664154,
0.... |
Two analogies that signify affordances are given in the form "A : B. C : ?". Affordance is the possibility of an action being done on an object, for example book is an affordance of writing. The phrase "A : B" implies that B is an affordance of A. Your task is to replace the question mark (?) with the appropriate affor... | employee
| 0 | NIv2 | task1153_bard_analogical_reasoning_affordance | fs_opt | [
0.20814025402069092,
1.1604909896850586,
-0.19634650647640228,
0.34916192293167114,
-0.3267776370048523,
-0.03316345065832138,
1.067358374595642,
0.8298879861831665,
0.05131811648607254,
-0.29966527223587036,
-0.6175826191902161,
0.057708725333213806,
-0.2946033477783203,
-0.20094151794910... |
Q: You are given a question or fill-in-the-blank question, two answer options (Option1 and Option2) and an Explanation. Your task is to find the correct answer (return the string of the correct option, not option1/2) for the given question from the given options and using explanation.
Question: The electrons with the _... | most | 7 | NIv2 | task178_quartz_question_answering | zs_opt | [
-0.2403116673231125,
0.5603047609329224,
0.138473242521286,
-0.19646012783050537,
-0.6691305637359619,
-1.3533196449279785,
0.7225663661956787,
0.4297622740268707,
0.5462281107902527,
0.04354088008403778,
-0.01573731005191803,
0.013737108558416367,
-0.5852171182632446,
-0.08790919184684753... |
Instructions: In this task, you have given an input which is agent's reply, based on that you have to identify what will be users' command for that reply. The user generally asks a question related to event scheduling or information of the scheduled events. Agent reply based on the available information or do the task ... | What time? | 3 | NIv2 | task1600_smcalflow_sentence_generation | zs_opt | [
-0.17230020463466644,
-0.05373939871788025,
-0.26916152238845825,
0.05638813227415085,
-0.4775027632713318,
-0.7856874465942383,
0.4787115156650543,
-0.12166588008403778,
0.5693068504333496,
-0.09619210660457611,
-0.014089956879615784,
-0.28053054213523865,
-0.9447433948516846,
0.378537416... |
TASK DEFINITION: In this task, you will be given a food review in Persian. You have to Classify the sentiment of the reviewer toward the food into: "negative", "neutral", "positive", and "mixed". The mixed category indicates reviews where none of the sentiments are dominant (mix of positive and negative, or borderline ... | very negative
| 8 | NIv2 | task527_parsinlu_food_overal_classification | fs_opt | [
-0.7390873432159424,
0.21987518668174744,
0.3838110864162445,
-0.3447731137275696,
-0.037399619817733765,
0.37352824211120605,
1.2642097473144531,
0.3948745131492615,
0.42597609758377075,
-0.060950275510549545,
-0.10894424468278885,
0.23939436674118042,
-0.3826357126235962,
0.3457281291484... |
Part 1. Definition
In this task, you are given two sentences in Persian separated with <sep>, and you have to determine whether the sentences are paraphrases or not. Classify your answers into "paraphrase" and "not-paraphrase".
Part 2. Example
اگر Apple ID و ایمیل خود را فراموش کرده ام چه کاری می توانم انجام دهم؟ <sep>... | paraphrase | 7 | NIv2 | task465_parsinlu_qqp_classification | fs_opt | [
-0.8735509514808655,
0.7835661172866821,
-0.029746413230895996,
-0.38465654850006104,
-0.9109484553337097,
0.11459311097860336,
2.055474281311035,
0.8208286762237549,
0.5646713376045227,
-0.44660091400146484,
-0.2879905104637146,
-0.3443811237812042,
-0.5944613814353943,
-0.010606976225972... |
Detailed Instructions: A text is given in Bengali. Translate it from the Bengali language to the Marathi language. The translation must not omit or add information to the original sentence.
See one example below:
Problem: স্তন্যপান সম্পর্কে অভিভাবকদের সচেতন ও উৎসাহদানে গুরুত্ব বিশ্ব স্তন্যপান সপ্তাহ পয়লা থেকে ৭ই আগস্ট... | आज इथे जमलेले 60 हून अधिक देशांचे सात हजारपेक्षा जास्त प्रतिनिधी ह्याच सामाईक इच्छेची परिणती आहे. | 4 | NIv2 | task1061_pib_translation_bengali_marathi | fs_opt | [
-0.10847393423318863,
0.14010483026504517,
-0.561516523361206,
0.4645973742008209,
-0.8499945402145386,
-1.0999292135238647,
0.3655562102794647,
0.1305452436208725,
0.2969447672367096,
-0.07920526713132858,
-0.7454771995544434,
0.16204532980918884,
-0.6004257798194885,
0.27768194675445557,... |
You're given a sentence and your task is to classify whether the sentence is acceptable or not. Any sentence which is grammatically correct, has a naturalistic text, is written by a native speaker and which minimizes superfluous content is acceptable, otherwise unacceptable. If the sentence is acceptable then write "ac... | acceptable | 0 | NIv2 | task616_cola_classification | zs_opt | [
-1.0777368545532227,
0.5468577742576599,
0.8635239601135254,
-0.42063552141189575,
-0.18662118911743164,
-0.4418942928314209,
0.227707177400589,
0.3553711771965027,
0.10730995237827301,
-0.13886365294456482,
-0.9976992011070251,
-0.16999664902687073,
-0.24218595027923584,
-0.30112525820732... |
Given a sentence in the Japanese and Central Khmer language. Your task is check if the Khamer sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Example: 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。
Khamer: បណ្តាអ្នកនយោបាយនៅចក្រភពអង់... | Solution: Yes | 5 | NIv2 | task1123_alt_ja_khm_answer_generation | fs_opt | [
-0.4299873113632202,
-0.37251055240631104,
-0.048871446400880814,
0.015853239223361015,
0.1344277411699295,
-0.599915623664856,
0.15959836542606354,
-0.043948665261268616,
-0.42872193455696106,
-0.3615601658821106,
0.20717722177505493,
0.8166724443435669,
-0.3044540286064148,
0.60983729362... |
Instructions: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Input: Review: This was a truly bad film. The charact... | yes | 3 | NIv2 | task285_imdb_answer_generation | zs_opt | [
-1.276662826538086,
0.40939152240753174,
0.5297551155090332,
-0.17213431000709534,
0.37098777294158936,
-0.44112831354141235,
0.3751639425754547,
0.8699765205383301,
0.3395461440086365,
0.20156076550483704,
-0.0701502114534378,
-0.35400158166885376,
0.046357303857803345,
-0.295736551284790... |
You will be given a definition of a task first, then some input of the task.
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 an... | Answer: 1932 | 1 | NIv2 | task237_iirc_answer_from_subtext_answer_generation | zs_opt | [
-0.12822513282299042,
0.14821267127990723,
-0.3553563356399536,
0.054319776594638824,
-0.02510801889002323,
0.008636295795440674,
1.1808983087539673,
1.0530544519424438,
-0.17436271905899048,
-0.20751939713954926,
-0.3908268213272095,
-0.29127272963523865,
-0.28833553194999695,
-0.37116539... |
Detailed Instructions: You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Hebrew.
Problem:Hace pocas semanas empacamos el SkySat 1, pusimos nuestras firmas en él y le despedimos por última vez en la Tierra.
Solution: | לפני מספר שבועות, ארזנו את הלוויין SkySat 1, חתמנו את שמותינו עליו ונפרדנו ממנו לשלום לפני שיעזוב את כדור הארץ. | 8 | NIv2 | task1229_ted_translation_es_he | zs_opt | [
-0.278725266456604,
1.6355199813842773,
-0.14683844149112701,
-0.8187925815582275,
-0.04983493685722351,
-0.891335129737854,
-0.0929749608039856,
0.5839841365814209,
0.6924905776977539,
0.314535915851593,
0.24548131227493286,
0.34546905755996704,
-0.1308971792459488,
-0.07240679115056992,
... |
In this task, you are given a sentence in the English language and your task is to convert it into the Japanese language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
One example: Italy have defeated Portugal 31-5 in Pool C of the 2007 Rugby... | 訴訟の原告には、キリスト教やヒンズー教から改宗した人もいた。 | 6 | NIv2 | task435_alt_en_ja_translation | fs_opt | [
0.04339525103569031,
0.8192577362060547,
-0.1916092485189438,
0.17743457853794098,
-0.13756811618804932,
-0.24099713563919067,
0.43274080753326416,
0.5153884887695312,
0.15783751010894775,
-0.6736823320388794,
-0.5268316268920898,
0.520526111125946,
-0.5055357217788696,
0.37496045231819153... |
Given the task definition and input, reply with output. 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 label... | No emotion,No emotion,No emotion,No emotion,happiness,No emotion,No emotion,No emotion,No emotion,happiness | 5 | NIv2 | task1532_daily_dialog_emotion_classification | zs_opt | [
-0.09730938076972961,
0.12645205855369568,
0.009086491540074348,
-0.34670236706733704,
-0.17778071761131287,
0.09262790530920029,
0.7462455630302429,
0.03971659392118454,
0.00605625519528985,
-0.36967217922210693,
-0.6715883016586304,
0.07321637868881226,
-0.744431734085083,
0.694271564483... |
You are given a sentence in Galician. Your job is to translate the Galician sentence into Arabic.
Example: É basicamente un caldeiro que rota.
Example solution: ويوجد أساسا مرجل دوار.
Example explanation: The Galician sentence is correctly translated into Arabic, because the meaning is preserved.
Problem: É coma se os... | Solution: وهي مثل عيونكم تحملق محاولة رؤية نفسها. | 5 | NIv2 | task1241_ted_translation_gl_ar | fs_opt | [
-0.02339477464556694,
0.5611529350280762,
0.053812820464372635,
-0.7047408819198608,
0.04054240509867668,
-0.0868631899356842,
1.046038031578064,
-0.43596774339675903,
0.007878892123699188,
-0.40718021988868713,
-0.7848758697509766,
-0.9161617755889893,
-1.0729737281799316,
0.7667580842971... |
In this task, you will be shown a Persian passage and a question, and you have to determine whether the question is answerable based on the passage or not. If the question is answerable, choose the "True" label, and if not select "False"
Q: نخستین سه تمدن جهان، بر اساس زمان آغاز آنها، بینالنهرین، مصر و هند هستند که به... | True | 4 | NIv2 | task396_persianqa_classification | zs_opt | [
0.15814189612865448,
1.1722602844238281,
-0.004666579887270927,
0.3088915944099426,
-0.08151857554912567,
0.0717436820268631,
0.8467033505439758,
1.151939034461975,
0.18826544284820557,
-0.04447109252214432,
-0.7103828191757202,
1.1054366827011108,
-0.5728327631950378,
-0.22318972647190094... |
In this task you will be given an arithmetic operation and you have to find its answer. The symbols of operators '+' and '-' has been swapped i.e you need to perform subtraction when you see a '+' symbol and addition in case of '-' symbol.
[Q]: 3394 - 2316 - 9713
[A]: 15423
[Q]: 4377 + 5604 - 8336 - 2652
[A]: 9761
... | 9656
| 5 | NIv2 | task085_unnatural_addsub_arithmetic | fs_opt | [
-0.8551477193832397,
0.09746803343296051,
-1.0858802795410156,
0.04381434619426727,
-0.4896446466445923,
0.037587400525808334,
1.041205883026123,
1.5775279998779297,
0.2030395269393921,
-0.2009972333908081,
-0.6982861757278442,
-0.41949087381362915,
-0.29137176275253296,
0.1441258788108825... |
This task is to translate the Telugu Language Input to English Language Output
Q: మాక్స్. వ్యవస్థ ఒత్తిడి (MPa) 18.6
A: | Max. system pressure (MPa) 18.6 | 4 | NIv2 | task1617_cc_alligned_translate_tel_eng | zs_opt | [
0.18057779967784882,
0.6551676392555237,
-0.2643311023712158,
-0.6112053394317627,
-0.04339074343442917,
-1.100914716720581,
0.020462242886424065,
0.5754932165145874,
0.4865846633911133,
-0.3420766294002533,
-0.04665958508849144,
0.04043314605951309,
-0.7501403093338013,
-0.307788968086242... |
Detailed Instructions: You are given a sentence in Persian. Your job is to translate the Farsi sentence into English.
Problem:من عاشق ادبیات انگلیسی بودم ، و وقتی کالج بودم شک داشتم که کدوم را انتخاب کنم ؟ من عاشق ادبیات انگلیسی بودم ، و وقتی کالج بودم شک داشتم که کدوم را انتخاب کنم ؟
Solution: | Well I used to love English literature, and I debated in college, which one should I do? | 8 | NIv2 | task1265_ted_translation_fa_en | zs_opt | [
-0.5471903085708618,
0.6781274676322937,
0.5916293859481812,
-0.324551522731781,
-0.3560011684894562,
-1.2066144943237305,
0.461760014295578,
0.2948867380619049,
0.32087135314941406,
-0.437593013048172,
0.08232694864273071,
-0.3554549217224121,
-0.8438248634338379,
0.47287026047706604,
-... |
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 | 9 | NIv2 | task936_defeasible_nli_snli_classification | zs_opt | [
-0.09376538544893265,
-0.08504770696163177,
-0.710376501083374,
-0.4844589829444885,
0.008744093589484692,
-0.7967031002044678,
0.8019072413444519,
1.2208037376403809,
0.5300029516220093,
-0.023928459733724594,
-0.4709051549434662,
-0.14446499943733215,
-0.7639881372451782,
0.2286963313817... |
You will be given a definition of a task first, then some input of the task.
This task is to identify the language of a sentence correctly by classifying if it is English or Telugu
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Output: | English | 1 | NIv2 | task1618_cc_alligned_classify_tel_eng | zs_opt | [
-0.4608914852142334,
0.3438831567764282,
0.8135330677032471,
-0.27666690945625305,
0.5573915243148804,
-0.3709273338317871,
0.5290406346321106,
0.3525311350822449,
-0.09606143832206726,
0.07865603268146515,
0.0194831695407629,
-0.4940339922904968,
-0.20195774734020233,
-0.01060873456299305... |
Teacher:In this task, you're given the title of a five-sentence story, the first four sentences, and two options for the fifth sentence as a and b. Your job is to pick the sentence option that does not connect with the rest of the story, indicating your choice as 'a' or 'b'. If both sentences are plausible, pick the on... | b | 6 | NIv2 | task214_rocstories_incorrect_ending_classification | zs_opt | [
0.05872277915477753,
-0.24876871705055237,
0.2109536975622177,
-0.0010875947773456573,
0.1263335794210434,
-0.02802293375134468,
0.3362465500831604,
0.9945677518844604,
-0.1722065508365631,
0.6886985301971436,
-0.23755592107772827,
-0.36663538217544556,
0.0428585521876812,
-0.7699378728866... |
Part 1. Definition
In this task, you're given a fill-in-the-blank question that contains two object names. Additionally, you're given one answer which is one of the objects present in the question. In this task, you need to minimally change the given question so that the answer flips to another object in the question. ... | After setting a goal of losing ten pounds, Brenda chose the yogurt instead of the doughnut, because the _ has more calories. | 7 | NIv2 | task034_winogrande_question_modification_object | fs_opt | [
0.8068530559539795,
0.038567833602428436,
0.1306668370962143,
-0.1711082011461258,
0.6607131361961365,
-0.7857694625854492,
0.9121800661087036,
1.0624923706054688,
-0.49463537335395813,
-0.1450989842414856,
-0.4548543095588684,
0.09123094379901886,
-0.3881600499153137,
0.11052196472883224,... |
Detailed Instructions: In this task, you are given an input list A comprising of numbers and alphabets. You need to extract and sort the unique alphabets in the list. The alphabets in the input list will only be in lowercase. Return -1 if there is no alphabet in the input list.
Q: ['9319', '1089', '4199', '9925', '3041... | c, d, j, k, u | 9 | NIv2 | task636_extract_and_sort_unique_alphabets_in_a_list | zs_opt | [
-0.49040237069129944,
0.6683459281921387,
-0.5495812296867371,
-0.7915990352630615,
0.03943900018930435,
0.23591718077659607,
0.9757822751998901,
0.03784388303756714,
-0.6836249828338623,
0.602124810218811,
-0.25517740845680237,
-0.25636494159698486,
0.08422110974788666,
-0.117040030658245... |
In this task, you are given an input list A. You need to find all the elements of the list that are alphabets in the same order as they appear in the list A. Do not change their case/capitalization.
Example Input: ['6119', 'G', '9025', '73', 'o', 'Z', 'n', 'a', '6929', 'w', '2257', '1847', 'P', 'd', 'r', '283', 'u', '... | V, K, t, x, z, p, S, Y, f, B, B, k, D, b, e
| 3 | NIv2 | task488_extract_all_alphabetical_elements_from_list_in_order | fs_opt | [
0.2623351216316223,
0.030462436378002167,
-0.3872092366218567,
-0.09501957148313522,
0.09474768489599228,
-0.66315096616745,
0.7917221188545227,
0.5020687580108643,
-0.2444782704114914,
0.01856071501970291,
-0.6118736267089844,
-0.5494596362113953,
0.14657266438007355,
-0.1384243369102478,... |
Given a command in a limited form of natural language, provide the correct sequence of actions that executes the command to thus navigate an agent in its environment. A command can be broken down into many different actions. Actions are uppercase and are individual steps that serve as the building blocks for a command.... | I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_LOOK I_TURN_RIGHT I_LOOK I_TURN_RIGHT I_LOOK I_TURN_RIGHT I_LOOK ... | 1 | NIv2 | task130_scan_structured_text_generation_command_action_long | fs_opt | [
0.5198281407356262,
0.6044235825538635,
-0.5438701510429382,
0.23130665719509125,
-0.009608167223632336,
-0.18252576887607574,
0.19311833381652832,
0.5137784481048584,
-0.14650201797485352,
-0.0015800576657056808,
-0.803338885307312,
-0.04789148271083832,
-0.5502172112464905,
-0.2875948250... |
Detailed Instructions: Languages typically provide more than one grammatical construction to express certain types of messages. Your task is to generate a senetence with the same meaning as given sentence, but with different grammatical construction.
Q: Maria phoned the man who was from work the greetings
A: | Maria phoned the greetings to the man who was from work | 9 | NIv2 | task132_dais_text_modification | zs_opt | [
-0.4580267071723938,
1.6517436504364014,
-0.11103616654872894,
-0.6316765546798706,
-0.09706095606088638,
-0.5075958371162415,
-0.159627303481102,
0.015079934149980545,
0.5702598094940186,
-0.5895794630050659,
-1.013461947441101,
0.046655796468257904,
0.41346901655197144,
-0.15011662244796... |
Definition: This task is to translate a news commentary given in Arabic language into Czech language. Translate the input statement into the output language while preserving the numberical values, special characters and context of the commentary done.
Input: ليس من المستغرب أن يسارع عدد كبير من هيئات الأمم المتحدة ووك... | Budou-li se Obama, Rudd, Zapatero a další lídři s\xa0myšlením upřeným do budoucna závazky ze summitu G8 nadále zabývat a budou-li trvat na tom, aby pomoc skutečně fungovala, mohou tudíž dokázat velké věci. Je nutné obejít byrokratické aparáty, aby se pomoc dostala tam, kde je jí třeba: na půdu obdělávanou nejchudšími r... | 2 | NIv2 | task1374_newscomm_translation | zs_opt | [
-0.046404458582401276,
-0.054255448281764984,
-0.3553047776222229,
0.19514226913452148,
-0.07119880616664886,
0.615441083908081,
1.3465638160705566,
0.24684900045394897,
0.670650839805603,
-0.7593222856521606,
-0.6118354797363281,
0.25907379388809204,
-0.8176684379577637,
0.302316933870315... |
Given a sentence, fill out the missing word with a 'no' or a number (between zero and ten). You should write the numbers with english alphabet, like: four instead of 4.
Most children stop wetting the bed at night by the time they are ____ or five. | four | 0 | NIv2 | task1359_numer_sense_answer_generation | zs_opt | [
0.05252504348754883,
0.8839752674102783,
-0.44480669498443604,
-1.0440309047698975,
-0.3462466597557068,
-0.3808174729347229,
0.6227149367332458,
0.8081616163253784,
-0.007024334743618965,
-0.322543203830719,
-0.42497506737709045,
0.01690482906997204,
-0.8793635368347168,
-0.99451929330825... |
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... | È probabile che si rifornisca un coniglio in un giardino di alimentari.
| 5 | NIv2 | task408_mickey_it_sentence_perturbation_generation | fs_opt | [
-0.18393507599830627,
0.41780537366867065,
-0.4320725202560425,
-0.5828441381454468,
0.1155516505241394,
-0.6881368160247803,
0.26267707347869873,
1.1665282249450684,
-0.42760419845581055,
0.009997030720114708,
-0.028204191476106644,
0.00439959391951561,
-0.24955794215202332,
0.10760936141... |
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 Hebrew.
Example: ويمكن اعادة تكرار هذه العملية على طول الشريط لكي نطبق شريط الحمض النووي فنشكل ما يشبه المستطيلات
Output: סך כל הפעולות של המהדקים על הגדיל ה... | כי אנחנו בעצם ניצבים מול בעיה גנאולוגית, שאלה גנאולוגית (על שושלות יוחסין). | 1 | NIv2 | task1233_ted_translation_ar_he | fs_opt | [
-0.9298421740531921,
0.2608177959918976,
-0.17289769649505615,
-0.3613438010215759,
-0.6394607424736023,
0.01295660249888897,
0.5936267375946045,
0.22258062660694122,
0.40069466829299927,
-0.3235352635383606,
-0.9557591080665588,
0.3258095979690552,
-0.27799272537231445,
0.0461592115461826... |
In this task, you are given a text of many news articles seperated by special token "|||||". Your task is to summarize them.
An 80-year-old Spanish nun appeared in court Thursday to face charges that she kidnapped an infant girl as part of a vast baby-trafficking ring that stole newborns from poor mothers and sold the... | An 80-year-old nun has been busted in Spain for her role in a massive Catholic church-linked baby-theft ring, according to investigators. The ring took babies from hundreds of poor or unwed mothers dating back to the 1980s and sold them into adoption, say officials. Sister Maria Gomez Valbuena, the first person to be a... | 0 | NIv2 | task1291_multi_news_summarization | zs_opt | [
1.0766361951828003,
0.22750253975391388,
-1.4624876976013184,
0.33477941155433655,
0.21722926199436188,
-0.11570870876312256,
-0.002565072849392891,
1.4166524410247803,
-0.27521559596061707,
0.6646315455436707,
-0.18072015047073364,
1.2422168254852295,
-0.7883869409561157,
0.69252848625183... |
Given the task definition and input, reply with output. You are given a sentence in Spanish. Your job is to translate the Spanish sentence into Polish.
Incluso si no sabes nada sobre el libro, te enfrentas a una persona que lucha entre dos planos de la existencia.
| Zatem nawet jeśli nie wie się nic o samej książce, jest się zmuszonym do pomyślenia o jednej osobie zawieszonej między dwoma płaszczyznami istnienia. | 5 | NIv2 | task1102_ted_translation_es_pl | zs_opt | [
-0.6700866222381592,
1.0225576162338257,
-0.031738970428705215,
-0.3264106810092926,
-0.0334952212870121,
0.24132797122001648,
1.311659336090088,
-0.4521505832672119,
0.43200430274009705,
-0.09455834329128265,
-0.2465643584728241,
0.08657355606555939,
-1.169508457183838,
0.1993861794471740... |
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".
--------
Question: Japanese: 香港は香港基本法の一環として、「ひとつの国、ふたつのシステム」という中国との間の合意の下、西洋式の... | No
| 7 | NIv2 | task1117_alt_ja_id_answer_generation | fs_opt | [
0.045924849808216095,
0.10377966612577438,
0.07932224869728088,
-0.46578747034072876,
-0.1469409465789795,
-0.48203012347221375,
0.7387143969535828,
0.18043889105319977,
-0.027298197150230408,
-0.636980414390564,
-0.7494953274726868,
0.22148114442825317,
0.05618327111005783,
0.814736664295... |
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Galician.
Q: בפעם הראשונה, צרכנים אמריקניים יראו את שרשרת האספקה של הנפט עומדת מולם.
A: | Por vez primeira os consumidores estadounidenses verán en fronte deles a cadea de subministración de petróleo. | 4 | NIv2 | task1110_ted_translation_he_gl | zs_opt | [
0.2374526858329773,
0.4208860993385315,
0.05522904545068741,
-0.3562481701374054,
-0.5146054029464722,
-1.1330609321594238,
0.20117202401161194,
0.6112300157546997,
-0.06388869881629944,
0.312923789024353,
0.6090762615203857,
-0.396298348903656,
-0.06414751708507538,
-0.6874125003814697,
... |
In this task, you are given a text of the article. Your task is to generate a headline (title) for this article.
--------
Question: confidence in greek assets sank to a new low monday , as chancellor angela merkel of germany kept up the pressure on greece , insisting on tougher austerity measures .
Answer: confidence ... | sars toll on toronto economy estimated at c$ # billion UNK us$ ### million with bc-as-gen world-sars virus
| 7 | NIv2 | task288_gigaword_summarization | fs_opt | [
-0.7257081270217896,
0.9354066848754883,
-0.20735551416873932,
-0.6599184274673462,
0.3487266004085541,
-0.17958426475524902,
0.5278328061103821,
0.30104368925094604,
-0.16198444366455078,
0.06303172558546066,
-0.27521902322769165,
0.42931151390075684,
-1.033682942390442,
0.000610386778134... |
In this task, you need to reverse all words of a given length in the sentence. The number of letters in a word determine its length. For example, the length of the word "apple" is 5.
[Q]: Sentence: 'a green apple and knife on dark wooden stairs'. Reverse all words of length '3' in the given sentence.
[A]: a green appl... | a bed and a desk ni a room
| 5 | NIv2 | task378_reverse_words_of_given_length | fs_opt | [
0.12373687326908112,
1.1037455797195435,
-0.28800633549690247,
-0.5567827224731445,
-0.2889823317527771,
-0.4410736858844757,
0.4080877900123596,
0.530219316482544,
-0.07705864310264587,
-0.259138286113739,
-0.9754233956336975,
0.3883695900440216,
-0.5041012763977051,
0.11137274652719498,
... |
Instructions: In this task, you are given a sentence in the English and Hindi language. Your task is check if the Hindi sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
Input: English: Boris Johnson, an English MP writing in The Times in London,... | Yes | 3 | NIv2 | task434_alt_en_hi_answer_generation | zs_opt | [
0.2739621698856354,
-0.11223629117012024,
0.46610724925994873,
0.3222616910934448,
0.5746530294418335,
-1.0067100524902344,
0.21953585743904114,
-0.06136268749833107,
0.3002672493457794,
0.36109989881515503,
-0.10875999927520752,
0.7260780334472656,
-0.3214413523674011,
-0.0998050570487976... |
Q: In this task you will be given two lists of numbers and you need to calculate the intersection between these two lists. The intersection between two lists is another list where every element is common between the two original lists. If there are no elements in the intersection, answer with an empty list. Your list o... | [2, 7, 8] | 7 | NIv2 | task098_conala_list_intersection | zs_opt | [
0.28161266446113586,
-0.2291879504919052,
-0.4063188433647156,
-0.22369179129600525,
0.3526307940483093,
-0.22905586659908295,
0.6673516631126404,
0.35509437322616577,
-0.14018234610557556,
0.25983744859695435,
-0.5729405879974365,
-0.5183642506599426,
-0.31217634677886963,
0.2672695517539... |
Definition: In this task, you need to answer the given multiple-choice question on the gain. Gain is the value by which to multiply the input. Classify your answers into 'a', 'b', 'c', 'd', and 'e'.
Input: Problem: seed mixture x is 40 percent ryegrass and 60 percent bluegrass by weight ; seed mixture y is 25 percent r... | b | 2 | NIv2 | task1419_mathqa_gain | zs_opt | [
0.32348179817199707,
0.38316813111305237,
-0.1751289963722229,
-0.3801223039627075,
-0.4614790976047516,
-0.3824949264526367,
0.8921144604682922,
1.3484156131744385,
0.23127490282058716,
0.26784655451774597,
-0.9622149467468262,
0.33693748712539673,
-0.6614178419113159,
0.35402536392211914... |
In this task, you will be shown a conversation and a question. You need to write an implausible answer to the question. Even though there exist multiple wrong answers, we only need a single wrong answer. "W" and "M" in the conversations stand for "woman" and "man".
Q: M: Hello, Mary. Why are you standing here? W: I'm w... | Early in the morning. | 4 | NIv2 | task283_dream_incorrect_answer_generation | zs_opt | [
0.2726108431816101,
0.6323882937431335,
-0.27144986391067505,
0.01260948833078146,
-0.24974727630615234,
-0.359145849943161,
0.3712102174758911,
0.37688663601875305,
0.7659268379211426,
0.12140610814094543,
-0.7029118537902832,
-0.02309517376124859,
0.6406114101409912,
-0.4394910931587219,... |
Given the task definition, example input & output, solve the new input case.
Given an Amazon customer review, write a title for the review. The preferred titles are under fifteen words.
Example: I was very surprised at the high quality of the stitching, the sturdiness of the handles and the padding for my laptop. The p... | One Star | 1 | NIv2 | task1342_amazon_us_reviews_title | fs_opt | [
-0.17051468789577484,
0.1820472925901413,
-0.13706262409687042,
0.08099972456693649,
0.650603711605072,
0.5260665416717529,
0.23484109342098236,
0.742431640625,
0.08235953748226166,
0.6775063276290894,
0.06400274485349655,
-0.09481505304574966,
0.16908025741577148,
-0.2602406144142151,
0... |
Definition: Given a sentence in English language, translate the sentence to Igbo language keeping the meaning of the original sentence intact
Input: English sentence: As a result of this, they decided to cook beans while they neglect repairing the roof but when the the rain started heavily, they were forced to repair t... | Dị ka a n'ihi nke a, ha kpebiri esi nri agwa mgbe ha na-eleghara anya ịrụzi elu ụlọ ma mgbe mmiri ozuzo malitere kpamkpam, a manyere ha ịrụzi elu ụlọ na ndị fọdụrụ n'ọbụ aka aka ụtọ. | 2 | NIv2 | task452_opus_paracrawl_en_ig_translation | zs_opt | [
0.087438203394413,
0.7634717226028442,
0.3817797601222992,
-0.5450407862663269,
-0.3596712052822113,
-0.6117909550666809,
0.777348518371582,
0.5254096984863281,
-0.6016378402709961,
0.22779440879821777,
-0.5901412963867188,
0.3285010755062103,
-1.2885891199111938,
0.48176103830337524,
-0... |
Detailed Instructions: In this task, you will be shown an extract from a movie plot and a question. You need to provide the correct answer for it. Short answers containing words that are present in the passage are preferred.
Q: Emma has a strong aversion towards her familys new house, especially the attic. After moving... | Answer: twelve days | 9 | NIv2 | task194_duorc_answer_generation | zs_opt | [
0.8608283996582031,
0.8501462936401367,
0.06603953242301941,
-0.009934471920132637,
0.15105853974819183,
-1.0155314207077026,
0.5732296705245972,
0.9397481083869934,
0.1492917239665985,
0.22416207194328308,
0.010492982342839241,
1.3091328144073486,
-0.8132364749908447,
0.09977491199970245,... |
Teacher: In this task, you are given a short story consisting of exactly 5 sentences where the second sentence is missing. You are given a candidate for the second sentence and you need to identify if the given sentence connects the first sentence with the rest of the story. Indicate your answer by "Yes" if it connects... | Yes | 2 | NIv2 | task066_timetravel_binary_consistency_classification | fs_opt | [
-0.09876475483179092,
-0.1894455999135971,
-0.3660091161727905,
0.25262928009033203,
0.49582526087760925,
-0.49879008531570435,
-0.20417913794517517,
1.485219955444336,
-0.12451464682817459,
-0.16907139122486115,
-0.05143749713897705,
-0.03670966625213623,
-0.8568496704101562,
-0.487346053... |
Given the task definition and input, reply with output. You are given a sentence in Japanese. Your job is to translate the Japanese sentence into English.
ここ何年か Kiva から借金する人たちと話してきて起業家精神の何たるかを教えられました
| Kiva borrowers, as I interviewed them and got to know them over the last few years, have taught me what entrepreneurship is. | 5 | NIv2 | task1222_ted_translation_ja_en | zs_opt | [
-0.5746580958366394,
-0.03463682904839516,
0.7409968376159668,
-0.643737256526947,
0.035399146378040314,
-0.3596879243850708,
0.7630467414855957,
-0.051248688250780106,
0.3222692012786865,
-0.11919721215963364,
0.4859275817871094,
0.29642605781555176,
-0.681801438331604,
0.606338620185852,... |
Teacher:In this task, you will be presented with an English sentence, and you have to translate it into Arabic.
Teacher: Now, understand the problem? Solve this instance: She wasn't even that good a fuck.
Student: | لم تكن أبداً بهذه البراعة فى الفراش | 6 | NIv2 | task651_opus100_en_ar_translation | zs_opt | [
-0.3862612843513489,
0.2775577902793884,
0.24126969277858734,
-1.0405486822128296,
-0.23951679468154907,
0.16235211491584778,
0.5159108638763428,
0.6146381497383118,
0.19488756358623505,
0.28512677550315857,
-0.0590212456882,
0.11306848376989365,
-0.6977815628051758,
-0.8068880438804626,
... |
Given a set of four words, generate the category that the words belong to. Words are separated by commas. The possible categories are social gathering, accomodation, physical property, measurement unit, corporate, nutritional value, boats, police punishment, location (proximity), card games, outdoor sport activity, mil... | emotional status | 0 | NIv2 | task143_odd-man-out_classification_generate_category | zs_opt | [
0.20408830046653748,
0.13763146102428436,
-0.47357141971588135,
0.0487547442317009,
0.12670981884002686,
-0.21980319917201996,
-0.4557841420173645,
0.2098679095506668,
0.11308620870113373,
-0.06447496265172958,
-0.3426881730556488,
0.04160398617386818,
-0.43962639570236206,
-0.417078614234... |
Given the task definition and input, reply with output. In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of... | ADV | 5 | NIv2 | task583_udeps_eng_coarse_pos_tagging | zs_opt | [
0.6585531234741211,
0.15530557930469513,
0.038012515753507614,
-0.06475445628166199,
0.1652064174413681,
-0.3156712055206299,
0.6426630020141602,
0.5073275566101074,
-0.30906739830970764,
-0.22517743706703186,
-0.3271210193634033,
0.007241646759212017,
-0.4521980881690979,
0.39707800745964... |
In this task, you are given a sentence from the Bible in Persian, and your task is to translate it into English.
و هنگامی که ابر را بالای زمین گسترانم، و قوس در ابر ظاهرشود، | And it shall come to pass, when I bring a cloud over the earth, that the bow shall be seen in the cloud: | 0 | NIv2 | task654_bible_fa_en_translation | zs_opt | [
-0.20496658980846405,
1.0035796165466309,
-0.7783617377281189,
-0.16473282873630524,
-0.74172043800354,
0.11133591830730438,
0.5966311693191528,
0.19227227568626404,
0.693023145198822,
0.14075744152069092,
-0.9784145355224609,
0.45824000239372253,
-1.0201526880264282,
0.3886801600456238,
... |
In this task you are given a sentence. You must judge whether subject of the main clause is singular or plural. Label the instances as "Singular" or "Plural" based on your judgment.
[Q]: A plastic tarp, stolen from the highway department, capped the works.
[A]: Singular
[Q]: These ideas already existed at that time ... | Singular
| 5 | NIv2 | task430_senteval_subject_count | fs_opt | [
-0.9242950677871704,
0.7465437650680542,
0.23355041444301605,
-0.5471883416175842,
-0.475538432598114,
-0.47558850049972534,
0.36981767416000366,
0.02120201475918293,
-0.2624206244945526,
-0.15504190325737,
-0.6557930707931519,
0.47732746601104736,
-0.30466222763061523,
-0.1402602791786193... |
Given the task definition and input, reply with output. Given a set of four words, generate the category that the words belong to. Words are separated by commas. The possible categories are social gathering, accomodation, physical property, measurement unit, corporate, nutritional value, boats, police punishment, locat... | police punishment | 5 | NIv2 | task143_odd-man-out_classification_generate_category | zs_opt | [
0.2269834280014038,
0.2612527012825012,
-0.507910966873169,
0.020237013697624207,
0.12198752164840698,
0.1734396368265152,
-0.4946308135986328,
0.38598915934562683,
0.24437637627124786,
-0.25621315836906433,
-0.4063476324081421,
-0.06857455521821976,
-0.3420477509498596,
-0.337245136499404... |
You are given a statement written in Hindi. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement. Output the word from the correct option .
Example input: Statement: सिग्नेचर केल्विन क्लेन अंडरवियर बुटीक, ब्यूनस आयर्स, टोरंटो, मेक्सिको सिटी, <MASK>, ग्लास... | तमिलनाडु | 3 | NIv2 | task947_wiki_cloze_hi_multiple_choice_question_answering | fs_opt | [
0.46435627341270447,
0.8511701822280884,
-0.7386090159416199,
0.03269287943840027,
-0.159909188747406,
-0.8431211113929749,
-0.44700512290000916,
0.5461291074752808,
-0.38101333379745483,
-0.33518120646476746,
0.478799045085907,
0.08052133023738861,
-0.6495161056518555,
-0.0184261389076709... |
Combine the given two facts to write a concluding fact. Note that there should be some parts of the first and second facts that are not mentioned in this conclusion fact. Your combined fact should be the result of a chain between the two facts. Chains form when two facts connect together to produce a concluding fact. A... | Fault movement causes the ground to shake.
****
| 4 | NIv2 | task038_qasc_combined_fact | fs_opt | [
0.5649646520614624,
0.5056909918785095,
-0.9910238981246948,
0.27457350492477417,
-0.4600974917411804,
-1.020491361618042,
0.2117309719324112,
1.4279509782791138,
-0.6477986574172974,
0.12793995440006256,
-1.3057708740234375,
0.2906390428543091,
-0.4643101096153259,
0.1455475091934204,
-... |
You will be given a definition of a task first, then some input of the task.
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 neither agree nor contradict each other. Generated sentences must be short, with less than ... | A dog rolls in the grass, excited spring is finally here. | 1 | NIv2 | task184_snli_entailment_to_neutral_text_modification | zs_opt | [
-0.41786766052246094,
0.33433014154434204,
0.06957587599754333,
-0.1399378776550293,
0.0037493854761123657,
-0.1637573540210724,
-0.11108224093914032,
0.5492984056472778,
0.4257028102874756,
-0.594513475894928,
-1.0237557888031006,
-0.5968844294548035,
-0.043306153267621994,
-0.47697165608... |
Detailed Instructions: In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e. tagset ... | ADJ | 9 | NIv2 | task583_udeps_eng_coarse_pos_tagging | zs_opt | [
0.9104483723640442,
0.40826988220214844,
-0.3238794803619385,
-0.26470962166786194,
-0.13214826583862305,
-0.8735288381576538,
0.789709210395813,
0.8834666013717651,
-0.15614557266235352,
-0.11333924531936646,
-0.04773171618580818,
0.31442683935165405,
-0.5657145380973816,
0.51221823692321... |
You are given a sentence in English. Your job is to translate the English sentence into Polish.
Let me give you an example: It's sort of the biggest TiVo box you've ever seen.
The answer to this example can be: To największa nagrywarka, jaką w życiu widzieliście.
Here is why: The English sentence is correctly translat... | Zatrzymajmy się chwilę przy tej myśli. | 8 | NIv2 | task1092_ted_translation_en_pl | fs_opt | [
0.024558033794164658,
0.5418765544891357,
0.5408238172531128,
0.5781166553497314,
0.4405185878276825,
-0.7095307111740112,
0.607089638710022,
-0.7173399329185486,
0.013271857984364033,
0.0009478959254920483,
0.4602072238922119,
0.5998772382736206,
-0.9192607998847961,
0.3613177537918091,
... |
In this task, you are given inputs i and A, where i is an integer and A is a list. You need to list all the elements of A preceding the last i elements. i will always have a value less than the length of A.
Q: 1, ['t', 'O', '5607', '1577', '9143', '5197', 'y', 'd', 'w', 's', '3331', '8701', '9409']
A: | t, O, 5607, 1577, 9143, 5197, y, d, w, s, 3331, 8701 | 4 | NIv2 | task078_all_elements_except_last_i | zs_opt | [
-0.6595897078514099,
0.7068841457366943,
-0.7256109714508057,
-0.7965348362922668,
-0.6290783882141113,
-0.5596654415130615,
0.2547394037246704,
-0.31758540868759155,
-0.21531030535697937,
0.12842197716236115,
-0.15095677971839905,
-0.3811674118041992,
0.3730071783065796,
-0.31698405742645... |
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 Portuguese. Your job is to translate the Portuguese sentence into English.
Os astrónomos acreditam que cada estrela da galáxia tem um planeta, e especulam que até um quin... | It doesn't produce more energy out than I put in, but it still does some pretty cool stuff. | 0 | NIv2 | task1274_ted_translation_pt_en | fs_opt | [
0.15163102746009827,
0.7430391907691956,
-0.005753935314714909,
-0.4588540196418762,
-0.2114669382572174,
-0.572610080242157,
0.011005229316651821,
0.5598925948143005,
0.6852286458015442,
-0.38719648122787476,
-0.1603233367204666,
0.2636631727218628,
-0.3746558725833893,
0.1247345060110092... |
Part 1. Definition
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Farsi.
Part 2. Example
私たちはただひたすら歌い続けましたすると驚くことに信頼が芽生え友情が花開いたのです
Answer: ما آواز خوندیم ، و خوندیم ، آواز خونديم ، و بطور شگفت انگیزی اعتماد جدید رشد کرد ، و درواقع دوستی شکوفه زد.
Explanation: The Japanese sent... | استیون: در واقع ، در بین دیگر چیزها ، دایره ی همدلیِ ما گسترش یافته است. | 7 | NIv2 | task1098_ted_translation_ja_fa | fs_opt | [
0.31416577100753784,
0.8516932725906372,
-0.3065311312675476,
-0.2604528069496155,
-0.3279741704463959,
-0.20177894830703735,
1.2655266523361206,
0.10794439166784286,
0.04846646636724472,
-0.5297019481658936,
-0.9497417211532593,
0.3008776307106018,
-1.3424031734466553,
0.5005361437797546,... |
You will be given a definition of a task first, then some input of the task.
A text is given in Telugu. Translate it from the Telugu language to the Urdu language. The translation must not omit or add information to the original sentence.
యుటి ఉద్యోగుల కు సెల్ఫ్- ఫైనాన్సింగ్ హౌసింగ్ స్కీము లో భాగం గా 3930 మంది అలాటీ ల... | مرکزکے زیر انتظام علاقو ں کے ملازمین کے لئے ازخود سرمایہ کاری ہاؤسنگ اسکیم کے تحت تین ہزار نوسو تیس (3930) الاٹیوں کے لئے اپارٹمنٹ کی تعمیر کی غرض سے چنڈی گڑھ ہاؤسنگ بورڈ کو اراضی الاٹ کرنے کی تجویز کو کابینہ کی منظوری | 1 | NIv2 | task1037_pib_translation_telugu_urdu | zs_opt | [
-0.1245412528514862,
1.3004443645477295,
-0.9176586866378784,
0.1254923939704895,
0.046059396117925644,
-1.032383918762207,
0.4780987501144409,
0.060132525861263275,
0.06088058650493622,
0.016838103532791138,
-0.07665111869573593,
0.08978119492530823,
-0.2754368782043457,
-0.16741536557674... |
Detailed Instructions: Given a sentence, an entity and its sentiment towards the entity, verify if it is the correct sentiment towards the entity. Answer should be yes or no. Note that URLs in the text have been replaced with [Link].
Problem:Verify if the sentiment of the following document towards the entity Cuomo is ... | yes | 8 | NIv2 | task422_persent_sentence_sentiment_verification | zs_opt | [
-0.8879890441894531,
-0.2348729968070984,
0.9598948955535889,
-0.1298738569021225,
-0.3549848794937134,
-1.3089218139648438,
0.010903265327215195,
0.34337055683135986,
0.08927226811647415,
0.015160749666392803,
0.7421796321868896,
-0.19410446286201477,
-0.11090709269046783,
-0.705880045890... |
Teacher: In this task you will be given a list, of lists, of integers. For every inner list contained in the input list, you should multiply every even number in that list. The output should be a list of integers with the same length as the number of lists in the input list. If there are no even numbers in an inner lis... | [-1656, 0, 52, 0, 960, 324] | 2 | NIv2 | task851_synthetic_multiply_evens | fs_opt | [
0.04442489147186279,
-0.19821138679981232,
-0.48277831077575684,
-0.2575291395187378,
0.3008546233177185,
-0.9334527254104614,
0.8153929710388184,
0.47280144691467285,
-0.6022777557373047,
-0.2973417043685913,
-0.5371330380439758,
-0.143769770860672,
-0.1656038463115692,
-0.695506453514099... |
Detailed Instructions: In this task, you are given a sentence in the English and Japanese language. Your task is check if the Japanese sentence is translation of English. if the translation is correct than generate label "Yes", otherwise generate label "No".
Q: English: The sculptures, a new replica of the "Goddess of ... | Yes | 9 | NIv2 | task437_alt_en_ja_answer_generation | zs_opt | [
-0.26854607462882996,
0.07451716810464859,
0.9294461011886597,
0.2749650478363037,
0.02216794714331627,
-1.1073956489562988,
0.0676828920841217,
0.6734918355941772,
0.3933732509613037,
0.045396070927381516,
0.7142964005470276,
0.24849316477775574,
-0.1492624282836914,
0.5422961711883545,
... |
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... | Das Schachspiel wird auf einem Schachstück gespielt.
| 7 | NIv2 | task416_mickey_de_sentence_perturbation_generation | fs_opt | [
0.31998512148857117,
0.549612820148468,
-0.07258456945419312,
-0.013493762351572514,
0.11141568422317505,
-0.5044975280761719,
1.2873518466949463,
1.1333589553833008,
-0.27149033546447754,
0.29415783286094666,
-0.7203425765037537,
0.172058567404747,
-1.0396480560302734,
-0.1844833493232727... |
In this task you are given a sentence with one coordinating conjunction (for, and, nor, but, or, yet, and so). You must judge whether the order of two coordinated clausal conjoints have been inverted or not. Inversion would result in the sentence sounding unnatural. Label the instances as "Original" or "Inversion" base... | Original | 8 | NIv2 | task516_senteval_conjoints_inversion | fs_opt | [
-0.3859238028526306,
0.7908982038497925,
0.810004711151123,
0.0831666886806488,
0.0980997383594513,
-0.7183713912963867,
0.8109185695648193,
0.7665524482727051,
-0.05104220286011696,
-0.02439248561859131,
-0.9018656015396118,
-0.37590330839157104,
-1.2997841835021973,
-0.3570861220359802,
... |
Part 1. Definition
In this task, you are given books product reviews in Japanese language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Part 2. Example
少年心 . 重松さんの作品の中でも、一番共感できる作品。 周りの人達に心を閉ざし、気が付いたら周りと距離を置... | NEG | 7 | NIv2 | task485_cls_japanese_books_classification | fs_opt | [
0.09135819226503372,
-0.25367364287376404,
-0.2662198543548584,
-0.4529542028903961,
0.6129963397979736,
0.07063062489032745,
1.369243860244751,
-0.055466584861278534,
0.20785176753997803,
0.04095614328980446,
-0.6270331144332886,
-0.2648778259754181,
-1.0224980115890503,
-0.04766122624278... |
In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: insult and non-insult. Insult is any lanugage or act that is disrespectful or scornfully abusive.
One example is below.
Q: Comment: your posts shows you are stupid period
A: Insult
Rationale: T... | Insult | 9 | NIv2 | task328_jigsaw_classification_insult | fs_opt | [
-1.3579668998718262,
0.7713012099266052,
0.8902233242988586,
0.20212069153785706,
0.06252656131982803,
-0.31512412428855896,
0.2098884880542755,
0.6610538959503174,
0.5615431070327759,
0.3442803621292114,
-0.15254732966423035,
0.5051687955856323,
-0.5961050391197205,
-0.7160125970840454,
... |
Given an input stream, the objective of this task is to classify whether words in the stream are grammatically correct or not. The input to this task is a stream of words, possibly from captions generated by a speech-to-text engine, and the output is a classification of each word from the labels (reason) = [NO_DIFF (co... | ['NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'PUNCUATION_DIFF', 'NO_DIFF', 'NO_DIFF'... | 0 | NIv2 | task1416_youtube_caption_corrections_incorrect_grammar_classification | fs_opt | [
0.20540234446525574,
0.01821320503950119,
0.02510393038392067,
-0.05616290494799614,
0.6245453953742981,
-0.12961995601654053,
0.6920021176338196,
1.0113390684127808,
-0.5090106725692749,
0.2466399371623993,
-0.02461790293455124,
-0.3869704008102417,
-0.25988882780075073,
0.009022684767842... |
In this task you will be given a text passage from a trivia quiz. You should choose the category this question belongs to from these categories: History, Science, Social Science, Fine Arts, Literature. You can only choose one category, so if in doubt, please choose the closest match.
Let me give you an example: In one... | Literature | 8 | NIv2 | task521_trivia_question_classification | fs_opt | [
0.4876503348350525,
0.6982580423355103,
-0.14479532837867737,
0.14184768497943878,
0.778710663318634,
0.17800427973270416,
1.2125556468963623,
0.3788376450538635,
0.20240822434425354,
-0.0005189033690840006,
-0.5439873933792114,
0.718704342842102,
-1.3391289710998535,
-0.2318859100341797,
... |
In this task, you will be presented with a question and you have to answer the question based on your knowledge. Your answers should be as short as possible.
Example input: Who were the builders of the mosque in Herat with fire temples ?
Example output: Ghurids
Example explanation: This is a good example. Ghurids were... | First baseman | 3 | NIv2 | task344_hybridqa_answer_generation | fs_opt | [
-0.9298387169837952,
0.5203682780265808,
-0.1895930916070938,
-0.6120599508285522,
-0.6384114027023315,
-0.6541320085525513,
0.12820139527320862,
-0.026147808879613876,
0.28628653287887573,
-0.2624686360359192,
-0.09951125085353851,
0.0656718760728836,
-0.3066812753677368,
-0.4986683726310... |
You're given a sentence and your task is to classify whether the sentence is acceptable or not. Any sentence which is grammatically correct, has a naturalistic text, is written by a native speaker and which minimizes superfluous content is acceptable, otherwise unacceptable. If the sentence is acceptable then write "ac... | unacceptable
| 6 | NIv2 | task616_cola_classification | fs_opt | [
-0.3205212354660034,
0.412165105342865,
0.62492436170578,
-0.6142266988754272,
0.319191575050354,
-1.0802932977676392,
0.23250487446784973,
0.09440445899963379,
0.5968635082244873,
0.4663374125957489,
-0.7201223373413086,
-0.0765518844127655,
-0.4897347390651703,
0.017256518825888634,
-0... |
Teacher: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".
Teacher: Now, understand the problem? Solve this instance: از کدامیک از برنامه های کاربردی زیر برای انجام امور... | common_knowledge | 6 | NIv2 | task474_parsinlu_mc_classification | zs_opt | [
-0.6508249640464783,
0.5829266905784607,
0.16246983408927917,
-0.7865802049636841,
-0.30545783042907715,
-0.37965720891952515,
1.0231804847717285,
0.2510790228843689,
0.7458698749542236,
-0.8004001379013062,
-0.19459545612335205,
0.28241032361984253,
-0.23576146364212036,
-0.17880359292030... |
A text is given in Tamil. Translate it from the Tamil language to the Urdu language. The translation must not omit or add information to the original sentence.
Example Input: மூன்றாம் மற்றும் நான்காம் இடத்திற்குப் பாராட்டுச் சான்றிதழ் வழங்கப்படுகிறது.
Example Output: تیسری اور چوتھی پوزیشن پانے والے پیپرس کے لئے سرٹیف... | 6فیصد کی شرح افراط زر 1991سے کسی بھی بھارتی حکومت کے لئے سب سے کم ہے۔ جب سے حکومت نے لبرلائزیشن(نرم کاری) کا عمل شروع کیاتھا’’۔
| 3 | NIv2 | task1035_pib_translation_tamil_urdu | fs_opt | [
-0.055509164929389954,
0.6700906157493591,
0.12030085921287537,
-0.4835853576660156,
0.2650670111179352,
-0.49405255913734436,
0.29048827290534973,
0.7835069894790649,
-0.2816561162471771,
0.2760730981826782,
-0.5738562941551208,
-0.08098283410072327,
-0.14106550812721252,
-0.1879957616329... |
Instructions: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Japanese.
Input: قيل لهم بأن هذه الجزر و الكثير من الجزر المحيطة تسكنها أكلة لحوم البشر
Output: | マルキーズ諸島とその周辺には食人種が住んでいるという噂です | 3 | NIv2 | task1231_ted_translation_ar_ja | zs_opt | [
0.37250712513923645,
0.1754235029220581,
-0.7183936834335327,
-0.7749758958816528,
-0.23446916043758392,
0.010259229689836502,
0.8673107028007507,
0.17325687408447266,
-0.33080577850341797,
-0.8562201261520386,
0.23939207196235657,
-0.3802485167980194,
-0.7783691883087158,
0.76843929290771... |
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 information related... | 1 | 0 | NIv2 | task1541_agnews_classification | zs_opt | [
-1.4528001546859741,
0.2470320761203766,
0.050727810710668564,
0.7445155382156372,
0.529621422290802,
0.026485703885555267,
0.10466882586479187,
-0.07974746823310852,
-0.0324455089867115,
-0.3668752908706665,
-0.8865666389465332,
0.4862605035305023,
-0.16156458854675293,
-0.324939906597137... |
Given a sentence in Dutch, generate a new Dutch sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being... | U kunt een klik gebruiken om uw reflectie te zien.
| 3 | NIv2 | task409_mickey_nl_sentence_perturbation_generation | fs_opt | [
-0.0254638884216547,
0.568683922290802,
-0.2778720259666443,
0.16638809442520142,
-0.21173346042633057,
-0.3740721344947815,
0.1011921763420105,
0.6090410947799683,
0.3064172565937042,
0.014965152367949486,
-0.574760913848877,
0.82181715965271,
-0.38588976860046387,
0.3132626414299011,
-... |
Given the task definition and input, reply with output. Given a sentence in Somali language, translate the sentence to English language keeping the meaning of the original sentence intact
Somali sentence: Ilaah waxaynu u caabudaynaa si waafaqsan fahankeenna.
| We do worship God according to what our understanding is of him. | 5 | NIv2 | task450_opus_paracrawl_so_en_translation | zs_opt | [
0.15643571317195892,
1.737697720527649,
0.13486886024475098,
-0.4542657434940338,
-0.4313633441925049,
-1.3701246976852417,
0.032255545258522034,
0.426052987575531,
0.6802490949630737,
0.516046404838562,
-0.18191185593605042,
0.610771119594574,
-1.2246700525283813,
-0.18723979592323303,
... |
Detailed Instructions: In this task, you're expected to write answers to questions involving multiple references to the same entity. The answer to the question should be unambiguous and a phrase in the paragraph. Most questions can have only one correct answer.
Q: Passage: In an interview with Pitchfork in October 2007... | Made in the Dark. | 9 | NIv2 | task002_quoref_answer_generation | zs_opt | [
0.6517843008041382,
0.19776614010334015,
-0.7584654688835144,
0.09454789757728577,
-0.05747551843523979,
-0.47630971670150757,
1.0498460531234741,
0.8002416491508484,
0.04233471676707268,
0.6782190799713135,
-0.33117568492889404,
0.1193414106965065,
-0.738090455532074,
-0.22927135229110718... |
Detailed Instructions: You are given a sentence in Polish. Your job is to translate the Polish sentence into Hebrew.
Q: (śmiech) Ten kontyngent wydawał się mieć szczęście i nie odniósł żadnych strat, pomimo tego, że wielu żołnierzy sił pokojowych zostało zabitych w Liberii.
A: | (צחוק) נציגות זו זכתה למזל גדול, ולא ספגה אבדות כלל, אף על פי שעשרות מכוחות השלום נהרגו בליבריה. | 9 | NIv2 | task1260_ted_translation_pl_he | zs_opt | [
-0.967695951461792,
0.7449453473091125,
-0.18713247776031494,
-0.7258866429328918,
-0.5854993462562561,
0.23071978986263275,
1.0255593061447144,
0.2803325653076172,
1.303576111793518,
-0.39690667390823364,
-0.558165431022644,
0.6049306392669678,
-1.0309147834777832,
0.13571949303150177,
... |
TASK DEFINITION: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. on... | for the position records of all rows , most of them fuzzily match to guard .
| 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt | [
0.30601176619529724,
-0.12436918169260025,
-0.24297435581684113,
0.0066645340994000435,
0.18929928541183472,
-0.29866868257522583,
0.5277801156044006,
0.675029993057251,
0.3563230335712433,
-0.40568807721138,
-0.39391523599624634,
0.030399244278669357,
0.07265318930149078,
0.39311411976814... |
instruction:
In this task, you are given a Reddit post as a text. Your task is to generate a short summary for this text. The summary must include a situation which caused humor. The summary should be one or two sentences long.
question:
Text: this happened a couple of nights ago, but lets just pretend it just happened... | took the blame for a girl at work that had a short register, backfired and got fired/possibly charged with theft
| 9 | NIv2 | task511_reddit_tifu_long_text_summarization | fs_opt | [
-0.15975022315979004,
0.46225303411483765,
0.1336316466331482,
-0.22400283813476562,
0.7905463576316833,
0.07062095403671265,
0.42951029539108276,
1.1692577600479126,
-0.0019447878003120422,
0.36299529671669006,
0.2485194355249405,
-0.272147536277771,
-0.6728562116622925,
0.061309620738029... |
Teacher:A text is given in Hindi. Translate it from the Hindi language to the Marathi language. The translation must not omit or add information to the original sentence.
Teacher: Now, understand the problem? Solve this instance: तो ये एक वो ही प्रयास है कि समाज में ऐसी जितनी भी शक्तियां हैं, उनको कैसे जोड़ा जाए?
Stude... | तर हा एक असा प्रयत्न आहे ज्यात समाजातील जितक्या शक्ती आहेत त्यांना एकत्र कशा प्रकारे आणता येईल? | 6 | NIv2 | task1081_pib_translation_hindi_marathi | zs_opt | [
0.21399280428886414,
0.6690528392791748,
0.7298989295959473,
-0.16667482256889343,
0.11896514892578125,
-0.779373049736023,
0.5907576084136963,
0.3138200640678406,
-0.16645994782447815,
-0.7690637707710266,
-0.4567886292934418,
-0.18762004375457764,
-0.7407636642456055,
-0.4004849195480346... |
instruction:
In this task you are given a tweet and you must identify whether the tweet contains any offense or any form of (untargeted) profanity. Label the post as NOT if the post does not contain offense or profanity. Non-offensive posts do not include any form of offense or profanity. label the post as OFFENSIVE i... | OFFENSIVE
| 9 | NIv2 | task286_olid_offense_judgment | fs_opt | [
-0.7537661790847778,
0.31630146503448486,
0.4512084126472473,
0.3037503957748413,
-0.3613187074661255,
-0.87044757604599,
0.45056042075157166,
0.31793534755706787,
0.6945654153823853,
0.3494197130203247,
-0.06524091958999634,
-0.3333660364151001,
-0.6240731477737427,
-0.5638347864151001,
... |
You will be given a definition of a task first, then some input 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'.
Person1: Ladies and gentlemen , welcome t... | 0 | 1 | NIv2 | task1534_daily_dialog_question_classification | zs_opt | [
-0.2130538523197174,
0.6011757254600525,
-0.3033931851387024,
0.24021825194358826,
0.15688854455947876,
-0.08376859873533249,
0.5096542835235596,
0.00037960615009069443,
0.2716330885887146,
-0.08081620931625366,
-0.4890977144241333,
-0.1964561939239502,
-0.46038299798965454,
0.430576682090... |
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 given a short story. One sentence from the story is chosen. Consider the events that happen after that sentence. Is any of them directly caused by it, or is made possible by... | Garrett gets a flat tire >Causes/Enables> He pulls over | 0 | NIv2 | task748_glucose_reverse_cause_event_detection | fs_opt | [
-0.14809101819992065,
0.03977698087692261,
0.34243741631507874,
0.11945639550685883,
-0.12769049406051636,
-1.2911127805709839,
0.07030421495437622,
1.072742223739624,
-0.6901029348373413,
-0.02420598268508911,
-0.6714546084403992,
-0.2905448079109192,
-0.03429524600505829,
-0.164301574230... |
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'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 ... | A grinning girl, sporting a red blouse, eats her strawberries in her chair | 0 | NIv2 | task188_snli_neutral_to_entailment_text_modification | fs_opt | [
-0.1625862717628479,
0.281141459941864,
0.681640625,
-0.3177058696746826,
0.4413354992866516,
-0.4962952136993408,
-0.35756629705429077,
0.7123279571533203,
0.0438065268099308,
0.08877298980951309,
-0.6775754690170288,
-0.35153621435165405,
-0.4834136664867401,
-0.19948281347751617,
0.17... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
This task is about translating a given English language sentence to Spanish.
It's this amazing wonderful feeling and you know it when you get it.
Solution: Es ese sentimiento asombroso e increíble, ... | Y esta reserva cumple con todos los parámetros de cada individuo. | 0 | NIv2 | task1691_qed_amara_translation | fs_opt | [
0.13039669394493103,
0.5312893390655518,
0.10395268350839615,
-0.1339312195777893,
-0.33876413106918335,
-1.1196224689483643,
1.0966541767120361,
0.7113908529281616,
0.39730554819107056,
-0.428669273853302,
0.17927348613739014,
0.31388059258461,
-0.18326880037784576,
0.5487326383590698,
... |
Indicate if the following Polish tweet contains cyber-bullying content with 'Yes'; otherwise, respond with 'No'.
--------
Question: Tweet: RT @anonymized_account JA JESTEM NORMALNY JA CHCE TYLKO ZAPOZOWAĆ Z ROWEREM PANI SYNA #topmodel , Question: Is the tweet free of any cyberbullying (harmful) content?
Answer: Yes
... | No
| 7 | NIv2 | task839_cdt_classification | fs_opt | [
-1.146277666091919,
1.0901198387145996,
0.21382252871990204,
0.7321329712867737,
-0.5375361442565918,
0.011393239721655846,
0.8463219404220581,
-0.14633339643478394,
0.11599110066890717,
-0.09697221219539642,
0.002787800971418619,
-0.010441108606755733,
-0.6206685304641724,
-0.017069511115... |
instruction:
You are given a paragraph (Passage), a question (Question) and two answer options (Option1 and Option2). Your task is to choose the correct answer to the question based on the passage. Answer of the question cannot be found directly from the passage, it is indirectly indicated in the passage. Do not answer... | board games
| 9 | NIv2 | task165_mcscript_question_answering_commonsense | fs_opt | [
1.1197593212127686,
0.1592634618282318,
-1.3474552631378174,
0.6382708549499512,
0.13172312080860138,
-0.4913628399372101,
0.9241965413093567,
0.5569632053375244,
-0.11027483642101288,
-0.3974266052246094,
-0.5186072587966919,
0.23565006256103516,
-0.7860244512557983,
0.15610793232917786,
... |
Detailed Instructions: In this task you will be given a list of numbers and you need to find the mean (average) of that list. The mean of a list can be found by summing every number in the list then dividing the result by the size of that list. The output should be rounded to 3 decimal places.
See one example below:
Pr... | 28.737 | 4 | NIv2 | task094_conala_calculate_mean | fs_opt | [
-0.062183015048503876,
-0.10934336483478546,
-1.4086861610412598,
-1.0058631896972656,
0.391414612531662,
0.15595364570617676,
0.819220244884491,
0.249338760972023,
-0.04045971482992172,
0.0780707374215126,
-1.243065357208252,
0.44584864377975464,
-0.6611956357955933,
0.08714348822832108,
... |
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