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 |
|---|---|---|---|---|---|---|
You will be given a definition of a task first, then some input of the task.
In this task, you are given a sentence in the 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".
English: The Plan B decision was the only one of 67 proposed prescription to OTC changes to be disapproved, even after advisory committees approved the changes.
Japanese: プランBの決定は、OCTに提案されて承認されなかった67の処方薬のうち、諮問委員会が変更を認めた後でさえも承認されなかった唯一のものであった。
Output: | Yes | 1 | NIv2 | task437_alt_en_ja_answer_generation | zs_opt | [
-0.2326492965221405,
0.07076063752174377,
0.5469367504119873,
-0.1527097374200821,
0.4737134575843811,
-0.7021744251251221,
0.8025546073913574,
0.40833908319473267,
0.3880617320537567,
-0.0849798247218132,
0.29670876264572144,
0.01480153389275074,
-0.0730617418885231,
0.3746914863586426,
... |
Definition: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into English.
Input: 学校に行く前に多くの人達からこう言われました「教育の質が低いのは教員が怠惰で学校に来ないからだ」とか「能力不足で指導法が分かっていないからだ」と
Output: | Before we went into schools, a lot of people told us that education quality is poor because either the teachers are lazy, they don't come into schools, or they're incapable, they actually don't know how to teach. | 2 | NIv2 | task1222_ted_translation_ja_en | zs_opt | [
-0.20613208413124084,
-0.161239355802536,
0.2835717797279358,
-0.9423615336418152,
0.2853665351867676,
-0.8271276354789734,
-0.6926519870758057,
0.5167694687843323,
0.06670823693275452,
-0.6713388562202454,
0.08479629456996918,
-0.03255622833967209,
-0.4402502179145813,
-0.1537447869777679... |
In this task, you're given passages that contain mentions of names of people, places, or things. Some of these mentions refer to the same person, place, or thing. Your job is to write questions that evaluate one's understanding of such references. Good questions are expected to link pronouns (she, her, him, his, their, etc.) or other mentions to people, places, or things to which they may refer. Do not ask questions that can be answered correctly without understanding the paragraph or having multiple answers. Avoid questions that do not link phrases referring to the same entity. For each of your questions, the answer should be one or more phrases in the paragraph, and it should be unambiguous.
--------
Question: Passage: The musical and philosophical ideas behind the opera had begun in Tippett's mind several years earlier. The story, which he wrote himself, charts the fortunes of two contrasting couples in a manner which has brought comparisons with Mozart's The Magic Flute. The strain of composition, combined with his continuing responsibilities at Morley and his BBC work, affected Tippett's health and slowed progress. Following the death in 1949 of Morley's principal, Eva Hubback, Tippett's personal commitment to the college waned. His now-regular BBC fees had made him less dependent on his Morley salary, and he resigned his college post in 1951. His farewell took the form of three concerts which he conducted at the new Royal Festival Hall, in which the programmes included A Child of Our Time, the British première of Carl Orff's Carmina Burana, and Thomas Tallis's rarely performed 40-part motet Spem in alium.In 1951 Tippett moved from Limpsfield to a large, dilapidated house, Tidebrook Manor in Wadhurst, Sussex. As The Midsummer Marriage neared completion he wrote a song cycle for tenor and piano, The Heart's Assurance. This work, a long-delayed tribute to Francesca Allinson (who had committed suicide in 1945), was performed by Britten and Pears at the Wigmore Hall on 7 May 1951. The Midsummer Marriage was finished in 1952, after which Tippett arranged some of the music as a concert suite, the Ritual Dances, performed in Basel, Switzerland, in April 1953. The opera itself was staged at Covent Garden on 27 January 1955. The lavish production, with costumes and stage designs by Barbara Hepworth and choreography by John Cranko, perplexed the opera-going public and divided critical opinion. According to Bowen, most "were simply unprepared for a work that departed so far from the methods of Puccini and Verdi". Tippett's libretto was variously described as "one of the worst in the 350-year history of opera" and "a complex network of verbal symbolism", and the music as "intoxicating beauty" with "passages of superbly conceived orchestral writing". A year after the première, the critic A.E.F. Dickinson concluded that "in spite of notable gaps in continuity and distracting infelicities of language, [there is] strong evidence that the composer has found the right music for his ends".Much of the music Tippett composed following the opera's completion reflected its lyrical style. Among these works was the Fantasia Concertante on a Theme of Corelli (1953) for string orchestra, written to commemorate the 300th anniversary of the composer Arcangelo Corelli's birth. The Fantasia would eventually become one of Tippett's most popular works, though The Times's critic lamented the "excessive complexity of the contrapuntal writing ... there was so much going on that the perplexed ear knew not where to turn or fasten itself". Such comments helped to foster a view that Tippett was a "difficult" composer, or even that his music was amateurish and poorly prepared. These perceptions were strengthened by controversies around several of his works in the late 1950s. The Piano Concerto (1955) was declared unplayable by its scheduled soloist, Julius Katchen, who had to be replaced before the première by Louis Kentner. The Dennis Brain Wind Ensemble, for whom Tippett had written the Sonata for Four Horns (1955), complained that the work was in too high a key and required it to be transposed down. When the Second Symphony was premièred by the BBC Symphony Orchestra under Boult, in a live broadcast from the Royal Festival Hall on 5 February 1958, the work broke down after a few minutes and had to be restarted by the apologetic conductor: "Entirely my mistake, ladies and gentlemen". The BBC's Controller of Music defended the orchestra in The Times, writing that it "is equal to all reasonable demands", a wording that implied the fault was the composer's.
Answer: What three things affected Tippett's health?
Question: Passage: Right before closing time Karen Kirsten and Jenny Johnsen, who work as waitresses at an Oslo night club, get an offer from the National Studios assistant director Jensen. He promises to make them both famous, and wants to give them screen test auditions. They accept the offer, and the very next day the girls show up at the film studio to try out for roles in the company's new production "Countess of Monte Cristo". There are two roles available: the countess herself and her maid.
However, the director, Mr. Hansen, manages to insult the young women gravely, and they leave the studios in anger, taking one of the studio's fancy cars as their ride while still wearing the costumes from the production. They drive to the luxurious Hotel Trollheimen, and use the costumes to lure the management into thinking they really are a countess and her maid. On the outside they encounter army Lt. Paul Von Cram, who is so captivated by their appearance - especially Karen's - that he offers to carry their suitcases up to their hotel suite. Because of this the two women mistake Paul for a bellboy.
Paul decides to cancel his imminent date with socialite woman Peg Manning, since he now has his eyes set on Karen. He then sends Karen a note at the hotel, asking her to meet "a lieutenant" at the hotel bar. Karen is intrigued by this and has no idea that it is Paul she is meeting. She makes a makeshift dress out of the curtains in the suite and goes down to meet the lieutenant. Arriving at the bar she instantly realises her earlier mistake.
Jenny discovers that they have been listed as thieves and wanted refugees from the law in a newspaper article. In a desperate attempt to hide this from the people at the hotel she buys every available newspaper she can find.
Answer: What are the first names of the people who are promised to become famous?
Question: Passage: Because of the 1932 Byrd Road Act, the state government controls most of Virginia's roads, instead of a local county authority as is usual in other states. As of 2018, the Virginia Department of Transportation owns and operates 57,867 miles (93,128 km) of the total 70,105 miles (112,823 km) of roads in the state, making it the third largest state highway system in the United States. Although the Washington Metropolitan Area, which includes Northern Virginia, has the second highest rate of traffic congestion in the nation, Virginia as a whole has the 21st-lowest rate of congestion and the average commute time is 26.9 minutes. Virginia hit peak car usage before the year 2000, making it one of the first such states.
Virginia has Amtrak passenger rail service along several corridors, and Virginia Railway Express (VRE) maintains two commuter lines into Washington, D.C. from Fredericksburg and Manassas. VRE is one of the nation's fastest growing commuter rail services, handling nearly 20,000 passengers a day. Arlington accounted for 40% of Virginia's public transit trips as of 2013, with most of that being from the Washington Metro transit system, which also serves Alexandria and communities in Fairfax County along I-66. The system is currently expanding west into additional areas of Loudoun County. Major freight railroads in Virginia include Norfolk Southern and CSX Transportation, the former of which is headquartered in Norfolk. Commuter buses include the Fairfax Connector and the Shenandoah Valley Commuter Bus. The Virginia Department of Transportation operates several free ferries throughout Virginia, the most notable being the Jamestown-Scotland ferry which crosses the James River in Surry County.Virginia has five major airports: Washington Dulles International and Reagan Washington National in Northern Virginia, both of which handle over 20 million passengers a year; Richmond International; and Newport News/Williamsburg International Airport and Norfolk International serving the Hampton Roads area. Several other airports offer limited commercial passenger service, and sixty-six public airports serve the state's aviation needs. The Virginia Port Authority's main seaports are those in Hampton Roads, which carried 17,726,251 short tons (16,080,984 t) of bulk cargo in 2007, the sixth most of United States ports. The Eastern Shore of Virginia is the site of Wallops Flight Facility, a rocket testing center owned by NASA, and the Mid-Atlantic Regional Spaceport, a commercial spaceport. Space tourism is also offered through Vienna-based Space Adventures.
Answer: | How many public airports are in Virginia?
| 7 | NIv2 | task001_quoref_question_generation | fs_opt | [
0.6085287928581238,
0.870142936706543,
-0.5947479009628296,
0.31020909547805786,
1.1540441513061523,
-0.03127618879079819,
0.7394614219665527,
0.6867195963859558,
-0.0553666427731514,
0.6351346373558044,
0.28050875663757324,
0.7999945878982544,
-0.9129846692085266,
0.37012040615081787,
-... |
Detailed Instructions: You are given a sentence in Polish. Your job is to translate the Polish sentence into Italian.
Q: Patrzyliby na to -,, ach, to jest rysunek "". Potem po ponownym przyjrzeniu się, widać, że to rzeczywiście istniało w czasie,
A: | E in effetti l'avrebbero percepito come un disegno a matita. Poi confrontate i fili col disegno e vedete che in effetti é qualcosa che esisteva nel tempo, | 9 | NIv2 | task1262_ted_translation_pl_it | zs_opt | [
-0.4461499750614166,
0.22856219112873077,
0.27883380651474,
0.09551545977592468,
-0.8638632893562317,
-1.0573064088821411,
0.6390463709831238,
1.1839244365692139,
0.47346633672714233,
-0.5271735191345215,
-0.49130314588546753,
0.2495398223400116,
0.299260675907135,
0.3333747982978821,
0.... |
instruction:
You are given a sentence in Italian. Your job is to translate the Italian sentence into Spanish.
question:
E ovviamente, Alessandro non poteva sostenere un governo e lo ha frammentato.
answer:
Y, por supuesto, Alejandro no pudo sostener un gobierno y se fragmentó.
question:
Il secondo comandamento di stasera è: una città del futuro deve gestire la mobilità e l'integrazione della sua popolazione.
answer:
Así que el segundo mandamiento que quiero dejaros esta noche es, que una ciudad del futuro tiene que lidiar con la movilidad y la integración de su gente.
question:
che è ormai scomparsa. Ed ora hanno grossi problemi economici.
answer:
| Ahora eso ha desaparecido. Y ahora tienen grandes problemas económicos.
| 9 | NIv2 | task1249_ted_translation_it_es | fs_opt | [
-0.20169687271118164,
0.7294101715087891,
0.6661940813064575,
-0.18080776929855347,
-0.37907740473747253,
-0.26834267377853394,
0.004050116520375013,
1.4269249439239502,
-0.5048160552978516,
-0.4583633542060852,
-0.19640100002288818,
0.12806233763694763,
-0.31270527839660645,
0.31493672728... |
instruction:
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Sentence 2 contradicts sentence 1. 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 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
question:
Sentence 1: Three men are visiting at a dressy gathering. Sentence 2: Three men are at a casual gathering
answer:
The men are wearing fancy tuxedos.
question:
Sentence 1: Children in bathing suits play. Sentence 2: There are no people outside.
answer:
Children are playing at the pool.
question:
Sentence 1: A mountain biker rides down a trail. Sentence 2: A person is sand surfing on a sand dune.
answer:
| A person is mountain biking in Colorado.
| 9 | NIv2 | task185_snli_contradiction_to_neutral_text_modification | fs_opt | [
-0.6910640001296997,
0.8803894519805908,
-0.6213173866271973,
-0.6967419385910034,
-0.25465020537376404,
-0.5050248503684998,
-0.04285016655921936,
0.37608444690704346,
0.49809789657592773,
-0.32409927248954773,
-1.0581235885620117,
-0.25719738006591797,
-0.37242722511291504,
-0.3756138086... |
In this task you will be given a list of integers. You should find the minimum absolute difference between 2 integers in the list. The absolute difference is the absolute value of one integer subtracted by another. The output should be a single integer which is the smallest possible absolute distance.
Q: [21, 1, 71, -12, 100]
A: | 13 | 4 | NIv2 | task1445_closest_integers | zs_opt | [
-0.7727677226066589,
0.8397012948989868,
0.30813735723495483,
-0.73274165391922,
-0.4998384118080139,
-0.37198927998542786,
1.1629160642623901,
-0.17604835331439972,
0.35009312629699707,
-0.07363671809434891,
-0.09731249511241913,
-0.12941130995750427,
-0.3578828275203705,
-0.1425838619470... |
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 works have been created before? What is still missing in the previous works? What are the high-level research questions? How might this help other research or researchers?), Purpose (What specific things do the researchers want to do? What specific knowledge do the researchers want to gain? What specific hypothesis do the researchers want to test?), Method (How did the researchers do the work or find what they sought? What are the procedures and steps of the research?), or Finding (What did the researchers find out? Did the proposed methods work? Did the thing behave as the researchers expected?). ",
Q: Sentence: Nine subjects completed the 3 dose vaccination schedule and were evaluated for vaccine safety and immune responses.
Section: finding
A: | False | 4 | NIv2 | task1164_coda19_section_correction_classification | zs_opt | [
-0.20535066723823547,
0.28190791606903076,
-0.1756327599287033,
-0.2015385925769806,
-0.22349460422992706,
0.11551427096128464,
0.5889011025428772,
0.9882181286811829,
-0.05544007569551468,
-0.12955397367477417,
-0.8810650110244751,
-0.10023418068885803,
-0.3227469325065613,
0.098813861608... |
In this task, you're given an ambiguous question (which can be answered in more than one way). Your task is to provide one question which clarifies the input question and it has one unique answer, and also provide an answer to the generated question. Generated question and answer should be separated with a new line.
One example: Lucifer how many episodes are in season 3?
Solution is here: How many episodes of season 3 of Lucifer were there, including bonus episodes?
26
Explanation: The generated question clarifies the input question by asking about bonus episodes because if the question is about regular episodes only then the answer will be different than including the bonus episodes. Also, the answer to the generated question is provided.
Now, solve this: When did the fast and the furious start?
Solution: | When did the fast and the furious start filming?
July 2000 | 6 | NIv2 | task671_ambigqa_text_generation | fs_opt | [
-0.33491605520248413,
0.2751461863517761,
0.19855955243110657,
-0.8024005889892578,
-0.2101699411869049,
0.25139108300209045,
0.48544323444366455,
0.3109830617904663,
-0.1356811821460724,
-0.5664194822311401,
-0.3308960199356079,
0.19158416986465454,
-1.118146538734436,
0.1803130805492401,... |
In this task, you are given a context paragraph of the tweet and question. Your task is to generate right answer of given question based on given context tweet paragraph.
Context: POWERFUL! 👊 Zimbabweans standing together against "corruption, injustice & poverty". #ThisFlag #ZimShutDown2016 Leandri J van Vuuren (@Lean3JvV) July 6, 2016 Question: what year was the zimbabwe shutdown movement?
2016
Context: Why isn't the House Intelligence Committee looking into the Bill & Hillary deal that allowed big Uranium to go to Russia, Russian speech....— Donald J. Trump (@realDonaldTrump) March 28, 2017 Question: where did the uranium go?
russia
Context: At this point, who DOESN'T want Trump impeached? Ann Coulter (@AnnCoulter) September 14, 2017 Question: who tweeted asking who doesn't want trump impeached?
| ann coulter
| 0 | NIv2 | task239_tweetqa_answer_generation | fs_opt | [
-0.23341530561447144,
0.753032386302948,
0.10001729428768158,
-0.0011658035218715668,
0.01281420886516571,
-0.16711053252220154,
-0.027720030397176743,
0.4386138617992401,
-0.12974324822425842,
0.16484466195106506,
-0.05220001935958862,
0.33117055892944336,
-0.7180067896842957,
-0.18739140... |
Definition: Given a question and a context passage, generate the answer having the word or phrase from the context passage. Here, the answer should be a shortest continous span from the passage.
Input: Context: Chronic myelogenous leukemia (CML) is caused by the BCR-ABL tyrosine kinase, the product of the Philadelphia chromosome. Imatinib mesylate, formerly STI571, is a selective inhibitor of this kinase. A total of 532 patients with late--chronic-phase CML in whom previous therapy with interferon alfa had failed were treated with 400 mg of oral imatinib daily. Patients were evaluated for cytogenetic and hematologic responses. Time to progression, survival, and toxic effects were also evaluated. Imatinib induced major cytogenetic responses in 60 percent of the 454 patients with confirmed chronic-phase CML and complete hematologic responses in 95 percent. After a median follow-up of 18 months, CML had not progressed to the accelerated or blast phases in an estimated 89 percent of patients, and 95 percent of the patients were alive. Grade 3 or 4 nonhematologic toxic effects were infrequent, and hematologic toxic effects were manageable. Only 2 percent of patients discontinued treatment because of drug-related adverse events, and no treatment-related deaths occurred. Imatinib induced high rates of cytogenetic and hematologic responses in patients with chronic-phase CML in whom previous interferon therapy had failed.
Question: What tyrosine kinase, involved in a Philadelphia- chromosome positive chronic myelogenous leukemia, is the target of Imatinib (Gleevec)?
Output: | bcr-abl | 2 | NIv2 | task469_mrqa_answer_generation | zs_opt | [
0.7840123176574707,
0.13867849111557007,
-0.13449043035507202,
-0.3653559982776642,
0.9194164276123047,
-0.564396858215332,
0.8007338047027588,
0.9577596187591553,
0.35947152972221375,
0.21577827632427216,
-0.8707253932952881,
0.4410356283187866,
-0.6934825778007507,
0.44095367193222046,
... |
Given the task definition and input, reply with output. Given a sentence in the Japanese, provide an equivalent translation in Bahasa Indonesia that retains the same meaning through the translation. In translation, keep numbers as it is.
その火災は、まだ原因が分からず、消火まで1時間半に渡って燃え続けた。
| Api tersebut, yang penyebabnya belum diketahui, terbakar selama satu setengah jam sebelum dapat dipadamkan. | 5 | NIv2 | task1115_alt_ja_id_translation | zs_opt | [
0.12463562935590744,
1.1103289127349854,
0.11413107067346573,
-0.1724085956811905,
-0.41733071208000183,
-0.6312894821166992,
0.6005021333694458,
-0.04559149593114853,
-0.2769702970981598,
-0.4644453227519989,
-0.7045363187789917,
0.641453206539154,
-1.3122246265411377,
0.5011152029037476,... |
Given a scientific question, generate a correct answer to it.
[EX Q]: What force increases a slide downhill and decreases a slide uphill?
[EX A]: gravity
[EX Q]: What are the ice crystals that form on the ground called?
[EX A]: frost
[EX Q]: What branch of science aims to understand all about our planet and its environments?
[EX A]: | earth science
| 6 | NIv2 | task591_sciq_answer_generation | fs_opt | [
-0.12610334157943726,
0.9882904291152954,
0.09267920255661011,
-0.5080461502075195,
-0.24824921786785126,
-1.0749530792236328,
-0.08698784559965134,
0.4052911400794983,
-0.319704532623291,
-0.6906245946884155,
-0.9313036203384399,
0.07280373573303223,
-1.7152483463287354,
0.334501296281814... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, you are given a sentence from the Bible in English, and your task is to translate it into Persian.
In the beginning God created the heaven and the earth.
Solution: در ابتدا، خدا آسمانها و زمین را آفرید.
Why? This is a good example. The above sentence is correctly translated from English to Persian.
New input: And on the sixth day eight bullocks, two rams, and fourteen lambs of the first year without blemish:
Solution: | و یک بز نر بجهت قربانی گناه، سوای قربانی سوختنی دائمی و هدیه آردیاش و هدیه ریختنی آن. | 0 | NIv2 | task655_bible_en_fa_translation | fs_opt | [
-0.02697182446718216,
1.381520390510559,
0.09710350632667542,
-0.21220162510871887,
-0.6910309791564941,
-0.2243531048297882,
0.829639196395874,
0.797825276851654,
0.30108368396759033,
0.3425859808921814,
-0.9128252267837524,
0.6966997385025024,
-0.5511247515678406,
-0.005884290207177401,
... |
In this task, you're given an article, a question which often contains a blank, four options (associated with "A", "B", "C", "D") and the answer to that question. Your task is to classify whether the given answer is correct or not by providing "Yes" or "No", based on the article.
Article: Bruce Alberts, the former President of the National Academies (USA), has now taken over as Editor-in Chief of Science. Judging by his editorial in this week's issueConsidering Science Education there could be some interesting times ahead inScience offices. Here's part of what Bruce has to say about science education... I consider science education to be critically important to both science and the world, and I shall frequently deal with this topic on this page. Let's start with a big-picture view. Science has greatly advanced our understanding of the natural world and has enabled the creation of countless medicines and useful devices. It has also led to behaviors that have improved lives. The public appreciates these practical benefits of science, and science and scientists are generally respected, even by those who are not familiar with how science works or what exactly it has discovered. But society may less appreciate the advantage of having everyone acquire the ways of thinking and behaving that are central to practice of successful science: scientific habits of mind. These habits include a critical attitude toward established claims and a strong desire for logic and evidence. As famous astronomer Carl Sagan put it, science is our best detector . Individuals and societies clearly need a means to logically test the constant clever attempts to operate our purchasing and political decisions. They also need to challenge what is unreasonable, including the intolerance that led to so many regional and global conflicts. So how does this relate of science education? Might it be possible to encourage, across the world, scientific habits of mind, so as to create more rational societies everywhere? In principle, a strong expansion of science education could provide the world with _ , but only if scientists, educators, and policy-makers redefine the goals of science education, beginning with college-level teaching. Rather than only conveying what science has discovered about the natural world, as is done now in most countries, we should provide first all students with the knowledge and practice of how to think like a scientist.
Question: Which of the following is NOTincluded in the "scientific habits of mind"?
Options: (A) A critical attitude toward established claims. (B) A strong desire for logic. (C) A clever and active mind. (D) A strong desire for evidence.
Asnwer: A
No
Article: Cole Bettles had been rejected by a number of universities when he received an e-mail from the University of California, San Diego, last month, congratulating him on his admission and inviting him to tour the campus. His mother booked a hotel in San Diego, and the 18-year-old Ojai high school senior arranged for his grandfather, uncle and other family members to meet them at the campus for lunch during the Saturday tour. "They were like 'Oh my God, that's so awesome ', " Bettles said. Right before he got in bed, he checked his e-mail one last time and found another message saying the school had made a mistake and his application had been denied. In fact, all 28, 000 students turned away from UC San Diego, in one of the toughest college entrance seasons on record, had received the same incorrect message. The students' hopes had been raised and then dashed in a cruel twist that shows the danger of instant communications in the Internet age. UCSD admissions director Mae Brown called it an "administrative error" but refused to say who had made the mistake, or if those responsible would be disciplined . The e-mail, which began, "We're thrilled that you've been admitted to UC San Diego, and we're showcasing our beautiful campus on Admit Day, " was sent to the full 46, 000 students who had applied, instead of just the 18, 000 who got in, Brown said. The error was discovered almost immediately by her staff, who sent an apology within hours. "It was really thrilling for a few hours; now he's crushed , " said Cole's mother, Tracy Bettles. "It's really tough on them." The admissions director said she was in the office on Monday until midnight answering e-mails and phone calls from disappointed students and their parents. She said she took full responsibility for the error. "We accessed the wrong database. We recognize the incredible pain receiving this false encouragement caused. It was not our intent."
Question: How many students received an admission e-mail from the University of California, San Diego (UCSD)?
Options: (A) 18, 000 (B) 28, 000 (C) 46, 000 (D) 18
Asnwer: C
Yes
Article: Northern Lights Tour Located in the middle of the northern lights belt, Tromso can offer some of the highest levels of northern lights activity on earth. Perhaps Tromso is the world's best place for a Northern Lights Tour. Join one of our Northern Lights Holidays this winter. It could become one of the greatest experiences in your life. DESTINATION Tromso county, Norway. PRICE $450 per person WHEN 2th September until 31st March. PICK-UP Each evening at 6 PM outside your hotel. DROP-OFF Earliest at 12 AM. When we have a sighting we often stay out later, at no extra cost. SIZE OF GROUP Maximum 8 participants is recommended and normal, but not absolute. A small group allows more freedom in terms of chasing the northern lights. INCLUDED - Transportation each day in a comfortable car - A meal each day - All necessary equipment such as snowshoes, flashlight, water-filled bottle, woolen underwear, a warm, hat, warm shoes, warm stockings, and reindeer skin to lie on, if needed. - A guide who will do anything necessary to find the northern lights. EXCITING CHASE A Northern Lights Holiday means an intense and exciting chase--to the coast or deep into the wild, perhaps even to the Finnish border. Each day on a Northern Lights Tour we contact meteorologists shortly before departure to get accurate information. In order to find out where we will have best chances to see the northern lights. WE GUARANTEE A GREAT TRIP The northern lights are unpredictable, but we guarantee that we will do everything to find _ . Patience is a keyword on Northern Lights Tour. ECO-TOURISM We offer ecologically sustainable and responsible tours. Travelling in small groups is an essential part of the ecotourism concept, as small groups have lesser impact on nature and will not disturb the wildlife unnecessarily.
Question: A small group is preferred for the following reasons EXCEPT that _ .
Options: (A) a small group is free to run after the northern lights (B) a small group has less effect on nature (C) a small group can save the travel cost (D) a small group will not disturb wildlife
Asnwer: B
| No
| 0 | NIv2 | task310_race_classification | fs_opt | [
0.18890982866287231,
0.6109440922737122,
-0.4347461462020874,
-0.45815038681030273,
0.17683453857898712,
-0.46167224645614624,
-0.07709744572639465,
0.3617580533027649,
-0.5106104612350464,
0.03936048597097397,
0.08394129574298859,
0.27162906527519226,
-0.310732364654541,
-0.19279892742633... |
Given the task definition and input, reply with output. You will be given a summary of a story. You need to create a question that can be answered from the story. You can create a question about characters, events, facts and beliefs, etc. Your question should be specific, try not to use pronouns instead of full names. As the stories are sometimes movie plots, they will contain actor names in parentheses. You should not use those names. Only use character names. Try to ask a question about all parts of the plot, not just the beginning.
Several residents of a Paris boarding-house write letters to their friends and family back home; their primary subject is their reaction to each other. The main character is Miranda Hope, an angular but likeable Yankee Miss from Bangor, Maine who, quite bravely for a young woman of that era, is traveling in Europe alone. In her letters, she chatters to her mother about seeing the sights in Europe but doesn't like the Old World's treatment of its women, "and that is a point, you know, on which I feel very strongly." Her expressions of petulance with William Platt, who we realize must have been a suitor of hers back in Maine, are so offhand as to be amusing. Although she is in general the least affected and most sympathetic character in the story, her unawareness of the disdain in which most of the characters hold each other (including herself) makes her seem somewhat naive.
Meanwhile, society girl Violet Ray of New York writes to a friend that Miranda, who she sees as provincial, is "really too horrible." Another boarder, wannabe aesthete Louis Leverett (quite possibly a self-satire by James) gushes in his letter that "the great thing is to live, you know," amid much precious verbiage about the good, the true and the bee-a-u-tiful. An English boarder, Evelyn Vane, pens a scoffing note that Louis is always talking about the color of the sky, but she doubts if he's ever seen it except through a window-pane; and the German sees Leverett's "decadence" as further evidence that the English-speaking world is weak and ripe for takeover.
The Frenchman Leon Verdier almost drools in his letter about the charms of ces demoiselles among the boarders, and focuses primarily on their appearance. The rather threatening German professor is the only character both cynical and intelligent enough to realize how disdainful all the English speakers are of each other. However, he's also the least sympathetic character in the story. (James disliked Germany and its culture.) While the other characters despise each other mostly on personal grounds, or from cultural misunderstanding, Herr Professor despises them all based on their national traits and general sub-human status (he calls the Frenchman "simian"). In a letter to his German friend, he simultaneously brags of his erudition and predicts that the weakness of these other nationalities augurs a bright future "for the deep-lunged children of the Fatherland!"
| Where is the boarding-house located? | 5 | NIv2 | task405_narrativeqa_question_generation | zs_opt | [
0.27874085307121277,
0.5301328897476196,
-0.14287957549095154,
-0.24221712350845337,
0.3921463191509247,
-0.3906594216823578,
0.5669258832931519,
0.3179197907447815,
-0.23504102230072021,
0.09418930113315582,
0.06608689576387405,
0.6993150115013123,
-0.3094296157360077,
0.04991769790649414... |
A text is given in Malayalam. Translate it from the Malayalam language to the Panjabi language. The translation must not omit or add information to the original sentence.
[EX Q]: -സാങ്കേതികമായി ഉയര്ന്ന ഗുണനിലവാരമുള്ള തീറ്റപ്പുല്ല് വികസിപ്പിക്കുക, തീറ്റയുമായി ബന്ധപ്പെട്ട മരങ്ങളുടെ നഴ്സറിയും തീറ്റ വിളകളും വികസിപ്പിക്കുകയും സംയോജിത കാര്ഷിക സമ്പ്രദായത്തിലൂടെ തീറ്റയുമായി ബന്ധപ്പെട്ട ഇനങ്ങള് കൃഷിചെയ്യുന്നതിനായി ആഗ്രോ-ഫോറസ്റ്ററി പ്രോത്സാഹിപ്പിക്കുക.
[EX A]: ਪਸ਼ੂਆਂ ਦੇ ਚਾਰੇ ਦੀਆਂ ਫ਼ਸਲਾਂ ਦੇ ਨਾਲ ਹਾਈ ਟੈਕ ਚਾਰੇ ਦੇ ਪੌਦਿਆਂ ਦੀਆਂ ਪ੍ਰਜਾਤੀਆਂ ਦੀਆਂ ਨਰਸਰੀਆਂ ਵਿਕਸਿਤ ਕਰਨਾ ਅਤੇ ਔੜ ਵਾਲੇ ਖੇਤਰਾਂ ਵਿੱਚ ਨਮੀ ਵਾਲੀ ਮਿੱਟੀ ਦੀ ਸਾਂਭ-ਸੰਭਾਲ ਸਹਿਤ ਏਕੀਕ੍ਰਿਤ ਖੇਤੀਬਾੜੀ ਪ੍ਰਣਾਲੀ ਦੇ ਤਹਿਤ ਚਾਰੇ ਵਾਲੇ ਪੌਦਿਆਂ ਦੀਆਂ ਪ੍ਰਜਾਤੀਆਂ ਦੇ ਪੌਦੇ ਲਗਾਉਣ ਲਈ ਖੇਤੀਬਾੜੀ ਵਣਾਂ ਨੂੰ ਪ੍ਰੋਤਸਾਹਿਤ ਕਰਨਾ।
[EX Q]: ഗുരു നാനാക് ദേവ് പറയാറുണ്ടായിരുു, 'ദരിദ്രരെയും ഇല്ലാത്തവരെയും സേവിക്കുതാണ് ഭഗവത് സേവ' എ്.
[EX A]: ‘‘ਗੁਰੂ ਗੋਬਿੰਦ ਦੋਉ ਖੜੇ, ਕਾ ਕੇ ਲਾਗੂੰ ਪਾਂਯ। ਬਲਿਹਾਰੀ ਗੁਰੂ ਆਪਨੇ, ਗੋਵਿੰਦ ਦਿਯੋ ਬਤਾਯ’’
[EX Q]: അതാണ് യോഗയെ സുന്ദരമാക്കുന്നത്.
[EX A]: | ਇਹ ਅੱਜ ਤੱਕ ਲਗਾਤਾਰ ਵਿਕਸਿਤ ਹੋ ਰਿਹਾ ਹੈ।
| 6 | NIv2 | task1005_pib_translation_malayalam_punjabi | fs_opt | [
-1.243443250656128,
0.3735557198524475,
-0.19818276166915894,
0.09335117042064667,
-0.6051465272903442,
-1.2179797887802124,
0.9616981148719788,
1.0067830085754395,
-0.698405921459198,
0.03408452868461609,
-0.6331964731216431,
-0.2537907660007477,
-0.5073227882385254,
0.2579909563064575,
... |
You are given a sentence in Polish. Your job is to translate the Polish sentence into Spanish.
Example Input: A ilość katastrof na całym świecie rosła w absolutnie niezwykłym i nieoczekiwanym tempie.
Example Output: Y los desastres en todo el mundo se han incrementado a un ritmo totalmente insólito y sin precedentes.
Example Input: Wielu ludzi próbuje hodować komórki w laboratorium
Example Output: Mucha gente ha tratado de cultivar células en el laboratorio.
Example Input: Obserwuje uważnie, jak obchodzić się z butelką.
Example Output: | Observan con mucha atención cómo debe ser tocada una botella de whisky.
| 3 | NIv2 | task1258_ted_translation_pl_es | fs_opt | [
-0.3765236735343933,
1.2131956815719604,
-0.4025144577026367,
0.10329239070415497,
-0.540276288986206,
-0.939734697341919,
-0.07023125886917114,
0.5532286167144775,
-0.15253347158432007,
-0.5562379360198975,
-1.0046021938323975,
0.6409590244293213,
-0.5366925001144409,
0.37776726484298706,... |
Q: In this task, you are given a sentence in either Spanish or English. Your task is to determine the language of the input sentence. Input sentences can only be in Spanish or English, and they cannot be in two languages at the same time.
Cuando se iniciaron las negociaciones entre la UE y China, se nos dijo a los diputados al Parlamento que, en realidad, no se presentarían grandes problemas, porque alrededor del ochenta por ciento de los objetivos de la Unión estaban ya incluidos en el resultado de las negociaciones entre EEUU y China.
A: | Spanish | 7 | NIv2 | task533_europarl_es-en_language_identification | zs_opt | [
-0.27105557918548584,
0.7339119911193848,
0.2881195843219757,
-0.2680893838405609,
0.30139607191085815,
-0.31852370500564575,
-0.4838985204696655,
0.6050669550895691,
-0.10182896256446838,
-0.01241972018033266,
0.004653364885598421,
0.2164580523967743,
-0.017835315316915512,
-0.34233418107... |
Teacher: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 key to keeping your abstract focused on the main idea and creating a clear and concise image.
Teacher: Now, understand the problem? Solve this instance: Evaluation of testicular functions (production of sperm and androgens) is an important aspect of preclinical safety assessment and testicular toxicity is comparatively far more common than ovarian toxicity. This chapter focuses (1) on the histological sequelae of disturbed reproductive endocrinology in rat, dog and nonhuman primates and (2) provides a review of our current understanding of the roles of gonadotropins and androgens. The response of the rodent testis to endocrine disturbances is clearly different from that of dog and primates with different germ cell types and spermatogenic stages being affected initially and also that the end-stage spermatogenic involution is more pronounced in dog and primates compared to rodents. Luteinizing hormone (LH)/testosterone and follicle-stimulating hormone (FSH) are the pivotal endocrine factors controlling testicular functions. The relative importance of either hormone is somewhat different between rodents and primates. Generally, however, both LH/testosterone and FSH are necessary for quantitatively normal spermatogenesis, at least in non-seasonal species.
Student: | False | 6 | NIv2 | task1589_scifact_classification | zs_opt | [
-0.016011908650398254,
0.18563202023506165,
-0.4012175500392914,
-0.29635387659072876,
-0.38008442521095276,
-0.777337908744812,
0.4037995934486389,
0.8282120227813721,
-0.128846675157547,
-0.45432716608047485,
-1.2903491258621216,
0.2105681300163269,
-0.41841334104537964,
-0.2568629980087... |
This task involves creating questions from a given passage that involve some kind of complex reasoning (including numerical reasoning).
The generated questions must require looking at more than one part of the passage to answer. Try to use a variety of reasoning types in your questions (some of the sample reasoning types are illustrated in the 'positive examples' field) and also have a variety of answer types (spans, numbers, dates). A span is a continuous phrase taken directly from the passage or question. In such questions, the answer spans are recommended to be five words. Questions with answer type "number", are expected to start with "How many". For instance, "How long did an event last?" can be phrased as "How many years did an event last?". To increase diversity, try to create more questions for which the answer will be multiple spans. Please create questions that require AT LEAST 2 arithmetic operations as illustrated in the 'positive examples' field. You are encouraged to try DIFFERENT COMBINATIONS of operations and not just limit to the combinations shown in those examples. The more challenging questions you create, the better it is.
Example input: Passage: The outbreak of the Seven Years' War in Europe in 1756 resulted in renewed conflict between French and British forces in India. The Third Carnatic War spread beyond southern India and into Bengal where British forces captured the French settlement of Chandernagore in 1757. However, the war was decided in the south, where the British successfully defended Madras, and Sir Eyre Coote decisively defeated the French, commanded by Comte de Lally at the Battle of Wandiwash in 1760. After Wandiwash, the French capital of Pondicherry fell to the British in 1761. The war concluded with the signing of the Treaty of Paris in 1763, which returned Chandernagore and Pondichéry to France, and allowed the French to have "factories" in India but forbade French traders from administering them. The French agreed to support British client governments, thus ending French ambitions of an Indian empire and making the British the dominant foreign power in India.
Example output: Which french settlement did the British capture first, Chandernagore or Pondicherry?
Example explanation: This is a good question since it involves a comparison around a particular event, "British capturing the French settlement", which requires looking at more than a single sentence.
Q: Passage: Somalias population is expanding at a growth rate of 1.75% per annum and a birth rate of 40.87 births/1,000 people. The total fertility rate of Somalia is 6.08 children born per woman (2014 estimates), the fourth highest in the world, according to the CIA World Factbook. Most local residents are young, with a median age of 17.7 years; about 44% of the population is between the ages of 0–14 years, 52.4% is between the ages of 15–64 years, and only 2.3% is 65 years of age or older. The Sex ratio is roughly balanced, with proportionally about as many men as women.
A: | How many more percentage points of the population is between 0 and 14 years than 65 and older? | 3 | NIv2 | task026_drop_question_generation | fs_opt | [
0.8438441753387451,
0.6726169586181641,
-0.016712985932826996,
-0.3459850251674652,
0.41812455654144287,
-0.7438927292823792,
0.7026962041854858,
0.6773670315742493,
0.44904273748397827,
0.2543509006500244,
-0.5764356851577759,
0.6852476596832275,
-1.2150194644927979,
0.06500192731618881,
... |
In this task you will be given a process, and a question. The process contains a sequence of steps that happen in order. The question asks about the effect of a certain event on another event. If the first event has a positive effect on the second event, answer with "for", if it has a negative effect, answer with "against". If there's no causal relationship between the two, answer with "none".
[Q]: Process: -Owls have specially adapted eyes that see better at night -Owls sit at high points in trees and look around -When an owl spots a rodent they track it -When the rodent is standing still the owl swoops down -The owl grabs the rodent with their tallons -The owl uses their beak to eat the rodent.
Question: What is the effect of less forests around on humans decide to decrease the owl population.?
[A]: none
[Q]: Process: -Bacteria enter the body -Bacteria start to divide and grow -The uncontrolled growth takes away resources from other cells -Other cells cannot function properly -We feel unwell -The growth and division of bacteria produce toxins -Toxins harm the body -The body tries to react to the toxins -The body's natural defenses can sometimes cause us to feel unwell.
Question: What is the effect of a person has a poor immune system on more bacteria enters the body.?
[A]: for
[Q]: Process: -Food leaves the esophagus and enters the stomach -The stomach churns the food -With the aid of stomach acids -The food becomes a thick liquid -Is then passed to the small intestine.
Question: What is the effect of less food enters the esophagus on less stomach acid will be produced.?
[A]: | against
| 5 | NIv2 | task1727_wiqa_what_is_the_effect | fs_opt | [
0.06304700672626495,
0.36317574977874756,
-0.6287807822227478,
0.01026073843240738,
-0.38541778922080994,
-0.7214769124984741,
0.21450288593769073,
0.8463586568832397,
0.055253028869628906,
0.022769905626773834,
-0.7063276767730713,
0.051146894693374634,
-1.173671007156372,
0.1412666738033... |
You are given a review about a place. You need to provide a rating from "1 star" to "5 stars" for this place.
Ex Input:
I quite like this venue. It has a vintage, cozy feel although it is a decently large venue. It's been around for ages, and hosted many a performance... you can almost feel its history when you walk in with remnants of its original theatrical structure giving homage to its origins. \nOk so maybe that last sentence was a tad romanticized and sentimental... but it's my story and I'm sticking to it.\n\nI've already seen quite a few shows here, well-known bands as well as the more obscure, and it's never disappointed. It's usually standing-only... which I prefer so I can dance to my favourite songs, the sound is good, the bar has decently-priced beers and friendly servers, there is an optional coat check and a balcony to boot. \n\nConveniently located in Griffintown near Autoroute Ville-Marie (720) and Lionel-Groulx station, it's easily accessible by metro or car. Corona Theatre has quickly become one of my favourite concert venues of Montreal. I'm a fan.
Ex Output:
4 stars
Ex Input:
Fantastic service and fresh fish! We had a great time and the sushi chef was kind enough to make a yellowfin salad to try while we were eating. I tried only the tuna, halibut and salmon but all three where fresh and tasty. Top it off with a tab that would have been doubled at a place like Ra or Kona, while getting lesser product. Thank you, Sushi Kee and we will be back soon!
Ex Output:
4 stars
Ex Input:
Stopped by to check out this place and loved it. Even though we visited a few months ago when it was very new, the service and food were excellent. Wonderful outdoor area with lots of comfortable furniture. I'll be back with more friends.
Ex Output:
| 5 stars
| 1 | NIv2 | task1292_yelp_review_full_text_categorization | fs_opt | [
0.5143059492111206,
-0.3349091112613678,
-0.6913071274757385,
-0.1870115101337433,
0.7743253707885742,
-0.8548169732093811,
0.2490857094526291,
0.5549564957618713,
-0.09958627820014954,
0.3516817092895508,
0.8225944638252258,
-0.278490275144577,
-0.26237156987190247,
-0.019223932176828384,... |
Given the task definition and input, reply with output. 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 determine whether The Tail is the intention of the PersonX from the Head or not. The intention is the likely intent or desire of PersonX behind the execution of an event. For example, given the Head PersonX gives PersonY gifts, an intention might be that PersonX wanted to be thoughtful. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Head: PersonX accepts the job<sep>Tail: to be employed
| Yes | 5 | NIv2 | task1201_atomic_classification_xintent | zs_opt | [
0.23869669437408447,
0.42494717240333557,
0.44547486305236816,
-0.030192404985427856,
-0.39318418502807617,
-0.4465959072113037,
0.8592693209648132,
0.5771585702896118,
-0.3494766354560852,
-0.1711253821849823,
-0.46343377232551575,
-0.48963087797164917,
-0.8600253462791443,
0.200597316026... |
Detailed Instructions: In this task, you are given two sets, and a question. You need to find whether an element is at the intersection of two given sets. A Set is shown by two curly braces and comma-separated numbers inside, like {1, 2, 3}. The intersection of two given sets is the largest set which contains all the elements that are common to both sets. An element is at the intersection of two given sets, A and B, if common to both A and B. Classify your answers into 'Yes' or 'No'.
Problem:Set1: '{1, 3, 6, 7, 9, 10, 11, 12, 18, 20}', Set2: '{2, 3, 7, 12, 14, 15, 17, 18}'. Is the element '14' in the intersection of Set1 and Set2 ?
Solution: | No | 8 | NIv2 | task245_check_presence_in_set_intersection | zs_opt | [
0.4740402102470398,
0.1301683485507965,
-0.5290262699127197,
0.2454846352338791,
-0.28369230031967163,
-0.41883453726768494,
1.0913634300231934,
0.6441129446029663,
-0.09362304210662842,
0.07667751610279083,
-0.375699907541275,
0.2602149546146393,
-0.02120818942785263,
-0.19687290489673615... |
You are given a math word problem and you are supposed to apply addition or subtraction mathematical operators on the numbers embedded in the text to answer the following question and then only report the final numerical answer.
Mrs. Santiago has 58 red roses . Mrs. Garrett has 24 . How many more red roses does Mrs. Santiago have than Mrs. Garrett ? | 34 | 0 | NIv2 | task865_mawps_addsub_question_answering | zs_opt | [
-0.1688205748796463,
0.8929858207702637,
-0.28804564476013184,
-0.38880130648612976,
-0.019218936562538147,
-0.9307305216789246,
0.39949366450309753,
0.8924980163574219,
0.24958842992782593,
-0.6788734197616577,
-0.6254248023033142,
0.10603306442499161,
0.041783034801483154,
0.547892749309... |
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 works have been created before? What is still missing in the previous works? What are the high-level research questions? How might this help other research or researchers?), Purpose (What specific things do the researchers want to do? What specific knowledge do the researchers want to gain? What specific hypothesis do the researchers want to test?), Method (How did the researchers do the work or find what they sought? What are the procedures and steps of the research?), or Finding (What did the researchers find out? Did the proposed methods work? Did the thing behave as the researchers expected?). ",
[EX Q]: Sentence: Readmission risk in younger patients was significantly associated with hospital 30-day risk-standardized readmission rates for elderly Medicare patients for all 3 conditions.
Section: purpose
[EX A]: False
[EX Q]: Sentence: and may play a role in the pathology.
Section: background
[EX A]: True
[EX Q]: Sentence: Pathogens that spill over between species cause a significant human and animal health burden.
Section: method
[EX A]: | False
| 6 | NIv2 | task1164_coda19_section_correction_classification | fs_opt | [
0.15308944880962372,
0.0715138241648674,
-0.6986510157585144,
-0.31798475980758667,
-0.14403991401195526,
-0.2095673680305481,
0.6142501831054688,
1.041413426399231,
0.1972143054008484,
-0.11131925880908966,
-0.9370739459991455,
0.4502900242805481,
-0.18974298238754272,
0.3834393620491028,... |
Detailed Instructions: You are given a sentence and a question in the input. If the information provided in the sentence is enough to answer the question, label "Yes", otherwise label "No". Do not use any facts other than those provided in the sentence while labeling "Yes" or "No". There are only two types of valid responses: Yes and No.
See one example below:
Problem: Sentence: GOP leaders submitted the new offer Tuesday afternoon in an effort to appease Democrats, whose votes are needed to avert a shutdown of federal agencies, several House and Senate aides said. Question: Who has to be appeased to keep the government open?
Solution: Yes.
Explanation: The sentence says that "the Democrats" have to be appeased, which answers the question. So, the correct label should be "Yes".
Problem: Sentence: His name is Sammy.
Question: What is the name of Katie's dog?
Solution: | Yes. | 4 | NIv2 | task050_multirc_answerability | fs_opt | [
-0.6017343997955322,
0.18790140748023987,
0.37783053517341614,
0.6444792151451111,
-0.4874189794063568,
-1.870021104812622,
0.3717336058616638,
0.7255224585533142,
0.1579977571964264,
0.08866756409406662,
-0.1124345064163208,
-0.10966907441616058,
-0.10789241641759872,
-0.06196592003107071... |
Instructions: In this task, you are given a sentence in Persian, and your task is to translate it into English.
Input: الجنید به محض دریافت این تهدید، تصویر پیغام را در دیوار فیسبوکش به نمایش گذاشت.
Output: | Once Al-Junid got the threat, he posted its screenshot on his Facebook wall. | 3 | NIv2 | task662_global_voices_fa_en_translation | zs_opt | [
-1.653672456741333,
1.1662216186523438,
-0.2577751874923706,
-1.209500789642334,
-0.6307564377784729,
0.1770247519016266,
0.7217651009559631,
-0.1499059647321701,
0.3313175439834595,
-0.06180589273571968,
0.20279204845428467,
0.2021656483411789,
-1.0168638229370117,
0.25160712003707886,
... |
Q: In this task, you are given Twitter posts. Your task is to label the post's emotion (as expressed by the user) as sadness, joy, love, anger, fear, or surprise.
i was more annoyed with the info dump because it made the book too long but i feel i ll miss something if i skipped it which annoyed me more pages
A: | anger | 7 | NIv2 | task512_twitter_emotion_classification | zs_opt | [
-1.077107548713684,
-0.04913513362407684,
0.2783510684967041,
-0.13952293992042542,
0.08560964465141296,
-0.31985151767730713,
0.4602532386779785,
0.03997111693024635,
-0.003025020007044077,
0.11537256836891174,
0.1274382472038269,
-0.6516776084899902,
-0.7426705360412598,
0.20267078280448... |
Detailed Instructions: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Italian.
Q: و كايلي — أعني أن كايلي كانت بمثابة طفلتها هي.
A: | E Kyle... voglio dire, era quasi come se Kyle fosse sua figlia. | 9 | NIv2 | task1106_ted_translation_ar_it | zs_opt | [
-0.45280513167381287,
1.639775276184082,
-0.6609588861465454,
0.05551721528172493,
-0.7726743817329407,
-0.08407486975193024,
0.937774121761322,
1.369028091430664,
0.7078620195388794,
-0.0564303882420063,
0.03863061964511871,
0.2597561478614807,
-0.02453378587961197,
0.9527188539505005,
... |
You are given a sentence in Italian. Your job is to translate the Italian sentence into Farsi.
Con un cellulare potete fermare un crimine contro l'umanità in Siria. Con un cellulare, | با یک گوشی تلفن همراه ، می تونید از یک جنایت علیه بشریت در سوریه فیلمبرداری کنید. با یک گوشی تلفن همراه | 0 | NIv2 | task1254_ted_translation_it_fa | zs_opt | [
-0.16282735764980316,
0.7882384061813354,
-0.49989089369773865,
-0.7411322593688965,
-0.7658729553222656,
-0.3991287350654602,
-0.10195285826921463,
0.9082596302032471,
0.1811085343360901,
0.9898394346237183,
-0.9741429090499878,
0.8436846733093262,
0.026354346424341202,
-0.175386443734169... |
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.
Problem:[11.276, 90, 2.655, 18.193, -49, -45, -9.944]
Solution: | [90, -49, -45] | 8 | NIv2 | task367_synthetic_remove_floats | zs_opt | [
-0.1615736335515976,
0.5172626376152039,
-0.3285975158214569,
-1.033090353012085,
-0.5553079843521118,
-0.6742140054702759,
1.2682240009307861,
0.5055022239685059,
-0.18702873587608337,
0.295149028301239,
-0.5894958972930908,
0.318053662776947,
-0.16459223628044128,
0.1884058117866516,
-... |
Detailed Instructions: Given an entity as input, output another entity which is part of the input entity. These are entities of meronym. In linguistics, meronymy is a semantic relation between a meronym denoting a part and a holonym denoting a whole. In simpler terms, a meronym (i.e., output entity) is in a part-of relationship with its holonym (i.e., input entity).
Problem:neocortex
Solution: | pyramidal cell | 8 | NIv2 | task471_haspart_answer_generation | zs_opt | [
-0.6731768846511841,
0.38384947180747986,
0.3717423677444458,
0.1247435063123703,
-0.578323483467102,
-0.047895170748233795,
-0.11942487955093384,
0.3713831305503845,
0.7208843231201172,
-0.8941490054130554,
-0.6655979156494141,
-0.0011972880456596613,
-0.18539749085903168,
0.1581351459026... |
Given the task definition, example input & output, solve the new input case.
Given an Amazon review, indicate whether it is a 'Positive Review' or 'Negative Review'.
Example: I was very surprised at the high quality of the stitching, the sturdiness of the handles and the padding for my laptop. The price is amazingly low and the look is very good. I am quite happy with this purchase. It fit my MacBook Pro perfectly, with a little bit of room to spare.
Output: Positive Review
This rating is correct based on this review provided by the user as they liked the product very much and they were surprised that product is so good.
New input case for you: It doesn't fit plush against the back, but it works great so, a good deal for the price for me. No problems have come up.
Output: | Positive Review | 1 | NIv2 | task1343_amazon_us_reviews_rating | fs_opt | [
0.13135868310928345,
-0.4482450783252716,
-0.3474804162979126,
0.051434777677059174,
0.6660487651824951,
-0.14693428575992584,
0.6003515720367432,
0.6268168687820435,
0.9552149176597595,
0.768902599811554,
-0.26909339427948,
-0.3060718774795532,
0.32655173540115356,
-0.22412648797035217,
... |
Detailed Instructions: In this task, you are given a sentence in the Japanese language and your task is to convert it into the English language. In translation, keep numbers as it is and make it sentence case (capitalize only the first word of each sentence and noun).
Q: オリンピックでの唯一のアーチェリーのイベントがターゲット・リカーブ競技で、イングレイが選手権で参加するただ一つのイベントである。
A: | The only Olympic archery event is the target recurve competition, and it is the only event Ingley will be participating in at Nationals. | 9 | NIv2 | task436_alt_ja_en_translation | zs_opt | [
0.4497615694999695,
0.4185529351234436,
0.43508589267730713,
-0.8078820109367371,
0.48953109979629517,
-0.40107181668281555,
0.29942089319229126,
0.2637767195701599,
0.06731174886226654,
-0.4773772656917572,
-0.4009769558906555,
0.01355573907494545,
-0.3785717487335205,
0.4371395707130432,... |
Given the task definition and input, reply with output. In this task, you are given a text which is the body of a document. You are given a question and options. Pick the correct number. Don't generate anything else apart from the numbers provided in options.
Context: Gyros is a genus of moths of the Crambidae family.
Question: The document can be classified to which topic?
Options: 1)WrittenWork, 2)Album, 3)Film, 4)Artist, 5)Animal
| 5 | 5 | NIv2 | task633_dbpedia_14_answer_generation | zs_opt | [
-0.45520904660224915,
0.5402168035507202,
0.28557848930358887,
0.4324682354927063,
-0.07309093326330185,
-0.6689445972442627,
-0.23242045938968658,
-0.20733191072940826,
-0.09460760653018951,
-0.44628608226776123,
-1.288620948791504,
0.02698945812880993,
0.21509569883346558,
0.304561674594... |
In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link].
One example: Este artículo no es un artículo de investigación, ya que sólo muestra cómo programar un robot mediante la herramienta de lógica difusa. Este tema ya ha sido propuesto como solución en navegación de robots.
Solution is here: es
Explanation: This review is written in spanish. Hence, the label is 'es'.
Now, solve this: El artículo presentado, describe cómo modelar un sistema multiagente de acuerdo a la metodología orientada a agentes “GAIA” para modelar la trazabilidad de requisitos. La propuesta de GAIA para modelar la trazabilidad de los requisitos mediante Sistemas multiagente parece ser novedosa. La presentación del artículo es bastante confusa, el documento presenta algunos errores ortográficos, de redacción y de estructuración, se referencia a tablas que son figuras, se presentan tablas no referenciadas, no existe la figura 6, el ítem “resultados” debe ser cambiado o descrito en otro lugar del documento. Conclusiones insuficientes.
Solution: | es | 6 | NIv2 | task265_paper_reviews_language_identification | fs_opt | [
-0.8979336023330688,
0.31727278232574463,
0.4587988257408142,
0.28330451250076294,
0.032491788268089294,
-1.1024136543273926,
0.49167096614837646,
0.691697359085083,
-0.2565368115901947,
0.45816099643707275,
-0.4424572288990021,
0.22074168920516968,
0.06368652731180191,
0.03650552406907081... |
You will be given a definition of a task first, then some input of the task.
In this task, you need to provide the parts-of-speech tag of a word present in a sentence specified within curly braces ( '{{ ... }}' ). The parts-of-speech tags are coarse labels that represent a category of words with similar grammatical properties. The list of part-of-speech tags i.e. tagset of this corpus is 'ADJ': Adjectives are words that typically modify nouns and specify their properties or attributes, 'ADP': Adposition is a cover term for prepositions and postpositions, 'ADV': Adverbs are words that typically modify verbs for such categories as time, place, direction or manner, 'AUX': An auxiliary is a function word that accompanies the lexical verb of a verb phrase and expresses grammatical distinctions not carried by the lexical verb, such as person, number, tense, mood, aspect, voice or evidentiality, 'CCONJ': A coordinating conjunction is a word that links words or larger constituents without syntactically subordinating one to the other and expresses a semantic relationship between them, 'DET': Determiners are words that modify nouns or noun phrases and express the reference of the noun phrase in context, 'INTJ': An interjection is a word that is used most often as an exclamation or part of an exclamation, 'NOUN': Nouns are a part of speech typically denoting a person, place, thing, animal or idea, 'NUM': A numeral is a word, functioning most typically as a determiner, adjective or pronoun, that expresses a number and a relation to the number, such as quantity, sequence, frequency or fraction, 'PART': Particles are function words that must be associated with another word or phrase to impart meaning and that do not satisfy definitions of other universal parts of speech, 'PRON': Pronouns are words that substitute for nouns or noun phrases, whose meaning is recoverable from the linguistic or extralinguistic context, 'PROPN': A proper noun is a noun (or nominal content word) that is the name (or part of the name) of a specific individual, place, or object, 'PUNCT': Punctuation marks are non-alphabetical characters and character groups used in many languages to delimit linguistic units in printed text, 'SCONJ': A subordinating conjunction is a conjunction that links constructions by making one of them a constituent of the other. The subordinating conjunction typically marks the incorporated constituent which has the status of a (subordinate) clause, 'SYM': A symbol is a word-like entity that differs from ordinary words by form, function or both, 'VERB': A verb is a member of the syntactic class of words that typically signal events and actions, can constitute a minimal predicate in a clause, and govern the number and types of other constituents which may occur in the clause, 'X': The tag X is used for words that for some reason cannot be assigned a real part-of-speech category.
Sentence: Questar has already informed us {{ that }} they would help obtain parts / materials to our specifications if it helps achieve an in - service date of May 1 .
Word: that
Output: | SCONJ | 1 | NIv2 | task583_udeps_eng_coarse_pos_tagging | zs_opt | [
0.7689568996429443,
0.17556200921535492,
-0.04057401418685913,
-0.005003396421670914,
0.012205461040139198,
-0.4732047915458679,
0.8636943101882935,
0.5187782049179077,
-0.43037480115890503,
-0.1308094561100006,
-0.2694850265979767,
0.019700869917869568,
-0.4441679120063782,
0.523766875267... |
Given the task definition and input, reply with output. In this task, you are given two strings A, B. Find the longest common substring in the strings A and B.
mkRlgPkFoZcmEPjr, iVPkFoZcmHAxO
| PkFoZcm | 5 | NIv2 | task600_find_the_longest_common_substring_in_two_strings | zs_opt | [
-0.03657529503107071,
0.8007084727287292,
0.4556807279586792,
-0.07814548909664154,
-0.21452507376670837,
-0.1296907365322113,
0.4975568652153015,
-1.3289821147918701,
0.07333013415336609,
-0.6638218760490417,
-0.8142072558403015,
-0.5471267700195312,
-0.10325680673122406,
0.31790184974670... |
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 list you should output 0 for that list.
[[-29, -46, 2, -48], [-48, 38, -16, -34], [-26, 4], [22, 43, 0, -24], [28, -30, -23], [45, -38, 17], [-36, -3, 35], [14, -20, -6], [-27, -47, -25], [29, -21, 37, -46], [2, -1], [-38, -41, 21, 31], [-9, -4, 33]]
[4416, -992256, -104, 0, -840, -38, -36, 1680, 0, -46, 2, -38, -4]
[[-9, -30], [-10, 7], [50, -8], [-42, 3, 31, 46, -50], [-23, -9, 25, -10, 7], [9, 19, -27], [-46, 49, -39], [-29, -5, -2, 35, 32], [38, -50, 43, -19], [6, -3, 26, -24, -7], [-1, -49, -35]]
[-30, -10, -400, 96600, -10, 0, -46, -64, -1900, -3744, 0]
[[28, -32, 8, 34], [32, -26, 6], [24, -33, 21, -30], [12, 33, -35, -4, 24], [17, -28, 16, -31], [18, -41], [-22, -35], [-49, 21, -2, 37, -31], [33, -46, -9, -44, -47], [24, -11, -3, 10], [17, -2, 48], [45, 22, -16, 24, -21], [-7, -24], [24, -48, 35, 1]]
| [-243712, -4992, -720, -1152, -448, 18, -22, -2, 2024, 240, -96, -8448, -24, -1152]
| 0 | NIv2 | task851_synthetic_multiply_evens | fs_opt | [
-0.0019363148603588343,
0.1510530412197113,
-0.9912536144256592,
0.06222517043352127,
-0.024846479296684265,
-0.1423390656709671,
0.8323007822036743,
0.8943077325820923,
-0.598787784576416,
-0.4110565781593323,
-0.8321660161018372,
0.18523123860359192,
-0.5420976877212524,
-0.3736364245414... |
Instructions: The provided file includes inquiries about restaurants in Italian, and we ask you to translate those to English language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for fully capitalized special placeholders (e.g. NUMBER, DATE, TIME). Please do the same in your translations.
Input: trova ristoranti con punteggio pari a 5.
Output: | find the restaurants with a rating of 5 . | 3 | NIv2 | task255_spl_translation_it_en | zs_opt | [
-0.07374085485935211,
0.6010615229606628,
0.012594159692525864,
0.36381298303604126,
-0.04668136686086655,
-0.4340958297252655,
0.6996645927429199,
0.7424713373184204,
-0.5052269697189331,
-0.2717258930206299,
0.3742613196372986,
0.6096559762954712,
-0.2460223287343979,
0.26996910572052,
... |
In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Q: Context Word: how to tune a room.
A: Sentence 1: Millie tried to watch a video on the best on how to tune a room but the _ was too soft.
Answer1: video.
Sentence 2: Millie tried to watch a video on the best on how to tune a room but the _ was too loud.
Answer2: room.
****
Q: Context Word: hybrid vegetables.
A: Sentence 1: Sue wanted to grow hybrid vegetables in the garden of her rooftop garden but the _ were too difficult.
Answer1: vegetables.
Sentence 2: Sue wanted to grow hybrid vegetables in the garden of her rooftop garden but the _ was too dry.
Answer2: garden.
****
Q: Context Word: university course.
A: | Sentence 1: She changed her university course from mathematics to history, because the _ course is too complex.
Answer1: mathematics.
Sentence 2: She changed her university course from mathematics to history, because the _ course is more simple.
Answer2: history.
****
| 4 | NIv2 | task029_winogrande_full_object | fs_opt | [
0.44999152421951294,
0.41960230469703674,
0.02837069146335125,
-0.14752189815044403,
0.801917314529419,
-0.7013254165649414,
0.5132075548171997,
1.214425802230835,
-0.8561479449272156,
-0.19871917366981506,
-0.35373905301094055,
-0.03370005264878273,
-0.6136049032211304,
-0.015889925882220... |
Detailed Instructions: Given a passage, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.
Q: There is no consensus about the impact of a high BMI on postoperative morbidity and survival after esophagectomy. The aim of this study was to determine the influence of a high BMI on postoperative complications and survival in a large cohort of esophageal cancer patients.', 'From January 2006 to December 2012, 1,342 consecutive esophageal cancer patients who underwent esophagectomy were included in this study. Patients were divided into three groups: 950 patients were classified as normal BMI (BMI 18.5-24.9 kg/m(2)), 279 were classified as high BMI (BMI ≥ 25 kg/m(2)), and 113 as low BMI (BMI < 18.5 kg/m(2)). Multivariate logistic regression models were used to identify confounding factors associated with postoperative complications. The impact of BMI on overall survival (OS) was estimated by the Kaplan-Meier method and Cox proportional hazard models.', 'The predominance of pathological type was esophageal squamous cell carcinoma (n = 1,280, 95.4 %). Overall morbidity, mortality, and hospital stay did not differ among groups. The incidence of pneumonia was higher in patients with high BMI compared with those with normal BMI (14.7 vs. 9.9 %, P = 0.025). However, chylothorax was less frequent in high-BMI group (0.4 % in high-BMI group, 3.1 % in normal group, and 3.5 % in low group, P = 0.011). Logistic regression analysis revealed high BMI was independently associated with decreased incidence of chylothorax [HR 0.86; 95 % confidence interval 0.76-0.97]. Overweight and obese patients had significantly better overall survival than underweight patients (median OS 55.6 vs. 32.5 months, P = 0.013), while the pathological stage was significantly higher in underweight patients (P = 0.001). In multivariate analysis, T status, N status, differentiation grade, and tumor length were identified as independent prognostic factors.
A: | Is a high body mass index in esophageal cancer patients associated with adverse outcomes following esophagectomy? | 9 | NIv2 | task847_pubmedqa_question_generation | zs_opt | [
0.7593622207641602,
-0.0260978601872921,
-0.5719592571258545,
-0.16504395008087158,
0.7650548219680786,
-0.49074819684028625,
1.0546494722366333,
0.9361839890480042,
0.3253805935382843,
0.18012399971485138,
-0.6597217321395874,
0.6763348579406738,
-0.5087565183639526,
0.6702388525009155,
... |
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.
Here are the defications of each category:
1. majority: Describing the majority values (most or all) over one column, with the scope of all table rows or a subset of rows
2. unique: Describing one unique row, regarding one column, with the scope of all table rows or a subset of rows
3. Superlative: Describing the maximum or minimum value in a column, with the scope of all table rows or a subset of rows
4. Ordinal: Describing the n-th maximum or minimum value in a column, with the scope of all table rows or a subset of rows
5. Comparative: Comparing two rows in the table, regarding their values in one column
6. Count: counting some rows in the table based on the values in one column, with the scope of all table rows or a subset of rows
7. Aggregation: Describing the sum or average value over a column, with the scope of all table rows or a subset of rows.
Here are the definitions of logical operators for understanding of command:
1. count: returns the number of rows in the view.
2. only: returns whether there is exactly one row in the view.
3. hop: returns the value under the header column of the row.
4. and: returns the boolean operation result of two arguments.
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column.
6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column.
7. argmax/argmin: returns the row with the max/min value in header column.
8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column.
9. eq/not_eq: returns if the two arguments are equal.
10. round_eq: returns if the two arguments are roughly equal under certain tolerance.
11. greater/less: returns if the first argument is greater/less than the second argument.
12. diff: returns the difference between two arguments.
13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument.
14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument.
15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument.
16. filter_all: returns the view itself for the case of describing the whole table
17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument.
18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument.
19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument.
20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument.
21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument.
22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.
One example: round_eq { sum { all_rows ; casinos } ; 217 }
Solution is here: aggregation
Explanation: In this example sum returns the sum of the values in all of the casinos rows. Hence, aggregation is right category.
Now, solve this: most_greater { all_rows ; conversions ; 50 }
Solution: | majority | 6 | NIv2 | task212_logic2text_classification | fs_opt | [
0.20780232548713684,
-0.29526233673095703,
-0.47496429085731506,
0.2986098527908325,
0.3639369606971741,
-0.5314186215400696,
0.7913339734077454,
0.6703905463218689,
0.3697599768638611,
0.007297763600945473,
-0.04132962226867676,
0.1612723469734192,
-0.05199266970157623,
0.4443542957305908... |
Detailed Instructions: 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 building blocks for a command. There are only six actions: 'I_LOOK', 'I_WALK', 'I_RUN', 'I_JUMP', 'I_TURN_LEFT', and 'I_TURN_RIGHT'. These actions respectively align with the commands 'look', 'walk', 'run', 'jump', 'turn left', and 'turn right'. For commands, 'left' and 'right' are used to denote the direction of an action. opposite turns the agent backward in the specified direction. The word 'around' makes the agent execute an action while turning around in the specified direction. The word 'and' means to execute the next scope of the command following the previous scope of the command. The word 'after' signifies to execute the previous scope of the command following the next scope of the command. The words 'twice' and 'thrice' trigger repetition of a command that they scope over two times or three times, respectively. Actions and commands do not have quotations in the input and output.
Problem:I_LOOK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK
Solution: | look and walk around left twice | 8 | NIv2 | task129_scan_long_text_generation_action_command_short | zs_opt | [
0.330997496843338,
0.8954766988754272,
-0.5590150356292725,
-0.0994601845741272,
-0.09365760535001755,
0.4906184673309326,
0.04663888365030289,
0.5761557817459106,
-0.43583202362060547,
-0.3296689987182617,
-0.6257133483886719,
-0.48231884837150574,
-0.6071388125419617,
0.04278124123811722... |
You are given a sentence in Polish. Your job is to translate the Polish sentence into Arabic.
Let me give you an example: Poradzi sobie, ale trzeba na nią uważać.
The answer to this example can be: لذا نعلم أنها ستكون ناجحة. ولكن علينا مراقبتها
Here is why: The Polish sentence is correctly translated into Arabic, because the meaning is preserved.
OK. solve this:
I w końcu - oto zdjęcie naszych pacjentów po przeszczepie szpiku, którzy spotykają się co roku w Stanford.
Answer: | وأخيرا — وهذه صورة لكم للناجين من عمليات زراعة نخاع العظام الذين يجتمعون سنويا في ستانفورد | 8 | NIv2 | task1259_ted_translation_pl_ar | fs_opt | [
-0.3598310649394989,
0.8938817381858826,
-0.10252577811479568,
-0.8801779747009277,
-0.11625857651233673,
-0.8441961407661438,
1.032105565071106,
-0.4564915895462036,
0.6335451602935791,
0.5071557760238647,
-0.5713986158370972,
0.7770432233810425,
-1.0155986547470093,
0.7068323493003845,
... |
In this task, you are given a abstract of article and corresponding title of an article. Your task is to generate label "yes" if title is right for article, otherwise generate "no".
Q: Abstract: Candida albicans produces lipid metabolites that are functionally similar to host prostaglandins. These studies, using mass spectrometry, demonstrate that C. albicans produces authentic prostaglandin E(2) (PGE(2)) from arachidonic acid. Maximal PGE(2) production was achieved at 37 degrees C in stationary-phase culture supernatants and in cell-free lysates generated from stationary-phase cells. Interestingly, PGE(2) production is inhibited by both nonspecific cyclooxygenase and lipoxygenase inhibitors but not by inhibitors specific for the cyclooxygenase 2 isoenzyme. The C. albicans genome does not possess a cyclooxygenase homolog; however, several genes that may play a role in prostaglandin production from C. albicans were investigated. It was found that a C. albicans fatty acid desaturase homolog (Ole2) and a multicopper oxidase homolog (Fet3) play roles in prostaglandin production, with ole2/ole2 and fet3/fet3 mutant strains exhibiting reduced PGE(2) levels compared with parent strains. This work demonstrates that the synthesis of PGE(2) in C. albicans proceeds via novel pathways.. Title: Nuclear accumulation of HDAC4 in ATM deficiency promotes neurodegeneration in ataxia-telangiectasia
A: no
****
Q: Abstract: The mobilization of nucleosomes by the ATP-dependent remodeler INO80 is quite different from another remodeler (SWI/SNF) that is also involved in gene activation. Unlike that recently shown for SWI/SNF, INO80 is unable to disassemble nucleosomes when remodeling short nucleosomal arrays. Instead, INO80 more closely resembles, although with notable exceptions, the nucleosome spacing activity of ISW2 and ISW1a, which are generally involved in transcription repression. INO80 required a minimum of 33 to 43 bp of extranucleosomal DNA for mobilizing nucleosomes, with 70 bp being optimal. INO80 prefers to move mononucleosomes to the center of DNA, like ISW2 and ISW1a, but does so with higher precision. Unlike ISW2/1a, INO80 does not require the H4 tail for nucleosome mobilization; instead, the H2A histone tail negatively regulates nucleosome movement by INO80. INO80 moved arrays of two or three nucleosomes with 50 or 79 bp of linker DNA closer together, with a final length of ∼30 bp of linker DNA or a repeat length of ∼177 bp. A minimum length of >30 bp of linker DNA was required for nucleosome movement and spacing by INO80 in arrays.. Title: The INO80 ATP-dependent chromatin remodeling complex is a nucleosome spacing factor.
A: yes
****
Q: Abstract: Human placental lactogen and unconjugated estriol concentrations in maternal serum were evaluated in 100 uneventful twin pregnancies, and these values were compared with those observed in 16 twin pregnancies associated with intrauterine growth retardation or single intrauterine fetal death. In pregnancies associated with intrauterine growth retardation (n = 8), human placental lactogen levels were at the lower limit of normal range for singleton pregnancies, whereas estriol levels were normal in most cases. When one of the fetuses had died before week 33 of pregnancy (n = 5), both human placental lactogen and estriol levels were low and they were almost at the levels in singleton pregnancy. When intrauterine fetal death occurred after week 36 of pregnancy (n = 3), both hormone levels remained normal until term. Thus human placental lactogen rather than estriol is a good indicator of intrauterine growth retardation in twin pregnancy. Both human placental lactogen and estriol are useful for the monitoring of the surviving fetus in the case of single intrauterine fetal death.. Title: Human placental lactogen and unconjugated estriol concentrations in twin pregnancy: monitoring of fetal development in intrauterine growth retardation and single intrauterine fetal death.
A: | yes
****
| 4 | NIv2 | task1587_scifact_classification | fs_opt | [
0.3342844843864441,
-0.02691357582807541,
-0.7948567271232605,
0.451315313577652,
0.4796832799911499,
-0.05152047052979469,
0.30117958784103394,
0.9049639105796814,
-0.28875815868377686,
0.6455807685852051,
-0.737533450126648,
0.14062127470970154,
-0.3282480239868164,
0.15859195590019226,
... |
Given the task definition, example input & output, solve the new input case.
In this task, you are given a context sentence containing a blank (_). You are expected to fill the blank with one word to make the sentence convey a cultural stereotype. A stereotype is an over-generalized belief about a particular group of people. Your answer must not contain more than one word.
Example: Context: Every commander tends to be _.
Output: controlling
Commanders are controlling is an existing and valid stereotype.
New input case for you: Context: Vietnam is such a _ country.
Output: | communist | 1 | NIv2 | task277_stereoset_sentence_generation_stereotype | fs_opt | [
0.0061034392565488815,
0.42150455713272095,
-0.6389896869659424,
0.016405638307332993,
0.762794017791748,
-0.29475489258766174,
0.6134936809539795,
1.7711470127105713,
0.25056615471839905,
-0.20887891948223114,
-0.37481752038002014,
-0.510375440120697,
0.04477131366729736,
0.10171046853065... |
instruction:
In this task your given two statements in Tamil. You must judge whether the second sentence is the cause or effect of the first one. Label the instances as "cause" or "effect" based on your judgment. The sentences are separated by a newline character.
question:
போக்குவரத்தை ஒழுங்குபடுத்தும் விளக்கு மஞ்சள் நிறமாக மாறியது
ஓட்டுநர் வேகம் குறைப்பானை அழுத்தினார்
answer:
effect
question:
நான் ஆத்திரம் தணிந்து சாந்தமானேன்
நான் நீண்ட மூச்சு வாங்கினேன்
answer:
cause
question:
காசாளர் பணப்பதிவேட்டைத் திறந்தார்
அந்த வாடிக்கையாளர் தன் பணத்தை ஒப்படைத்தாள்
answer:
| cause
| 9 | NIv2 | task1177_xcopa_commonsense_cause_effect_ta | fs_opt | [
-0.10987815260887146,
0.0974959284067154,
0.31544309854507446,
-0.4704679548740387,
-0.19695305824279785,
-0.6547606587409973,
-0.30207177996635437,
1.0042277574539185,
0.27097323536872864,
0.3662654161453247,
-0.5194358229637146,
-0.2515454888343811,
-0.4049854576587677,
-0.23986631631851... |
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Hebrew.
そこで私は仲間たちと共にここキュラソーで幼生サンゴが生存するために最も大事な時期に必要なもの求めているものそしてその過程で私たちにできることを探し出そうとしています | אז במחקר שאני עושה עם הקולגות שלי בקורסאו, אנחנו מנסים להבין מה אלמוגים תינוקות צריכים בשלב הראשוני הקריטי הזה, מה הם מחפשים ואיך אנחנו יכולים לעזור להם בתהליך. | 0 | NIv2 | task1225_ted_translation_ja_he | zs_opt | [
-0.009486367926001549,
0.22658959031105042,
-0.4336170554161072,
-0.5756166577339172,
-0.8561164140701294,
-0.7979112863540649,
0.29178735613822937,
-0.15555113554000854,
-0.2602538764476776,
0.0002823987742885947,
1.117194414138794,
-0.13170020282268524,
-1.968904733657837,
0.257745563983... |
Given the task definition, example input & output, solve the new input case.
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: 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。
Output: ອິຕາລີໄດ້ເສຍໃຫ້ປ໊ອກຕຸຍການ 31 ຕໍ່ 5 ໃນພູລ C ຂອງ ການແຂ່ງຂັນຣັກບີ້ລະດັບໂລກປີ 2007 ທີ່ ປາກເດແພຣັງ ປາຣີ ປະເທດຝຣັ່ງ.
This is a correct and accurate translation from Japanese to Lao because translated text is just paraphrased of Japanese sentence. Also, it preserves the numbers as it is.
New input case for you: 乗り物の新しいオペレーターはガリンの存在に気づかず、ガリンがまだそこに乗っている間に乗り物を動かし始めた。
Output: | ຜູ້ຂັບເຄື່ອນເຄື່ອງໃໝ໋ ບໍ່ໄດ້ ຮູ້ວ່າ ນາງກາລິນກໍ່ຢູ່ທີ່ນັ້ນ ແລະ ໄດ້ດໍາເນີນເຄື່ອງຫຼີ້ນໃນຂະນະ ທີ່ນາງກາລິິນຍັງຢູ່ບ່ອນນັ້ນ. | 1 | NIv2 | task1124_alt_ja_lo_translation | fs_opt | [
-0.631118655204773,
0.41309937834739685,
-0.7432360649108887,
0.1770806610584259,
-0.03854022175073624,
-0.2748676836490631,
0.300847589969635,
0.43403899669647217,
0.04279671236872673,
-0.8393908143043518,
-1.0069700479507446,
0.9027124643325806,
-0.2571549117565155,
0.666238009929657,
... |
Q: 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.
In the present day (1970), 121-year-old Jack Crabb, the oldest living man in the world and residing in a hospice, recounts his plentiful life story to a curious historian. Among other things, Crabb claims to have had been a captive of the Cheyenne, a gunslinger, an associate of Wild Bill Hickok, a scout for General George Armstrong Custer, and the sole white survivor of the Battle of Little Bighorn.Jack begins his story in a flashback to 1859 when he was 10 years old where he and his older sister Caroline (Carole Androsky) survive the massacre of their parents by the Pawnee, and are discovered by a Cheyenne brave who takes the pair to his village. Caroline escapes, but Jack is reared by the goodhearted tribal leader Old Lodge Skins. As Jack gets older, he unwittingly makes an enemy of another boy, Younger Bear; however, Younger Bear eventually owes his life to Jack since he saved his life from a Pawnee brave. Jack is given the name "Little Big Man" because he is short but very brave. In 1865, when Jack is 16, he is captured by U.S. cavalry troopers during a skirmish and renounces his Cheyenne upbringing in order to save himself. He is put in the care of Reverend Silas Pendrake and his sexually frustrated wife, Louise, who tries to seduce Jack. When he witnesses Mrs. Pendrake having sex with the soda shop owner, Jack leaves the Pendrake household, and religion.The following year, Jack becomes the apprentice of the snake-oil salesman Merriweather. The two are tarred and feathered when their customers realize that Merriweather's products are fraudulent. One of the angry customers is Jack's now-grown sister, Caroline, with whom he reunites. She attempts to mold her brother into a gunslinger named the Soda Pop Kid. Jack meets Wild Bill Hickok at a saloon, and Hickok takes a liking to the young man. When Hickok is forced to kill a man in self-defense, Jack loses his taste for gunslinging and Caroline deserts him.Another year or so later, Jack becomes a partner in a general store and marries a Swedish woman named Olga (Kelly Jean Peters). Unfortunately, Jack's business partner turns out to be a thieving scoundrel. The famous cavalry officer George Armstrong Custer suggests the couple restart their lives further west and assures them they have nothing to fear of Indians. They set out, but their stagecoach is ambushed by Cheyenne warriors. Olga is abducted and Jack sets out in search for her. He is reunited with Old Lodge Skins. Younger Bear has become a Contrary, a warrior who does everything in reverse. Jack makes friends with the hwame Little Horse, but continues on his search for Olga.Jack eventually becomes a "muleskinner" in Custer's 7th Cavalry, only because Custer incorrectly determines that was Jack's past job. He takes part in a battle against the Cheyenne, but when the troopers begin killing women and children, Jack turns on them. Jack discovers a Cheyenne woman, Sunshine (Aimée Eccles), giving birth. He returns with her to Old Lodge Skins's tribe. Sunshine becomes his wife and bears him a child. Jack again encounters Younger Bear, not a Contrary anymore, who is now the henpecked husband of the long-lost Olga. Olga does not recognize Jack, who makes no attempt to make her remember him. Sunshine asks Jack to take in her three widowed sisters as wives and to father children with them. He is reluctant at first, but finally agrees.In November 1868, Custer and the 7th Cavalry make a surprise attack on the Cheyenne camp at the Washita River. A now-blind and elderly Old Lodge Skins is saved by Jack, but Sunshine, their child, and her sisters are killed. Jack tries to infiltrate Custer's camp to exact revenge, but loses his nerve to kill Custer.Disheartened, Jack withdraws from life and becomes the town drunk living in Deadwood, South Dakota for the next several years. While in a drunken stupor, he is recognized by Wild Bill Hickok, who gives him money to get cleaned up. Hickok is shot and killed while playing cards and, with his last breath, asks Jack to bring some money to a widow he was having an affair with. Jack visits the widow, now a prostitute who turns out to be Louise Pendrake. Jack gives her the money that Hickok intended for her to use to start a new life, but again rebuffs her sexual advances. This scene provides an homage to Hoffman's role in the movie The Graduate and his seduction by Mrs. Robinson.Jack soon becomes a trapper and hermit. His mind becomes unhinged after coming across an empty trap with a severed animal limb. He prepares to commit suicide, but sees Custer and his troops marching nearby, and decides to return to his quest for revenge. Custer hires him as a scout, reasoning that anything Jack says will be a lie, thus serving as a perfect reverse barometer. Jack tricks Custer into leading his troops into a trap at the Little Bighorn by truthfully telling Custer of the overwhelming force of Native Americans hidden within the valley. As Custer's troops are slaughtered by the combined Sioux and Cheyenne group, he begins to rave insanely. The mad Custer attempts to shoot Jack who is wounded, but is killed by Younger Bear, who then carries Jack away from the battlefield. Having thus discharged his life debt, Younger Bear tells Jack that the next time they meet, he can kill Jack without becoming an evil person.Back at the Indian camp, Jack accompanies Old Lodge Skins to a nearby hill, the Indian burial ground, where the old man, dressed in full chief's regalia, has declared "It is a good day to die", and decides to end his life with dignity. He offers his spirit to the Great Spirit, and lies down at his spot at the Indian Burial Ground to wait for death. Instead, it begins to rain. Old Lodge Skins is revealed to still be alive, and says, "Sometimes the magic works, and sometimes it doesn't". They return to his tepee to have dinner.Back in the present, Jack's narrative ends and he dismisses the historian. The final shot shows the elderly Jack thinking with sadness about the memories of a world which is no more., Question: What is Jack Crabb's age?
A: | Answer: 121 | 7 | NIv2 | task194_duorc_answer_generation | zs_opt | [
1.0659511089324951,
0.4632917642593384,
-0.6932119131088257,
-0.3187333047389984,
0.3783506751060486,
-0.13067364692687988,
0.8638607263565063,
0.699134111404419,
0.037935107946395874,
0.2069573700428009,
-0.41276809573173523,
0.2524920701980591,
-1.3160526752471924,
0.4116421341896057,
... |
Detailed Instructions: Given a passage classify if the passage has a definite objective/aim/goal or not. Output '1' if the passage has a defininte objective/aim/goal and output '0' if the passage does not have a definite objective/aim/goal.
Problem:The significance of bile duct injury and ductular reaction in biopsies from autoimmune hepatitis patients is not clear. We aim to establish the prevalence and clinical relevance of both phenomena in autoimmune hepatitis.', 'Cases of newly diagnosed, untreated autoimmune hepatitis without overlap syndrome were selected. Pretreatment and follow up biopsies were scored for inflammation, fibrosis, bile ductal injury and ductular reaction.', 'Thirty-five cases were studied of whom 14 cases had follow up biopsies. Bile duct injury was present in 29 cases (83%), mostly in a PBC-like pattern and was not correlated with demographical or laboratory findings. Ductular reaction, observed in 25 of 35 cases (71%) using conventional histology and in 30 of 32 cases (94%) using immunohistochemistry, was correlated with portal and lobular inflammation, interface hepatitis and centrilobular necrosis as well as bile duct injury and fibrosis. In 11 of 14 cases (79%) ductular reaction remained present on post-treatment biopsy whereas bile duct injury persisted in six of 14 (43%) of cases.
Solution: | 1 | 8 | NIv2 | task848_pubmedqa_classification | zs_opt | [
0.04106646403670311,
0.06534034013748169,
-0.1920148730278015,
0.23593157529830933,
0.38692906498908997,
-0.31524190306663513,
0.6258910894393921,
0.7784599661827087,
0.6744523048400879,
0.39648672938346863,
-0.1658937782049179,
0.05386281758546829,
-0.42295950651168823,
-0.136959522962570... |
Definition: You are given a sentence in Spanish. Your job is to translate the Spanish sentence into English.
Input: Así se programaba a principios de los años 60.
Output: | That was programming in the early 1960s. | 2 | NIv2 | task1226_ted_translation_es_en | zs_opt | [
0.07113363593816757,
0.7287328839302063,
0.34834128618240356,
-0.7387439012527466,
-0.12539908289909363,
-0.5558428764343262,
0.3737209141254425,
1.1579363346099854,
0.6873457431793213,
-0.018854673951864243,
0.036578916013240814,
0.23186787962913513,
-0.8676779270172119,
0.047425825148820... |
Detailed Instructions: In this task, you are given a question. Your task is to generate an answer that is relevant to the question.
Problem:Just bought the new Star Wars video game, you want to just stay in and game all weekend?
Solution: | I have to work all weekend. | 8 | NIv2 | task565_circa_answer_generation | zs_opt | [
0.5586978197097778,
0.6452735066413879,
-1.0801445245742798,
-0.02655082568526268,
-0.48966485261917114,
-1.0144857168197632,
-0.15624696016311646,
0.44781598448753357,
0.7101688981056213,
-0.45095762610435486,
0.1922915130853653,
-0.05578296631574631,
-0.40967369079589844,
-0.253388255834... |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
In this task, you are given a statement spoken by a politician in natural language. Your task is to generate the subject of the discussion for the given statement. The subject generated is not necessarily a part of the given input. Your answer should contain one or more words.
Says the Annies List political group supports third-trimester abortions on demand.
Solution: abortion
Why? It's a correct subject of the statement because it talks about a political group supporting demans of abortions.
New input: Every president since Eisenhower has taken executive action to address immigration issues.
Solution: | history | 0 | NIv2 | task613_politifact_text_generation | fs_opt | [
0.212054044008255,
0.2129347026348114,
0.05209356173872948,
0.22902292013168335,
-0.478089302778244,
-0.3306378126144409,
0.7033156156539917,
0.07340101152658463,
0.019496412947773933,
0.25050675868988037,
-0.6496995687484741,
0.1400989145040512,
-0.43676066398620605,
0.4338284134864807,
... |
In this task, you are given a Reddit post as a text. Your task is to generate a title for this text. The title should start with "TIFU by", followed by a situation that caused humor. The title should contain 7-12 words, ideally.
Text: this happened to my brother some time back but thought i'd share it anyway.
he was on a plane flying from someplace to someplace other. after a while he realises he doesn't know where his phone is. he remembered walking onto the plane with it in his hands and then putting it into the seat pocket in front of him.
anyway, he double checks his pockets, his bag and the floor space around him. nothing.
he asks the female passenger in the seat next to him if she'd seen his phone to which she answered she hadn't. after more frantic searching my brother came to the conclusion that this female passenger next to him had stolen it. he accused her which resulted in a full blown out argument. the stewards had to get involved and it was obviously quite an embarrassing story when my brother found it between the seats about 10 minutes later.
to make things worse this happened in the first hour of what i think was quite a long flight.
ouch! | TIFU by thinking the girl next to me stole my phone | 0 | NIv2 | task510_reddit_tifu_title_summarization | zs_opt | [
-0.8116196990013123,
0.835159182548523,
-0.34763604402542114,
-0.7484520673751831,
0.0527399405837059,
0.17674456536769867,
0.41061532497406006,
0.12193383276462555,
0.32569822669029236,
0.14255639910697937,
-0.49622154235839844,
0.06653326004743576,
-0.8816946148872375,
0.0191545225679874... |
Definition: In this task, you're given a review from Amazon and your task is to generate the name of the category of the product based on the review given by the user. The categories are: kitchen, office product, watch, wireless, other, toy, digital video download, camera, jewelry, pet products, sports, industrial supplies, baby product, grocery, drugstore, home improvement, pc, shoes, automotive, digital ebook purchase, musical instruments, beauty, book, electronics, lawn and garden, apparel, home, video games, luggage, furniture, personal care appliances.
Input: Knobs started melting less than six months after purchase. Contacted seller they replied to contact ge which might take forever to hear from . Not what I expected by ordering through amazon. Very disappointed
Output: | other | 2 | NIv2 | task617_amazonreview_category_text_generation | zs_opt | [
-0.06576882302761078,
-0.1557646095752716,
-0.36656057834625244,
-0.03737017512321472,
0.4491059184074402,
0.2939493656158447,
0.2164585143327713,
0.2896270751953125,
-0.24861231446266174,
0.6406668424606323,
0.10343319177627563,
0.35197773575782776,
-0.39615848660469055,
-0.12727040052413... |
Given a sentence in the Central Khmer, provide an equivalent translation in Japanese that retains the same meaning through the translation. In translation, keep numbers as it is.
Input: Consider Input: កញ្ចប់ថវិការនេះ បង្ហាញដល់ប្រជាជនអាមេរិកថា បើទោះបីជាក្នុងឆ្នាំបោះឆ្នោតក៏ដោយ គណបក្សសធារណៈរដ្ឋ និងប្រជាធិបតេយ្យ អាចរួបរួមគ្នាក្នុងការជួយគាំទ្រទាហានរបស់យើង និងគ្រួសាររបស់ពួកគេ។
Output: この法案は、選挙の年でさえ、アメリカ国民は共和党と民主党が一緒になって軍隊とその家族を支援するということを示している。
Input: Consider Input: ក្រុមតវ៉ាថាវាគឺជាលួចចូលលើកដំបូងនៃប្រភេទរបស់វានៅផានហ្គេព។
Output: そのグループは、これがパインギャップで初めてのこの種の潜入だと主張した。
Input: Consider Input: ចំណែក ហ្វុនសិកា មិនអាចចូលរួមបោះឆ្នោតបានឡើយដោយសារតែឈ្មោះរបស់លោកពុំមាននៅក្នុងបញ្ជីចុះឈ្មោះបោះឆ្នោតឆ្នាំ2008 ដែលគេប្រើសំរាប់ការបោះឆ្នោតនេះឡើយ។
| Output: しかしながら、フォンセカ氏は、選挙に使用された2008年の選挙名簿に氏名がなかったため投票できなかった。
| 2 | NIv2 | task1122_alt_khm_ja_translation | fs_opt | [
0.1553766429424286,
-0.16529586911201477,
-0.46072810888290405,
0.10927227884531021,
-0.03506609797477722,
-0.9791635870933533,
0.7583838701248169,
0.4640316367149353,
-0.27811434864997864,
0.1017492413520813,
-0.00040616653859615326,
0.20474925637245178,
-0.6476030349731445,
-0.2514076232... |
Detailed Instructions: Given news headlines and an edited word. The original sentence has word within given format {word}. Create new headlines by replacing {word} in the original sentence with edit word. Classify news headlines into "Funny" and "Not Funny" that have been modified by humans using an edit word to make them funny.
Problem:News Headline: Climate agreement withdrawal : ' Trump just stepped on the {gas} ' toward catastrophe
Edit: frog
Solution: | Not Funny | 8 | NIv2 | task495_semeval_headline_classification | zs_opt | [
0.06487321853637695,
0.6185651421546936,
0.31288594007492065,
-0.24485993385314941,
-0.5593273639678955,
-1.2093322277069092,
-0.24955318868160248,
0.8760792016983032,
-0.41355472803115845,
-0.34858816862106323,
-0.5939947366714478,
-0.7967912554740906,
-0.5769734382629395,
0.0113736297935... |
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'.
--------
Question: Context: Kelly was opposed by John C. Jacobs, who proposed Ex-State Senator Henry C. Murphy, Jacobs's predecessor from the 3rd District Link Information: John C. Jacobs (December 16, 1838 Lancaster County, Pennsylvania – September 22, 1894 Question: Who was the older, John C. Jacobs or his predecessor?
Answer: Answer: Henry C. Murphy
Question: Context: He moved to Germany in 1901 and studied in rapid succession at Berlin, Heidelberg, and Zurich universities. Link Information: It was established by Frederick William III on the initiative of Wilhelm von Humboldt, Johann Gottlieb Fichte and Friedrich Ernst Daniel Schleiermacher as the University of Berlin (Universität zu Berlin) in 1809 Question: Which German school that Ganetsky studied in was found first?
Answer: Answer: Heidelberg
Question: Context: Following the Pittsburgh drug trials, an unsuccessful attempt was made to purchase the Pittsburgh Pirates and relocate them Link Information: Peter Ueberroth handed down suspensions to 11 players. All the suspensions were commuted in exchange for fines and community service. Question: How many Pirates players were removed from the MLB because of the Pittsburgh drug trials?
Answer: | Answer: 0
| 7 | NIv2 | task237_iirc_answer_from_subtext_answer_generation | fs_opt | [
-0.36039429903030396,
0.25985532999038696,
-0.8805029392242432,
-0.11886969208717346,
-0.19881968200206757,
-0.2803072929382324,
0.21086473762989044,
0.4617483615875244,
0.5075260400772095,
0.17445187270641327,
0.0582536980509758,
0.41538533568382263,
-0.3837010860443115,
0.189941942691802... |
Detailed Instructions: In this task, you are given two statements. The task is to output whether a given textual premise, i.e. Statement 2, entails or implies a given scientific fact, i.e. Statement 1. The output should be 'entails' if Statement 2 supports Statement 1 and should be 'neutral' otherwise.
Problem:Sentence 1: Vertebrates reproduce sexually. Sentence 2: Wheat reproduces sexually .
Solution: | neutral | 8 | NIv2 | task1554_scitail_classification | zs_opt | [
-0.4421936571598053,
0.6191307306289673,
0.030561547726392746,
0.5977209806442261,
-0.5922746658325195,
-0.9302273988723755,
-0.11789172887802124,
0.8010338544845581,
-0.15669457614421844,
-0.2775959372520447,
-0.7332873344421387,
-0.32715803384780884,
-0.2508918046951294,
-0.2152484655380... |
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 additional information about the situation that might weaken or strengthen the hypothesis. A weakener is a statement that weakens the hypothesis, that is, it makes you much less likely to believe the hypothesis is true. A strengthener is a statement that strengthens the hypothesis, that is, it makes you much more likely to believe the hypothesis is true. Your task is to answer with 'strengthener' or 'weakener' if the update strengthens or weakens the hypothesis, respectively.
Teacher: Now, understand the problem? Solve this instance: Premise: A man wearing a red hat is holding an instrument up to his mouth.
Hypothesis: A man plays the flute.
Update: The man is happy to be added to the symphony.
Student: | strengthener | 6 | NIv2 | task936_defeasible_nli_snli_classification | zs_opt | [
-0.015296781435608864,
0.6357811689376831,
-0.4184069037437439,
-0.2675367295742035,
0.03841030225157738,
-0.9731554985046387,
1.1597574949264526,
1.2864913940429688,
0.5267480611801147,
-0.28096774220466614,
-0.8627005815505981,
-0.07622995972633362,
-0.7201798558235168,
-0.23794975876808... |
You are given a conversation between two people. 'Person1:' and 'Person2:' are used to separate their respective dialogues. Your task is to classify the conversation either convey 'No emotion' or 'Happiness' by providing '1' and '0', respectively.
Person1: Hello , Joanna . You are looking very charming in the new dress .
Person2: Thanks . Does it suit me ?
Person1: Yes , it suits you very well . It certainly is unique . I don ’ t think I ’ Ve seen anything like it before .
Person2: I know . That ’ s why I bought it . I hate wearing the same styles like everybody else is wearing .
Person1: And the necklace , it matches your dress marvelously .
Person2: It ’ s very nice of you to say so . I should say you are glamorous yourself , as a matter of fact .
Person1: Thank you for saying so . | 1 | 0 | NIv2 | task1536_daily_dialog_happiness_classification | zs_opt | [
0.09804688394069672,
0.402185320854187,
0.05997593700885773,
0.061522748321294785,
0.20571348071098328,
0.07235820591449738,
0.35424670577049255,
0.36161890625953674,
0.15041518211364746,
0.10270020365715027,
-0.3601875305175781,
-0.48284468054771423,
-0.15387298166751862,
-0.1108991727232... |
Teacher: In this task, you are given a context tweet and an answer. Your job is to generate a question for the given answer based on the given tweet paragraph. Note that your question should be answerable based on the given tweet, and the answer to your question should be the given answer.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Context: Our prayers are with the students, educators & families at Independence High School & all the first responders on the scene. #PatriotPride— Doug Ducey (@dougducey) February 12, 2016 Answer: independence high school
Solution: at which school were first responders on the scene for?
Reason: We can see that independence high school should answer the generated question. Based on the tweet, all the first responders are on the scene at independence high school. So we can create a question based on this sentence.
Now, solve this instance: Context: We are not responding to Trump but everyone who understands the humiliation this degrading language inflicts on all women should. #imwithher— Jennifer Palmieri (@jmpalmieri) December 22, 2015 Answer: he is using degrading language against women.
Student: | what is trump doing to incite jennifer palmieri in this tweet? | 2 | NIv2 | task240_tweetqa_question_generation | fs_opt | [
-0.20911602675914764,
0.4665290415287018,
0.47569605708122253,
-0.3355799913406372,
0.3708890676498413,
-0.85234135389328,
-0.22706305980682373,
0.26774197816848755,
-0.17600882053375244,
-0.224827378988266,
-0.37208452820777893,
-0.10329638421535492,
-0.15100407600402832,
-0.5047664046287... |
In this task, you are given a sentence and a profession. The sentence mentions two professions: one's gender is identifiable using the gendered pronouns in the text and the other's gender is unidentifiable. You are expected to return whether the given profession's gender is identifiable or unidentifiable.
Let me give you an example: Sentence: The farmer needed the accountant for crop tabulation and asked him for help.
Profession: accountant
The answer to this example can be: Identifiable
Here is why: The accountant's gender is identifiable(male) because the pronoun "him" is linked to the accountant.
OK. solve this:
Sentence: The librarian was unable to find the book for the developer and instead offered her a magazine.
Profession: developer
Answer: | Identifiable | 8 | NIv2 | task351_winomt_classification_gender_identifiability_anti | fs_opt | [
-0.9425160884857178,
0.5878236293792725,
0.06785228848457336,
-0.5058891773223877,
0.035642825067043304,
-0.2488427609205246,
0.2776447832584381,
0.6778069734573364,
0.629327654838562,
0.06096014007925987,
-1.4174169301986694,
0.03029904142022133,
-0.7328885197639465,
-0.2197854220867157,
... |
Detailed Instructions: Given a post that is a real-life anecdote of a complex ethical situation and an associated claim about its type, verify if the claim is true or not. The claim asks if the posts are historical or hypothetical. The posts are "HISTORICAL" when the author has already done something and they are "HYPOTHETICAL" when the author is considering doing something in the future. Say 'yes' if the claim is true otherwise say 'no'
Q: CLAIM : The following post is HISTORICAL. POST : I had some buddies back in elementary. It was the end of the day. I was talking with my friend, when another girl came in. I don’t remember exactly what we were talking about, but eventually she started punching my arm. Hard. After a bit of that, I let my bottled anger out. I’m a naturally a shy kid. I knew what being an introvert was, but I didn’t think I was one at the time. I hit my breaking point and I grabbed her backpack. I threatened to dump it all out, and she started hitting me again. Another kid comes along and keeps bumping into me. It was intentional. I then did one of those “push the dude with your body while your walking into him” things. Another girl comes along, I don’t remember what she did, but I remember also getting angry at her. Back then. I didn’t get angry very easily, and when I did I let it go. I actually held a grudge against these three for like a week. We’re still friends. I just let my anger out then.
A: | no | 9 | NIv2 | task501_scruples_anecdotes_post_type_verification | zs_opt | [
-0.2101992815732956,
-0.10926295816898346,
0.1894376575946808,
0.14507576823234558,
-0.21726909279823303,
-1.2614914178848267,
0.4229060411453247,
1.203843355178833,
-0.4639571011066437,
-0.07911351323127747,
0.037380822002887726,
0.46062955260276794,
-0.7270967364311218,
-0.32090777158737... |
You are given a movie review in the French language. You need to predict its sentiment. Output a 0 for negative sentiment and a 1 for positive sentiment.
Let me give you an example: Si vous cherchez du cinéma abrutissant à tous les étages,n\'ayant aucune peur du cliché en castagnettes et moralement douteux,"From Paris with love" est fait pour vous.Toutes les productions Besson,via sa filière EuropaCorp ont de quoi faire naître la moquerie.Paris y est encore une fois montrée comme une capitale exotique,mais attention si l\'on se dirige vers la banlieue,on y trouve tout plein d\'intégristes musulmans prêts à faire sauter le caisson d\'une ambassadrice américaine.Nauséeux.Alors on se dit qu\'on va au moins pouvoir apprécier la déconnade d\'un classique buddy-movie avec le jeune agent aux dents longues obligé de faire équipe avec un vieux lou complètement timbré.Mais d\'un côté,on a un Jonathan Rhys-meyers fayot au possible,et de l\'autre un John Travolta en total délire narcissico-badass,crâne rasé et bouc proéminent à l\'appui.Sinon,il n\'y a aucun scénario.Seulement,des poursuites débiles sur l\'autoroute,Travolta qui étale 10 mecs à l\'arme blanche en 8 mouvements(!!)ou laisse son associé se faire démolir la tronche pendant qu\'il scrute à la jumelle.Ca pourrait être un plaisir coupable,tellement c\'est "hénaurme",c\'est juste de la daube dans la droite lignée d\'un "Transporteur","Taken"ou "Banlieue 13".
The answer to this example can be: 0
Here is why: The English translation of the input is: If you are looking for stupefying cinema on all floors, having no fear of the cliché in castanets and morally doubtful, "From Paris with love" is for you. All Besson productions, via its EuropaCorp channel, have something to do with Paris is once again shown as an exotic capital, but be careful if you go to the suburbs, there are plenty of Muslim fundamentalists ready to blow up the box of an ambassador American.Nauséeux.So we say to ourselves that we will at least be able to enjoy the fun of a classic buddy-movie with the young agent with the long teeth forced to team up with a completely crazy old Lou. on the side, we have a Jonathan Rhys-Meyers fayot as possible, and on the other a John Travolta in total narcissistic-badass delirium, shaved head and prominent goatee in support. Otherwise, there is no scenario .Only, stupid pursuits on the highway, Travolta who spreads 10 guys with knives in 8 movement s (!!) or let his partner get his face smashed while he peers through binoculars. It could be a guilty pleasure, it's so "bullshit", it's just crap in the straight line of a "Transporter", "Taken" or "Suburb 13". In this, the words bullshit and crap justifies the negative sentiment label. Thus its a positive example.
OK. solve this:
Le film paraissait poetique et abondait dans un style cinématographique apparemment nouveau.Eh bien quelle décèption même si le film dégage un certain esthétisme qui dénote malgré tout une forme de poesie, la réalisation est lourde, pataude.L'image est souvent sombre et le cadrage parfois approximatif.Et l'histoire et bien elle aurait pu être originale si elle avait été établie sous forme d'un conte moderne. Là finalement on sombre dans une sorte de mélodrame sur fond d'alcoolisme, de méli-mélo amoureux pour déboucher sur un mariage improbable entre la belle et le clochard.Les scénes sont interminables et les décors peu variés.Entre un bateau, une roulotte et le bar du coin sans oublier les rochers.On est bien loin de la petit sirene
Answer: | 0 | 8 | NIv2 | task1591_allocine_classification | fs_opt | [
0.5618625283241272,
0.4995969235897064,
-0.24686825275421143,
0.19132490456104279,
0.9400890469551086,
-0.5479137897491455,
0.707653284072876,
1.052527666091919,
-0.24380874633789062,
0.6672512292861938,
-0.3219696879386902,
0.34829914569854736,
-0.44537603855133057,
-0.12831509113311768,
... |
In this task, you're given the title of a story consisting of five sentences, numbered 1 through 5. Your job is to arrange the sentences in order to make a story that makes complete sense and is apt for the title. Indicate your answer using the number of the sentences in order, such as '34152'.
One example is below.
Q: Title: Marcus Buys Khakis. Sentence 1: All of his clothes were either too formal or too casual. Sentence 2: Marcus needed clothing for a business casual event. Sentence 3: The pair he bought fit him perfectly. Sentence 4: Marcus was happy to have the right clothes for the event. Sentence 5: He decided to buy a pair of khakis.
A: 21534
Rationale: Marcus's reasons for buying khakis is established, followed by his purchase of them and reaction.
Q: Title: Shoe Shopping. Sentence 1: Will went to his local sporting goods store. Sentence 2: Will was looking for a new pair of running shoes. Sentence 3: Will finally made his choice - a pair of New Balance shoes. Sentence 4: Will compared styles, fits and prices. Sentence 5: Michael went home feeling good about his purchase.
A: | 21435 | 9 | NIv2 | task217_rocstories_ordering_answer_generation | fs_opt | [
0.1404961496591568,
-0.302979052066803,
-0.5190994739532471,
0.26142799854278564,
0.5920841693878174,
-0.0384487509727478,
0.2301379144191742,
0.8966313600540161,
-0.2657826840877533,
0.3354733884334564,
-0.6351606845855713,
0.1604294627904892,
-0.3081516921520233,
0.4562666416168213,
-0... |
Teacher:In this task, you are given sentences from movie reviews. The task is to classify a sentence as "POS" if the sentiment of the sentence is positive or as "NEG" if the sentiment of the sentence is negative
Teacher: Now, understand the problem? Solve this instance: A movie that feels like the pilot episode of a new teen-targeted action TV series .
Student: | NEG | 6 | NIv2 | task363_sst2_polarity_classification | zs_opt | [
-0.6329322457313538,
0.1851014792919159,
0.2245185375213623,
-0.42219921946525574,
0.23563629388809204,
-0.7016056776046753,
1.4155341386795044,
1.0189226865768433,
0.4554106593132019,
0.16268397867679596,
-0.5110137462615967,
-0.6924242377281189,
-0.79487544298172,
-0.6432198286056519,
... |
Instructions: In this task, you're given four sentences of a story written in natural language in which one part is missing. Your job is to predict the position and missing part of the story and return in the following format: position, missing part. The missing part is a sentence that completes the story, and the position is the number of the missing sentence in the new story.
Input: Sentence1: Sophie's nana was terminally ill. Sentence2: Sophie visited her in the hospital to say goodbye. Sentence3: She told Sophie to keep it to remember her by. Sentence4: Sophie cried.
Output: | 3, Her nana gave Sophie her prized gold locket. | 3 | NIv2 | task299_storycloze_sentence_generation | zs_opt | [
-0.47959232330322266,
0.9043421745300293,
-0.10782594233751297,
-1.0755681991577148,
0.1662437468767166,
0.30264320969581604,
1.0233891010284424,
0.5609543919563293,
0.28579145669937134,
-0.15565064549446106,
-0.18691986799240112,
-0.07078327238559723,
0.3111872971057892,
0.045293163508176... |
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 additional information about the situation that might weaken or strengthen the hypothesis. A weakener is a statement that weakens the hypothesis, that is, it makes you much less likely to believe the hypothesis is true. A strengthener is a statement that strengthens the hypothesis, that is, it makes you much more likely to believe the hypothesis is true. Your task is to answer with 'strengthener' or 'weakener' if the update strengthens or weakens the hypothesis, respectively.
Q: Premise: A black male in a dirty white long-sleeved shirt is working.
Hypothesis: a man working at the steel mill
Update: The mill is full of grain.
A: | weakener | 4 | NIv2 | task936_defeasible_nli_snli_classification | zs_opt | [
-0.04939117282629013,
0.3350290060043335,
-0.34423738718032837,
-0.20048180222511292,
-0.053491175174713135,
-0.7445011138916016,
0.8811327219009399,
1.4662425518035889,
0.6062761545181274,
-0.03793545812368393,
-1.6314293146133423,
-0.02892507240176201,
-0.6690043210983276,
0.017770741134... |
In this task, you are given a set of context paragraphs, some supporting facts and an answer of a question. Your task is to generate question for given answer based on set of context paragraphs, supporting facts and an answer.
Let me give you an example: Context_1 : Charles Edward Ives ( ; October 20, 1874May 19, 1954) was an American modernist composer. He is one of the first American composers of international renown, though his music was largely ignored during his life, and many of his works went unperformed for many years. Over time, he came to be regarded as an "American original". He combined the American popular and church-music traditions of his youth with European art music, and was among the first composers to engage in a systematic program of experimental music, with musical techniques including polytonality, polyrhythm, tone clusters, aleatory elements, and quarter tones, foreshadowing many musical innovations of the 20th century. Context_2 : Daniel Evan Freeman (born 27 April 1959) is an American musicologist who specializes in European art music of the eighteenth century, in particular the musical culture of eighteenth-century Prague and the Bohemian lands. He is also active as a pianist and music editor. Context_3 : Art music (also known as Western classical music, cultivated music, serious music, canonic music, and more flippantly, real music or normal music) is an umbrella term that refers to musical traditions, implying advanced structural and theoretical considerations and a written musical tradition. "Serious" or "cultivated" music are terms frequently used as a contrast for ordinary, everyday music (popular and folk music, also called "vernacular music"). After the 20th century, art music was divided into two extensions: "serious music" and "light music". Context_4 : In the history of European art music, the term "common practice period" refers to the era between the formation and the dissolution of the tonal system. Though there are no exact dates for this phenomenon, most features of the common-practice period persisted from the mid to late baroque period, through the Classical and Romantic periods, or roughly from around 1650 to 1900. While certain prevailing patterns and conventions characterize the music of this period, the time period also saw considerable stylistic evolution. Some conventions evolved during this period that were rarely employed at other times during what may still be labeled "common practice" (for example, Sonata Form). Thus, the dates 1650–1900 are necessarily nebulous and arbitrary borders that depend on context. The most important unifying feature through this time period concerns a harmonic language to which modern music theorists can apply Roman numeral analysis. Context_5 : The Festival Oude Muziek Utrecht ("Utrecht Early Music Festival") is an annual music festival that showcases and celebrates early European art music. The ten-day festival takes place in the Dutch city of Utrecht, and begins in August. The programme comprises concerts, activities, lectures, exhibitions, and a symposium. Context_6 : Assaf Shelleg (Hebrew: אסף שלג ), is a musicologist and pianist, a senior lecturer of musicology at The Hebrew University of Jerusalem. He was previously the Schusterman Visiting Assistant Professor of Musicology and Jewish Studies in the Department of Religious Studies at the University of Virginia (2011–14), and had taught prior to that as the visiting Efroymson Scholar in the Jewish, Islamic & Near Eastern Languages and Cultures Department at Washington University in St. Louis (2009–11). Shelleg specializes in twentieth-century Jewish and Israeli art music and has published in some of the leading journals in both musicology and Israel Studies on topics ranging from the historiography of modern Jewish art music to the theological networks of Israeli art music. Shelleg's book, "Jewish Contiguities and the Soundtrack of Israeli History", appeared in November 2014 with Oxford University Press. The book studies the emergence of modern Jewish art music in central and Western Europe (1910s-1930s) and its translocation to Palestine/Israel (1930s-1970s), exposing the legacies of European antisemitism and religious Judaism in the making of Israeli art music. Moving to consider the dislocation of modern Jewish art music the book examines the paradoxes embedded in a Zionist national culture whose rhetoric negated its pasts, only to mask process of hybridizations enchained by older legacies. "Jewish Contiguities" has won the 2015 Engle Prize for the study of Hebrew Music, and the 2016 Jordan Schnitzer Book Award. Context_7 : Vocal harmony is a style of vocal music in which a consonant note or notes are simultaneously sung as a main melody in a predominantly homophonic texture. Vocal harmonies are used in many subgenres of European art music, including Classical choral music and opera and in the popular styles from many Western cultures ranging from folk songs and musical theater pieces to rock ballads. In the simplest style of vocal harmony, the main vocal melody is supported by a single backup vocal line, either at a pitch which is above or below the main vocal line, often in thirds or sixths which fit in with the chord progression used in the song. In more complex vocal harmony arrangements, different backup singers may sing two or even three other notes at the same time as each of the main melody notes, mostly with consonant, pleasing-sounding thirds, sixths, and fifths (although dissonant notes may be used as short passing notes). Context_8 : David Wallis Reeves (February 14, 1838 – March 8, 1900), also known as D. W. Reeves or Wally Reeves, was an American composer, cornetist, and bandleader. He developed the American march style, later made famous by the likes of John Philip Sousa, and his innovations include adding a countermelody to the American march form in 1876. Sousa called Reeves "The Father of Band Music in America", and stated he wished he himself had written Reeves' "Second Regiment Connecticut National Guard March". Charles Ives also borrowed from the "Second Connecticut" on four occasions. Context_9 : "Indian classical music is one of many forms of art music that have their roots in particular regional cultures. For other "classical" and art music traditions, see List of classical and art music traditions." Context_10 : Progressive music is music that subverts genre and expands stylistic boundaries outwards. Rooted in the idea of a cultural alternative, musical progressiveness embodies a continuous move between explicit and implicit references to genres and strategies derived from various cultural domains, such as European art music, Celtic folk, West Indian, or African. The word "progressive" comes from the basic concept of "progress", which refers to development and growth by accumulation, and is often deployed in numerous music genres such as progressive country, progressive folk, progressive jazz, and (most significantly) progressive rock. fact_1 : Charles Ives also borrowed from the "Second Connecticut" on four occasions. fact_2 : Charles Edward Ives ( ; October 20, 1874May 19, 1954) was an American modernist composer. fact_3 : He combined the American popular and church-music traditions of his youth with European art music, and was among the first composers to engage in a systematic program of experimental music, with musical techniques including polytonality, polyrhythm, tone clusters, aleatory elements, and quarter tones, foreshadowing many musical innovations of the 20th century. Answer: 1874May
The answer to this example can be: What is the birthyear of the American composer that borrowed from "Second Connecticut" on four occasions and combined American popular and church-music traditions with European art music?
Here is why: From the fact_1 from context _8, and fact _2 and fact _3 from context _1, we can arrive at 1874 May which is accurate answer of generated question.
OK. solve this:
Context_1 : Penny Mickelbury (born 1948) is an African-American playwright and mystery novelist who worked as a print and television journalist for ten years before concentrating on fiction writing. After leaving journalism, she taught fiction and script writing in Los Angeles and saw two of her plays (‘’Waiting for Gabriel’’ and ‘’Hush Now’’) produced there. She began writing detective novels with "Keeping Secrets", published by Naiad Press in 1994, the first of a series featuring 'Gianna Maglione’, a lesbian chief of a hate-crimes unit based in Washington D.C. and her lover 'Mimi Patterson', a journalist. Her second series features ‘Carol Ann Gibson’, a Washington D.C attorney who is widowed in the first book and subsequently runs an investigation agency with 'Jake Graham', the detective who investigated her husband’s death. Her third features 'Phil Rodriguez', a Puerto Rican private investigator on the Lower Easter Side of New York City. Context_2 : Justin Hopson is a retired New Jersey State Trooper, licensed private investigator, whistle-blower, and author of ""Breaking the Blue Wall: One Man's War Against Police Corruption."" As a rookie state trooper, Justin Hopson witnessed an unlawful arrest and false charges of a woman made by his training officer, so Hopson refused to testify in court supporting the arrest. As a result, Trooper Hopson was targeted by a rogue group of troopers known as the Lords of Discipline or "LOD." The LOD bullied and hazed fellow troopers for decades until Justin Hopson blew the whistle. Hopson brought tangible evidence and a written chronology of events that occurred to internal affairs and the attorney general's office...which sparked the largest internal investigation in state police history and high profile federal case (Hopson v State of New Jersey #1:03-CV-5817). "I was an ordinary cop with an extraordinary cause. My cause is constant - to unearth corruption by shining a light on integrity," says Hopson. Context_3 : Operation Underworld, published in 2009, is a novel written by author Paddy Kelly. The title is taken from the real life operation instituted by the U.S. Navy in February 1942 following the false alert that German saboteurs had invaded the New York City waterfront in preparation for a possible invasion. The story is set five weeks after the bombing of Pearl Harbour when America is poorly equipped to enter a world conflict. The story revolves around Mike 'Doc' McKeowen, a New York private investigator, Commander Charles Haffenden, a naval intelligence operative and Charles 'Lucky' Luciano, the then head of the New York Mafia. The World War II episode was a common story known to New York area Italian-Americans for many years but one that had never been novelized or much written about. The characters are involved with murder, a large sum of counterfeit currency and the misconception that a large scale invasion of Nazi saboteurs is underway. Context_4 : The Tuxedo Club is a private member-owned country club located on West Lake Road in the village of Tuxedo Park, New York, in the Ramapo Mountains. Founded in 1886 by Pierre Lorillard IV, its facilities now include an 18-hole golf course, lawn tennis, court tennis, racquets, squash, platform tennis, olympic-sized pool, and boating. The tuxedo was introduced by New York millionaire James Potter at the club's first Autumn ball in 1886, after a trip to England. Context_5 : Doctor Richard Occult is a fictional superhero appearing in American comic books published by DC Comics. Created by Superman's creators Jerry Siegel and Joe Shuster, Doctor Occult, also known as the Ghost Detective, is a private investigator and user of magic who specializes in cases involving the supernatural. Doctor Occult is the earliest character created by DC Comics still currently used in the DC Universe. Context_6 : Santosky v. Kramer, 455 U.S. 745 (1982) , is a Supreme Court case involving the burden of proof for the revocation of parental rights. The case arose when the Ulster County, New York Department of Social Services sought to revoke John Santosky II and Annie Santosky's parental rights to their three children. Under Section 622 of the New York State Family Court Act, the state was permitted to revoke parental rights to a natural child if, after a fair preponderance of the evidence, a court found "permanent neglect." The New York State Family Court found such neglect by using the "fair perponderance" standard. The Appellate Division of the New York Supreme Court upheld the constitutionality of the burden of proof used. Context_7 : Bobbi Bacha is a Texas Private Investigator portrayed in 2004 TV Sony Pictures Movie "Suburban Madness" played by actress Sela Ward. Bobbi Bacha also was involved and worked on the case of New York millionaire Robert Durst who was charged with murder in Galveston, Texas for killing his neighbor Morris Black but was found not guilty by a Galveston County Jury. Context_8 : Robert Alan Durst (born April 12, 1943) is an American real estate heir, the son of New York City mogul Seymour Durst, and the elder brother of Douglas Durst, head of the Durst Organization. He is primarily known for being suspected of foul play against three individuals in different states: Kathleen McCormack Durst, his first wife, who disappeared in New York in 1982; Susan Berman, his longtime friend, who was murdered in California in 2000; and his neighbor, Morris Black, who was murdered in Texas in 2001. Durst was the subject of a multi-state manhunt and was ultimately convicted of dismembering Black, but acquitted of his murder. Context_9 : David Goodwillie (born March 25, 1972) is an American novelist and memoirist. He has written two acclaimed books: the novel "American Subversive" (Scribner, 2010) and the memoir "Seemed Like a Good Idea at the Time" (Algonquin, 2006). Hailed as "genuinely thrilling" by "The New Yorker", and "a triumphant work of fiction" by the Associated Press, "American Subversive" was a "New York Times" Notable Book of 2010, and a "Vanity Fair" and "Publishers Weekly" top ten spring debut. Upon publication of his previous book, "Seemed Like a Good Idea at the Time", he was named one of the Best New Writers of 2006 by members of the PEN American Center. Goodwillie writes about books for "The Daily Beast", and his fiction and nonfiction have appeared in numerous magazines, newspapers, and websites, including "New York Magazine", "Men's Health", "Black Book", "The New York Times", "The New York Observer", "The New York Post", The Rumpus, and Deadspin. He has also played professional baseball, worked as a private investigator, and been an expert at Sotheby’s auction house. A graduate of Kenyon College, he lives in New York City. Context_10 : Broken City is a 2013 American neo-noir crime drama film directed by Allen Hughes and written by Brian Tucker. Mark Wahlberg stars as a police officer turned private investigator and Russell Crowe as the mayor of New York City who hires the private detective to investigate his wife. fact_1 : Bobbi Bacha is a Texas Private Investigator portrayed in 2004 TV Sony Pictures Movie "Suburban Madness" played by actress Sela Ward. fact_2 : Bobbi Bacha also was involved and worked on the case of New York millionaire Robert Durst who was charged with murder in Galveston, Texas for killing his neighbor Morris Black but was found not guilty by a Galveston County Jury. fact_3 : He is primarily known for being suspected of foul play against three individuals in different states: Kathleen McCormack Durst, his first wife, who disappeared in New York in 1982; Susan Berman, his longtime friend, who was murdered in California in 2000; and his neighbor, Morris Black, who was murdered in Texas in 2001. Answer: being suspected of foul play against three individuals in different states
Answer: | Texas Private Investigator worked on a case involving a New York millionaire primarily known for what? | 8 | NIv2 | task191_hotpotqa_question_generation | fs_opt | [
0.7837376594543457,
0.3380376994609833,
-0.8237434029579163,
1.0233982801437378,
0.5193663835525513,
-0.15907111763954163,
0.6986279487609863,
0.5837059020996094,
-0.07403048872947693,
0.3463640809059143,
-0.06835490465164185,
0.5107598304748535,
-0.9527741074562073,
-0.06729194521903992,
... |
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.
One example: Sox - 4 is important for very early B - cell differentiation , while TCF - 1 / LEF - 1 play a crucial role in early thymocyte development
Solution is here: TCF - 1
Explanation: The gene, TCF - 1 has been tagged as protein since it plays a crucial role in early thymocyte development.
Now, solve this: Diagnostic importance of determining leucine aminotransferase activity in acute pancreatitis
Solution: | leucine aminotransferase | 6 | NIv2 | task1481_gene_extraction_bc2gm_dataset | fs_opt | [
-0.5148899555206299,
0.5182102918624878,
-0.7616543769836426,
-0.2492193728685379,
0.410831481218338,
-0.44326573610305786,
0.10592754185199738,
0.6174992322921753,
0.45048266649246216,
-0.3554312586784363,
-0.6724485158920288,
-0.09534799307584763,
-0.8259588479995728,
-0.3091598153114319... |
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 input: [-83, 53, -48, 8]
Example output: [-80, 50, -50, 10]
Example explanation: The output correctly rounds each integer in the input list to the nearest ten. So this is a good example.
Q: [-572, -454, 198, -951, 194, 289, -747, 820, 635, 451, 293, -430]
A: | [-570, -450, 200, -950, 190, 290, -750, 820, 640, 450, 290, -430] | 3 | NIv2 | task373_synthetic_round_tens_place | fs_opt | [
-0.6306936144828796,
0.5643346309661865,
-0.3662138879299164,
-0.15131248533725739,
-0.37744659185409546,
-0.490473210811615,
1.0189933776855469,
-0.016457118093967438,
-0.32024991512298584,
0.336001455783844,
-0.646504282951355,
0.09738905727863312,
-0.454481303691864,
0.27019891142845154... |
Part 1. Definition
You are given a science question (easy-level) and four answer options (associated with "A", "B", "C", "D"). Your task is to find the correct answer based on scientific facts, knowledge, and reasoning. Do not generate anything else apart from one of the following characters: 'A', 'B, 'C', 'D'. There is only one correct answer for each question.
Part 2. Example
Which part of a bicycle BEST moves in a circle?
(A) Seat (B) Frame (C) Foot pedal (D) Kickstand
Answer: C
Explanation: Seat, frame and Kickstand are static parts of the bicycle, even when bicycle moves. Foot pedal moves in a circle as bicycle moves.
Part 3. Exercise
Which is the best example of an object with kinetic energy?
(A) a plate sitting on a table (B) a bird perching in a tree (C) a marble rolling down a ramp (D) a dam holding back some water
Answer: | C | 7 | NIv2 | task228_arc_answer_generation_easy | fs_opt | [
0.4895438253879547,
0.5472117066383362,
-0.8141855001449585,
-0.2513112723827362,
-0.10082437843084335,
-0.4417797029018402,
0.5956436395645142,
0.31142324209213257,
0.19075354933738708,
-0.21547456085681915,
-0.4074462652206421,
0.8075474500656128,
0.19740739464759827,
-0.1285065114498138... |
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 event. You have to determine whether the Head can be characterized by being or having the Tail or not. Being characterized usually describes entities' general characteristics such as rose is red, or subjective attributes such as thirst is uncomfortable. It can also map to descriptors that speak to the substance or value of items such as meat has the property of being stored in the freezer or bike is powered by a person's legs. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
See one example below:
Problem: Head: water<sep>Tail: effect of making things wet
Solution: Yes
Explanation: This is a good example. The water can be characterized by making things wet.
Problem: Head: apartment<sep>Tail: kitchen
Solution: | Yes | 4 | NIv2 | task1212_atomic_classification_hasproperty | fs_opt | [
0.10085996240377426,
-0.11847634613513947,
0.3130478262901306,
0.11574871838092804,
-0.012254886329174042,
-1.11176335811615,
0.4355534315109253,
1.1211047172546387,
-0.8933560848236084,
0.0444759726524353,
-0.6947547793388367,
-0.5101075172424316,
-0.3304174244403839,
-0.30346328020095825... |
In this task, you will be shown a passage. You need to write a fill-in-the-gap question based on your understanding of the events that might be inferred from the passage. Your question should be answerable based on the passage and only have one correct answer. Show the gap in your question with a _ .
One example: For four years we have waited expectantly for the pitter patter of tiny paws. Soon, that wait could finally be over. Tian Tian, the UK's only female giant panda, has conceived and could give birth to a cub as early as August. However Edinburgh Zoo, where the pandas live, have warned people 'not to get too excited' as the process is 'extremely complex'. Moreover, on the two previous occasions keepers inseminated Tian Tian - whose name means 'Sweetie' - she has failed to produce a panda cub. She was artificially inseminated again in March this year, but keepers at the zoo say implantation - when a fertilised egg attaches to the uterus - has not yet occurred.Tian Tian has conceived and could give birth to a cub as early as August. She has been inseminated twice before but so far failed to produce a cubTian Tian and Yang Guang arrived in 2011 from China to great fanfareOn loan at £600k a year, became first giant pandas to live in UK for 17 years
Solution is here: Under the terms of the agreement any cubs will return to _ at the age of two, the age at which they would normally leave their mother in the wild.
Explanation: This is a good example. Based on the passage you can answer this question.
Now, solve this: Gareth Southgate wants his players to show England teams can entertain and win with style as their preparations for Euro 2015 intensify. Though the senior side have not lost a game since the World Cup finals last summer, they have rarely provided football to quicken the pulse in the time since and never was that more apparent than in the charmless 0-0 draw with the Republic of Ireland. The situation has been different for the Under-21s. They have thrived under Southgate’s guidance and their ability to play with fluency and class was shown when they put together a 35-pass move that ended with James Ward-Prowse scoring the decisive goal in a 3-2 win over Germany in March.England Under 21's are continuing their preparations for this summer's European Championship in the Czech RepublicGareth Southgate wants his side to win and do so in styleSouthgate has high hopes for his U21 squad this summerHarry Kane returned to training following a break away on Tuesday, while Danny Ings trained for the first time since signing for Liverpool
Solution: | _ will play a near full-strength side but Chelsea’s Ruben Loftus-Cheek may figure. | 6 | NIv2 | task301_record_question_generation | fs_opt | [
-0.10451105982065201,
0.2715730667114258,
-0.8872148990631104,
0.1134505644440651,
0.2938641905784607,
-0.1121734231710434,
0.5856441259384155,
0.7838892936706543,
-0.5111972689628601,
0.17588603496551514,
0.10798916220664978,
0.5115329027175903,
-1.1012377738952637,
0.13126562535762787,
... |
instruction:
Based on the given context, craft a common-sense question, especially those that are LONG, INTERESTING, and COMPLEX. The goal is to write questions that are easy for humans and hard for AI machines! To create such questions, here are some suggestions: A. What may (or may not) be the plausible reason for an event? B. What may (or may not) happen before (or after, or during) an event? C. What may (or may not) be a plausible fact about someone (or something)? D. What may (or may not) happen if an event happens (or did not happen)? You can also create other types of questions. DO NOT make your question answerable without looking at the context, or question of which the correct answer can be directly extracted from the context. DO NOT ask a question that requires very specialized knowledge that is not common sense. DO NOT ask too simple or too short questions. Your question must be related to the context and answerable with common sense. Try to add more variations and complexity to the questions.
question:
Context: The walk in was quite tiring actually plus the hot scorching sun . And as for today , our main activity was to watch Money Not Enough 2 . It was supposely a humurous movie but I ended up tearing . I do nt know why but probably because I jus feel sad for the Mother who was put to Old Folks Home by the 3 Sons .
answer:
Given the context , which is true of the narrator ?
question:
Context: Although I know he will not read my blog in future , I still write this blog in English since I know he ca n't understand any English . I do n't want him to read this blog . Suddenly , I realised that I even have n't taken a photo with him .
answer:
What do you know about the speaker ?
question:
Context: Now that the stroke job is over , Mike talked about this on his show today . It 's an obituary that was posted in a local newspaper called the Daily Breeze in a community close to Los Angeles . When it first made the rounds on the internet it was believe it was a hoax . But it 's not , it 's been verified by the newspaper which has a copy of the death certificate .
answer:
| How was it known that the death was not a hoax after all ?
| 9 | NIv2 | task023_cosmosqa_question_generation | fs_opt | [
0.3890891969203949,
0.5073071122169495,
-0.174209326505661,
0.5397846102714539,
0.08151078224182129,
-0.46271318197250366,
0.4599570035934448,
0.7179557085037231,
-0.35626912117004395,
0.2565772533416748,
0.15540659427642822,
-0.060346513986587524,
-0.42718255519866943,
0.6688894033432007,... |
You will be given a definition of a task first, then some input of the task.
Given a post that is a real-life anecdote of a complex ethical situation and a question asks if AUTHOR, NOBODY, EVERYBODY, or OTHER is wrong in the situation. Answer the question and classify your answers into yes or no.
Is AUTHOR wrong in the post ? POST : I am in a class in university that consists of only juniors and seniors. In this class, I sit in the second row all the way to the left. It being a higher level class that doesn't always take attendance, many people decide not to show up to class, so there are often empty seats around me. However, I always sit next to my friend and there is always someone sitting in front of me.
An assignment for the class is to write an Op-Ed, basically a short opinionated article. As part of the assignment, everyone in the class was randomly assigned two others to peer review their article.
Of the two I was assigned, one was pretty good. They had a few grammatical errors and their points were a little confusing at times, but overall decent. I also didn't know too much about their topic to begin with.
The second one I reviewed was a train wreck at best. There were so many grammatical errors that I couldn't even read through the paper once without having to make corrections. Their sentence structure was so bad that I had to stop and try to parce out what it was supposed to say. I also knew a lot about this topic since I had written a paper on it a semester ago. They had the basic idea about the topic, but they left out a huge part of it that was really important to their point they were making. All of that I left in my review that had my name attached to it online, but I didn't know who the person really was.
As class was ending the other day, my friend and I's conversation drifted to the Op-Eds that we had reviewed as people were packing up to leave. It turns out that he had looked at the first one I reviewed for fun and he had liked it as well. The other one he reviewed had some issues, but was ok overall. I told him about the topic that my second reviewed Op-Ed was about and what the person had left out. I reffered to the grammatical errors and bad sentence structure as a "hot mess" as I complained.
I started to hear someone near me saying "hey" to get my attention and I looked up at the person who sat right in front of me. They informed me that I was talking about their paper and then walked away. My friend and I got real quiet and he gave me a 'you really screwed up now' face. I said that I stand by what I said, since basically all the things I mentioned were in my review online that had my name attached to it anyway.
Now I'm not sure if I should feel bad about trash talking someone's paper and them calling me out for it.
Output: | yes | 1 | NIv2 | task502_scruples_anecdotes_whoiswrong_verification | zs_opt | [
0.4435758590698242,
-0.035711467266082764,
-0.0762178972363472,
-0.16136442124843597,
0.5730101466178894,
-0.40759778022766113,
0.8282651901245117,
0.9200831651687622,
0.09141227602958679,
-0.004633571021258831,
-0.07930472493171692,
-0.1748613715171814,
-0.00780061399564147,
-0.1671309173... |
Given a 'poster' sentence and a corresponding 'response' (often, from Facebook or Reddit)classify the sentiment of the given response into four categories: 1) Positive, 2) Negative, 3) Neutral, and 4) Mixed if it contains both positive and negative.
Example Input: Poster: Isakson Statement on Budget Deal That Avoids Shutdown of Government Responser: Glad we take all our pay on the first, surely they will work it out before then, just in case, we will live on a shoe string this month!
Example Output: Mixed
Example Input: Poster: WATCH: Ja Rule's Music Festival Turns Into Chaos From Good Morning America Responser: Arbol Hombre, you didn't tell me Ja Rule was the headliner! That's the real travesty!
Example Output: Positive
Example Input: Poster: On Sun,11/22,join @American_Heart 4 the 2015 #Miami-Dade #Heart Walk at Museum Park 8am 2 help work 4 heart health!Call (954)364-5012 4 info Responser: http://www.presstv.ir/Detail/2015/11/05/436362/Palestine-Israel-UN-Riyad-Mansour-organ-trafficking
Example Output: | Negative
| 3 | NIv2 | task823_peixian-rtgender_sentiment_analysis | fs_opt | [
-0.30073919892311096,
-0.3381161391735077,
0.10254737734794617,
0.21391597390174866,
0.3665987253189087,
-0.32237666845321655,
0.2922282814979553,
0.024047117680311203,
-0.45813626050949097,
0.6049503684043884,
-0.48838749527931213,
-0.3407471477985382,
-0.13867148756980896,
-0.30022394657... |
Teacher:The given sentence contains a typo which could be one of the following four types: (1) swapped letters of a word e.g. 'niec' is a typo of the word 'nice'. (2) missing letter in a word e.g. 'nic' is a typo of the word 'nice'. (3) extra letter in a word e.g. 'nicce' is a typo of the word 'nice'. (4) replaced letter in a word e.g 'nicr' is a typo of the word 'nice'. You need to identify the typo in the given sentence. To do this, answer with the word containing the typo.
Teacher: Now, understand the problem? Solve this instance: a vintage photo of a baseball platyer
Student: | platyer | 6 | NIv2 | task088_identify_typo_verification | zs_opt | [
-0.8185623288154602,
0.14158667623996735,
-0.19628486037254333,
0.8916854858398438,
0.5263786315917969,
-1.0311957597732544,
0.9760129451751709,
0.0725424587726593,
0.34734755754470825,
0.025530684739351273,
0.40818607807159424,
-0.31955686211586,
-0.7878605127334595,
-0.15863916277885437,... |
A text is given in Tamil. Translate it from the Tamil language to the Hindi language. The translation must not omit or add information to the original sentence.
One example is below.
Q: முன் கூட்டி அறிந்துகொள்ள முடியாத பருவநிலையினால் ஏற்படும் பாதிப்புகளில் இருந்து விவசாயிகலை பாதுகாக்க பிரதமர் பயிர் காப்பீட்டுத் திட்டம் செயல்படுத்தப்படுகிறது
A: फार्म की रक्षा के लिए प्रधान मंत्री की फसल बीमा योजना लागू की जाती है
Rationale: Correct translation for given sentence. Input sentence means 'The Prime Minister's Crop Insurance Plan is implemented to protect the farm' which is the same as the output sentence.
Q: நண்பர்களே, தோல்வி மனப்பான்மை நிலை, விரக்தி நிலை, நம்பிக்கையற்ற நிலைகள் ஒருபோதும் நாட்டை முன்னெடுத்துச் செல்லாது.
A: | साथियों, हार-हताशा-निराशा का वातावरण कभी किसी देश को आगे नहीं ले जा सकता। | 9 | NIv2 | task994_pib_translation_tamil_hindi | fs_opt | [
-0.23697425425052643,
0.07159881293773651,
0.1391991674900055,
-0.08356352150440216,
0.09464840590953827,
-1.3604955673217773,
0.15544524788856506,
0.5393276214599609,
-0.7155455350875854,
0.4449673891067505,
-0.8409487009048462,
-0.20665937662124634,
-0.5077527761459351,
0.311187505722045... |
Q: You are given a sentence in Polish. Your job is to translate the Polish sentence into Arabic.
O rasizmie, ucisku, o tym, że ludzie tacy jak ja nie mają lekko w życiu.
A: | العنصرية ، الاكتئاب ، الأشخاص المشابهين لي الذين لم ينالوا فرصتهم في الحياة. | 7 | NIv2 | task1259_ted_translation_pl_ar | zs_opt | [
-0.4833659827709198,
0.6957603693008423,
-0.20861518383026123,
-0.20892608165740967,
-0.5864987373352051,
0.14430473744869232,
1.3050086498260498,
0.5160688757896423,
0.6233607530593872,
0.23284223675727844,
-0.3557378053665161,
0.07190948724746704,
-0.947840690612793,
0.1090271919965744,
... |
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].
One example: Verify if the sentiment of the following document towards the entity Bill Clinton is Negative. Bill Clinton knows how to win friends and influence people.
Solution is here: no
Explanation: Here the author of the document praises Bill for this ability to win friends. So the sentiment should be Positive and not Negative.
Now, solve this: Verify if the sentiment of the following document towards the entity Michael Moore is Neutral . “While not at all presidential I must point out that the Sloppy Michael Moore Show on Broadway was a TOTAL BOMB and was forced to close. Sad!” Trump tweeted Saturday evening about Moore’s show.
Solution: | yes | 6 | NIv2 | task422_persent_sentence_sentiment_verification | fs_opt | [
-1.5096981525421143,
0.21058309078216553,
0.9586238861083984,
0.38871467113494873,
0.47304806113243103,
-1.5280766487121582,
0.7483083605766296,
0.596463680267334,
0.30676814913749695,
0.397128701210022,
0.257392555475235,
-0.40574735403060913,
-0.29774755239486694,
-0.2565445303916931,
... |
You will be given a definition of a task first, then some input of the task.
Given a sentence and two mentions from the text (arguments), indicate a phrase (a verb or noun phrase) that describes the relationship between the provided arguments.
Sentence: 'Buck turned his attention to Vin .', Argument/Subject 1: 'vin', Argument/Subject 2: 'buck'
Output: | turn to | 1 | NIv2 | task676_ollie_relationship_answer_generation | zs_opt | [
-0.5613155364990234,
0.7114686369895935,
0.05705057457089424,
0.46449318528175354,
-0.5407966375350952,
-0.01713727042078972,
0.5736958384513855,
0.5425107479095459,
0.9114397764205933,
0.15654537081718445,
-0.42668184638023376,
-0.20781302452087402,
-0.5591000318527222,
0.2422839850187301... |
Detailed Instructions: In this task you will be given a list of integers. You should find the minimum absolute difference between 2 integers in the list. The absolute difference is the absolute value of one integer subtracted by another. The output should be a single integer which is the smallest possible absolute distance.
Q: [-52, -39, -20, -7, 56, 47, 51, 97, -68, 69]
A: | 4 | 9 | NIv2 | task1445_closest_integers | zs_opt | [
-0.4445800185203552,
0.9661228060722351,
0.2880363166332245,
-0.5439285635948181,
-0.06757916510105133,
-0.879165530204773,
1.027984857559204,
0.07607030868530273,
0.4305031895637512,
-0.19252540171146393,
-0.29785317182540894,
-0.3515704870223999,
-0.9739991426467896,
0.582040548324585,
... |
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 have to determine whether the Head is located or can be found at/in/on the Tail or not. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Input: Head: PersonX accepts ___ as PersonX's savior<sep>Tail: to go to heaven
Output: | No | 3 | NIv2 | task1207_atomic_classification_atlocation | zs_opt | [
0.23274022340774536,
0.5583156943321228,
0.30451470613479614,
-0.22726444900035858,
-0.7839507460594177,
-0.7235448360443115,
1.1302119493484497,
0.46046674251556396,
-0.5331013798713684,
-0.6379498839378357,
-0.5783286094665527,
-0.44202888011932373,
-0.5969318747520447,
0.487591087818145... |
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Spanish.
コメディー番組のテコ入れに突然新しい親戚の子が登場するみたいなひょんなところからきた子供だったんです
Output: | Era como el primo Oliver en la comedia de TV de la familia Krosoczka el niño nuevo que salió de la nada. | 1 | NIv2 | task1223_ted_translation_ja_es | zs_opt | [
-0.336179256439209,
0.6146882176399231,
0.04012563079595566,
-0.397657573223114,
0.3296717405319214,
0.02956712245941162,
0.39452505111694336,
0.8433188199996948,
0.6568061113357544,
-0.7696520686149597,
-0.34892958402633667,
-0.17011651396751404,
-0.6552019119262695,
-0.05704601854085922,... |
Given the task definition and input, reply with output. You are given a sentence in English. Your job is to translate the English sentence into Persian.
He liked to talk about the spiritual geniuses of the ages.
| او دوست داشت درباره نوابغ روحانی زمان خود صحبت کند. | 5 | NIv2 | task1093_ted_translation_en_fa | zs_opt | [
-1.5136168003082275,
0.5497889518737793,
0.41908735036849976,
-0.28324177861213684,
-0.589795708656311,
-0.0029861785005778074,
0.7008828520774841,
-0.25084176659584045,
0.3953211307525635,
0.009073087945580482,
-0.3400088846683502,
0.9697360992431641,
-0.601526141166687,
-0.11864055693149... |
Instructions: You are given a password and you need to generate the number of steps required to convert the given password to a strong password. A password is considered strong if (a) it has at least 6 characters and at most 20 characters; (b) it contains at least one lowercase letter and one uppercase letter, and at least one digit; (c) it does not contain three repeating characters in a row. In one step you can: (1) Insert one character to password, (2) delete one character from password, or (3) replace one character of password with another character.
Input: password = OLuRVCHM.6IT68Ej8RF2L.x2JLRnazu9Q
Output: | 13 | 3 | NIv2 | task956_leetcode_420_strong_password_check | zs_opt | [
0.620278000831604,
1.2958152294158936,
0.07239243388175964,
-0.8322981595993042,
-0.1387985646724701,
-0.16906586289405823,
1.3268311023712158,
-0.24446254968643188,
0.2367221713066101,
-1.0295497179031372,
0.03160284459590912,
-0.10936813056468964,
-0.8968820571899414,
-0.4481308162212372... |
In this task, you are given two simple actions (associated with "A", "B"). You must identify which action is considered less ethical. Do not generate anything else apart from one of the following characters: 'A', 'B'.
(A) saying no to going to formal with someone
(B) not wanting to room with my friend | B | 0 | NIv2 | task106_scruples_ethical_judgment | zs_opt | [
0.005582960322499275,
1.0582258701324463,
0.5043228268623352,
-0.4554722011089325,
-0.7883914709091187,
-0.4034932255744934,
0.02390221692621708,
-0.2087620198726654,
0.04727649688720703,
0.6058522462844849,
-0.014612361788749695,
-0.0676300972700119,
0.06711047887802124,
-0.80392622947692... |
Given a sentence in Chinese, provide an equivalent paraphrased translation in German that retains the same meaning both through the translation and the paraphrase.
[EX Q]: 特拉布宗世界贸易中心的大楼靠近特拉布宗机场。
[EX A]: Der Komplex des World Trade Center Trabzon befindet sich in der Nähe des Flughafens Trabzon.
[EX Q]: 他曾多次被选为阿萨姆足球协会和阿萨姆体育委员会主席，并且还是阿萨姆板球协会的副主席。
[EX A]: Er wurde für mehrere Amtszeiten zum Präsidenten des Assam Football Association und des Assam Sports Council gewählt. Er war auch der Vizepräsident der Assam Cricket Association.
[EX Q]: 克罗克从密西西比州的纳奇兹搬到康科迪亚教区的总部维达利亚，并在黑河区穿越了下瓦希塔。
[EX A]: | Crocker zog von Natchez, Mississippi, nach Vidalia, dem Sitz der Concordia-Gemeinde, und überquerte die Uuachita im Black River.
| 6 | NIv2 | task811_pawsx_chinese_german_translation | fs_opt | [
0.15639953315258026,
0.5002070665359497,
-0.6176732778549194,
-0.6807081699371338,
0.06942860037088394,
0.154214009642601,
0.4665568470954895,
0.025999020785093307,
-0.0330265611410141,
0.6384289264678955,
0.2330615222454071,
0.6924535036087036,
-1.0256247520446777,
0.5626000165939331,
-... |
Detailed Instructions: In this task you are given a sentence. You must judge whether the object of the main clause is singular(like: apple) or plural(like: apartments). Label the instances as "Singular" or "Plural" based on your judgment.
Problem:I heard the gunfire. "
Solution: | Singular | 8 | NIv2 | task431_senteval_object_count | zs_opt | [
-0.7852617502212524,
0.6101856231689453,
-0.02101781778037548,
-0.12169403582811356,
-0.21956412494182587,
-0.7878197431564331,
1.116620421409607,
0.4152439832687378,
0.21905545890331268,
-0.3202991187572479,
-0.23845824599266052,
-0.43311038613319397,
-0.9589556455612183,
-0.5869628787040... |
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 part-of-speech tags i.e. tagset of this corpus is 'ADJ': Adjectives are words that typically modify nouns and specify their properties or attributes, 'ADP': Adposition is a cover term for prepositions and postpositions, 'ADV': Adverbs are words that typically modify verbs for such categories as time, place, direction or manner, 'AUX': An auxiliary is a function word that accompanies the lexical verb of a verb phrase and expresses grammatical distinctions not carried by the lexical verb, such as person, number, tense, mood, aspect, voice or evidentiality, 'CCONJ': A coordinating conjunction is a word that links words or larger constituents without syntactically subordinating one to the other and expresses a semantic relationship between them, 'DET': Determiners are words that modify nouns or noun phrases and express the reference of the noun phrase in context, 'INTJ': An interjection is a word that is used most often as an exclamation or part of an exclamation, 'NOUN': Nouns are a part of speech typically denoting a person, place, thing, animal or idea, 'NUM': A numeral is a word, functioning most typically as a determiner, adjective or pronoun, that expresses a number and a relation to the number, such as quantity, sequence, frequency or fraction, 'PART': Particles are function words that must be associated with another word or phrase to impart meaning and that do not satisfy definitions of other universal parts of speech, 'PRON': Pronouns are words that substitute for nouns or noun phrases, whose meaning is recoverable from the linguistic or extralinguistic context, 'PROPN': A proper noun is a noun (or nominal content word) that is the name (or part of the name) of a specific individual, place, or object, 'PUNCT': Punctuation marks are non-alphabetical characters and character groups used in many languages to delimit linguistic units in printed text, 'SCONJ': A subordinating conjunction is a conjunction that links constructions by making one of them a constituent of the other. The subordinating conjunction typically marks the incorporated constituent which has the status of a (subordinate) clause, 'SYM': A symbol is a word-like entity that differs from ordinary words by form, function or both, 'VERB': A verb is a member of the syntactic class of words that typically signal events and actions, can constitute a minimal predicate in a clause, and govern the number and types of other constituents which may occur in the clause, 'X': The tag X is used for words that for some reason cannot be assigned a real part-of-speech category.
Sentence: Kids {{ fun }} games and video shows are added to the other facilities .
Word: fun
| ADJ | 5 | NIv2 | task583_udeps_eng_coarse_pos_tagging | zs_opt | [
0.656956672668457,
0.2747812569141388,
0.030127719044685364,
0.031644389033317566,
0.03550541400909424,
-0.37095212936401367,
0.7067725658416748,
0.5946206450462341,
-0.3546738624572754,
-0.2911023497581482,
-0.30095374584198,
0.07999016344547272,
-0.41437581181526184,
0.38332223892211914,... |
You will be given a definition of a task first, then some input of the task.
You are supposed to identify the category of a high-school level math question. There are five possible categories (1) algebra (2) arithmetic (3) measurement (4) numbers, and (5) probability. Use the following guidelines: (1) 'algebra' questions will typically contain letter variables and will ask you to find the value of a variable (2) 'arithmetic' questions will ask the sum, difference, multiplication, division, power, square root or value of expressions involving brackets (3) 'measurement' questions are questions that ask to convert a quantity from some unit to some other unit (4) 'numbers' questions will be about bases, remainders, divisors, GCD, LCM etc. (5) 'probability' questions will ask about the probability of the occurrence of something. A question must belong to only one category.
How many months are there in 21/8 of a century?
Output: | measurement | 1 | NIv2 | task834_mathdataset_classification | zs_opt | [
0.21456244587898254,
0.28296947479248047,
-0.22932052612304688,
-0.017194941639900208,
0.02331892028450966,
0.0012328103184700012,
0.23668581247329712,
0.26264986395835876,
0.10685031116008759,
-0.39069056510925293,
-0.6897923946380615,
-0.010850397869944572,
0.06120971217751503,
-0.125047... |
Given a sentence, generate what should be the most likely next statement. The next statement should be reasonable and logically correct.
Input: Consider Input: Next, the lemon is squeezed over the cub and honey is put in the mason jars. Now the water is boiled and put it the jars and slices of the lemons
Output: are added and stirred.
Input: Consider Input: The person add egg and swirls it around. The person
Output: pushes the egg into a corner and continues cooking it.
Input: Consider Input: The boy lingers, staring at her. She
| Output: leans forward with an inviting smile.
| 2 | NIv2 | task453_swag_answer_generation | fs_opt | [
0.3830951154232025,
1.1192072629928589,
0.05118534713983536,
-0.06622516363859177,
0.23736244440078735,
-0.48355019092559814,
-0.09385925531387329,
0.5116719603538513,
-0.06577242165803909,
-0.7055944204330444,
0.15183410048484802,
0.3740638196468353,
-0.5373267531394958,
0.125469177961349... |
Given the task definition and input, reply with output. Given a part of privacy policy text, identify the type of personal information which is collected, used, tracked or retained. The type of information should be present inside the given policy text, answer as 'Not Specified' otherwise
An unnamed third party does receive unspecified information about you for service operations or security. The data is aggregated or anonymized.
| Unspecified | 5 | NIv2 | task684_online_privacy_policy_text_information_type_generation | zs_opt | [
-0.7491180896759033,
0.35846102237701416,
-0.4496508538722992,
0.1491345465183258,
-0.7427616119384766,
-0.3815377354621887,
0.0507228709757328,
0.17960737645626068,
0.11400826275348663,
0.5785713791847229,
-0.0016944323433563113,
-0.08638975024223328,
-0.33738672733306885,
-0.820700824260... |
In this task, you are given inputs i,j, and A, where i and j are integers and A is a list. You need to list all elements of A from the ith element to the jth element in the reverse order. i and j will be non-negative, and will always have a value less than the length of A. i will always be less than j.
1, 2, ['9721', 't']
t, 9721
2, 4, ['F', 'R', '5171', 'a', '2645', 'x', '2201', '8475', '5067', 'X', '823', 'z', '2065', '495', '9501', '7417', 'd', 'x', 'W', '6295', 'f', 'I', 'q']
a, 5171, R
11, 20, ['9987', '8635', '6965', 'l', '7499', '7407', 'Q', '6615', '6425', '5669', '187', 'a', '8159', '2801', '5245', '411', '4135', 'q', 'i', '5569', '3403', '6153', '7899', '9793', '4301', '3961', 'E']
| 5569, i, q, 4135, 411, 5245, 2801, 8159, a, 187
| 0 | NIv2 | task099_reverse_elements_between_index_i_and_j | fs_opt | [
-0.06953510642051697,
0.06455722451210022,
-0.4885253310203552,
-0.17519307136535645,
-0.17443567514419556,
-0.3069568872451782,
0.8701827526092529,
0.40443524718284607,
-0.6310959458351135,
0.4484556317329407,
-0.825263261795044,
0.2590879797935486,
-0.08850929886102676,
0.248086333274841... |
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