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Detailed Instructions: Given reviews from Amazon, classify those review based on their content into two classes: Negative or Positive.
Q: Very compact, well made, helps me level the camera when I set it on sloped surfaces and it stays in place due to the rubber feet. For the price and size it's a great alternative.
A: | Positive | 9 | NIv2 | task493_review_polarity_classification | zs_opt | [
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|
Given the task definition and input, reply with output. In this task, you are given a sentence and a profession. The sentence mentions two professions: one's gender is identifiable using the coreference link with gendered pronouns and the other's gender is unidentifiable. You are expected to return whether the given profession's gender is identifiable or unidentifiable.
Sentence: The sheriff chatted with the tailor and invited her to dinner later.
Profession: sheriff
| Unidentifiable | 5 | NIv2 | task350_winomt_classification_gender_identifiability_pro | zs_opt | [
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|
You will be given a definition of a task first, then some input of the task.
You are given a short paragraph, a question and two choices to answer from. Choose the correct answer based on the paragraph and write the answer(not the key).
Paragraph: Its harder to overcome friction between heavier objects and the floor than it is between lighter objects and the floor.
Question: If Milo is sliding a basketball and a baseball across the floor and the baseball is the heavier of the two objects, which object will experience more friction?
Choices: A)basketball
B)baseball
Output: | baseball | 1 | NIv2 | task1731_quartz_question_answering | zs_opt | [
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|
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.
Ex Input:
I_TURN_LEFT I_JUMP I_TURN_LEFT I_JUMP I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK I_TURN_LEFT I_LOOK
Ex Output:
look around left after jump left twice
Ex Input:
I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_LEFT I_WALK I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP I_TURN_RIGHT I_JUMP
Ex Output:
walk left thrice and jump around right twice
Ex Input:
I_TURN_LEFT I_TURN_LEFT I_JUMP I_TURN_LEFT I_TURN_LEFT I_JUMP I_TURN_LEFT I_TURN_LEFT I_JUMP I_WALK I_WALK I_WALK
Ex Output:
| walk thrice after jump opposite left thrice
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|
In this task you will break down a question into the basic steps required to answer it.
A question decomposition is a numbered list of operations that must be performed to answer the original question. Imagine explaining your question to a friendly droid by listing each action it should take in order for the question to be answered. Each step in our decomposition should refer to either an entity (known or unknown), a propery of an entity or a query operation (count, group, union, etc.)
Here are the list of step templates and their description:
Select: A select step is used to return a set of objects. There are no references to previous steps in a select step. template: Return [attributes]
Filter: A filter step is used to return results from a previous step to which a certain condition applies. template: Return [#step] [condition]
Project: A project step should return certain attributes of the results of a previous step. template: Return [attributes] of [#step]
Aggregate: An aggregate step returns an aggregator function applied on a step's result. template: Return the [aggregator] of [#step].
Group: A group step is an aggregator applied on attributes. template: Return the [aggregator] of [#step] for each [attribute]
Superlative: A superlative step is used to return the result with a highest/lowest attribute among other results. template: Return [#step1] [where] [#step2] [is] [highest / lowest]
Comparative: A comparative step is used when we need to compare an attribute with a number to filter results. template: Return [#step1] [where] [#step2] [comparator] [number]
Union: A union step is used to return results of two steps together. template: Return [#step1] [or / ,] [#step2]
Intersection: An intersection step returns the result that two steps have in common. template: Return [attribute] of both [#step1] and [#step2]
Discard: A discard step returns result of a step and excludes result of another step from it. template: Return [#step1] besides [#step2]
Sort: A sort returns result of another step in a specific order. template: Return [#step1] [ordered / sorted by] [#step2]
Is true: An is true step checks a condition on another result and returns a true or false. template: Return [is / if] [condition]
Arithmetic: An arithmatic step operates an arithmatic operation on one or more steps. template: Return the [arithmetic op.] of [#step1] [and] [#step2].
Input: Consider Input: question: If each image features one bamboo flute displayed diagonally so one end is on the upper right.
Output: #1 return flutes
#2 return #1 that are bamboo
#3 return #2 that are displayed diagonally
#4 return end of #3
#5 return #3 where #4 is in the upper right
#6 return images
#7 return number of #5 for each #6
#8 return #6 where #7 is equal to one
#9 return number of #6
#10 return number of #8
#11 return if #9 is equal to #10
Input: Consider Input: question: Who got the shortest TD run?
Output: #1 return TD runs
#2 return how short are #1
#3 return #1 where #2 is the lowest
#4 return who got #3
Input: Consider Input: question: How many more men did the UN forces have throughout the course of the battle then they had at the start of the battle?
| Output: #1 return the UN forces
#2 return men of #1
#3 return #2 throughout the course of the battle
#4 return #2 at the start of the battle
#5 return number of #3
#6 return number of #4
#7 return the difference of #5 and #6
| 2 | NIv2 | task176_break_decompose_questions | fs_opt | [
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|
In this task, you are given a sentence in the Swedish language and a corresponding English translation of the Swedish sentence. Your task is to generate a label "Yes" if the translation is correct, otherwise generate label "No".
One example: Swedish: Jag förklarar debatten avslutad.
English: The debate is closed.
Solution is here: Yes
Explanation: Swedish sentence is properly converted into English sentence.
Now, solve this: Swedish: Det fick starkt stöd från övriga kommissionärer och samråd om det har hållits i hela kommissionen.
English: Despite all these successes – and I think that this shows that the euro may well be one of the EU’s most successful, if not most successful, project to date – we notice that many regular consumers do not seem to be in agreement with us.
Solution: | No | 6 | NIv2 | task314_europarl_sv-en_classification | fs_opt | [
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|
In this task you will be given an arithmetic operation and you have to find its answer. The operators '+' and '-' have been replaced with new symbols. Specifically, '+' has been replaced with the symbol '@' and '-' with the symbol '#'. You need to perform the operations in the given equation return the answer
Let me give you an example: 6 @ 17
The answer to this example can be: 23
Here is why: Here, '@' represents the addition operation. So, the answer is 23 (6+17=23).
OK. solve this:
4563 @ 9607 # 8291 @ 8605 # 2965 # 8742 # 1182 @ 155 @ 3490
Answer: | 5240 | 8 | NIv2 | task087_new_operator_addsub_arithmetic | fs_opt | [
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|
You will be given a definition of a task first, then some input of the task.
In this task, given a sentence in the English language, your task is to convert it into the Chinese language.
It began its existence flying a small 15 seat aircraft between Waterford and London Gatwick with the small aim of breaking the duopoly on London-Ireland flights, held at that time by British Airways and Aer Lingus.
Output: | 它最初是在沃特福德和伦敦盖特威克机场之间运营一架15座的小型飞机，目的是打破当时由英国航空公司和爱尔兰航空公司把持的伦敦-爱尔兰航线的双头垄断。 | 1 | NIv2 | task548_alt_translation_en_ch | zs_opt | [
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|
Q: In this task, you will be shown an extract from a movie plot. You need to read the extract and create questions that can be answered from the extract. Once you create a question you also need to provide the correct answer for it. Write your answer like "Question: your question, Answer: your answer". The questions should be well-formed and grammatically correct. The questions should be completely answerable from the given passage and should not require any external knowledge. Subjective questions are not allowed. Short answers containing words that are present in the passage are preferred. Create questions that result in factoid answers. A simple rule of thumb to decide whether a question is a factoid or not is to see if two different people with average reading/comprehension skills would come up with the same answer after reading the passage.
Set in 1953, during the early days of television broadcast journalism. Edward R. Murrow (David Strathairn) and his dedicated staff â headed by his co-producer Fred Friendly (George Clooney) and reporter Joseph Wershba (Robert Downey, Jr.) in the CBS newsroomâdefy corporate and sponsorship pressures, and discredit the tactics used by Joseph McCarthy during his crusade to root out Communist elements within the government.Murrow first defends Milo Radulovich, who is facing separation from the U.S. Air Force because of his sister's political leanings and because his father is subscribed to a Serbian newspaper. Murrow makes a show on McCarthy attacking him. A very public feud develops when McCarthy responds by accusing Murrow of being a communist. Murrow is accused of having been a member of the leftist union Industrial Workers of the World, which Murrow claimed was false.In this climate of fear and reprisal, the CBS crew carries on and their tenacity ultimately strikes a historic blow against McCarthy. Historical footage also shows the questioning of Annie Lee Moss, a Pentagon communication worker accused of being a communist based on her name appearing on a list seen by an FBI infiltrator of the American Communist Party. The film's subplots feature Joseph and Shirley Wershba, recently married staffers, having to hide their marriage to save their jobs at CBS as well as the suicide of Don Hollenbeck (Ray Wise) who had been accused in print of being a Communist.The film is framed by performance of the speech given by Murrow to the Radio and Television News Directors Association in 1958, in which Murrow harshly admonishes his audience not to squander the potential of television to inform and educate the public, so that it does not become only "wires and lights in a box".[2]
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|
A text is given in Hindi. Translate it from the Hindi language to the Oriya language. The translation must not omit or add information to the original sentence.
One example: ଏହି ପ୍ରସଙ୍ଗରେ ନୀତି ପ୍ରଣୟନ ସମୟରେ ଉଚ୍ଚସ୍ତରୀୟ କମିଟିର ସୁପାରିସଗୁଡ଼ିକୁ ପେଟ୍ରୋଲିୟମ ଏବଂ ପ୍ରାକୃତିକ ବାଷ୍ପ ମନ୍ତ୍ରଣାଳୟ ବିବେଚନା କରିବ ବୋଲି ସୂଚନା ମିଳିଛି ।
Solution is here: इस घटना की जानकारी को निजी समिति को जानकारी के रूप में पाया गया है, उच्च स्तरीय समिति की सिफारिश प्राप्त की जाएगी।
Explanation: Correct translation for given sentence. Input sentence means 'The information in this event have been found private committeeers as information, the recommendation of the high-level committee will have been obtained.' which is the same as the output sentence.
Now, solve this: ମଧୁମେହ ଭଳି ସ୍ୱାସ୍ଥ୍ୟଗତ ସମସ୍ୟାଠାରୁ ଦୂରେଇ ରହିବା ଲାଗି ସୁସ୍ଥ ଜୀବନଯାପନ ଶୈଳୀ ଆପଣେଇବାକୁ ହେବ । ଏଥିଲାଗି ବିଶ୍ୱ ମଧୁମେହ ଦିବସରେ ଶପଥ ନେବାକୁ ପ୍ରଧାନମନ୍ତ୍ରୀ ଶ୍ରୀ ନରେନ୍ଦ୍ର ମୋଦୀ ଜନସାଧାରଣଙ୍କୁ ଆହ୍ଵାନ କରିଛନ୍ତି ।
Solution: | जीएसटी कानून में उल्लिखित मुनाफारोधी उपाय यह सुनिश्चित करने के लिए संस्थागत ढांचे की व्यवस्था करती है कि वस्तुओं और सेवाओं की आपूर्ति पर इनपुट टैक्स क्रेडिट और जीएसटी की घटी हुई दरों का पूर्ण लाभ उपभोक्ताओं तक पहुंचे। | 6 | NIv2 | task986_pib_translation_oriya_hindi | fs_opt | [
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|
Instructions: In this task, you're given a review from Amazon's food products. Your task is to generate a short summary of the given review in the input. Note that you don't need to write a complete sentence as a summary.
Input: Product is always excellent. It is very hard to find Packaging in any smaller sizes. still trying to find a Link for smaller and different quantities available.
Output: | Glitterati candy | 3 | NIv2 | task589_amazonfood_summary_text_generation | zs_opt | [
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|
Instructions: Given a real-life anecdote of a complex ethical situation, generate a suitable title that describes the main event/root cause of the situation. Imagine that the given text is a social media post, and you have to write the title of the post, so the users can decide to read the main text or not.
Input: There is a party tonight, which I do not want to attend, I will be going (against my will) and I was told I am shitty for holding the group back/ not participating. I view this differently, I have no close friends that will be attending the party, and didn't have fun at the same party last year. It'd be different if it was just me going to one of my band parties where I know and appreciate the company of the other people, but I am truly wondering if AITA for voicing against attending the party and being a buzzkill?
Output: | not wanting to go a to a party | 3 | NIv2 | task500_scruples_anecdotes_title_generation | zs_opt | [
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|
Teacher:In this task, you're given reviews from Amazon's products. Your task is to generate the Summary of the review.
Teacher: Now, understand the problem? Solve this instance: Don't expect this to last. Consider another brand.
Student: | It's unfortunate that SoundPEATS products aren't built for the long-haul. | 6 | NIv2 | task618_amazonreview_summary_text_generation | zs_opt | [
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You are given a paragraph, with numbered sentences, and a question. Write the numbers of the sentences needed to answer the given question. Separate multiple sentence numbers with a comma (", "). E.g. "1, 2" would be the correct response if Sent 1 and Sent 2 are needed to answer the given question (do not include sentences that contain no information that is necessary to answer the question). Sort the sentence numbers in an increasing order (i.e., '1, 2', instead of '2, 1'). Your answer should not contain anything than the sentence numbers separated by a comma (e.g. '1, 2, 3, 4'). The given question requires more than one sentence to answer. So, your answer must contain at least one comma (", ").
One example is below.
Q: Paragraph- Sent 1: A Republican bid to keep the government open past Friday includes no new money for the construction of a border wall along the U.S.-Mexico border, according to several congressional aides familiar with ongoing talks.
Sent 2: 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.
Sent 3: However, Republicans also insisted on increases in border security and defense spending, including money to repair existing fencing and new surveillance technology to patrol the nearly 2,000-mile border.
Sent 4: Democrats have indicated that they would support such appropriations so long as no money goes toward an actual wall.
Question: Who has to be appeased to keep the government open?.
A: 1, 2.
Rationale: The question is: Who has to be appeased to keep the government open? The phrase "appease Democrats" is mentioned in Sent 2, about accepting offer that is mentioned in Sent 1 to "keep the government open". So, Sent 1 and Sent 2 are the sentences needed to answer this question.
Q: Paragraph- Sent 1: He repeatedly calls on his followers to embrace martyrdom since "the walls of oppression and humiliation cannot be demolished except in a rain of bullets."Sent 2: For those yearning for a lost sense of order in an older, more tranquil world, he offers his "Caliphate" as an imagined alternative to today's uncertainty.
Sent 3: For others, he offers simplistic conspiracies to explain their world.
Sent 4: Bin Ladin also relies heavily on the Egyptian writer Sayyid Qutb.
Sent 5: A member of the Muslim Brotherhood executed in 1966 on charges of attempting to overthrow the government, Qutb mixed Islamic scholarship with a very superficial acquaintance with Western history and thought.
Sent 6: Sent by the Egyptian government to study in the United States in the late 1940s, Qutb returned with an enormous loathing of Western society and history.
Sent 7: He dismissed Western achievements as entirely material, arguing that Western society possesses "nothing that will satisfy its own conscience and justify its existence."Sent 8: Three basic themes emerge from Qutb's writings.
Sent 9: First, he claimed that the world was beset with barbarism, licentiousness, and unbelief (a condition he called jahiliyya, the religious term for the period of ignorance prior to the revelations given to the Prophet Mohammed).
Sent 10: Qutb argued that humans can choose only between Islam and jahiliyya.
Sent 11: Second, he warned that more people, including Muslims, were attracted to jahiliyya and its material comforts than to his view of Islam; jahiliyya could therefore triumph over Islam.
Sent 12: Third, no middle ground exists in what Qutb conceived as a struggle between God and Satan.
Sent 13: All Muslims-as he defined them-therefore must take up arms in this fight.
Sent 14: Any Muslim who rejects his ideas is just one more nonbeliever worthy of destruction.
Sent 15: Bin Ladin shares Qutb's stark view, permitting him and his followers to rationalize even unprovoked mass murder as righteous defense of an embattled faith.
Sent 16: Many Americans have wondered, "Why do 'they' hate us?"Sent 17: Some also ask, "What can we do to stop these attacks?"Sent 18: Bin Ladin and al Qaeda have given answers to both these questions.
Question: How did Sayyid Qutb learn about the Western World, such as the US?.
A: | 2. | 9 | NIv2 | task049_multirc_questions_needed_to_answer | fs_opt | [
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]
|
Given the task definition, example input & output, solve the new input case.
Given a scientific question, generate a correct answer to it.
Example: Who proposed the theory of evolution by natural selection?
Output: darwin
This is a direct fact that Charles Darwin proposed the theory of evolution.
New input case for you: Double strands of what wrap around histone proteins to form nucleosomes, which are coiled into a chromatin fiber?
Output: | dna | 1 | NIv2 | task591_sciq_answer_generation | fs_opt | [
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|
In this task, you are given a sentence in the Swedish 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).
One example: Jag förklarar debatten avslutad.
Solution is here: The debate is closed.
Explanation: Swedish sentence is properly converted into English sentence.
Now, solve this: Om allting fungerar, om vi är nöjda, om kommissionens agerande i huvudsak har varit korrekt, varför behövs det då en ändring?
Solution: | If it functions well, if we are satisfied, if the Commission has basically acted correctly, why the need for the modification? | 6 | NIv2 | task312_europarl_sv_en_translation | fs_opt | [
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|
Part 1. Definition
You are given a sentence in English. Your job is to translate the English sentence into Galician.
Part 2. Example
Now, it's next door, or in my house.
Answer: Agora, está ao lado, ou na miña casa.
Explanation: The English sentence is correctly translated into Galician, because the meaning is preserved.
Part 3. Exercise
What is the imagery of God?
Answer: | Cal é a imaxenería de Deus? | 7 | NIv2 | task1090_ted_translation_en_gl | fs_opt | [
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|
Q: In this task you are given a medical question pair hand-generated. Your task is to classify a given post into two categories 1) 'Similar' if the given two questions have a same connotation 2) 'Dissimilar' if the given two questions have a different connotation or meaning.
Sentence1: Can gabapentin work for headaches caused by trimethoprim. I have started taking 100mg gabapentin daily for 4 days and trimethoprim 200mg twice a day.
Sentence2: I was diagnosed with a urine infection for which I was given Trimethoprim 200 mg to be taken twie daily. I have developed headaches because of the medication. Would it be safe to take Gabapentin?
A: | Similar | 7 | NIv2 | task1645_medical_question_pair_dataset_text_classification | zs_opt | [
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|
Given the task definition and input, reply with output. In this task, you're given a question, a context passage, and four options which are terms from the passage. After reading a passage, you will get a brief understanding of the terms. Your job is to determine by searching and reading further information of which term you can answer the question. Indicate your choice as 'a', 'b', 'c', or 'd'. If you think more than one option is plausible, choose the more probable option to help you answer the question.
Question: How long did the battle last that was initially fought at Gospić, Otočac and Bihać? Passage:From May, 1941, it was transferred to an occupation force in Croatia. The battles with Yugoslav Partisans of increasing intensity were fought in November–December 1941 at Štirovača forest, Divoselo (Croatia), and Žuta Lokva, resulting ultimately in the Battle of the Neretva. It was fought initially at Gospić, Otočac and Bihać. The Yugoslav Partisans has launched a major assault on Korenica and Udbina from 2 January until 15 January 1942. These attacks were fended off by division Re, and in February–March, 1942, it participated in the mopping-up operation in the same area. The culmination of Battle of the Neretva for division Re was the Operation K, between 23 – 28 March 1942, carried out over six days by the Italian V Corps. The objective was to break through to and relieve the surrounded garrisons in Titova Korenica, Udbina and Donji Lapac the operation was successful and the division suffered only light casualties. In April, 1942, the Yugoslav Partisans has launched an assault on Mogorić and Bihać. Pressure was such what he garrison of Bihać had to be evacuated in June, 1942. All lost positions were recovered by the end of June, 1942, after fierce fighting.
Links: a. Croatia b. Štirovača c. Case White d. Case White
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|
Detailed Instructions: Given a set of four words, generate the category that the words belong to. Words are separated by commas. The possible categories are social gathering, accomodation, physical property, measurement unit, corporate, nutritional value, boats, police punishment, location (proximity), card games, outdoor sport activity, military rank, baby animals, weather, consumer product, animals, boxing terminology, food, chocolate food, bird, type of sandwich, date status, body part, ocean, employment activity, moral characteristic, elements, poker, computers, construction, guitar part, shady activities, physical activity, kitchenware, temperature, type of rigidity, emotional status, season, mode of transportation, window material, activity, emotional display, geographical property, fried food, store status, widespread, aesthetic characteristic, alcoholic drinks, secretary duty, direction, personal characteristic, and animal.
Q: valley, flat, plane, lined
A: | geographical property | 9 | NIv2 | task143_odd-man-out_classification_generate_category | zs_opt | [
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]
|
Teacher:In this task, you need to count the occurrences of the given word in the given sentence.
Teacher: Now, understand the problem? Solve this instance: Sentence: 'the woman is going to blow out the candles on the piece of cake'. Count the occurrences of the word 'the' in the given sentence.
Student: | 3 | 6 | NIv2 | task158_count_frequency_of_words | zs_opt | [
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|
In this task, you will be presented with a text, a pronoun from the text, and two candidate names. You should determine what the pronoun refers to and classify the answers into A, B, or Neither. A and B here are referring to option A and option B. Position of the pronoun in the text is showed within two "_"s.
She shifted to high school, working in Gu*nica between 1942 and 1957. In 1947 and again in 1955, she served as acting school principal. Her first marriage ended in divorce and on December 25, 1944, she married Ismael Olivieri. The couple subsequently had two daughters, Antonia and Rebeca Olivieri Figueroa. In 1947, _she_ published her first book of poetry Acridulces, which was described by critics as neo-Romantic, but which placed her within the first generation of academic and professional Puerto Ricans known as the Generation of the 50s. <sep>, Pronoun: she <sep>, A: Antonia <sep>, B: Rebeca Olivieri Figueroa | Neither | 0 | NIv2 | task329_gap_classification | zs_opt | [
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|
instruction:
You are given a sentence in Galician. Your job is to translate the Galician sentence into Hebrew.
question:
Di que todo o que vedes llo debe aos espaguetis.
answer:
היא אומרת שכל מה שאתם רואים היא חייבת לספגטי.
question:
Problemas similares están xurdindo tamén no Leste.
answer:
בעיות דומות מתעוררות גם במזרח.
question:
Isto é só un bocado do que buscamos.
answer:
| אז זה חלק ממה שאנחנו מחפשים.
| 9 | NIv2 | task1242_ted_translation_gl_he | fs_opt | [
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|
Part 1. Definition
In this task, you are given a sentence in Persian, and your task is to translate it into English.
Part 2. Example
جناب گرانت خیلی دلش میخواست روز یکشنبه بعد از آن همه خستگی روزانه بنشیند و بوقلمون را بخورد.
Answer: because I know how much more Dr. Grant would enjoy it on Sunday after the fatigues of the day,
Explanation: This is a good example. The above sentence is correctly translated from Persian to English.
Part 3. Exercise
به نحوهی عشق او، سبک او و دستخط او نوشت.
Answer: | and kind of love that he had attributed to him in the first letter, | 7 | NIv2 | task660_mizan_fa_en_translation | fs_opt | [
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]
|
You will be given a definition of a task first, then some input of the task.
In this task, you will be presented with a text, a pronoun from the text, and two candidate names. You should determine what the pronoun refers to and classify the answers into A, B, or Neither. A and B here are referring to option A and option B. Position of the pronoun in the text is showed within two "_"s.
She is best known for a series of well-regarded television roles including Virginia Braithwaite, daughter of a lottery winning family in the comedy drama At Home with the Braithwaites. Sparkhouse (Red Production Company / BBC 2002); and her appearance in Jane Hall (Red Production Company / ITV1 2006) marked a fruitful link between Smart and television writer Sally Wainwright. Between 2008 and 2010, _she_ featured as Anne-Britt Hoglund in Wallander, six feature-length adaptations of Henning Mankell 's Wallander novels, for the BBC. <sep>, Pronoun: she <sep>, A: Smart <sep>, B: Sally Wainwright
Output: | A | 1 | NIv2 | task329_gap_classification | zs_opt | [
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|
Instructions: 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.
Input: Context_1 : War and Peace ("Jang Aur Aman") is a 2002 Indian documentary film directed by Anand Patwardhan. The film covers the Indian and Pakistani nuclear weapons tests in 1998, as well as the nationalist rhetoric that accompanied these tests. It also explores the ill-effects of the Indian test on the surrounding population and the reactions to the test among the government and the public. The latter part of the film also covers the perception of nuclear weapons in Japan and the United States. Upon the film's completion, the Indian censor board demanded that Patwardhan make 21 cuts before it could be released, including cutting all speeches by politicians. Patwardhan refused and took the matter to court; the Bombay high court ruled in his favor a year later, and the film was released without any cuts. Context_2 : Father, Son, and Holy War ("Pitra, Putra, aur Dharmayuddha") is a 1995 film by Indian documentary filmmaker Anand Patwardhan. The film is shot in two parts, with the first ("Trial by Fire") examining the link between the violence of the Hindu nationalist movement, such as the demolition of the Babri Masjid, and sexual violence against women. The second part ("Hero Pharmacy") looks at the nature of masculinity in contemporary urban India, and its role in encouraging sexual violence. As with other films of his, Patwardhan had to fight multiple court battles in order to force the national carrier "Doordarshan" to screen the film, a screening which eventually occurred on the orders of the Supreme court. The film received numerous national and international awards, and was also seen positively by critics. Context_3 : William Taylor "Tay" Garnett (June 13, 1894 – October 3, 1977) was an American film director and writer. Context_4 : Prestige is a 1932 American pre-Code drama film directed by Tay Garnett and written by Tay Garnett, Rollo Lloyd and Francis Edward Faragoh. The film stars Ann Harding, Adolphe Menjou, Melvyn Douglas and Guy Bates Post. The film was released on January 22, 1932, by RKO Pictures. Context_5 : Trade Winds is a 1938 comedy film distributed by United Artists. It was directed by Tay Garnett, and starred Fredric March and Joan Bennett. The screenplay was written by Dorothy Parker, Alan Campbell and Frank R. Adams, based on story by Tay Garnett. Context_6 : A Narmada Diary is a 1995 documentary on the struggle of those adversely impacted by the Sardar Sarovar Dam project. It was directed by Anand Patwardhan and Simantini Dhuru and released in the year 1995. A record from about 1990-1993, of the measures adopted and hardship faced by the Narmada Bachao Andolan movement and the people inhabiting the place affected was presented. The documentary won the "Filmfare Award for Best Documentary, 1996" and the "Grand Prize" at Earth-Vision Film Festival, Tokyo, 1996. In spite of winning the central government's national awards, the movie was not allowed to be shown on National TV Context_7 : Bombay: Our City ("Hamara Sahar") is a 1985 Indian documentary film directed by Anand Patwardhan. Context_8 : Anand Patwardhan (born 18 February 1950) is an Indian documentary filmmaker known for his socio-political, human rights-oriented films. Some of his films explore the rise of religious fundamentalism, sectarianism and casteism in India, while others investigate nuclear nationalism and unsustainable development. Notable films include "Bombay: Our City" ("Hamara Shahar") (1985), "In Memory of Friends" (1990), "In the Name of God" ("Ram ke Nam") (1992), "Father, Son, and Holy War" (1995), "A Narmada Diary" (1995), "War and Peace" (2002) and "Jai Bhim Comrade" (2011), which have won national and international awards. A secular rationalist, Anand Patwardhan is a vocal critic of Hindutva ideology. Context_9 : Bad Company is a 1931 American Pre-Code gangster film directed and co-written by Tay Garnett with Tom Buckingham based on Jack Lait's 1930 novel "Put on the Spot". It stars Helen Twelvetrees and Ricardo Cortez. Told from the view of a woman, the working titles of this film were "The Gangster's Wife" and "The Mad Marriage". Unlike many static early sound films, Garnett includes several scenes using a moving camera climaxing in a gigantic assault on an office building with both sides using heavy machine guns. Context_10 : Ram ke Naam (English: "In the Name of God") is a 1992 documentary by Indian filmmaker Anand Patwardhan. The film explores the campaign waged by the Hindu-nationalist Vishva Hindu Parishad to build a Ram temple at the site of the Babri Masjid in Ayodhya, as well as the communal violence that it triggered. A couple of months after "Ram ke Naam" was released, VHP activists demolished the Babri Masjid in 1992, provoking further violence. The film earned Patwardhan a wide recognition, and received several national and international awards. fact_1 : Anand Patwardhan (born 18 February 1950) is an Indian documentary filmmaker known for his socio-political, human rights-oriented films. fact_2 : William Taylor "Tay" Garnett (June 13, 1894 – October 3, 1977) was an American film director and writer. Answer: filmmaker
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]
|
Definition: In this task, you need to answer 'Yes' if the given word is the longest word (in terms of number of letters) in the given sentence, else answer 'No'. Note that there could be multiple longest words in a sentence as they can have the same length that is the largest across all words in that sentence.
Input: Sentence: 'a dog is posed to look like the driver of the car'. Is 'is' the longest word in the sentence?
Output: | No | 2 | NIv2 | task114_is_the_given_word_longest | zs_opt | [
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]
|
Instructions: In this task, you are given dvd product reviews in German language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Input: Einer seiner Besten! . Hudson Hawk ist eine wriklich gut gelungene Komödie. In diesem Film fehlt es an nichts, ein wares muss für jeden Fan.
Output: | POS | 3 | NIv2 | task480_cls_german_dvd_classification | zs_opt | [
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|
Teacher:Given an trivia question precisely answer the question with a word/phrase/name. External resources such as Wikipedia could be used to obtain the facts.
Teacher: Now, understand the problem? Solve this instance: What is the highest mountain in England?
Student: | scafell pike | 6 | NIv2 | task898_freebase_qa_answer_generation | zs_opt | [
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|
Detailed Instructions: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
Problem:私がその学生より賢いというのではなくアメリカの文化的経済的影響力のために私にはたくさんのアメリカの物語がありました
Solution: | Isto non é porque eu sexa unha persoa mellor ca ese estudiante, pero debido ao poder económico e cultural dos EE.UU. teño moitas historia de EE.UU. | 8 | NIv2 | task1095_ted_translation_ja_gl | zs_opt | [
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|
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.
Q: [[36, 40, 27, -3], [-3, 14, -14, 45, 48], [32, -30, 8, -8], [12, -43, -3], [22, 46, -50, 49, 0], [20, -12, 33, 23, 32], [27, -38, -39, 20, -12], [-25, 21], [-6, -23, 11], [24, 19, 30, -46], [-5, 23, -15, 29], [-21, 11], [-44, -34, 30]]
A: [1440, -9408, 61440, 12, 0, -7680, 9120, 0, -6, -33120, 0, 0, 44880]
****
Q: [[-39, -14, 23, -37, 41], [-24, 49, -29, 38], [-49, -46, -8, -28, 0], [40, -29, 11, 20], [6, 13, -41, -34], [-26, -42, 2, -2], [-22, -11, 24, -35, -36]]
A: [-14, -912, 0, 800, -204, -4368, 19008]
****
Q: [[21, 1, 32, 38, -17], [-27, -49, -24], [-23, 45], [8, -2], [-9, -47, 11, 38], [46, -3, -41], [-12, -7, 12, -41, -39], [10, -20, -50, -35], [-13, 42, -40, 32]]
A: | [1216, -24, 0, -16, 38, 46, -144, 10000, -53760]
****
| 4 | NIv2 | task851_synthetic_multiply_evens | fs_opt | [
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|
You will be given a definition of a task first, then some input of the task.
In this task, you are given a set of context paragraphs, some supporting facts and an answer of a question. Your task is to generate question for given answer based on set of context paragraphs, supporting facts and an answer.
Context_1 : Family tree mapping is the process of geocoding places in family tree files to produce geospatial data suitable for viewing with a virtual globe or 2D mapping program. Context_2 : MacChoro (pronounced MacKoro) was a computer program for choropleth mapping developed for early versions of the Apple Macintosh computer. A choropleth map shades areas, such as states or counties, to represent values and is mainly used for the mapping of statistical data. Released in 1986, MacChoro was the first computer mapping program to implement Macintosh's point-and-click user interface for the analysis and production of thematic maps. MacChoro II, released in 1988, was the first program to incorporate interaction in animated mapping. Context_3 : The Lunar Reconnaissance Orbiter (LRO) is a NASA robotic spacecraft currently orbiting the Moon in an eccentric polar mapping orbit. Data collected by LRO has been described as essential for planning NASA's future human and robotic missions to the Moon. Its detailed mapping program is identifying safe landing sites, locating potential resources on the Moon, characterizing the radiation environment, and demonstrating new technologies. Context_4 : Apple Maps is a web mapping service developed by Apple Inc. It is the default map system of iOS, macOS, and watchOS. It provides directions and estimated times of arrival for automobile, pedestrian, and public transportation navigation. Apple Maps also features the "Flyovers" mode, a feature that enables a user to explore certain densely populated urban centers and other places of interest in a 3D landscape composed of models of buildings and structures. Context_5 : Satellite imagery are images of Earth or other planets collected by Imaging satellites operated by governments and businesses around the world. Satellite imaging companies sell images by licensing them to governments and businesses such as Apple Maps and Google Maps. Context_6 : The Vegetation Classification and Mapping Program (VegCAMP) is the California component of the National Vegetation Classification System coordinated by the California Department of Fish and Wildlife. It implements vegetation assessment and vegetation mapping projects in high-priority conservation and management areas. It conducts training programs, classification of vegetation data, and fine-scale vegetation mapping. Context_7 : Randall Ridge ( ) is an arc-shaped rock ridge at the north side of the Guthridge Nunataks, in the Gutenko Mountains of central Palmer Land. Mapped by the United States Geological Survey (USGS) in 1974. Named by Advisory Committee on Antarctic Names (US-ACAN) after Robert H. Randall (1890–1966), Assistant on Cartography with the U.S. Bureau of the Budget in the Executive Office of the President, with responsibility for coordinating the mapping activities of the Government, 1941-60. In 1954 he set up the Technical Advisory Committee on Antarctic Mapping that established a mapping program for Antarctica based on the best technical methods. Context_8 : Kebira Crater (Arabic: فوهة كبيرة ) is the name given to a circular topographic feature that was identified in 2007 by Farouk El-Baz and Eman Ghoneim using satellite imagery, Radarsat-1, and Shuttle Radar Topography Mission (SRTM) data in the Sahara desert. This feature straddles the border between Egypt and Libya. The name of this feature is derived from the Arabic word for "large", and also from its location near the Gilf Kebir ("Great Barrier") region in southwest Egypt. Based solely on their interpretations of the remote sensing data, they argue that this feature is an exceptionally large, double-ringed, extraterrestrial impact crater. They suggest that the crater's original appearance has been obscured by wind and water erosion over time. Finally, they speculated that this feature might be the source of the yellow-green silica glass fragments, known as "Libyan desert glass", that can be found across part of Egypt's Libyan Desert. They neither conducted any fieldwork at this feature nor studied any samples collected from it. However, the Kebira Crater is currently not listed in the Earth Impact Database. Field trips to investigate the feature have found no supporting evidence. The "central uplift" clearly retains the horizontal bedding of the surrounding sandstone tableland, providing clear evidence against a possible impact origin. Context_9 : Endoxon is a mapping company that was acquired by Google in December 2006. The company is based in Switzerland. Endoxon now provides the maps for European countries in Google Maps. It has created geo-mapping software since 1988, and currently has 75 employees. Its products included maps that have geo-referenced data with high-resolution aerial and satellite images for dynamic internet and mobile services. Context_10 : PERSIANN, "Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks", is a satellite-based precipitation retrieval algorithm that provides near real-time rainfall information. The algorithm uses infrared (IR) satellite data from global geosynchronous satellites as the primary source of precipitation information. Precipitation from IR images is based on statistical relationship between cloud top temperature and precipitation rates. The IR-based precipitation estimates are then calibrated using satellite microwave data available from low Earth orbit satellites (e.g., Tropical Rainfall Measuring Mission Microwave Imager, Special Sensor Microwave Imager, Advanced Microwave Scanning Radiometer‐Earth observing system). The calibration technique relies on an adaptive training algorithm that updates the retrieval parameters when microwave observations become available (approximately at 3 hours intervals). fact_1 : Satellite imagery are images of Earth or other planets collected by Imaging satellites operated by governments and businesses around the world. fact_2 : Apple Maps is a web mapping service developed by Apple Inc. It is the default map system of iOS, macOS, and watchOS. fact_3 : Apple Maps also features the "Flyovers" mode, a feature that enables a user to explore certain densely populated urban centers and other places of interest in a 3D landscape composed of models of buildings and structures. Answer: Apple Maps
Output: | What internet mapping program operated by using satellite images of the earth features a flyover feature? | 1 | NIv2 | task191_hotpotqa_question_generation | zs_opt | [
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|
In this task you will be given a string of characters. You should remove all vowels from the given string. Vowels are: i,e,a,u,o. The character 'y' or 'Y' does not count as a vowel.
Input: Consider Input: PqUTlorUZhFiQhyrqT
Output: PqTlrZhFQhyrqT
Input: Consider Input: olivwAOowEgXA
Output: lvwwgX
Input: Consider Input: ETXviEcaeoWBem
| Output: TXvcWBm
| 2 | NIv2 | task365_synthetic_remove_vowels | fs_opt | [
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|
Q: A text is given in Gujarati. Translate it from the Gujarati language to the Tamil language. The translation must not omit or add information to the original sentence.
எனது முந்தைய ஆட்சிக் காலத்தில், பிரதமர் என்ற முறையில் முதலில் பூடானுக்குப் பயணம் மேற்கொள்வது என்பது இயல்பான தேர்வாக இருந்தது.
A: | મારા છેલ્લા કાર્યકાળ દરમિયાન પ્રધાનમંત્રીના રૂપમાં મારી પહેલી યાત્રા માટે ભૂતાનની પસંદગી સ્વાભાવિક હતી. | 7 | NIv2 | task1064_pib_translation_tamil_gujarati | zs_opt | [
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|
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. It makes you much less likely to believe the hypothesis is true. A strengthener is a statement that strengthens the hypothesis. It makes you much more likely to believe the hypothesis is true. Your task is to output 'strengthener' or 'weakener' if the update strengths or weakens the hypothesis, respectively.
Teacher: Now, understand the problem? Solve this instance: Premise: PersonX bakes one
Hypothesis: PersonX is seen as welcoming
Update: PersonX is making a personal pie.
Student: | weakener | 6 | NIv2 | task935_defeasible_nli_atomic_classification | zs_opt | [
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|
Part 1. Definition
Given a sentence in Hindi, generate a new Hindi sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Part 2. Example
आप एक जूरी नहीं करना चाहते हैं तो आप एक वकील बनना चाहिए.
Answer: आप एक जूरी जीतने के लिए जीते हैं तो आप एक राजा बनना चाहिए.
Explanation: This is the good example. The created sentence is semantically similar to the input as both are talking about what to become if one doesn’t want to become the jury and the changes in the sentence follows the commonsense knowledge.
Part 3. Exercise
आप इंजन सेवा कर सकते हैं जब प्रकाश पर आता है.
Answer: | आप इंजन आदेश कर सकते हैं जब डायल पर आता है। | 7 | NIv2 | task407_mickey_hi_sentence_perturbation_generation | fs_opt | [
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]
|
Instructions: You are given a sentence in Galician. Your job is to translate the Galician sentence into Italian.
Input: Vale.
Output: | Ok. | 3 | NIv2 | task1243_ted_translation_gl_it | zs_opt | [
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|
Q: This task is about classifying the similarity of two sentences. The sentences can be classified as (a) SIMILAR - similar to each other, and (b) DISSIMILAR - not similar to each other. Sentences that have the same RDF relationship in terms of [subject, predicate, object] are similar to each other. The input is a list of two sentences and the output is either SIMILAR or DISSIMILAR.
['Pork belly is an ingredient in Bandeja paisa.', 'one of the ingredients of Pork belly is Bandeja paisa.']
A: | DISSIMILAR | 7 | NIv2 | task1408_dart_similarity_classification | zs_opt | [
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|
Definition: Given a sentence, generate a most unlikely next statement. The next statement should not be logically relevant to the given context
Input: The person dips out the rag and begins using it on wood. The person
Output: | places the silverware down and sprays the panel. | 2 | NIv2 | task454_swag_incorrect_answer_generation | zs_opt | [
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|
Definition: 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 accidentally left ___<sep>Tail: to put their purse down
Output: | No | 2 | NIv2 | task1207_atomic_classification_atlocation | zs_opt | [
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|
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
Example Input: Provides a satisfactory overview of the bizarre world of extreme athletes as several daredevils express their own views .
Example Output: POS
Example Input: By the end , you just do n't care whether that cold-hearted snake Petrovich ( that would be Reno ) gets his comeuppance .
Example Output: NEG
Example Input: In my own very humble opinion , In Praise of Love lacks even the most fragmented charms I have found in almost all of his previous works .
Example Output: | NEG
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]
|
Detailed Instructions: In this task, you're given a question, along with a context passage which has extra information available on certain terms mentioned in it, i.e., the proper nouns in the passage. Your job is to determine whether information from more than one term is needed to answer the question. Indicate your choice as `a` for Yes or `b` for No.
See one example below:
Problem: Question: When did the operation during which the 704th dropped supplies to allied troops near Nijmegen begin? Passage: The group was occasionally diverted from strategic missions to carry out air support and interdiction missions. It supported Operation Overlord, the invasion of Normandy by attacking transportation targets, including bridges, along with airfields and strong points in France. On D Day, the squadron and the rest of the 446th Group led the first heavy bomber mission of the day. The 446th aided ground forces at Caen and Saint-Lô during July by hitting bridges, gun batteries, and enemy troops. During Operation Market Garden, the attempt to seize a bridgehead across the Rhine in the Netherlands, the 704th dropped supplies to allied troops near Nijmegen. It struck lines of communications during the Battle of the Bulge. During Operation Varsity in March 1945, it supplied ground and airborne troops near Wesel. The squadron flew its last combat mission on 25 April 1945 against Salzburg, Austria. The group had flown 273 missions and had lost 58 aircraft during the war,
.
Solution: b
Explanation: The passage describes the 704th's actions during Operation Market Garden so only information about the operation is needed.
Problem: Question: Which of the offices that Charles E. Vreeland worked at is the oldest? Passage:Vreeland was further promoted to master and then lieutenant after successive tours of duty on board the screw steamer , the gunboat and the sloop-of-war . He was then assigned to the Nautical Almanac Office of the US Naval Observatory in November 1881 after a brief period ashore awaiting orders. In March 1884, Lt. Vreeland began a three-year tour at sea aboard the sloop-of-war , after which he was assigned for two years at the Bureau of Navigation. He was then assigned briefly (from July to September 1889) with the Office of Naval Intelligence and reported to the Coast Survey late in October, a posting he took until the spring of 1893, when Vreeland was assigned a series of tours as naval attaché — first in Rome, Vienna and finally in Berlin.
Solution: | a | 4 | NIv2 | task232_iirc_link_number_classification | fs_opt | [
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|
Instructions: You are given a sentence in Portuguese. Your job is to translate the Portuguese sentence into Galician.
Input: Vejam os compositores clássicos, os melhores dos melhores.
Output: | Pensade nos compositores clásicos, os mellores dos mellores. | 3 | NIv2 | task1279_ted_translation_pt_gl | zs_opt | [
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|
In this task, you are given a sentence in the Spanish language. Your task is to translate the Spanish sentence into the English language.
[EX Q]: Un paciente acude a un servicio de urgencias hospitalarias presentando hematemesis franca. En la valoración inicial el paciente está pálido y sudoroso, tiene una frecuencia cardiaca de 110 latidos por minuto y una presión arterial sistólica de 98 mmHg. ¿Cuál de las siguientes acciones NO realizaría en la atención inicial a este paciente?
[EX A]: A patient goes to a hospital emergency department presenting frank hematemesis. In the initial assessment the patient is pale and sweaty, has a heart rate of 110 beats per minute and a systolic blood pressure of 98 mmHg. Which of the following actions would NOT be performed in the initial care of this patient?
[EX Q]: ¿Cuál de los siguientes factores influye en la tasa de filtración glomerular (TFG)?
[EX A]: Which of the following factors influences the glomerular filtration rate (GFR) ?
[EX Q]: El papiloma virus humano (HPV) está implicado en la patogenia del
[EX A]: | The human papilloma virus (HPV) is involved in the pathogenesis of
| 6 | NIv2 | task1433_head_qa_language_translation_es_to_en | fs_opt | [
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|
Given a story, answer the question about the story. The question is the last sentence in the input. These stories can be difficult due to their length and how each story has at least one of the three following scenarios: the first is when the individual's belief matches reality, the second is when the individual's belief does not match reality, and the third is when an individual has a false belief about another individual's beliefs. The question will ask about the location of an object in the story with respect to either none or one of the three scenarios. Note that there are distractor sentences in each story that are unrelated to the question and are designed to confuse the reader.
One example: Jacob entered the dining_room. William entered the dining_room. The tomato is in the green_drawer. William exited the dining_room. Jacob moved the tomato to the blue_cupboard. Jacob is in the dining_room. Olivia entered the dining_room. The cucumber is in the blue_cupboard. Olivia exited the dining_room. Jacob moved the cucumber to the green_drawer. William entered the pantry. Jacob entered the pantry. The asparagus is in the red_cupboard. Jacob exited the pantry. Phone rang. William moved the asparagus to the green_pantry. Abigail entered the hall. William entered the hall. The persimmon is in the blue_pantry. William exited the hall. Abigail moved the persimmon to the blue_envelope. Where does Abigail think that William searches for the persimmon?
Solution is here: blue_pantry
Explanation: The persimmon was last in the blue_pantry before William exited the hall. After William exited the hall, Abigail moved the persimmon to the blue_envelope, so she knows where William will look for it.
Now, solve this: Aria entered the front_yard. Liam entered the front_yard. Phone rang. The onion is in the green_box. Liam exited the front_yard. Aria moved the onion to the green_suitcase. Mia entered the playroom. Liam entered the playroom. The lime is in the red_drawer. Liam exited the playroom. Mia moved the lime to the blue_crate. Aria entered the workshop. Phone rang. Liam entered the workshop. The green_pepper is in the red_envelope. Liam exited the workshop. Aria moved the green_pepper to the blue_treasure_chest. Mia entered the front_yard. Aria entered the front_yard. The tomato is in the green_suitcase. Aria exited the front_yard. Phone rang. Mia moved the tomato to the green_box. Where does Mia think that Aria searches for the tomato?
Solution: | green_suitcase | 6 | NIv2 | task154_tomqa_find_location_hard_noise | fs_opt | [
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|
instruction:
You are given a sentence in English. Your job is to translate the English sentence into Italian.
question:
Tell me what's wrong. I can't understand you.
answer:
Dimmi cosa e successo. Non riesco a capirti.
question:
The first frack job was in '47.
answer:
La prima fratturazione è stata fatta nel '47.
question:
But the problem with camera traps is that the researcher has to go back to the forest every so often to retrieve those images, and that takes a lot of time, especially if there are dozens or hundreds of these cameras placed in the forest.
answer:
| Ma il problema con le fotocamere trappola è che i ricercatori devono tornare nella foresta di tanto in tanto per recuperare le immagini, e ci vuole molto tempo, specialmente se ci sono dozzine o centinaia di queste fotocamere piazzate nella foresta.
| 9 | NIv2 | task1091_ted_translation_en_it | fs_opt | [
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|
Given the task definition and input, reply with output. You are given a statement written in Telugu. Choose the most logical word from the given 4 options which can be used to replace the <MASK> token in the statement. Output the word from the correct option .
Statement: బుద్ధుని అవశేషాలలోని ఎనిమిదవ భాగం భీమిలి సమీపంలోని తిమ్మాపురం <MASK> బౌద్ధకేత్రంలో లభ్యమైందట.1641వ సంవత్సరంలో హైదరాబాదు నవాబు అబ్దుల్లా కులీకుతుబ్ షా నుండి అనుమతి పొందారు డచ్ దేశస్థులు.1754లో జరిగిన మరాఠీ దాడుల్లోనూ, 1781 లో ఫ్రాన్స్, బ్రిటన్ల మధ్య జరిగిన యుద్ధంలోనూ డచ్కోట పాక్షికంగా ధ్వంసమైంది. 1825 లో భీమిలి రేవు పట్టణం బ్రిటిష్వారి వశమైంది. 1854లో రిప్పన్ కంపెనీని ప్రారంభించారు. యాత్రా చరిత్ర, రచయిత మండపాక పార్వతీశ్వర శాస్త్రి తన గ్రంథంలో.... పుట 6 లో భీముని పట్నం గురించి ఇలా వ్రాసి యున్నారు.
Option A: బావికొండ
Option B: ఐరోపా
Option C: సూరత్
Option D: పావురాళ్ళకొండ
| బావికొండ | 5 | NIv2 | task954_wiki_cloze_te_multiple_choice_question_answering | zs_opt | [
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]
|
Definition: Read the given query and classify it as a 'Good' or 'Bad' query depending on how well the query is formed, 'Bad' being the expected output for a not so well formed query and 'Good' being the expected output for a well formed query. A query may be wrong based on common sense or general facts, but if it is well formed, you should answer with Good.
Input: Level of criminal categories of crime ?
Output: | Bad | 2 | NIv2 | task673_google_wellformed_query_classification | zs_opt | [
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|
In this task, you get an English sentence and a corresponding Spanish translation of the English sentence. Your task is to return a "Yes" if the translation is correct, otherwise return "No"
English: And the fact that coins are to have a national design on one side will make them even harder to identify.
Spanish:En el caso de las monedas en euros el problema de su identificación se agudiza todavía más por el hecho de que una de sus caras puede tener una configuración nacional.
Yes
English: But to enlighten the decision makers, let us practise honest science, without the ulterior motive of having the European Union finance excuses to destroy our fishing boats.
Spanish:Carta de derechos fundamentales de la UE
No
English: First of all, with regard to the lack of clarity in the agreement, I can confirm that the provisional agreement between the EC and Israel on trade and related matters specifies that it applies to the territory of the Member States of the European Community and, I quote, "the territory of Israel" .
Spanish:Los expedientes relativos a la coordinación de la seguridad social, la ampliación a terceros países y los sistemas complementarios de seguridad social se encuentran bloqueados en el Consejo desde hace años.
| No
| 0 | NIv2 | task532_europarl_en-es_classification | fs_opt | [
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|
Teacher:You are given a sentence in Galician. Your job is to translate the Galician sentence into Hebrew.
Teacher: Now, understand the problem? Solve this instance: Lugares desfeitos pola guerra como Monrovia, a xente viña directa a ti.
Student: | במקומות שסועי קרבות כמו מונרוביה, אנשים הגיעו ישר אלינו. | 6 | NIv2 | task1242_ted_translation_gl_he | zs_opt | [
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|
Given the task definition, example input & output, solve the new input case.
In this task you need to indicate the plausibility of reasoning for the pronoun coreference relations. Each of the provided inputs contains a sentence with a target pronoun and a sentence that justifies which noun phrase the pronoun refers to. Correct reasons do not need to use all the knowledge from the sentence. The resolution of the pronoun coreference relations typically involve one or multiple following knowledge types about commonsense: First: 'Property', the knowledge about property of objects (e.g., ice is cold). Second: 'Object', the knowledge about objects (e.g., cats have ears). Third: 'Eventuality', the knowledge about eventuality (e.g., 'wake up' happens before 'open eyes'). Forth: 'Spatial', the knowledge about spatial position (e.g., object at the back can be blocked). Fifth: 'Quantity', the knowledge about numbers (e.g., 2 is smaller than 10). Sixth: all other knowledge if above ones are not suitable. You should answer 'Correct' if the reasoning made sense, otherwise, you should answer 'Wrong'.
Example: Sentence: The city councilmen refused the demonstrators a permit because they feared violence.
Reason: The 'they' refers to the city councilmen because city councilmen are administrative so they are more likely to fear.
Question: Is the above reasoning correct or wrong?
Output: Correct.
This is a correct reason since the pronoun in the sentence is descibed as ones who fear violence and the city councilmen are attached with this property.
New input case for you: Sentence: Ann asked Mary what time the library closes, but she had forgotten.
Reason: The 'she' refers to mary because all info is waiting to be gotten from mary so she is the she.
Question: Is the above reasoning correct or wrong?
Output: | Correct | 1 | NIv2 | task133_winowhy_reason_plausibility_detection | fs_opt | [
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|
Given a sentence in Dutch, generate a new Dutch sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Tokens zijn gemaakt van karton papier, een recycleerbaar materiaal. | bits zijn gemaakt van karton papier, een recycleerbaar materiaal. | 0 | NIv2 | task409_mickey_nl_sentence_perturbation_generation | zs_opt | [
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|
In this task, you are given inputs i and A, where i is an integer and A is a list. You need to list all the elements of A preceding the last i elements. i will always have a value less than the length of A.
3, ['w', '273', '3987', 'J', 'm', 'v', '321', '8839', 'e', 'E', '5029', '1825', 't', 'a', '1257']
w, 273, 3987, J, m, v, 321, 8839, e, E, 5029, 1825
5, ['G', '1303', '4847', '8601', '1243', 'o', '4001', 'Z', '2907', 'b', 'M', 'F', '6585', 'Q', '2829', '4275', '4821', 'g', 'h', 'o', 'C', '1059', 'L', '9531', '3303']
G, 1303, 4847, 8601, 1243, o, 4001, Z, 2907, b, M, F, 6585, Q, 2829, 4275, 4821, g, h, o
6, ['B', 'F', '2095', '8245', 'U', 'U', 'K', '933', '1533', '7895', 'c', '4095', 'f', '2649', '55', 'J', 'E', 'b', 'L', '6971', '985', 'D']
| B, F, 2095, 8245, U, U, K, 933, 1533, 7895, c, 4095, f, 2649, 55, J
| 0 | NIv2 | task078_all_elements_except_last_i | fs_opt | [
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|
In this task, you are given the abstract of a research paper. Your task is to generate a summary of this abstract. Your summary should not be very short, but it's better if it's not more than 30 words.
Q: We present a weakly-supervised data augmentation approach to improve Named Entity Recognition (NER) in a challenging domain: extracting biomedical entities (e.g., proteins) from the scientific literature. First, we train a neural NER (NNER) model over a small seed of fully-labeled examples. Second, we use a reference set of entity names (e.g., proteins in UniProt) to identify entity mentions with high precision, but low recall, on an unlabeled corpus. Third, we use the NNER model to assign weak labels to the corpus. Finally, we retrain our NNER model iteratively over the augmented training set, including the seed, the reference-set examples, and the weakly-labeled examples, which results in refined labels. We show empirically that this augmented bootstrapping process significantly improves NER performance, and discuss the factors impacting the efficacy of the approach.
A: | Augmented bootstrapping approach combining information from a reference set with iterative refinements of soft labels to improve Name Entity Recognition from biomedical literature. | 4 | NIv2 | task668_extreme_abstract_summarization | zs_opt | [
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|
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 and a category word that defines the relation between the input sentence and the output to be generated. Your job is to generate another sentence that satisfies the relation specified by the category. If the category is specified as entailment, then the output sentence must clearly agree with the input sentence. If the category specified is contradiction , then the output sentence must clearly disagree with the input sentence.
sentence_A: A young girl is enjoying the green grassy trail . category: entailment
Solution: A young girl is happily having fun on the green grassy hike
Why? The words happy and enjoying both mean the same, so they are entailed to each other.
New input: sentence_A: The motorcycle racer is riding a red and black bike. category: contradiction
Solution: | No motorcycle racer is riding a red and black bike | 0 | NIv2 | task1613_sick_given_category_generate_sentence | fs_opt | [
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Q: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating 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.
select the rows whose championship record fuzzily matches to dayton , oh . there is only one such row in the table . the date record of this unqiue row is 8 february 1976 .
A: | and { only { filter_eq { all_rows ; championship ; dayton , oh } } ; eq { hop { filter_eq { all_rows ; championship ; dayton , oh } ; date } ; 8 february 1976 } } | 7 | NIv2 | task210_logic2text_structured_text_generation | zs_opt | [
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|
In this task, you are given a text from a social media post. Your task is to classify the given post into two categories: 1) yes if the given post is sexually offensive, 2) no, otherwise. Emphasis on sexually offensive or any lewd reference. Generate label 'no' for offensive posts that do not reference sexually explicit content. Warning: the examples and instances may contain offensive language.
Q: How are virginity and Indian Land the same? If they don’t give it to you when you ask nicely, take it from them and kill them when you’re done.
A: | Yes | 4 | NIv2 | task608_sbic_sexual_offense_binary_classification | zs_opt | [
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|
Detailed Instructions: A text is given in Malayalam. Translate it from the Malayalam language to the Oriya language. The translation must not omit or add information to the original sentence.
Q: ദുഖത്തിന്റെ ഈ വേളയില് എന്റെ ചിന്തകള് അദ്ദേഹത്തിന്റെ കുടുംബത്തോടും അനുയായികളോടുമൊപ്പമാണ്, പ്രധാനമന്ത്രി പറഞ്ഞു.
A: | ଭୁବନେଶ୍ୱରରେ ଜାତୀୟ ଅବକ୍ଷୟ ନିୟନ୍ତ୍ରଣ ସମ୍ମିଳନୀ କେନ୍ଦ୍ରମନ୍ତ୍ରୀ ଧର୍ମେନ୍ଦ୍ର ପ୍ରଧାନଙ୍କ ଦ୍ୱାରା ଉଦ୍ଘାଟିତ | 9 | NIv2 | task979_pib_translation_malayalam_oriya | zs_opt | [
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|
Detailed Instructions: You are given a sentence in English. Your job is to translate the English sentence into Portugese.
Q: If you're interested in giving it a try, I'd encourage you to go to the Scratch website.
A: | Se estiverem interessados em experimentar, convido-vos a visitar o sítio Web do Scratch. | 9 | NIv2 | task1094_ted_translation_en_pt | zs_opt | [
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]
|
Instructions: In this task, you're given a statement, and three sentences as choices. Your job is to determine which sentence clearly disagrees with the statement. Indicate your answer as '1', '2', or '3' corresponding to the choice number of the selected sentence.
Input: Statement: Microsoft's inclusion of IE with Windows does not prevent computer manufacturers from installing competing browsers or putting those browsers on the desktop. Choices: 1. Microsoft included IE on windows. 2. Microsoft made IE optional. 3. Microsoft forces all Windows uses to use IE.
Output: | 2 | 3 | NIv2 | task202_mnli_contradiction_classification | zs_opt | [
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|
In this task, You are given an open-domain question that can be answered based on factual information. Your task is to provide \*short\* answer (in a few words only) for the given question. The short answer can be one or more entities or it can also be boolean \*yes\* or \*no\*.
Let me give you an example: when are hops added to the brewing process?
The answer to this example can be: The boiling process
Here is why: The answer is correct because, at the end of the boil, solid particles in the hopped wort are separated.
OK. solve this:
who is julie having an affair with on desperate housewives
Answer: | Danny's father, Nick | 8 | NIv2 | task582_naturalquestion_answer_generation | fs_opt | [
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]
|
Given the task definition and input, reply with output. In this task, you will be given a list of integers. You should remove all of the odd integers from the list(consider 0 an even number). If every integer in the input list is odd then an empty list ("[]") should be returned. Otherwise, answer with the list of even numbers separated by comma inside brackets.
[-14, -100, 60, -46, -84, -54, -81]
| [-14, -100, 60, -46, -84, -54] | 5 | NIv2 | task369_synthetic_remove_odds | zs_opt | [
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]
|
Detailed Instructions: In this task, you get an English sentence and a corresponding Spanish translation of the English sentence. Your task is to return a "Yes" if the translation is correct, otherwise return "No"
See one example below:
Problem: English: Resumption of the session
Spanish: Reanudación del período de sesiones
Solution: Yes
Explanation: The English sentence correctly translated into a Spanish sentence because it's translated all the words and prepositions in the sentence "Resumption of the session" correctly.
Problem: English: Firstly, anyone familiar with the region knows that the future of the Palestinian economy is intimately linked to the economic cooperation agreement with Israel.
Spanish:. (EN) Una cosa que evidentemente tenemos que hacer es anunciar muy claramente lo que tenemos a nuestra disposición.
Solution: | No | 4 | NIv2 | task532_europarl_en-es_classification | fs_opt | [
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|
The provided file includes inquiries about restaurants, and we ask you to translate those to the German language. Please bear in mind the following guidlines 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 are named entities and *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. 5) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
One example: are there any " italian " restaurants nearby with 8 star reviews ?
Solution is here: gibt es hier in der nähe " italian " restaurants mit 8-sterne-bewertungen?
Explanation: The translation correctly preserves " italian " entity and is accurate
Now, solve this: find me " italian " restaurants
Solution: | finde " italian " restaurants für mich | 6 | NIv2 | task117_spl_translation_en_de | fs_opt | [
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|
Definition: A text is given in Oriya. Translate it from the Oriya language to the Tamil language. The translation must not omit or add information to the original sentence.
Input: ସଂସଦୀୟ ବ୍ୟାପାର ମନ୍ତ୍ରଣାଳୟର ଅଧିକାରୀ ଓ କର୍ମଚାରୀଙ୍କୁ ‘ସ୍ୱଚ୍ଛତା ଶପଥ’ କରାଇଲେ ଅର୍ଜୁନ ରାମ ମେଘୱାଲ
Output: | முத்ரா திட்டத்தில் இதுவரை பயன்பெற்றவர்களில் 74 சதவிதத்தினர் பெண்கள் என்றும் அவர் கூறினார். | 2 | NIv2 | task1073_pib_translation_oriya_tamil | zs_opt | [
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|
Detailed Instructions: You are given an open-domain question from an open movie database. Your task is to provide an answer to that question. Try to only include the answer. Do not put it in a sentence.
See one example below:
Problem: what kind of film is Best Seller?
Solution: crime
Explanation: The answer is correct because crime genre movie is among best seller.
Problem: who is the writer of A Short Film About Killing?
Solution: | Krzysztof Kieslowski, Krzysztof Piesiewicz | 4 | NIv2 | task615_moviesqa_answer_generation | fs_opt | [
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|
"Yes, and" is a rule-of-thumb in improvisational comedy that suggests that a participant in a dialogue should accept what another participant has stated ("Yes") and then expand on that line of thought or context ("and..."). Given a prompt and two responses, identify which response is the type of "yes, and". Indicate your answer by 'Response 1' if the first response is correct, otherwise 'Response 2'. Note that a "Yes, and" does not require someone explicitly saying 'yes, and...' as part of a dialogue exchange.
[EX Q]: Prompt: Yeah, I did notice that. But I wasn't going to say nothing because I've been criticized for having thoughts in the past.
Response 1: You shouldn't have been criticized for that. Your thoughts are just as valuable as anyone else's thoughts, if not more so.
Response 2: He was so brave, trying to save our family.
[EX A]: Response 1
[EX Q]: Prompt: We're gonna be, I guess, going back out in the world after the show is done in an hour. It's 5AM now, so we'll be back out on the street around eight, I guess.
Response 1: Well you just made your death seem inevitable, and we just met you.
Response 2: Yes and then I have to go directly home. I can't dilly dally. So don't get any ideas, both of you.
[EX A]: Response 2
[EX Q]: Prompt: What were you screaming about over there behind the couch??
Response 1: We just uh... we just talking about, uh, temperatures. You know how in Europe they got different temperatures than here.
Response 2: Well he's awfully big for age five.
[EX A]: | Response 1
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|
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Given a 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 : Pretty much was hanging out with two friends. I was watching the Lakers game. They won at the very last minute and I immediately hopped up and celebrated. Before I could even finish celebrating one friend started going on about how the Lakers suck. It just pissed me off so much I screamed at her to get out my room until she left.
She knows I'm a huge fan and she likes them too. She was only saying it to antagonize me. Am I the dick here?
Solution: yes
Why? It is very rude to shout at someone and ask her to leave the room even if her comments may have antagonized the author. Hence author is at fault here.
New input: Is OTHER wrong in the post ? POST : This sounds bad, but I'll elaborate. I don't often tell people I am in a relationship **unless the conversation warrants it** (i.e. the discussion shifts to talking about our partners, etc.)
In my perspective, this isn't necessarily "lying" per se, as much as it is the omission of irrelevant details.
My primary reason for this is that I have been criticized before (particularly by men) claiming that I'm entitled for thinking they "want me" because I told them I was in a relationship straight-up.
This has been an area of contention for me because, on one hand, it does seem a bit odd to disclaim that outright, but on the other hand, I have gotten shit for "leading people on," if I don't reveal my relationship status early on in a conversation.
My boyfriend is uncomfortable by my decision to keep our relationship relatively private unless I am asked/the context permits it, but he also has a better sense of intuition than I do.
My environment makes it so I constantly interact with individuals my age that I'm obligated to be nice/courteous to, and I am a petite and relatively conventionally attractive woman. This makes my boyfriend worry because I have been confronted both publicly and privately by people after "leading them on," which compromises my safety.
My partner isn't insecure and our relationship isn't unhealthy, but AITA if I decide to continue only discussing my relationship status when asked or when the social context permits it?
Solution: | yes | 0 | NIv2 | task502_scruples_anecdotes_whoiswrong_verification | fs_opt | [
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|
Given a sentence in Hindi, generate a new Hindi sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
One example is below.
Q: आप एक जूरी नहीं करना चाहते हैं तो आप एक वकील बनना चाहिए.
A: आप एक जूरी जीतने के लिए जीते हैं तो आप एक राजा बनना चाहिए.
Rationale: This is the good example. The created sentence is semantically similar to the input as both are talking about what to become if one doesn’t want to become the jury and the changes in the sentence follows the commonsense knowledge.
Q: आप आकाश का उपयोग आँखों के विपरीत एक हवाई जहाज़ की जाँच करने के लिए कर सकते हैं ।
A: | आप मंच पर एक हवाई जहाज़ पार करने के लिए सेवा का इस्तेमाल कर सकते हैं । | 9 | NIv2 | task407_mickey_hi_sentence_perturbation_generation | fs_opt | [
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|
Teacher:In this task, you're given a review from Amazon and rating for the product on a scale of 1-5 based on the review. The rating means 1: extremely poor, 2: poor, 3: neutral, 4: good, 5: extremely good. Your task is to generate whether the rating matches the review or not. Answer with "True" if the sentence belongs to that section, otherwise answer with "False"
Teacher: Now, understand the problem? Solve this instance: Review: I would put a sippie spout on the top lid. Its akward to have to have to undo the big top, drink then put it back. The tub also sweats a lot from condensation. Include a bottom with a sweat edge that will catch condensation in future models.
Rating: 2
Student: | True | 6 | NIv2 | task1311_amazonreview_rating_classification | zs_opt | [
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|
Given the task definition, example input & output, solve the new input case.
In this task, you are given a context tweet, a question and corresponding answer of given question. Your task is to classify given passage into two categories: (1) "yes" if the given context is useful in answering the question, and (2) "no" if the given context is not useful.
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 Question: at which school were first responders on the scene for? Answer: independence high school
Output: yes
Here, the generated label is 'yes' because the given context is useful in answering the question.
New input case for you: Context: Well I guess it is time to say goodbye to all my friends, family, support team. I will be making my final impact very soon.— MESSENGER (@MESSENGER2011) April 30, 2015 Question: when will the tweeter make final impact? Answer: very soon
Output: | yes | 1 | NIv2 | task242_tweetqa_classification | fs_opt | [
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]
|
Instructions: In this task, you are given a public comment from online platforms. You are expected to classify the comment into two classes: threat and non-threat. Threat is a statement that someone will be hurt or harmed, especially if the person does not do something in particular.
Input: Comment: "I could stand in the middle of 5th Avenue and shoot somebody and I wouldn't lose voters," Donald J Trump
Output: | Threat | 3 | NIv2 | task322_jigsaw_classification_threat | zs_opt | [
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|
Definition: A text is given in English. Translate it from the English language to the Marathi language. The translation must not omit or add information to the original sentence.
Input: पण याच 40 वर्षात जर टूरिजमवर(पर्यटनावर) भर दिला असता तर आज संपूर्ण जग काश्मीर खो-याच्या पायाशी येऊन बसले असते, काश्मीर खो-यामध्ये ही क्षमता आहे आणि म्हणूनच आपण टूरिजमची ताकद ओळखली पाहिजे.
Output: | Brothers and sisters, Id like to tell the youth of Jammu and Kashmir that there are two ways before them to decide their destiny. | 2 | NIv2 | task1086_pib_translation_marathi_english | zs_opt | [
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|
Teacher:In this task you are given a premise and two alternatives in Haitian. You must choose the alternative that is more plausibly the cause or effect of the situation described by the premise. The input format is "premise
(1)alternative_1(2)alternative_2", the output should either be "1" or "2" based on your judgment.
Teacher: Now, understand the problem? Solve this instance: Mwen te pliye papye a.
(1)Mwen te resikle papye a.(2)Papye a te pran yon pli.
Student: | 2 | 6 | NIv2 | task1168_xcopa_commonsense_reasoning_ht | zs_opt | [
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|
In this task, you are given an input list. A list contains several comma-separated items written within brackets. You need to return the position of all the numerical elements in the given list in order. Assume the position of the 1st element to be 1. Return -1 if no numerical element is in the list.
Let me give you an example: ['238', 'h', '92', 'U', '2799']
The answer to this example can be: 1, 3, 5
Here is why: Here, the numerical elements in the input list are '238', '92' and '2799' and they are at positions '1', '3', and '5', respectively.
OK. solve this:
['113', '4837']
Answer: | 1, 2 | 8 | NIv2 | task507_position_of_all_numerical_elements_in_list | fs_opt | [
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|
Given the task definition and input, reply with output. In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no".
Here are the definitions of logical operators:
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.
Command: eq { hop { argmax { all_rows ; attendance } ; date } ; 1970 - 10 - 04 }, interpretation: select the rows whose silver record is equal to 3 . there is only one such row in the table . the nation record of this unqiue row is soviet union .
| no | 5 | NIv2 | task211_logic2text_classification | zs_opt | [
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|
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 Arabic.
アンドリューはちょっとした研究を続けていましたが他の人に教えられた事の一つについて文献を調べてみると実に大きなボトルネックがあることが分かったのです
Output: | و قد كان "" Andrew "" يجري بحوثه حول الموضوع و من الأشياء التي قيلت له و التي تعلمها خلال مراجعاته الأدبية هو وجود عائق كبير. | 1 | NIv2 | task1224_ted_translation_ja_ar | zs_opt | [
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|
Teacher:Given a sentence in Chinese, generate a new Chinese sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Teacher: Now, understand the problem? Solve this instance: 它能提高珍珠的影响力或纯度
Student: | 它能改善界面的外观或噪音。 | 6 | NIv2 | task412_mickey_zh_sentence_perturbation_generation | zs_opt | [
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|
In this task, you are given a sentence in the English language. Your job is to translate the English sentence into the Romanian language.
Let me give you an example: A man is spreading shreded cheese on a pizza.
The answer to this example can be: Un bărbat pune brânză mărunțită pe o pizza.
Here is why: In the given translation process, the tense of both sentences, quantitative measures, entity name, the polarity of the sentence remains the same.
OK. solve this:
There are three main factors that drive the low shadow economy in the US.
Answer: | Există trei factori principali care conduc economia subterană în Statele Unite. | 8 | NIv2 | task1436_ro_sts_parallel_language_translation_en_to_ro | fs_opt | [
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]
|
Detailed Instructions: In this task, you need to count the number of nouns/verbs in the given sentence.
Problem:Sentence: 'A bird is sitting on a telephone wire'. Count the number of verbs in this sentence.
Solution: | 1 | 8 | NIv2 | task155_count_nouns_verbs | zs_opt | [
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|
instruction:
Given a sentence in the Japanese and Thai language. Your task is check if the Filipino sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
question:
Japanese: 米ドルの価格は、世界の他の通貨に対して下落したが、金の価格は上昇した。
Thai: เจ้าหน้าที่ตำรวจกล่าวว่า อุบัติเหตุเกิดเมื่อคุณวินเนอร์ ขับรถเอนกประสงค์ของเขาเข้าไปในเลนรถสวนมา
answer:
No
question:
Japanese: フロリダ州、ボニータ・スプリングス出身の67歳男性、トーマス・ウーレットは月曜日、大型旅客機に花火を持ち込んだ後、FBIから質問を受けた。
Thai: นายโทมัส อูวเลตเต้ ชายวัย 67ปีจากโบนิต้าสปริงส์ รัฐฟลอริดา ถูกสอบสวนโดยเอฟบีไอ เมื่อวันจันทร์ หลังจากที่เขาได้นำดอกไม้ไฟขึ้นไปบนเครื่องบิน
answer:
Yes
question:
Japanese: BBCは、今日のラジオ1チャート・ショーで”ディン・ドン!魔女は死んだ”は全く放送しない、と発表した。
Thai: บีบีซีประกาศว่าจะไม่ออกอากาศ "Ding-Dong! The Witch is Dead" ในผังรายการทั้งหมดของช่อง เรดิโอ 1 ในวันนี้
answer:
| Yes
| 9 | NIv2 | task1129_alt_ja_th_answer_generation | fs_opt | [
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|
The task is to generate the correct answer for a given math problem.
Problem: a and b invests rs . 10000 each , a investing for 6 months and b investing for all the 12 months in the year . if the total profit at the end of the year is rs . 24000 , find their shares ?
8000
Problem: if the sides of a triangle are 26 cm , 24 cm and 15 cm , what is its area ?
180
Problem: if it would take one machine 20 minutes to fill a large production order and another machine 30 minutes to fill the same order , how many minutes would it take both machines working together , at their respective rates , to fill the order ?
| 12 min
| 0 | NIv2 | task1726_mathqa_correct_answer_generation | fs_opt | [
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|
TASK DEFINITION: Given a sentence in Dutch, generate a new Dutch sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
PROBLEM: Als je kunst wilt bekritiseren dan moet je een kunstpers bezoeken.
SOLUTION: Als je kunst wilt doneren dan moet je een kunstdisplay bezoeken.
PROBLEM: U zult waarschijnlijk een busreservering vinden in een universiteitslijn.
SOLUTION: U zult waarschijnlijk een busopvang vinden in een transitshop.
PROBLEM: Als je een restaurant moet verdragen dan moet je naar de bioscoop gaan.
SOLUTION: | Als je naar een geest wilt kijken dan moet je naar de bioscoop gaan.
| 8 | NIv2 | task409_mickey_nl_sentence_perturbation_generation | fs_opt | [
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]
|
Given the task definition, example input & output, solve the new input case.
Given a sentence in the Japanese and Indonesian(Bahasa variant) language. Your task is check if the Bahasa Indonesia sentence is translation of Japanese. if the translation is correct than generate label "Yes", otherwise generate label "No".
Example: Japanese: 詳細は昨日UTC17時30分、英国議会でイギリスのルス・ケリー運輸大臣によって伝えられた。
Bahasa Indonesia: Detil diberikan oleh Sekretaris Kementerian Transportasi UK, Ruth Kelly, di Dewan Perwakilan Rakyat kemarin 17:30 UTC.
Output: Yes
The converted Bahasa Indonesia sentence is correctly translated from Japanese because converted sentence has the same message as the original Japanese sentence that Details were given yesterday in the House of Commons at 1730 UTC by Britain's Transport Secretary Ruth Kelly.
New input case for you: Japanese: しかし、サーバーの設計を変えてオープンソースにすることによって、同社は、他の人が自分たちで改善する方法を見つけることを望んでいる。
Bahasa Indonesia: Keputusan tersebut mempengaruhi perusahaan seperti Grokster dan StreamCast, yang keduanya terdakwa dalam gugatan ini.
Output: | No | 1 | NIv2 | task1117_alt_ja_id_answer_generation | fs_opt | [
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|
Detailed Instructions: In this task, you will be given a set of steps that are required to answer a specific question. Your job is to generate that question. Each given step refers to either an entity (known or unknown), a propery of an entity or a query operation (count, group, union, etc.) Knowing those operations and how they appear in the input may help you generate more accurate questions.
Select: A select step is used to return a set of objects. There are no references to previous steps in a select step. template: Return [attributes]
Filter: A filter step is used to return results from a previous step to which a certain condition applies. template: Return [#step] [condition]
Project: A project step should return certain attributes of the results of a previous step. template: Return [attributes] of [#step]
Aggregate: An aggregate step returns an aggregator function applied on a step's result. template: Return the [aggregator] of [#step].
Group: A group step is an aggregator applied on attributes. template: Return the [aggregator] of [#step] for each [attribute]
Superlative: A superlative step is used to return the result with a highest/lowest attribute among other results. template: Return [#step1] [where] [#step2] [is] [highest / lowest]
Comparative: A comparative step is used when we need to compare an attribute with a number to filter results. template: Return [#step1] [where] [#step2] [comparator] [number]
Union: A union step is used to return results of two steps together. template: Return [#step1] [or / ,] [#step2]
Intersection: An intersection step returns the result that two steps have in common. template: Return [attribute] of both [#step1] and [#step2]
Discard: A discard step returns result of a step and excludes result of another step from it. template: Return [#step1] besides [#step2]
Sort: A sort returns result of another step in a specific order. template: Return [#step1] [ordered / sorted by] [#step2]
Is true: An is true step checks a condition on another result and returns a true or false. template: Return [is / if] [condition]
Arithmetic: An arithmatic step operates an arithmatic operation on one or more steps. template: Return the [arithmetic op.] of [#step1] [and] [#step2].
Problem:#1 return countries
#2 return airlines that operate out of #1
#3 return number of #2 for each #1
#4 return #3 sorted by descending order
Solution: | How many airlines operate out of each country in descending order? | 8 | NIv2 | task184_break_generate_question | zs_opt | [
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]
|
You will be given a definition of a task first, then some input of the task.
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) leaving my best friend's bday because of a girl
(B) disputing rather than paying a debt over a clerical mistake
Output: | A | 1 | NIv2 | task106_scruples_ethical_judgment | zs_opt | [
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|
Instructions: In this task, you are given a sentence in English and your task is to translate it into Spanish. In translation, keep the numbers and capitalization (capitalize only the first word of each sentence and name).
Input: Between 1998 and 1999, loyalists assaulted and shot 123 people, while republicans assaulted and shot 93 people.
Output: | Entre 1998 y 1999 los leales asaltaron y dispararon a 123 personas, mientras que los republicanos asaltaron y dispararon a 93. Entre 1998 y 1999, los leales asaltaron y dispararon a 123 personas, mientras que los republicanos asaltaron y dispararon a 93 personas. | 3 | NIv2 | task530_europarl_en_es_translation | zs_opt | [
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|
Given a sentence in English, provide an equivalent paraphrased translation in German that retains the same meaning both through the translation and the paraphrase.
Q: The Tweenies consist of Bella , Milo , Fizz , Jake , Doodles , Izzles , Max , Judy , and are sometimes joined by Max 's sister Polly .
A: Die Tweenies bestehen aus Bella, Milo, Fizz, Jake, Scribbles, Izzles, Max, Judy und werden manchmal von Max 'Apos begleitet. Schwester Polly.
****
Q: There were also 58 liaison aircraft but 20 of these were only used for messengers .
A: Es gab auch 58 Verbindungsflugzeuge, von denen 20 nur für Boten eingesetzt wurden.
****
Q: The school is connected with the secondary department of the autistic school Ysgol Plas Brondyffryn , which was built in 2003 .
A: | Die Schule steht in Verbindung mit der Sekundärabteilung der autistischen Schule Ysgol Plas Brondyffryn, die 2003 errichtet wurde.
****
| 4 | NIv2 | task780_pawsx_english_german_translation | fs_opt | [
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|
instruction:
In this task, answer 'Yes' if the frequency of the given word in the two sentences is equal, else answer 'No'.
question:
Sentence1: 'a picture of some people out of snow', Sentence2: 'people approach and order at a red food truck'. Is the frequency of the word 'a' in two sentences equal?
answer:
Yes
question:
Sentence1: 'a white truck travelling on a street pass homes', Sentence2: 'a paper plate with a hot dog and french fries'. Is the frequency of the word 'a' in two sentences equal?
answer:
Yes
question:
Sentence1: 'a close up of a street sign with leaves and a sky background', Sentence2: 'several people riding surfboards on waves in the ocean'. Is the frequency of the word 'close' in two sentences equal?
answer:
| No
| 9 | NIv2 | task159_check_frequency_of_words_in_sentence_pair | fs_opt | [
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|
In this task, you will be given a short story. One sentence from the story is chosen. Consider the events that happen before that sentence, or are likely to have happened before it. Does any of them directly cause it, or simply make it possible? You should write your answer in the form " A >causes/enables> B". Try to use phrases and sentences from the story to compose your answer when possible.
Let me give you an example: story: It was bedtime at our house. Two of the three kids hit the pillow and fall asleep. The third is a trouble maker. For two hours he continues to get out of bed and want to play. Finally he becomes tired and falls asleep.
selected sentence: Finally he becomes tired and falls asleep.
The answer to this example can be: A kid wants to play before sleep >Causes/Enables> A kid eventually falls asleep
Here is why: The selected sentence is about a kid falling sleep, the answer correctly identifices an event causing the sentence to happen.
OK. solve this:
story: Tom bought four things of ice cream. One was mint, one was orange, and one was brownie fudge. He got stuck in traffic on the way home from the store. The ice cream got melty and sort of made a mess. When he got home, he froze what was left of it.
selected sentence: One was mint, one was orange, and one was brownie fudge.
Answer: | Tom bought four things near ice cream >Causes/Enables> One was mint | 8 | NIv2 | task614_glucose_cause_event_detection | fs_opt | [
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]
|
Instructions: In this task you are given a list of integers and you need to find the absolute value of the difference between each two consecutive values. The output should be a list of the absolute value of the differences of each two consecutive values.
Input: [-78, -40, 5, 70, -33, 89, 96, -31, 56, -49]
Output: | [38, 45, 65, 103, 122, 7, 127, 87, 105] | 3 | NIv2 | task125_conala_pair_differences | zs_opt | [
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|
Given the task definition, example input & output, solve the new input case.
In this task, you're given a fill-in-the-blank question that contains two object names. Additionally, you're given one answer which is one of the objects present in the question. In this task, you need to minimally change the given question so that the answer flips to another object in the question. Remember the question has to be about both objects which are related but different; for example, "trophy" and "suitcase". This task typically involves replacing one word i.e., the 'trigger word' with its antonym (e.g., changing from "small" to "big"). You should not change any content in the given question beyond a word or two, i.e., the trigger word/phrase. The expected answer to your question must not be associated with just the trigger word; instead, it should depend on the context present in the question. The expected answer should not be ambiguous. For your question, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. In your generated question, retain the object names from the input question. Avoid repeating the same style or phrase in generating your modified question e.g. this task can be always solved using a simple negation i.e. by adding not, never, etc. Instead, try to increase the word diversity. Your question must contain at least 15 and at most 30 words. Your question must have at least 70% overlapping words with the given question. You must utilize the given context word while writing the question. Your question must contain only one blank. The two objects should be used ONCE in your question. Here is a list of attributes and associated contrastive words that may help write contrastive trigger words. Note that contrastive trigger words help in flipping the label.
| 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 |
Example: Context word: fit.
Question: The trophy doesn't fit into the brown suitcase because _ is too large.
Answer: trophy.
Output: The trophy doesn't fit into the brown suitcase because _ is too small.
Here, replacing the trigger word "large" by its antonym "small" flips answer to the second object ("suitcase") in the question. So, this is a valid question.
New input case for you: Context Word: prune.
Question: The girl had to prune more plants in the summer than the winter because they grew better in the _ .
Answer: summer.
Output: | The girl had to prune more plants in the summer than the winter although they grew better in the _ . | 1 | NIv2 | task034_winogrande_question_modification_object | fs_opt | [
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|
Q: In this task, you need to answer 'Yes' if the given word is the longest word (in terms of number of letters) in the given sentence, else answer 'No'. Note that there could be multiple longest words in a sentence as they can have the same length that is the largest across all words in that sentence.
Sentence: 'a woman eating a hot dog while standing on a sidewalk'. Is 'standing' the longest word in the sentence?
A: | Yes | 7 | NIv2 | task114_is_the_given_word_longest | zs_opt | [
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]
|
You will be given a definition of a task first, then some input of the task.
The task is to generate text based of an event. For the given event, there will be a person who does the action in the event (usually PersonX). Your task is to write that persons emotional reaction to the event, i.e. how that person feels after doing the action.
PersonX goes to the bow-wows
Output: | happy | 1 | NIv2 | task1595_event2mind_text_generation_1 | zs_opt | [
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|
Detailed Instructions: The provided text is in English, and we ask you to translate the text to the Croatian language. Please bear in mind the following guidelines while translating: 1) We want a natural translation, a formal form. 2) Use the symbols like '#@%$-+_=^&!*' as-is. *Include* the special characters as suited when translating to Croatian. 3) Quantities like millions or billions should be translated to their equivalent in Croatian language 4) Note the input is all case-sensitive except for special placeholders and output is expected to be case-sensitive. 5) The output must have Croatian characters like Ž or č and the output must preserve the Croatian language characters. 6) The input contains punctuations and output is expected to have relevant punctuations for grammatical accuracy.
Q: What can managers do -- enlightened managers, hopefully -- what can they do to make the office a better place for people to work, so it's not the last resort, but it's the first resort?
A: | Što mogu menadžeri napraviti -- prosvijetljeni menadžeri, nadam se -- što oni mogu napraviti da uredi budu bolja mjesta za ljude koji rade, tako da ne budu zadnja mjesta za rad, već prva? | 9 | NIv2 | task1365_opustedtalks_translation | zs_opt | [
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|
In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_). The sentence pair should look similar and should be about two different persons (PersonX and PersonY). Additionally, the two sentences must be different in terms of trigger words (e.g., "sympathetic" and "stern") which express contrasting attributes about the two persons. The answer to the first and the second sentence must be PersonX and PersonY, respectively. PersonX and PersonY should not be equally likely to fill the blank. 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 the names of real people (e.g., Donald Trump, Putin, etc.) in your sentences. 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 PersonX and PersonY have the same gender. In each sentence, PersonX and PersonY should be used only ONCE and PersonX should appear earlier than PersonY.
Context Word: sap. | Sentence 1: PersonX yelled at PersonY for getting sap stuck in their hair and _ ended up having to shave their head.
Sentence 2: PersonX consoled aPersonY for getting sap stuck in their hair and _ ended up having to have their head shaved. | 0 | NIv2 | task030_winogrande_full_person | zs_opt | [
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|
Given the task definition and input, reply with output. You are given an original reference as well as a system reference. Your task is to judge the quality of the system reference. If the utterance is grammatically correct and fluent output 1, else output 0.
System Reference: can i double check you want a hotel that has internet?
Original Reference: would you like to select from only hotel -s that provide internet access?.
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]
|
You will be given a trivia clue, and the category it belongs to. You should answer with the best answer that belongs in the category and is described by the clue. For simplicity, answers should be in all lower cased letters.
Category: AT THE ZOO
Clue: Wow! It's a spiny-tailed iguana, one of these that holds the 21 mph reptile land speed record | a lizard | 0 | NIv2 | task308_jeopardy_answer_generation_all | zs_opt | [
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|
In this task, you are given a sentence which is either in the Gujarati language or English language. You task is to identify the language of input sentence. Input sentence can be in Gujarari or English language only and also it cannot have two languages at a time.
One example: A herd of sheep standing together grazing in a pasture.
Solution is here: English
Explanation: Input sentence is in English language.
Now, solve this: There are large stacks of kitchenware neatly arranged on the stainless stail counter.
Solution: | English | 6 | NIv2 | task441_eng_guj_parallel_corpus_gu-en_language_identification | fs_opt | [
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|
Detailed Instructions: In this task, you are given a text of article and corresponding title of an article. Your task is to generate label "yes" if headline (title) is right for article, otherwise generate "no".
Problem:Article: imf managing director dominique strauss-kahn welcomed tuesday the `` bold steps '' taken by the united states to stabilise the financial system , but warned global steps were required to get past the crisis . Title: ice hockey team invites republican vp pick palin to join fold
Solution: | no | 8 | NIv2 | task289_gigaword_summarization | zs_opt | [
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|
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