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Update tasks (#660)
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yeganehkordi authored Nov 30, 2021
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6 changes: 4 additions & 2 deletions doc/task-hierarchy.md
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- `Classification -> Verification -> Answer Verification`: Verify whether a text answers the question
- `Classification -> Verification -> Claim Verification`
- `Classification -> Verification -> Clarification Verification`
- `Classification -> Verification -> Entailment Verification`
- `Classification -> Verification -> Ethical Verification`
- `Classification -> Verification -> Grammar Verification`: Verify whether a text is grammatical
- `Classification -> Verification -> Relevance Verification`
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- `Text Generation -> Sentence Generation -> Explanation Generation`
- `Text Generation -> Sentence Generation -> Completion`
- `Text Generation -> Sentence Generation -> Completion -> Story`
- `Text Generation -> Sentence Generation -> Completion -> Story -> Incorrect`
- `Text Generation -> Sentence Generation -> Completion -> Story -> Incorrect`
- `Text Generation -> Sentence Generation -> Summary Generation`
- `Text Generation -> Structured Text Generation`: Generate structured text in the output e.g. a task that converts questions in natural language to SQL queries
- `Text Generation -> Structured Text Generation -> Code`
- `Text Generation -> Structured Text Generation -> List`
- `Text Generation -> Structured Text Generation -> List`
- `Text Generation -> Structured Text Generation -> Table`
- `Text Generation -> Summary Generation`
- `Text Generation -> Title Generation`
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],
"Definition": "You will be given a context, a subject and a relation. Your task is to generate a question based on the subject and relation. The generated question should include the given subject. Try to use a minimum number of words that are not present in either context, subject or relation while generating question.",
"Domains": [
"Countries"
"Wikipedia"
],
"Positive Examples": [
{
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25 changes: 14 additions & 11 deletions tasks/task1326_qa_zre_question_generation_from_answer.json
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"Question & Answer zre (http://nlp.cs.washington.edu/zeroshot/)"
],
"Categories": [
"Question Generation"
"Question Generation -> Contextual Question Generation -> Generate from an Answer"
],
"Input_language": [
"English"
],
"Output_language": [
"English"
],
"Instruction_language": [
"English"
],
"Definition": "Generate a question which can yield the answer mentioned in the input. Generated question must be answered by the answer provided in input, without using any extra knowledge.",
"Domains": [
"Wikipedia"
],
"Input_language": [
"English"
],
"Output_language": [
"English"
],
"Instruction_language": [
"English"
],
"Definition": "Generate a question which can yield the answer mentioned in the input. Things to follow while generating the dataset. 1. Generated question must be answered by the answer provided in input, without using any extra knowledge.",
"Positive Examples": [
{
"input": "Context : Isaac Nicola Romero (1916 in Havana, Cuba -- 1997) was a prominent Cuban guitarist and one of the founders of the modern Cuban Guitar School. \nAnswer : Havana",
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24 changes: 14 additions & 10 deletions tasks/task1327_qa_zre_answer_generation_from_question.json
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"Question & Answer zre (http://nlp.cs.washington.edu/zeroshot/)"
],
"Categories": [
"Answer Generation"
"Question Answering -> Contextual Question Answering -> Extractive",
"Text Span Selection"
],
"Input_language": [
"English"
],
"Output_language": [
"English"
],
"Instruction_language": [
"English"
],
"Input_language": [
"English"
],
"Output_language": [
"English"
],
"Instruction_language": [
"English"
],
"Definition": "Generate a correct and concise answer for the question based on the words in the context.",
"Domains": [
"Wikipedia"
],
"Positive Examples": [
{
"input": "Context : Isaac Nicola Romero (1916 in Havana, Cuba -- 1997) was a prominent Cuban guitarist and one of the founders of the modern Cuban Guitar School. \nQuestion : What was Isaac Nicola's city of birth?",
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24 changes: 14 additions & 10 deletions tasks/task1328_qa_zre_relation_generation_from_question.json
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"Question & Answer zre (http://nlp.cs.washington.edu/zeroshot/)"
],
"Categories": [
"Classification"
"Classification",
"Detection -> Relation Detection"
],
"Input_language": [
"English"
],
"Output_language": [
"English"
],
"Instruction_language": [
"English"
],
"Input_language": [
"English"
],
"Output_language": [
"English"
],
"Instruction_language": [
"English"
],
"Definition": "Classify the relation of question with context to one of these categories: 1) award received, 2) based on, collection, 3) conflict, 4) constellation, 5) convicted of, 6) date of death, 7) director, 8) drafted by, 9) educated at, 10) medical condition, 11) military branch, 12) narrative location, 13) occupation, 14) original network, 15) parent company, 16) point in time, 17) production company, 18) residence, 19) series, 20) service entry, 21) sex or gender, 22) spouse, 23) standards body question.",
"Domains": [
"Wikipedia"
],
"Positive Examples": [
{
"input": "Context : Isaac Nicola Romero (1916 in Havana, Cuba -- 1997) was a prominent Cuban guitarist and one of the founders of the modern Cuban Guitar School. \nQuestion : What was Isaac Nicola's city of birth?",
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45 changes: 25 additions & 20 deletions tasks/task1329_open_subtitles_en_hi_translation.json
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"Open Subtitles Datset (https://opus.nlpl.eu/OpenSubtitles.php)"
],
"Categories": [
"Language Translation"
"Translation"
],
"Input_language": [
"English"
],
"Output_language": [
"Hindi"
],
"Instruction_language": [
"English"
],
"Input_language": [
"English"
],
"Output_language": [
"Hindi"
],
"Instruction_language": [
"English"
],
"Definition": "Translate from English to Hindi.",
"Domains": [
"Narrative",
"Dialogue",
"Commonsense -> Concepts and Relations"
],
"Positive Examples": [
{
"input": "Go to the employment office.",
"output": "रोजगार कार्यालय जाओ.",
"explanation": "The translation is accurate"
"explanation": "The translation is accurate."
},
{
"input": "They'll give you a work permit.",
"output": "वे तुम्हें वर्क परमिट दे देंगे.",
"explanation": "The translation is fluent and precise"
"explanation": "The translation is fluent and precise."
},
{
"input": "My God, a job!",
"output": "हे भगवान, नौकरी!",
"explanation": "The translation is accurate"
"explanation": "The translation is accurate."
},
{
"input": "Hey, what about us?",
"output": "अरे, हमारे बारे में क्या?",
"explanation": "The translation is correct"
"explanation": "The translation is correct."
},
{
"input": "I've got two jobs, but they're not for you.",
"output": "मेरे पास दो के लिए काम है, लेकिन वे तुम्हारे लिए नहीं हैं.",
"explanation": "It is a correct translation"
"explanation": "It is a correct translation."
}
],
"Negative Examples": [
{
"input": "THE BICYCLE THIEF",
"output": "साइकिल चोरी",
"explanation": "This is a wrong translation since the translation is using verb form of thief that is theft"
"explanation": "This is a wrong translation since the translation is using verb form of thief that is theft."
},
{
"input": "Ricci?",
"output": "धनी?",
"explanation": "This is wrong translation because instead of the name the ricci is wrongly interpreted as ricchi which means wealthy"
"explanation": "This is wrong translation because instead of the name the ricci is wrongly interpreted as ricchi which means wealthy."
},
{
"input": "Was Ricci there?",
"output": "रिच्ची है क्या?",
"explanation": "This translation is temporally wrong. Because English sentenece is in past and the translation is in present tense"
"explanation": "This translation is temporally wrong. Because English sentenece is in past and the translation is in present tense."
},
{
"input": "Are you deaf? Come on",
"output": "तुम बहरे हो क्या?",
"explanation": "The above translation is partially translated. hence it is a wrong translation"
"explanation": "The above translation is partially translated. hence it is a wrong translation."
},
{
"input": "Get a move in.",
"output": "उठो! चलो.",
"explanation": "The above translation is a wrong translation since the translated sentence means 'get up and move'"
"explanation": "The above translation is a wrong translation since the translated sentence means 'get up and move'."
}
],
"Instances": [
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45 changes: 25 additions & 20 deletions tasks/task1330_open_subtitles_en_te_translation.json
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"Open Subtitles Datset (https://opus.nlpl.eu/OpenSubtitles.php)"
],
"Categories": [
"Language Translation"
"Translation"
],
"Input_language": [
"English"
],
"Output_language": [
"Telugu"
],
"Instruction_language": [
"English"
],
"Input_language": [
"English"
],
"Output_language": [
"Telugu"
],
"Instruction_language": [
"English"
],
"Definition": "Translation from English to Telugu.",
"Domains": [
"Narrative",
"Dialogue",
"Commonsense -> Concepts and Relations"
],
"Positive Examples": [
{
"input": "Many strange legends are told of these jungles of India, but none so strange as the story of a small boy named Mowgli.",
"output": "అనేకవింతపురాణములు భారతదేశం యొక్క ఈ అరణ్య యొక్క చెప్పబడ్డాయి, కానీమోగ్లీఅనేచిన్నబాలుడుకథ కాబట్టి వింత ",
"explanation": "The translation is fluent, formal, and Precise"
"explanation": "The translation is fluent, formal, and Precise."
},
{
"input": "It all began when the silence of the jungle was broken by an unfamiliar sound.",
"output": "అడవియొక్కనిశ్శబ్దం అధిగమించేఇదిఅన్నిప్రారంభమైంది ఒకతెలియనిశబ్దం",
"explanation": "The translation is fluent, accurate, and Precise"
"explanation": "The translation is fluent, accurate, and Precise."
},
{
"input": "It was a sound like one never heard before in this part of the jungle.",
"output": "ఇదిముందువిన్నఎప్పుడూ ఒక వంటి ఒక శబ్దం అడవియొక్కఈభాగంలో",
"explanation": "The translation is fluent, temporally correct and clean"
"explanation": "The translation is fluent, temporally correct and clean."
},
{
"input": "It was a man cub!",
"output": "ఇదిఒకవ్యక్తిపిల్లఉంది",
"explanation": "The translation is fluent, formal, and Precise"
"explanation": "The translation is fluent, formal, and Precise."
},
{
"input": "Had I known how deeply I was to be involved,",
"output": "నేనుచేరిఎలాలోతుగా తెలిసిన,",
"explanation": "The translation is fluent, formal, and temporally correct"
"explanation": "The translation is fluent, formal, and temporally correct."
}
],
"Negative Examples": [
{
"input": "Then it occurred to me.",
"output": "ఇప్పుడు నాకు ఏర్పడిం",
"explanation": "The above translation is temporally incorrect"
"explanation": "The above translation is temporally incorrect."
},
{
"input": "A family of wolves I knew had been blessed with a litter of cubs.",
"output": "తోడేళ్ళుఒకకుటుంబంనేను ఒక ఈతలో తో దీవించిన జరిగింది తెలుసు",
"explanation": "Translation is missing some words"
"explanation": "Translation is missing some words."
},
{
"input": "It was a sound like one never heard before in this part of the jungle.",
"output": "ఇదిముందువిన్నఎప్పుడూ రెండు వంటి రెండు శబ్దం అడవియొక్కఈభాగంలో",
"explanation": "The count in the translation is wrong"
"explanation": "The count in the translation is wrong."
},
{
"input": "This meeting was to change the man cub's entire future.",
"output": "ఈసమావేశంలో మార్చడానికి మ్యాన్ పిల్ల యొక్క మొత్తం గతం",
"explanation": "Translation is is opposite to what source and dosen't make sense"
"explanation": "Translation is is opposite to what source and dosen't make sense."
},
{
"input": "Had I known how deeply I was to be involved,",
"output": "నేనుచేరిఎలాా తెలిసిన,",
"explanation": "Translation is incorrect as it is missing some words"
"explanation": "Translation is incorrect as it is missing some words."
}
],
"Instances": [
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6 changes: 5 additions & 1 deletion tasks/task1331_reverse_array.json
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"synthetic"
],
"Categories": [
"Answer Generation"
"Text Generation -> Command Execution -> Code Execution",
"Text Generation -> Structured Text Generation -> List"
],
"Definition": "In this task, you are given a list of integers in a random order. You need to return the same list of integers in the reverse order.",
"Domains": [
"Mathematics"
],
"Positive Examples": [
{
"input": "[139, 192, 48, 118, 158, 52, 41, 137, 172, 285, 57, 187, 269, 277, 13, 114, 250, 99, 210, 155]",
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7 changes: 6 additions & 1 deletion tasks/task1332_check_leap_year.json
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"synthetic"
],
"Categories": [
"Classification"
"Classification -> Verification",
"Reasoning -> Numerical Reasoning",
"Mathematics -> Arithmetic"
],
"Definition": "In this task, you are given a year. You need to check if it is a leap year or not. A year may be a leap year if it is evenly divisible by 4. Years that are divisible by 100 (century years such as 1900 or 2000) cannot be leap years unless they are also divisible by 400. Return 1 if it is a leap year, else return 0.",
"Domains": [
"Mathematics"
],
"Positive Examples": [
{
"input": "1644",
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7 changes: 6 additions & 1 deletion tasks/task1333_check_validity_date_ddmmyyyy.json
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"synthetic"
],
"Categories": [
"Classification"
"Classification -> Verification",
"Reasoning -> Numerical Reasoning"
],
"Definition": "In this task, you are given a date in \"dd/mm/yyyy\" format. You need to check if the date is valid or not. Return 1 if it is valid, else return 0. A date is valid if the components day(\"dd\"), month(\"mm\") and year(\"yyyy\") are all valid individually. A day(dd) is valid if it: a) lies between 1 and 31 for the months of January, March, May, July, August, October, December, b) lies between 1 and 28 for February on non-leap years and between 1-29 on leap years, c) lies between 1-30 for all other months. A month(mm) is valid if it lies in the range from 1 to 12 as there are 12 months in a year. A year is always valid if it is expressed in the form of \"yyyy\".",
"Domains": [
"Mathematics",
"Commonsense -> Concepts and Relations"
],
"Positive Examples": [
{
"input": "15/2/2014",
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6 changes: 5 additions & 1 deletion tasks/task1334_sqac_answer_generation.json
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"https://huggingface.co/datasets/BSC-TeMU/SQAC"
],
"Categories": [
"Answer Generation"
"Question Answering -> Contextual Question Answering -> Abstractive"
],
"Input_language": [
"Spanish"
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"English"
],
"Definition": "You will be given a context and a question in Spanish. Your job is to generate answers that are at least THREE words long.\n The answers need to be context specific and can not be general knowledge or a random guess.",
"Domains": [
"Wikipedia",
"News"
],
"Positive Examples": [
{
"input": "CONTEXT: La historia de Japón (日本の歴史 o 日本史, Nihon no rekishi / Nihonshi?) es la sucesión de hechos acontecidos dentro del archipiélago japonés. Algunos de estos hechos aparecen aislados e influenciados por la naturaleza geográfica de Japón como nación insular, en tanto que otra serie de hechos, obedece a influencias foráneas como en el caso del Imperio chino, el cual definió su idioma, su escritura y, también, su cultura política. Asimismo, otra de las influencias foráneas fue la de origen occidental, lo que convirtió al país en una nación industrial, ejerciendo con ello una esfera de influencia y una expansión territorial sobre el área del Pacífico. No obstante, dicho expansionismo se detuvo tras la Segunda Guerra Mundial y el país se posicionó en un esquema de nación industrial con vínculos a su tradición cultural.\nQUESTION: ¿Cuándo se detuvo el expansionismo de Japón?",
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