ceselder/lots-of-loras-task-definitions huggingface dataset:
Task: In this task, you are given inputs i,j, and A, where i and j are integers and A is a list. You need to list all elements of A from the ith element to the jth element. i and j will be non-negative, and will always have a value less than the length of A. i will always be less than j.
Categories: Program Execution
Domains: Code

Positive examples:
input: 6, 14, ['9545', '5185', '1667', 'w', 's', '9559', 'T', 'u', 'U', '6843', 'L', 'l', '6365', '7103', 'A', '2381', '5037', 'X', '4487', 'd']
output: 9559, T, u, U, 6843, L, l, 6365, 7103
explanation: Here, all the elements between the 6th element and 14th element are '9559', 'T', 'u', 'U', '6843', 'L', 'l', '6365', and '7103'.; input: 8, 9, ['U', '6923', 'y', 'm', 'v', 'M', 'Y', 'A', 'E', '6059', 'p']
output: A, E
explanation: Here, all the elements between the 8th element and 9th element are 'A' and 'E'.

Negative examples:
input: 5, 9, ['7475', 'B', '2459', 'm', '8349', 'O', 'q', 'Y', 'f']
output: 7475, B
explanation: Here, the answer should have been '8349, O, q, Y, f' as all the elements between the 5th element and 9th element are  '8349', 'O', 'q', 'Y', and 'f'.; input: 2, 4, ['A', 'B', '39', 'd', '329', '11', 'e']
output: A, B, 39, d
explanation: Here, the answer should have been 'B, 39, d' as all the elements between the 2nd element and 4th element are  'B', '39', and 'd'.
Task: Given a text paragraph and a fact, generate a statement that is using the content of the given paragraph yet, it is **incorrect** (i.e., it contradicts the statements of the input).
Categories: Wrong Candidate Generation
Domains: Commonsense -> Concepts and Relations

Positive examples:
input: Anne is rough. Cold people are rough. If Anne is green then Anne is blue. Rough people are young. Anne is blue. If someone is rough and furry then they are blue. All young people are cold. If someone is rough and nice then they are green. Anne is young.
output: Anne is not young.
explanation: From the given paragraph particulary this parts 'Anne is rough' and 'Rough people are young', we can infer that Anne is young. So, this is a good example; input: Harry is kind. Harry is white. Harry is round. If someone is furry then they are white. If someone is green and kind then they are round. If someone is green then they are blue. If someone is not white and not furry then they are not kind. Harry is quiet. If someone is green and not round then they are furry. If someone is green then they are furry. Harry is furry. If someone is not kind then they are not green. Harry is blue. Harry is green. If someone is green then they are quiet.
output: Harry is not white.
explanation: From the given paragraph, we can infer that Harry is white. So, this is a good example.

Negative examples:
input: Gary is cold. Furry, kind things are smart. All cold, smart things are kind. Gary is smart. If something is smart and furry then it is cold. If something is kind and round then it is nice. Gary is round. All cold things are round. Gary is big. Gary is furry. Gary is kind. Gary is nice. If Gary is kind then Gary is round. If something is furry and cold then it is kind. Nice, furry things are round.
output: Gary is smart.
explanation: From the given paragraph, we can infer that Gary is smart. So, this is a bad example; input: Gary is green. Erin is smart. Charlie is quiet. Bob is not green. Gary is big. If Charlie is not smart then Charlie is furry. Bob is quiet. Gary is smart. Charlie is cold. All quiet people are smart. Bob is smart. If Charlie is quiet and Charlie is not cold then Charlie is furry. Charlie is furry.
output: Gary is green.
explanation: From the given paragraph, we can infer that Gary is green. So, this is a bad example
Task: In this task, you will be presented with a question in Dutch language, and you have to write the person names from the question if present. B denotes the first item of a phrase and an I any non-initial word. Phrase used for the person name - PER. There can be instances with no person name entity, then return 'None'.
Categories: Named Entity Recognition
Domains: Miscellaneous

Positive examples:
input: De belle van het bal is Hillary
output: Hillary: B-PER, Clinton: I-PER
explanation: In the given sentence, Hillary is identified as the person name, which is correct.; input: Mpenza -- hij begon gaandeweg zelfs ÃƒÆ’Ã‚Â©cht op Davids te lijken -- mocht draaien en keren zoveel hij wou , de squadra azzura stond pal.
output: Mpenza: B-PER, Davids: B-PER
explanation: Given sentence has two person names, Mpenza and Davids, which is correct.; input: Er zijn veel domeinen waar geld tekort is.
output: None
explanation: Given sentence has no person names, which is correct.

Negative examples:
input: Stan Ockers
output: Stan: B-PER, Ockers: I-PER
explanation: In the given sentence, combined two words should be the person name but it is identified as two different person names, which is incorrect.; input: Lucien Van Impe
output: Lucien: B-PER, Van: I-PER, Impe: I-PER
explanation: In the given sentence, combined three words should be the person name but it is identified as three different person names, which is incorrect.; input: Joseba Beloki ( Spa )
output: Joseba: B-PER, Beloki: I-PER
explanation: In the given sentence, first two words should be the person name but it is identified as two different names, which is incorrect.
Task: You are given a sentence in Arabic. Your job is to translate the Arabic sentence into Galician.
Categories: Translation
Domains: TED Talks; Captions -> Video Captions

Positive examples:
input: ويوجد أساسا مرجل دوار.
output: É basicamente un caldeiro que rota.
explanation: The Arabic sentence is correctly translated into Galician, because the meaning is preserved.; input: أو يقومون بإحراق البلاستيك للوصول إلى المعادن في منازل حرق كما ترون هنا
output: Ou queiman os plásticos para chegar aos metais en incineradoras como estas.
explanation: The Arabic sentence is correctly translated into Galician, because the meaning is preserved.; input: وهي تستجيب عندما تفكّر حول ما يفكّر فيه شخص آخر.
output: Esta rexión reacciona cando pensamos sobre o que outra persoa está pensando.
explanation: The Arabic sentence is correctly translated into Galician, because the meaning is preserved.

Negative examples:
input: تلك المغناطيسات بالداخل هناك.
output: Así que desata a Ulises e este tolea.
explanation: The Arabic sentence is not correctly translated into Galician, because the meaning is different.; input: لذلك وكناشطة ، بدأت العمل مع مؤسسة مرض باركنسون وموقعها الإلكتروني هو pdf.org من أجل خلق مبادرة كبرى بغرض وضع النساء على خارطة مرض باركنسون.
output: Así, como activista, comecei a traballar coa Fundación Parkinson — pdf.org — para crear un movemento importante que sitúe as mulleres no mapa do párkinson.
explanation: The Arabic sentence is not correctly translated into Galician, because the meaning is different.; input: فينفعل أوديسيوس ويقول له أيها الاحمق أيها الغبي
output: Os imáns están aí dentro.
explanation: The Arabic sentence is not correctly translated into Galician, because the meaning is different.
Task: In this task, given a sentence in the English language, your task is to convert it into the Japanese language.
Categories: Translation
Domains: News

Positive examples:
input: Test subjects will be administered either a placebo or PA-457 that will be taken in combination with the medication they already take.
output: 被験者は、彼らがすでに服用している薬剤と一緒に偽薬またはPA-457を与えられる。
explanation: The above sentence is correctly translated from English to Japanese.; input: As part of his effort to educate Palestinians, Mahameed has printed 2,000 booklets in Arabic describing photographs of Nazi horrors, offered stipends to Arab students of the subject, and started a new museum website (Alkaritha.org) with some translations offered in English, Arabic, and Hebrew.
output: パレスチナ人を教育する彼の取り組みの一環として、Mahameedはナチスの恐怖の写真を掲載したアラブ語の小冊子を2,000冊印刷し、その科目のアラブの学生に奨学金を提供し、そして英語、アラビア語、そしてヘブライ語といういくつかの翻訳を提供して新しい博物館のウェブサイト（Alkaritha.org）を始めた。
explanation: The above sentence is correctly translated from English to Japanese.; input: "It's against our Charter of Rights, that clearly says there's not to be any discriminations based on their religion, beliefs, race or their skin colour."
output: 「それは私たちの人権憲章に反していて、人権憲章は、人々の宗教、信条、人種、そして彼らの肌の色に基づくいかなる差別もあるべきではないと明確に述べています」
explanation: The above sentence is correctly translated from English to Japanese.

Negative examples:
input: For more than 260 days he was fed water, vitamins, and additional materials only by infusion.
output: あらゆる範囲の政治指導者らがJugalKishoreRaibir氏に花を手向けた。
explanation: The above sentence is not correctly translated from English to Japanese as none of the words match the translation.; input: According to the Tribunal spokesman Raed Jouhi, the Iraqi High Tribunal's appeals court in Baghdad confirms the sentence of death against the former Iraqi President Saddam Hussein, after a month and a half of trial review.
output: イブはキング教授の研究チームによって開発される２番目のＡＩコンピューターである。
explanation: The above sentence is not correctly translated from English to Japanese as none of the words match the translation.; input: He said: "Except for New Orleans after Katrina, it's basically the largest drop for a U.S. city in history.
output: 国際通貨基金（IMF）と欧州連合（EU）は、ギリシャに1100億ユーロの支援パッケージ、アイルランドに850億ユーロの救済パッケージを引き渡す契約に署名した。
explanation: The above sentence is not correctly translated from English to Japanese as none of the words match the translation.
Task: In this task, you are given reviews written about the books in Bengali. You are expected to classify the sentiment of the reviews into two classes: positive or negative.
Categories: Sentiment Analysis
Domains: Books; Reviews -> Books

Positive examples:
input: অসাধারণ একটি বই, লজিকাল স্কিল ডেভেলপমেন্ট এর জন্যে অতুলনীয়..
output: positive
explanation: Here the reviewer seems to love the logical development of the storyline in the book, so this should be classified as positive.; input: একদম ছোট ছোট লেখা, পড়তেই কষ্ট হয়। আর বইটি দেখতে অনেকটা খাতার মত, একদম বেডপ।.
output: negative
explanation: Here the reviewer expresses less readability of the book and so this should be classified as negative.

Negative examples:
input: অসাধারণ একটি বই, লজিকাল স্কিল ডেভেলপমেন্ট এর জন্যে অতুলনীয়..
output: awesome
explanation: You are expected to return "positive" or "negative". This should be classified as positive as the reviewer seems to love the logical development of the storyline in the book.; input: একদম ছোট ছোট লেখা, পড়তেই কষ্ট হয়। আর বইটি দেখতে অনেকটা খাতার মত, একদম বেডপ।
output: bad
explanation: You are expected to return "positive" or "negative". This should be classified as negative as the the reviewer expresses less readability of the book.; input: অসাধারণ একটি বই, লজিকাল স্কিল ডেভেলপমেন্ট এর জন্যে অতুলনীয়..
output: negative
explanation: Here the reviewer seems to love the logical development of the storyline in the book, so this should be classified as positive instead of negative.
Task: You are given a sentence in Galician. Your job is to translate the Galician sentence into Spanish.
Categories: Translation
Domains: TED Talks; Captions -> Video Captions

Positive examples:
input: Grazas.
output: Gracias.
explanation: The Galician sentence is correctly translated into Spanish, because the meaning is preserved.; input: Pero aquí falta algo, porque non creo que xente como Max Vision deba estar no cárcere.
output: Ahora, aquí nos falta algo, porque no creo que gente como Max Vision deba estar en la cárcel.
explanation: The Galician sentence is correctly translated into Spanish, because the meaning is preserved.; input: Para ver — un momento, podémonos mergullar! — aqui mesmo — baixo o océano, ver o que as baleas ven.
output: Para ver — - esperen un momento, podemos zambullirnos aquí mismo, ja — bajo el mar, ver lo que las ballenas ven.
explanation: The Galician sentence is correctly translated into Spanish, because the meaning is preserved.

Negative examples:
input: Se a obesidade non é máis que un representante das enfermidades metabólicas, en que axuda castigar ao representante?
output: Y sé que esto es aterrador, lo sé. Pero sé también, y esta experiencia nos muestra, que contamos con la tecnología y la capacidad para ganar la batalla para vencer esto y sacar ventaja a los virus.
explanation: The Galician sentence is not correctly translated into Spanish, because the meaning is different.; input: O primeiro emprego que tivo no negocio dos safaris era reparar os camións.
output: El primer trabajo que tuvo en el negocio del safari fue arreglar los camiones de safari.
explanation: The Galician sentence is not correctly translated into Spanish, because the meaning is different.; input: E sei que iso é aterrador, enténdoo, pero tamén sei, e esta experiencia amósanolo, que temos a tecnoloxía e temos a capacidade para gañar esta batalla, para gañar e ter vantaxe sobre os virus.
output: Si la obesidad no es más que una cara falsa de la enfermedad metabólica, ¿Qué bien hacemos al castigar esa cara falsa?
explanation: The Galician sentence is not correctly translated into Spanish, because the meaning is different.
Task: In this task, given a sentence in the Hindi language, your task is to convert it into the English language.
Categories: Translation
Domains: News

Positive examples:
input: राउंडअबाउट के लिए ट्विनिंग को चिह्नित करने वाला एक चिह्न योजनाबद्ध है।
output: A sign marking the twinning is planned for the roundabout.
explanation: The above sentence is correctly translated from Hindi to English; input: आश्चर्यजनक रूप से, अमेरिका के पास इस शानदार पक्षी और सुंदर जंगलों, जिसमें वह रहता है के भविष्य की रक्षा करने का एक और मौका हो सकता है।"
output: Amazingly, America may have another chance to protect the future of this spectacular bird and the awesome forests in which it lives."
explanation: The above sentence is correctly translated from Hindi to English; input: मि बेज़ले हाल के हफ्तों में अफगानिस्तान के बजाय इराक पर सैन्य ध्यान केंद्रित करने के कारण सरकार के लिए महत्वपूर्ण हैं, जो वह कहते हैं कि आतंकवादी खतरे का स्रोत है।
output: Mr Beazley has been critical of the government in recent weeks because of its military focus on Iraq rather than Afghanistan, which he says is the source of the terrorist threat.
explanation: The above sentence is correctly translated from Hindi to English

Negative examples:
input: हमास के नेताओं और तुर्की के विदेश मंत्री अब्दुल्ला गुल के बीच वार्ता हुई है।
output: The protesters consider that these caricatures insulted their prophet, and thus, they contend, their religion and themselves.
explanation: The above sentence is not correctly translated from Hindi to English as none of the words match the translation.; input: मोजांबिक के राष्ट्रीय चुनाव आयोग के अध्यक्ष लियोपोल्डा दा कोस्टा ने कहा, "इस दौरान हमें कोई भी शिकायत नहीं मिली।"
output: This despite the posthumous video recording of one of the 7/7 bombers, Shehzad Tanweer who said his actions were provoked by British foreign policy and that attacks would continue until British soldiers were withdrawn from Iraq and Afghanistan.
explanation: The above sentence is not correctly translated from Hindi to English as none of the words match the translation.; input: अन्य संभावित उम्मीदवारों में 2004 के नामित सीनेटर जॉन केरी, उनके उपराष्ट्रपति के उम्मीदवार, पूर्व कैरोलिना सीनेटर जॉन एडवर्ड्स; न्यू मेक्सिको गवर्नर बिल रिचर्डसन; और डेलवेयरके सीनेटर जो बिडेन और कनेक्टिकट के क्रिस्टोफर डॉड शामिल हैं।
output: The rally began earlier this week after the news from Citigroup Inc. about managing profits during first two months of the year.
explanation: The above sentence is not correctly translated from Hindi to English as none of the words match the translation.
Task: Given a sentence in German, generate a new German sentence by performing small changes on the sentence. Here, make sure that the changes are semantically related and syntactically similar to the input. And the generated sentence should have high commonsense plausibility, that is to have reasonable probability of it being true.
Categories: Sentence Perturbation
Domains: Commonsense; Knowledge Base -> Wikidata

Positive examples:
input: Sie verwenden den Behälter, um Kohlenstoff zur Anlage zu transportieren.
output: Sie arrangieren den Behälter, um Wasser an die Anlage zu versenden.
explanation: This is a good example of a change in the input. The created sentence is semantically similar to the input as both are talking about giving water/carbon to a plant and the changes in the sentence follows the commonsense knowledge.; input: Eine Gemeinschaft kann Bomben gegen Bequemlichkeit handeln.
output: Eine Gemeinschaft kann Dienstleistungen für Lebensmittel versuchen.
explanation: The output sentence is semantically related to the input sentence as both are talking about communities and follows the commonsense. Hence, the answer is correct.

Negative examples:
input: Sie können mit einem Finger eine Kühlschranktür aufziehen.
output: Можете да използвате нокът за кипене на вода.
explanation: The output is semantically similar to the input but it does not follow the commonsense as we cannot use nails to boil the water.; input: Wenn Sie keine Fähigkeit hatten, würde es Sie per Scheck bezahlen wollen.
output: Du würdest Krieg führen, weil du dein Dogma richtig machst.
explanation: The output has the commonsense but it is not semantically related or similar to the input. Hence, the answer is incorrect.
Task: In this task, you are given a sentence. You are expected to recognize the name of gene or protein. Although there might be several correct answers, you need to write one of them.
Categories: Named Entity Recognition
Domains: Biology -> Bioinformatics

Positive examples:
input: Sox - 4 is important for very early B - cell differentiation , while TCF - 1 / LEF - 1 play a crucial role in early thymocyte development 
output: TCF - 1
explanation: The gene, TCF - 1 has been tagged as protein since it plays a crucial role in early thymocyte development.; input: The NF - kappaB / Rel family represents one signal transduction pathway induced during such activation .
output: NF - kappaB
explanation: NF - kappaB, protein transcription factor, should be tagged.

Negative examples:
input: Sox - 4 is important for very early B - cell differentiation , while TCF - 1 / LEF - 1 play a crucial role in early thymocyte development 
output: development
explanation: development does not refer to gene or protein, and hence should not be tagged.; input: The NF - kappaB / Rel family represents one signal transduction pathway induced during such activation .
output: signal
explanation: signal is not a protein or gene, and hence should not be tagged.
Task: A text is given in Tamil. Translate it from the Tamil language to the Urdu language. The translation must not omit or add information to the original sentence.
Categories: Translation
Domains: Sociology; News

Positive examples:
input: இந்தியா-இஸ்ரேல் வர்த்தக மாநாட்டில் பிரதமர் தெரிவித்த கருத்துகள் (ஜனவரி 15, 2018)
output: بھارت-اسرائیلی کامرس کانفرنس پر وزیراعظم تبصرے (15 جنوری، 2018)
explanation: Correct translation for given sentence. Input sentence means 'PM comments on the India-Israeli Commerce Conference (January 15, 2018)' which is the same as the output sentence.; input: மாவட்டங்களின் வளர்ச்சி வீதத்தை 3 முதல் 4 சதவீதம்வரை உயர்த்துவதற்கான செயல் திட்டம் அமைச்சர் திரு
output: پلاننگ پروگرام کے وزیر ضلعوں کی ترقی کی شرح کو بڑھانے کے لئے 3 سے 4 فی صد
explanation: Correct translation for given sentence. Input sentence means 'Minister of Planning Program to raise the growth rate of the districts 3 to 4 percent' which is the same as the output sentence.

Negative examples:
input: அரசுமுறைப் பயணத்தைத் தொடங்குவதற்கு முன்பு அவர் வெளியிட்ட செய்திக் குறிப்பு வருமாறு:
output: 32 ہے، جبکہ کامیاب ہونے والی لڑکیوں کا مجموعی فیصد 88
explanation: Incorrect translation for given sentence. Input sentence means 'The message he published before the kingdom of the kingdom is to come up:'' which is not the same as the output sentence meaning '32, while the overall percentage of successful girls 88'; input: மாணவியர் தேர்ச்சி விகிதம் 88
output: چین روانگی سے قبل وزیراعظم کا بیان
explanation: Incorrect translation for given sentence. Input sentence means 'Student mastery 88'' which is not the same as the output sentence meaning 'Prime Minister's statement before China departure'
Task: A text is given in Tamil. Translate it from the Tamil language to the Telugu language. The translation must not omit or add information to the original sentence.
Categories: Translation
Domains: Sociology; News

Positive examples:
input: ఆయ‌న తీసుకొన్న చొర‌వ‌ తో అగ‌ర్త‌లా లో ఒక విమానాశ్ర‌యాన్ని నిర్మించ‌డం జ‌రిగింది
output: ஒரு விமான நிலையம் அகர்தலாவில் அவரது முன்முயற்சியுடன் கட்டப்பட்டது
explanation: Correct translation for given sentence. Input sentence means 'A airport was built in Agartala with his taken initiative' which is the same as the output sentence.; input: ప్ర‌భుత్వ కార్య‌క్ర‌మాల‌లో అనేక కార్య‌క్ర‌మాలు స‌ర్కారు మ‌ద్దతు పైన ఆధార‌ప‌డి ఉన్న‌ప్ప‌టికీ, ‘డిజిట‌ల్ ఇండియా’ ప్ర‌జ‌ల ఆదరణ లభిస్తున్న కార‌ణంగా విజ‌య‌వంతం అవుతోంది
output: அரசாங்க திட்டங்களில் உள்ள பல திட்டங்கள் மேற்கூறிய ஆதரவின் அடிப்படையில், 'டிஜிட்டல் இந்தியா' மக்களின் வரவேற்பு காரணமாக வெற்றிகரமாக உள்ளது
explanation: Correct translation for given sentence. Input sentence means 'Although many programs in government programs are based on the above support, 'Digital India' is successful due to the reception of people' which is the same as the output sentence.

Negative examples:
input: ప్ర‌స్తుత ఎల్‌టిఎ లు 31
output: 2019 ஆம் ஆண்டை அடைந்த போது நாங்கள் வியப்பில் ஆழ்ந்தோம்
explanation: Incorrect translation for given sentence. Input sentence means 'Current ELTAs 31' which is the not same as the output sentence meaning 'We are surprised when we reach 2019'; input: 2019లోకి అడుగు పెట్టేస‌రికి నాకు ఆశ్చ‌ర్యం వేసింది
output: தற்போதைய நீண்டகால ஒப்பந்தங்கள் 31
explanation: Incorrect translation for given sentence. Input sentence means 'Surprised me to step into 2019' which is the  not same as the output sentence meaning 'Current long-term contracts 31'
Task: Translate from English to Hindi.
Categories: Translation
Domains: Narrative; Dialogue; Commonsense -> Concepts and Relations

Positive examples:
input: Go to the employment office.
output: रोजगार कार्यालय जाओ.
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.; input: My God, a job!
output: हे भगवान, नौकरी!
explanation: The translation is accurate.; input: Hey, what about us?
output: अरे, हमारे बारे में क्या?
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.

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.; input: Ricci?
output: धनी?
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.; input: Are you deaf? Come on
output: तुम बहरे हो क्या?
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'.