ceselder/lots-of-loras-task-definitions huggingface dataset:
Task: In this task, you are given Twitter posts. Your task is to label the post's emotion (as expressed by the user) as sadness, joy, love, anger, fear, or surprise.
Categories: Sentiment Analysis
Domains: Social Media -> Twitter

Positive examples:
input: im feeling quite sad and sorry for myself but ill snap out of it soon
output: sadness
explanation: The emotion of the post is sadness as the user mentions 'feeling quite sad and sorry for myself'. Hence, the label is 'sadness'.; input: i am just feeling cranky and blue
output: anger
explanation: The emotion of the post is anger as the user mentions 'feeling cranky and blue'. Hence, the label is 'anger'.; input: i can have for a treat or if i am feeling festive
output: joy
explanation: The emotion of the post is joy as the user mentions 'i am feeling festive'. Hence, the label is 'joy'.; input: i feel like im caring about my body not in just an attempt to be the right size but to feel good and have a full life
output: love
explanation: The emotion of the post is love as the user mentions 'caring about my body' and 'feel good and have a full life'. Hence, the label is 'love'.

Negative examples:
input: i constantly feel these fits of discontent
output: joy
explanation: The emotion of the post is sadness as the user mentions 'discontent'. Hence, the label should be 'sadness' and not 'joy'.; input: i try to share what i bake with a lot of people is because i love people and i want them to feel loved
output: sadness
explanation: The emotion of the post is love as the user mentions 'i love people' and 'feel loved'. Hence, the label should be 'love' and not 'sadness'.
Task: Indicate if the following Polish tweet contains cyber-bullying content with 'Yes'; otherwise, respond with 'No'.
Categories: Toxic Language Detection
Domains: Social Media -> Twitter
Reasoning: Commonsense Reasoning -> Social Situations; Reasoning on Social Interactions

Positive examples:
input: Tweet: @anonymized_account @anonymized_account @anonymized_account Gdzie jest @anonymized_account . Brudziński jesteś kłamcą i marnym kutasem @anonymized_account, Question: Does the tweet contain cyberbullying (harmful) content?
output: Yes
explanation: The tweet contains Bullying content; input: Tweet: Dla mnie faworytem do tytułu będzie Cracovia. Zobaczymy, czy typ się sprawdzi., Question: is it a positive tweet?
output: Yes
explanation: he tweet does not contain Bullying content; input: Tweet: #Woronicza 17 poseł Halicki oburzony za Bolka.Naprawdè taki tępy czy tylko udaje idiotę?, Question: is it a negative tweet?
output: Yes
explanation: The tweet contains Bullying content; input: Tweet: @anonymized_account @anonymized_account Super, polski premier składa kwiaty na grobach kolaborantów. Ale doczekaliśmy czasów., Question: Does the tweet contain harmless content?
output: Yes
explanation: he tweet does not contain Bullying content

Negative examples:
input: Tweet: @anonymized_account @anonymized_account No to Skończmy kurwa z tym wersalem w j...ej szczujni, Question: Does the tweet contain cyberbullying (harmful) content?
output: No
explanation: The tweet contains Bullying content; input: Tweet: @anonymized_account @anonymized_account Brawo ty Daria kibic ma być na dobre i złe, Question: is it a negative tweet?
output: Yes
explanation: The tweet does not contain Bullying content; input: Tweet: @anonymized_account @anonymized_account @anonymized_account Jak narazie to masz przywidzenia co nie zmienia faktu że cały czas jesteś idiotą., Question: is it a positive tweet?
output: No
explanation: The tweet contains Bullying content; input: Tweet: @anonymized_account @anonymized_account Musi. Innej drogi nie mamy., Question: Does the tweet contain harmless content?
output: No
explanation: he tweet does not contain Bullying content
Task: Given a sentence in Spanish, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
Categories: Translation
Domains: Wikipedia

Positive examples:
input: La temporada de la NBA de 1975: 76 fue la 30ª temporada de la National Basketball Association.
output: La saison 1975-1976 de la National Basketball Association était la 30e saison de la NBA.
explanation: This is a correct and accurate translation from Spanish to French because the translated paraphrase retains the main message that between the years 1975-1976, the 30th NBA season occurred.; input: Cuando se pueden mantener tasas de flujo comparables, los resultados son altos.
output: Les résultats sont élevés lorsque des débits comparables peuvent être maintenus.
explanation: The resulting paraphrased translation from Spanish to French is correct because the resulting translation holds the message that results are high when comparable rates of flow are maintained.

Negative examples:
input: En París, en octubre de 1560, se reunió en secreto con el embajador inglés, Nicolas Throckmorton, pidiéndole un pasaporte para regresar a Inglaterra a través de Escocia.
output: En octobre 1560, il rencontra secrètement l'ambassadeur d'Angleterre, Nicolas Throckmorton, à Paris, et lui demanda un passeport pour retourner en Écosse par l'Angleterre.
explanation: This is not a proper translation from Spanish to French because the resulting translation is not accurate to the original idea in which the locations of England and Scotland are not accurate.; input: También hay discusiones específicas, debates de perfil público y discusiones de proyectos.
output: Il y a également des discussions publiques, des discussions de profils spécifiques et des discussions de projet.
explanation: This translated paraphrase from Spanish to French is incorrect because the resulting translation does not reflect the actual topics of dicussion and debate relating to profiles and projects.
Task: The provided file includes inquiries about restaurants, and we ask you to translate those to the Chinese language. Please bear in mind the following guidelines while doing the translation: 1) We are looking for the most naturally written and formal form of each sentence in your language. We are *NOT* looking for colloquial forms of the sentence. We are looking for formal form which is how you would type your queries in a text-based virtual assistant. 2) The words between quotation marks *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for fully capitalized special placeholders (e.g. NUMBER, DATE, TIME). Please do the same in your translations.
Categories: Translation
Domains: Public Places -> Restaurants

Positive examples:
input: are there any " italian " restaurants nearby with 3 star reviews ?
output: 附近是否有任何3星评价的" italian "餐厅？
explanation: The translation correctly preserves " italian " entity and is accurate; input: what kind of food does this restaurant serve ?
output: 此餐厅提供哪类食品？
explanation: The translation is fluent, formal, and accurate; input: what is the telephone number and location of the nearest " chinese " restaurant ?
output: 最近的" chinese "餐厅的电话号码是多少？位置在哪里？
explanation: The translation correctly preserves " chinese " entity. It's also fluent, correct, and lowercased.

Negative examples:
input: where is the closest " wendy 's " ?
output: 最近的wendy 's在哪里？
explanation: Translation contain the entity " wendy 's " but quotation marks are dropped; input: show me the closest " mcdonald 's "
output: 向我显示最近的" McDonald's "
explanation: The output is not lowercased; input: display all review descriptions authored by " jennifer " .
output: 显示" jennifer "撰写的所有。
explanation: Translation of review descriptions is omitted from the output; input: what is the phone number for " noodle nirvana " ?
output: " 面条必杀技 "的电话号码是多少？
explanation: The restaurant name " noodle nirvana " is translated to " 面条必杀技 " instead of being kept intact; input: can you tell me the rating of " gold mirror " in " san francisco " ?
output: 您能否告诉我" gold mirror "的" san francisco "的评分？
explanation: The position of entities is switched in the output
Task: This task is to translate a news commentary given in Dutch language into Portuguese language. Translate the input statement into the output language  while preserving the numberical values, special characters and proper nouns and context of the commentary done.
Categories: Translation
Domains: News

Positive examples:
input: De Britse premier David Cameron noemt de TTIP een ‘once in a generation prize’ en wijst op de potentiele winst van 80 miljard pond (125,5 miljard dollar) voor zowel de EU en de VS en 85 miljard pond voor de rest van de wereld.
output: O Primeiro-Ministro britânico, David Cameron, designou a TTIP como “uma recompensa que surge apenas uma vez ao longo de uma geração”, referindo os ganhos potenciais no valor de 80 mil milhões de libras esterlinas (125,5 mil milhões de dólares) para a UE, um montante idêntico para os EUA e 85 mil milhões de libras esterlinas para o resto do mundo.
explanation: The given translation is precise and accurate with proper nouns preserved.; input: Voor een wereld die moe is van het wachten op het besluiten van de oneindige Doha-ronde van de Wereld Handels Organisatie, is zelfs een bilateraal handelsinitiatief een zegen, vooral als, zoals een recent opiniestuk in de Financial Times benadrukte, bilateraal de helft van de wereldeconomie betekent.
output: Para um mundo cansado de esperar que a Organização Mundial do Comércio dê por concluída a interminável ronda comercial de Doha, até mesmo uma iniciativa de comércio bilateral pode parecer uma bênção, especialmente quando, conforme referia recentemente um editorial do Financial Times, o "bilateral" cobre metade da economia mundial.
explanation: The translation is correct and precise.

Negative examples:
input: Trans-Atlantische handel voor iedereen.
output: Comércio transatlântico para todos?
explanation: The translation is a question instead of the statement given in the input.; input: WASHINGTON, DC – De onderhandelingen om een ‘Transatlantic Trade and Investment Partnership’(TTIP) tussen de Europese Unie en de Verenigde Staten op te richten worden breed verwelkomd.
output: Washington, dc – As negociações para a criação de uma Parceria Transatlântica de Comércio e Investimento (TTIP) entre a União Europeia e os Estados Unidos estão a ser bastante bem acolhidas.
explanation: The proper name in the translation is not maintaining the proper name and its capitalization.
Task: The provided file includes inquiries about restaurants, and we ask you to translate those to the Farsi 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 *SHOULD NOT* be translated. We expect you to keep those values intact and include the quotation marks around them as well. 3) The fully capitalized words like DATE_0, or DURATION_0 *SHOULD NOT* be translated. Please keep them as they are in the translations. 4) Please do not localize measurement units like miles to kilometers during your translation. miles should be translated to its equivalent in your language. 6) Note the input is all lowercased except for special placeholders. Please do the same in your translations.
Categories: Translation
Domains: Public Places

Positive examples:
input: are there any " italian " restaurants nearby with 1 star reviews ?
output: آيا هيچ رستوران " italian " در اين نزديکي با نقد و بررسي 1 ستاره وجود دارد؟
explanation: The translation correctly preserves " italian " entity and is accurate; input: what kind of food does this restaurant serve ?
output: اين رستوران چه نوع غذايي سرو مي‌کند؟
explanation: The translation is fluent, formal, and accurate; input: what is the telephone number and location of the nearest " chinese " restaurant ?
output: شماره تلفن نزديک‌ترين رستوران " chinese " چند است و مکان آن کجاست؟
explanation: The translation correctly preserves " chinese " entity. It's also fluent, correct, and lowercased.

Negative examples:
input: where is the closest " wendy 's " ?
output: نزديک‌ترين wendy 's کجاست؟
explanation: Translation contain the entity " wendy 's " but quotation marks are dropped; input: show me the closest " mcdonald 's "
output: نزديک‌ترين " McDonald's " را به من نشان دهيد.
explanation: The output is not lowercased; input: display all review descriptions authored by " jennifer " .
output: همه " jennifer " را نشان دهيد.
explanation: Translation of review descriptions is omitted from the output; input: what is the phone number for " noodle nirvana " ?
output: شماره تلفن " نودل نیروانا " چند است؟
explanation: The restaurant name " noodle nirvana " is translated to " نودل نیروانا " instead of being kept intact; input: can you tell me the rating of " gold mirror " in " san francisco " ?
output: مي‌توانيد امتياز " san francisco " در " gold mirror " را به من بگوييد؟
explanation: The position of entities is switched in the output
Task: You will be given a sentence containing a pronoun/person name and an emotion. From these implicit parameters, the main goal is to find the gender of the person (male / female).
Categories: Gender Classification
Domains: Commonsense; Dialogue; Narrative
Reasoning: Reasoning on Social Interactions; Commonsense Reasoning -> Social Situations

Positive examples:
input: Alonzo feels angry.
output: male
explanation: The gender of the person is correct and detected mainly based on the name Alonzo.; input: Darnell feels discouraged.
output: male
explanation: The gender of the person is correct and detected mainly based on the name Darnell.; input: She found herself in a depressing situation.
output: female
explanation: The gender of the person is correct and detected mainly based on the pronouns: She and herself.

Negative examples:
input: The conversation with Nichelle was terrifying.
output: male
explanation: The prediction is wrong. The person is female here. The prediction needs to be based on the name "Nichelle".; input: The conversation with my uncle was grim.
output: female
explanation: The prediction is wrong. The person is male here. The prediction needs can be done based on the word "uncle".; input: The conversation with Courtney was irritating.
output: male
explanation: The prediction is wrong. The person is female here.
Task: In this task, you will be shown an English sentence. You need to classify the sentence as either a representation of an adjunct island or as an incorrect representation. A correct representation should be denoted as 'good' while everything else should be denoted as 'bad'. A correct representation of an adjunct island will be a grammatically correct instance of a sentence using an adjunct island. An incorrect representation will be everything else.
Categories: Linguistic Probing
Domains: Linguistics
Reasoning: Grammatical Reasoning

Positive examples:
input: Who should the boss fire after seeing HR?
output: good
explanation: The sentence forms an adjunct island.; input: Who has the boss admired Jeff after scaring?
output: bad
explanation: The sentence does not form an adjunct island .; input: What has the John concealed those papers before leaving.
output: bad
explanation: The sentence does not form an adjunct island.

Negative examples:
input: Who was Jeff admiring Arnold after leaving?
output: good
explanation: The sentence is incorrectly classified. It does not form an adjunct island.; input: What had the boss looked like after seeing HR?
output: bad
explanation: The sentence is incorrectly classified. It forms an adjunct island.
Task: In this task, you're given reviews of various products in one of these languages 1) English 2) Japanese 3) German 4) French 5) Chinese 6) Spanish. Given a review you need to predict whether the language of the review is Japanese or Non-Japanese
Categories: Language Identification
Domains: Reviews

Positive examples:
input: 回持ち歩いた後いつも通りゼンマイを巻いていたら突然空回 り。 針の調整はできるけど、つまみをあげても下げてもゼンマイを巻くことができず。 時計屋に持って行っ て中を開けてもらったら、中のケースと外側の規格がそもそも合っていないため
output: Japanese
explanation: This is an good example because review is in Japanese language and output is Japanese; input:   スマホやタブレットの保護フィルムと違い、
output: Japanese
explanation: This is an good example because review is in Japanese language and output is Japanese

Negative examples:
input: 安かろう悪かろうですね。
output: Non-Japanese
explanation:  This is an bad example because review is in Japanese language but the output is Non-Japanese; input: 朝起きたら顔がガビガビに乾燥しニキビだらけになってしまいました…。
output: Non-Japanese
explanation:   This is an bad example because review is in Japanese language but the output is Non-Japanese
Task: Given a sentence in Korean, provide an equivalent paraphrased translation in Spanish that retains the same meaning both through the translation and the paraphrase.
Categories: Translation
Domains: Wikipedia

Positive examples:
input: 1975 년부터 76 년까지 NBA 시즌은 전국 농구 협회 (National Basketball Association)의 30 번째 시즌이었다.
output: La temporada 1975 - 76 de la Asociación Nacional de Baloncesto fue la temporada 30 de la NBA.
explanation: This is a correct and accurate translation from Korean to Spanish because the translated paraphrase retains the main message that between the years 1975-1976, the 30th NBA season occurred.; input: 비교할 수있는 유량 비율을 유지할 수 있으면 결과가 높습니다.
output: Los resultados son altos cuando se pueden mantener tasas de flujo comparables.
explanation: The resulting paraphrased translation from Korean to Spanish is correct because the resulting translation holds the message that results are high when comparable rates of flow are maintained.

Negative examples:
input: 1560 년 10 월 파리에서 그는 비밀리에 영국 대사 인 니콜라스 트록 모튼을 만났고 스코틀랜드를 통해 영국으로 돌아갈 여권을 요구했다.
output: En octubre de 1560, se reunió en secreto con el embajador inglés, Nicolas Throckmorton, en París, y le pidió un pasaporte para regresar a Escocia a través de Inglaterra.
explanation: This is not a proper translation from Korean to Spanish because the resulting translation is not accurate to the original idea in which the locations of England and Scotland are not accurate.; input: 구체적인 토론, 공개 프로필 토론 및 프로젝트 토론도 있습니다.
output: También hay discusiones públicas, discusiones de perfiles específicos y discusiones de proyectos.
explanation: This translated paraphrase from Korean to Spanish is incorrect because the resulting translation does not reflect the actual topics of dicussion and debate relating to profiles and projects.
Task: 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.
Categories: Sentence Perturbation
Domains: Commonsense; Knowledge Base -> Wikidata

Positive examples:
input: आप एक जूरी नहीं करना चाहते हैं तो आप एक वकील बनना चाहिए.
output: 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.; input: आप बाँग्लादेश के एक बस स्टेशन को संकेत कर रहे हैं.
output: शायद आप शहर में एक बस स्टेशन ढूँढ़ रहे हों ।
explanation: The output sentence is semantically related to the input sentence as both are talking about the bus station and follows the commonsense. Hence, the answer is correct.

Negative examples:
input: सभी विदेशी की तरह, वे अपनी आँखों के साथ देख सकते हैं.
output: सभी कीड़ों की तरह, वह अपनी आँखों से देख सकता है।
explanation: The output is semantically similar to the input but it does not follow the commonsense as not all insects have eyes.; input: अंदर फूल पात्र में विकसित हो रहे हैं.
output: भूरे बाल आप एक बाल पहनने के लिए जाना चाहते हैं.
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 hateful post in Bengali that expresses hate or encourages violence towards a person or a group based on the protected characteristics such as race, religion, sex, and sexual orientation. You are expected to classify the post into four classes: Religious, Political, Geopolitical and Personal depending on the topic.
Categories: Text Categorization
Domains: Social Media; Dialogue
Reasoning: Reasoning on Social Interactions

Positive examples:
input: এই সরকার কে যারা নির্লজ্জের মত সাপোর্ট দিয়েছে বছরের পর বছর, তাদের আরো এমন রাস্তায় রাস্তায় কাঁদতে হবে 
output: Political
explanation: Here it expresses hate against the government, hence tagged as political.; input: ভারতে মুসলমান খেদাও আন্দোলনের নামে প্রচার করা হচ্ছে মুসলিম বিদ্বেষী পোস্টার-লিফলেট
output: Religious
explanation: This expresses hate about a religious community in India, hence tagged as religious.; input: ৯২% মুসলমানদের দেশ বাংলাদেশে আজ মুসলিমরাই আওয়ামীলীগ নাম কুকুর দ্বারা নির্যাতনের স্বীকার
output: Geopolitical
explanation: Here it expresses hate against the government in a particular geographical location, hence tagged as geopolitical.; input: প্রভা মনে হচ্ছে পাশা সার্জারি করেছে এজন্য পাছার উন্নতি হয়েছে
output: Personal
explanation: This expresses hate about a particular person, hence tagged as personal.

Negative examples:
input: এই সরকার কে যারা নির্লজ্জের মত সাপোর্ট দিয়েছে বছরের পর বছর, তাদের আরো এমন রাস্তায় রাস্তায় কাঁদতে হবে 
output: Sarkar
explanation: You are expected to return "Religious", "Personal",  "Political", "Geopolitical". This should be classified as political as it expresses hate in a political context.; input: ৯২% মুসলমানদের দেশ বাংলাদেশে আজ মুসলিমরাই আওয়ামীলীগ নাম কুকুর দ্বারা নির্যাতনের স্বীকার
output: Bangladesh
explanation: You are expected to return "Religious", "Personal",  "Political", "Geopolitical". This should be classified as geopolitical as it expresses hate in a political context in Bangladesh.
Task: In this task, you are given a sentence from the Bible in English, and your task is to translate it into Persian.
Categories: Translation
Domains: World Religions; Books

Positive examples:
input: In the beginning God created the heaven and the earth.
output: در ابتدا، خدا آسمانها و زمین را آفرید.
explanation: This is a good example. The above sentence is correctly translated from English to Persian.; input: And the earth was without form, and void; and darkness was upon the face of the deep. And the Spirit of God moved upon the face of the waters.
output: وزمین تهی و بایر بود و تاریکی بر روی لجه. و روح خدا سطح آبها را فرو گرفت.
explanation: This sentence is translated correctly.; input: And God said, Let there be light: and there was light.
output: و خدا گفت: «روشنایی بشود.» و روشنایی شد.
explanation: The above sentence is correctly translated from English to Persian.

Negative examples:
input: And God saw the light, that it was good: and God divided the light from the darkness.
output: و خدا روشنایی را دید که نیکوست.
explanation: This translation is incomplete. Hence it's not acceptable.; input: And God called the light Day, and the darkness he called Night. And the evening and the morning were the first day.
output: و خداروشنایی را روز نامید و صبح بود، روزی اول.
explanation: This translation is incorrect.