ceselder/lots-of-loras-task-definitions huggingface dataset:
Task: In this task, you are given a sentence from the Bible in Persian, and your task is to translate it into English.
Categories: Translation
Domains: World Religions; Books

Positive examples:
input: در ابتدا، خدا آسمانها و زمین را آفرید.
output: In the beginning God created the heaven and the earth.
explanation: This is a good example. The above sentence is correctly translated from Persian to English.; input: وزمین تهی و بایر بود و تاریکی بر روی لجه. و روح خدا سطح آبها را فرو گرفت.
output: 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.
explanation: This sentence is translated correctly.; input: و خدا گفت: «روشنایی بشود.» و روشنایی شد.
output: And God said, Let there be light: and there was light.
explanation: The above sentence is correctly translated from Persian to English.

Negative examples:
input: و خدا روشنایی را دید که نیکوست و خداروشنایی را از تاریکی جدا ساخت.
output: And God saw the light, and God divided the light from the darkness.
explanation: This translation is incomplete. Hence it's not acceptable.; input: و خداروشنایی را روز نامید و تاریکی را شب نامید. وشام بود و صبح بود، روزی اول.
output: And God called the light Night, and the darkness he called Day. And the evening and the morning were the first day.
explanation: This translation is incorrect.
Task: In this task, you are given the name of an Indian food dish. You need to return whether the dish is "non vegetarian" or "vegetarian". Do not answer with any words other than those two.
Categories: Misc.
Domains: Food
Reasoning: Commonsense Reasoning

Positive examples:
input: Balu shahi
output: vegetarian
explanation: Balu shahi is a vegetarian dish.; input: Pork Bharta
output: non vegetarian
explanation: Pork Bharta contains pork and is a non vegetarian dish.

Negative examples:
input: Malapua
explanation: Malapua is not a non vegetarian dish
output: non vegetarian; input: Kadhai Chicken
explanation: Kadhai Chicken is not a vegetarian dish
output: vegetarian
Task: In this task, you are given a sentence in English language and its corresponding French translation. Here, your job is to output "yes" if the translation is correct, otherwise output "no".
Categories: Text Matching
Domains: Miscellaneous

Positive examples:
input: English: What can I do? 
 French: Que puis je faire?
output: yes
explanation: English sentence is properly converted into French sentence.; input: English: What are some themes for your display? 
 French: Qu’êtes-vous prêts à faire pour favoriser l’avènement de ce nouveau contexte de travail ?
output: no
explanation: The correct translation of the input to French is "Quels sont quelques-uns des thèmes pour votre présentation?".

Negative examples:
input: English: What is the link between isotopes and hair? 
 French: Quel lien existe-t-il entre les isotopes et les cheveux?
output: Correct
explanation: The answer can only be yes or no.; input: English: What are some of your next steps for securing additional resources? 
 French: Quelles sont les prochaines étapes que vous prévoyez pour obtenir d'autres ressources ?
output: no
explanation: English sentence is properly converted to French sentence. So, the output should have been yes instead of no.
Task: In this task, an input sentence is given which can be in the English, Bengali, Filipino, Hindi, Indonesian(Bahasa variant), Japanese, Central Khmer, Lao, Malay, Burmese, Thai, Vietnamese or Chinese languages. There are a total of 13 languages. Your task is to identify the language of the input sentence. The input sentence can only be in any of the 13 languages provided.
Categories: Language Identification
Domains: News

Positive examples:
input: Kenneth Goldman is suing the United States Democratic political action committee Twenty-First Century Democrats (also 21st Century Democrats) and its former executive director Kelly Young.
output: English
explanation: Input sentence is in the English language.; input: ২০১০ সালের জাতিসংঘ জলবায়ু পরিবর্তন সম্মেলনের সন্ধি-স্থাপন এই সপ্তাহে জার্মানির বন শহরে অব্যাহত হয়েছে।
output: Bengali
explanation: Input sentence is in the Bengali language.; input: 'लाइव' देखने के लिए! मोबाइल टीवी चैनल, ग्राहकों को असीमित उपयोग के लिए या तो $2.99 प्रति सप्ताह शुल्क देना होगा, या पंद्रह मिनट तक चलने वाले एक-सत्र के लिए 99 सेंट का भुगतान करना होगा।
output: Hindi
explanation: Input sentence is in the Hindi language.

Negative examples:
input: Ang radyo sa Israel ay nakapuna na ito ay ang ikatlong Palestinong bata sa loob ng dalawang buwan na nahuli na nagtatangkang magpuslit ng mga pampasabog lampas ng tsekpoint na Israeli.
output: Cannot identify the language
explanation: Input sentence should be in one of the 13 languages which are English,Bengali,Filipino,Hindi,Bahasa Indonesia,Japanese,Khmer,Lao,Malay,Myanmar,Thai,Vietnamese or Chinese language. ; input: Kajian penduduk, yang dikeluarkan oleh Statistik New Zealand menajukkan Sejarah penyelamat di New Zealand, menekankan bahawa menjangkakan kehidupan lelaki yang lahir di New Zealand pada pertengahan tahun 1890 mungkin menjadi lima tahun tinggi tanpa impak dari perang duni, kerana 10% lelaki mati dalam perang.
output: English
explanation: Input sentence is in the Malay language not in English language.; input: ការបោះឆ្នោតត្រូវបានធ្វើឡើងនៅថ្ងៃសុក្រ បន្ទាប់ពីលោក ខេវិន រូត បានប្រជែងធ្វើជាប្រធានបក្សជាមួយអតីតប្រធានបក្សលោក គីម ប៊ីសស្លេ។
output: Lao
explanation: Input sentence is in the Khmer language not in Lao language.
Task: You will be given a context and a verb separated with a newline character, and you have to answer if the given verb is a negation or not. A verb is a negation if it is not going to exist, not happen, or has no effect. The output should be "Yes" if the verb is a negation and "No" otherwise.
Categories: Word Semantics
Domains: News

Positive examples:
input: Only the government of the United States can decide if it prefers this variant, continued the letter, which Castro read on a state television station broadcast. Gonzalez for months refused requests by Elian's Miami relatives to go to the United States to (claim) the boy.  
 Verb: claim
output: Yes
explanation: This is a good example. Gonzalez refused to "claim" the boy. So, the claim didn't happen and it's a negation.; input: In Washington today, the Federal Aviation Administration (released) air traffic control tapes from the night the TWA Flight eight hundred went down.  
 Verb: released
output: No
explanation: In this sentence, the releasing event happened in the past, and it's not a negation.; input: Nobody hurried her up. No one (held) her back.  
 Verb: held
output: Yes
explanation: In this example, No one held her back. So "held" didn't happened and it's a negation.

Negative examples:
input: WASHINGTON ( AP ) -- Preliminary DNA tests link a missing anti-abortion activist to a strand of hair found near where a sniper shot and killed a Buffalo, N.Y., doctor who (performed) abortions, a law enforcement official said Friday.  
 Verb: performed
output: Yes
explanation: In this sentence, the performing action happened in the past, and it's not a negation.; input: He insisted that the NGO law " will not change our position at all ". " We won't (refuse) foreign donations, nor will we register as a 'foreign agent', " he said.  
 Verb: refuse
output: No
explanation: In this sentence, "refuse" won't happen, so it's a negation.; input: Hungary has come home. We (are) back in the family, said Hungarian Foreign Minister Janos Martonyi.  
 Verb: are
output: Yes
explanation: In this example, they are back in the family. So "are" is happening now, and it's not a negation.
Task: You are given a paper review either in Spanish or English language. Based on the given review, evaluate the paper by classifying it to one of the five classes: (1) very negative, (2) negative, (3) neutral, (4) positive, and (5) very positive. Note that URLs in the text have been replaced with [Link].
Categories: Sentiment Analysis
Domains: Conference

Positive examples:
input: El artículo presenta un interesante desarrollo de un caso, como una propuesta más de metodología de inicio para la didáctica de la lógica de programación. Las conclusiones presentadas no tienen mucho fundamento en términos del logro del objetivo de inducir de esta manera el razonamiento lógico.
output: very positive
explanation: Based on the review text, we can see that paper evaluation is very positive.; input: Paper fácil de leer y bien escrito.  Está en la línea de los trabajos de INFONOR.  Sin embargo, no queda claro cómo aplica la 'Teoría de la relevancia', es demasiado escueto en este ámbito del artículo que a mi parecer es lo más importante. Por lo que no es posible dar una opinión certera sobre el trabajo.  Se sugiere expandir la sección 2.2, en lo referente a cómo los aspectos para determinar la relevancia son utilizados o mezclados para determinar si una 'news' es relevante o no.  La herramienta elaborada es interesante como también los elementos utilizados en su desarrollo.
output: neutral
explanation: Based on the review text, we can see that paper evaluation is neutral.; input: Unless there is a strong info sci and business IT community for the conference, and unless the paper addresses its shortcomings (which are significant) - it just doesn't measure up.
output: negative
explanation: Based on the review text, we can see that paper evaluation is negative because reviewer criticized paper via saying that it doesn't have significant contribution.

Negative examples:
input: Unless there is a strong info sci and business IT community for the conference, and unless the paper addresses its shortcomings (which are significant) - it just doesn't measure up.
output: positive
explanation: Based on the review text, we can see that review is negative. Hence, paper evaluation is negative, but given label is 'positive' which is wrong.; input: El artículo presenta un interesante desarrollo de un caso, como una propuesta más de metodología de inicio para la didáctica de la lógica de programación. Las conclusiones presentadas no tienen mucho fundamento en términos del logro del objetivo de inducir de esta manera el razonamiento lógico.
output: very negative
explanation: Based on the review text, we can see that review is positive. Hence, paper evaluation is positive, but given label is 'very negative' which is wrong.
Task: In this task, you will be presented with a question in Dutch language, and you have to write the part-of-speech tag for each word and punctuation in the question. Here is the list of part-of-speech tags used in this task: Adj: Adjective, Adv: Adverb, Art: Article, Conj: Conjunction, Int: Interjection, N: Noun, V: Verb, Num: Number, Misc: Miscellaneous, Pron: Pronoun, Prep: Preposition, Punc: Punctuation.
Categories: Pos Tagging
Domains: Miscellaneous

Positive examples:
input: 1968 : 1.
output: Num Punc Num Punc
explanation: Based on the given question, All of the POS tags are correct.; input: Misschien raken er wat kiezers overboord door de regularisatieprocedure van illegalen of de snel-Belgwet.
output: Adv V Adv Pron N Adv Prep Art N Prep N Conj Art N Punc
explanation: This is a good example. All of the POS tags are correct.; input: Toenmalig Tsjechisch bondscoach Dusan Uhrin was vol lof over Karel Poborsky.
output: Adj N N N N V Adj N Prep N N Punc
explanation: Based on the given question, All of the POS tags are correct.

Negative examples:
input: Ik gooi alle ramen open.
output: Pron N Pron N Adj Art
explanation: In this sentence, the hyphen is tagged as the article instead of punctuation, which is incorrect.; input: Liaanrozen hebben hele lange , slappe takken.
output: N Pron Adj Adj Punc Adj N Punc
explanation: In this sentence, hebben is tagged as Pronoun instead of Verb, which is incorrect.; input: Momenteel werken er reeds twaalf mensen bij Waterleau.
output: Adj V Adv Adv Num N Prep Adj
explanation: The input question should have 9 tags including punctuation but the output has 8 tags. Note that you have to write the part-of-speech tag for every word and symbol in the question.
Task: You are given a sentence in Persian. Your job is to translate the Farsi sentence into Galician.
Categories: Translation
Domains: TED Talks; Captions -> Video Captions

Positive examples:
input: وقتی به این جامعه های در حال توسعه می روید زنها رکن اصلی اجتماعشان هستند ولی هنوز این مردها هستند که خیابون ها رو در دست دارند.
output: Cando chegas a estas sociedades en desenrolo, as mulleres son os piares da súa comunidade, pero os homes seguen a ser os que controlan as rúas.
explanation: The Farsi sentence is correctly translated into Galician, because the meaning is preserved.; input: تنها سلاح من نوت بوک و دوربین لایکایم بود.
output: A miña única arma era o meu caderno e a miña Leica.
explanation: The Farsi sentence is correctly translated into Galician, because the meaning is preserved.; input: متشکرم.
output: Grazas.
explanation: The Farsi sentence is correctly translated into Galician, because the meaning is preserved.

Negative examples:
input: اگر یه روزی از اینجا هم بیرون برم ، همواره یک علامت بر روی نام منه.
output: (Risas) Venden gafas por internet.
explanation: The Farsi sentence is not correctly translated into Galician, because the meaning is different.; input: و همین طور برای سطح متوسط درآمد ، با درآمدی حدود ۸۰ِ۰۰۰ دلار ، همین اتفاق می افتد.
output: E o mesmo acontece no percentil 50, arredor dos 80,000 dólares.
explanation: The Farsi sentence is not correctly translated into Galician, because the meaning is different.; input: (خنده حضار) بصورت آنلاین عینک می فروشند.
output: Se algún día saio de aquí, sempre terei unha marca no meu nome.
explanation: The Farsi sentence is not correctly translated into Galician, because the meaning is different.
Task: Given a sentence in Tagalog language, translate the sentence to English language keeping the meaning of the original sentence intact.
Categories: Translation
Domains: Web

Positive examples:
input: Tagalog sentence: Si Roger Federer ang unang manlalaro na nanalo ng 20 Grand Slams
output: Roger Federer was the first player to win 20 Grand Slams
explanation: The output is an exact translation of the Tagalog sentence and its meaning remains the same.; input: Tagalog sentence: Ang tagagawa ng LED panggayak liwanag sa Guangdong China.
output: A manufacturer of LED flashing light at GuangDong China.
explanation: The output is the exact English translation of the input Tagalog text.; input: Tagalog sentence: 22:48 Sa makatuwid baga'y ang Dios na ipinanghihiganti ako. At pinangangayupapa sa akin ang mga bayan
output: 2:48 God who giveth me revenge, and bringest down people under me
explanation: The English translation exactly means the same as the input Tagalog sentence.

Negative examples:
input: Tagalog sentence: Hindi ako nagugutom ngunit gusto ko pa ring kumain
output: I'm not hungry but I don't want to eat.
explanation: The English translation changes the actual meaning of the tagalog sentence; output: Tagalog sentence: Tawagan mo ako sa umaga, papunta na ako
input: Call me in the morning, I'll be on my way
explanation: The English translation changes the tense from present tense to future tense.; input: Tagalog sentence: May sisingilin para sa isang tinanggihan na paulit-ulit na transaksyon sa debit card
output: There will not be any charge for a declined recurring debit card transaction
explanation: The English translation actually implies the exact opposite meaning of the input Tagalog sentence
Task: In this task, given 2 input sentences, you must classify the relation between them. If the second sentence has a similar meaning to that of the first sentence then the output is ' B_entails_A', if the second sentence has the opposite meaning to the first sentence then it is classified as ' B_contradicts_A'. If you cannot clearly ascertain agreement/disagreement between the two sentences, the label is ' B_neutral_A'.
Categories: Textual Entailment
Domains: Captions -> Video Captions; Captions -> Image Captions
Reasoning: Textual Entailment -> Deductive Reasoning

Positive examples:
input: sentence_A: man is wearing a hard hat and dancing. sentence_B: There is no man with a hard hat dancing.
output: B_contradicts_A
explanation: The sentence B has opposite meaning as sentence_B says, "No man with a hat", but sentence_A says, "A man is wearing a hat", so B is contradicting A.; input: sentence_A: A baby is crying. sentence_B: A man is exercising.
output: B_neutral_A
explanation: Sentence B says exercising but sentence A says crying, which are two different tasks and is not contradicting as they don't have the opposite meaning, so B_neutral_A.; input: sentence_A: A tiger is pacing around a cage. sentence_B: A tiger is walking around a cage
output: B_entails_A
explanation: Walking and pacing are synonyms, so B_entails_A is correct.

Negative examples:
input: sentence_A: There is no man playing an instrument. sentence_B: A man is playing an instrument.
output: B_neutral_A
explanation: B says man is playing an instrument, while A says no man is playing, so this is a contradiction not neutral.; input: sentence_A: A man is walking slowly across a rope bridge sentence_B: A boy is fearfully walking across a bridge
output: B_entails_A
explanation: Fearfully and walking slowly are different meanings and not same, they are not even opposite words, so this is B_Neutral_A, not B_entails_A.; input: sentence_A: A lady is mixing a meat mixture in a bowl sentence_B: The woman is stirring meat in a bowl
output: B_contradicts_A
explanation: Stirring meat and mixing meat are synonyms, so this is B_entails_A, not B_Contradicts_A.
Task: In this task, you will be given a passage consisting of set of facts. The task is to create a question of form 'Where is <person_name>?' that is answerable from exactly one of the given facts. Avoid creating questions that are unanswerable from all of the facts.
Categories: Question Generation
Domains: Commonsense -> Concepts and Relations -> Spatial Commonsense
Reasoning: Commonsense Reasoning -> Spatial Reasoning

Positive examples:
input: Passage: Mary moved to the bathroom. John went to the hallway.
output: Where is Mary?
explanation: 'Mary moved to the bathroom.' is a supporting fact from which we can create a question 'Where is Mary?'; input: Passage: Mary moved to the bathroom. John went to the hallway. Daniel went back to the hallway. Sandra moved to the garden.
output: Where is Daniel?
explanation: 'Daniel went back to the hallway.' is a supporting fact from which we can create a question 'Where is Daniel?'; input: Passage: Mary moved to the bathroom. John went to the hallway. Daniel went back to the hallway. Sandra moved to the garden. John moved to the office. Sandra journeyed to the bathroom.
output: Where is Daniel?
explanation: 'Daniel went back to the hallway.' is a supporting fact from which we can create a question 'Where is Daniel?'; input: Passage: Mary moved to the bathroom. John went to the hallway. Daniel went back to the hallway. Sandra moved to the garden. John moved to the office. Sandra journeyed to the bathroom. Mary moved to the hallway. Daniel travelled to the office.
output: Where is Daniel?
explanation: There are two facts mentioning Daniel; 'Daniel went back to the hallway.' and 'Daniel travelled to the office.'. First Daniel was in the hallway and then he went to the office. Therefore, we can create a question 'Where is Daniel?' to know where he is currently.; input: Passage: Mary moved to the bathroom. John went to the hallway. Daniel went back to the hallway. Sandra moved to the garden. John moved to the office. Sandra journeyed to the bathroom. Mary moved to the hallway. Daniel travelled to the office. John went back to the garden. John moved to the bedroom.
output: Where is Sandra?
explanation: There are two facts mentioning Sandra; 'Sandra moved to the garden.' and 'Sandra journeyed to the bathroom.'. First Sandra went to the garden and then she went to the bathroom. Therefore, we can create a question 'Where is Sandra?' to know where she is currently.

Negative examples:
input: Passage: Mary moved to the bathroom. John went to the hallway.
output: Which place is Mary at?
explanation: This is a bad question as it is not of the form 'Where is <person_name>?'. The correct question would be- 'Where is Mary?'; input: Passage: Mary moved to the bathroom. John went to the hallway.
output: Where is Jack?
explanation: Though the question is of form 'Where is <person_name>?', this is a bad example because the question is not answerable from any facts provided. Question must refer to the name of the person that appears in the facts. That way, the question would be answerable. In this case, there are two questions possible; 'Where is Mary?' and 'Where is John?'.
Task: You will be given two sentences. One of them is created by paraphrasing the original one, with changes on an aspect, or using synonyms. Your task is to decide what is the difference between two sentences. Types of change are explained below:
 Tense: The verbs in the sentence are changed in tense.
Number: Plural nouns, verbs and pronouns are changed into single ones or the other way around.
Voice: If the verbs are in active voice, they're changed to passive or the other way around.
Adverb: The paraphrase has one adverb or more than the original sentence.
Gender: The paraphrase differs from the original sentence in the gender of the names and pronouns.
Synonym: Some words or phrases of the original sentence are replaced with synonym words or phrases. Changes in the names of people are also considered a synonym change. Classify your answers into Tense, Number, Voice, Adverb, Gender, and Synonym.
Categories: Text Matching
Domains: Dialogue; Narrative
Reasoning: Commonsense Reasoning

Positive examples:
input: original sentence: Lily spoke to Donna , breaking her silence . paraphrase: Lily is speaking to Donna , breaking her silence .
output: Tense
explanation: The verbs in this example are changed from past tense to present tense.; input: original sentence: I'm sure that my map will show this building ; it is very good . paraphrase: I'm sure that my maps will show these buildings ; they are very good .
output: Number
explanation: In this example, map and building and their pronouns has been changed. So, the output should be Number.; input: original sentence: Jim signaled the barman and gestured toward his bathroom key . paraphrase: Jim dreamily signaled the barman and vaguely gestured toward his bathroom key .
output: Adverb
explanation: In this example the adverbs "vaguely" and "dreamily" are added to the original sentence.

Negative examples:
input: original sentence: The dog chased the cat , which ran up a tree . It waited at the bottom . paraphrase: The dog is chasing the cat , which is running up a tree . It is waiting at the bottom .
output: Voice
explanation: The change in the original sentence is to tense, as the past tense verbs are changed to present tense ones. "Voice" is not a correct answer here.; input: original sentence: John was doing research in the library when he heard a man humming and whistling . He was very annoyed . paraphrase: John and Steve were doing research in the library when they heard men humming and whistling . They were very annoyed .
output: Number is changed.
explanation: You should only output the title of the change, and nothing more.