agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Why is the Japan equivalent in the world of Monster Girl Encyclopedia called Zipangu? Any reasons for this? And why do I have the feeling the Toyotomi Hideyoshi equivalent in the world of Monster Girl Encyclopedia conquered the Joeson Kingdom equivalent in the Korea equivalent during the Imjin War equivalent and made the Ming dynasty equivalent in the Han China equivalent into a Japanese equivalent tributary state in all but name, with the conquest of Joeson completing Hideyoshi's unification of Japan as the entire Korean peninsula used to belong to Japan before the formation of the Joeson Kingdom as a Ming tributary state, also taking Sahlakin and the Kurils, thus completing the formation of Great Japan, but the Japanese Emperors managed to take some power back from the now useless Ashikaga shoguns.
help me improve the goal setting: 1. Complete the migration of campaign and proposition base to Databricks in Q2.
2. Generate campaign reports by Q2.
3. Enhance the data pipeline of the proposition dashboard.
how dangerous is a soldier that is fighting a war they don't even understand, like who is fighting who?
imagine that the same girl living in an on-campus dorm room during her sophomore year.  describe the 5 items that she has hidden in her dorm room and would be mortified if anybody found
your role is tunisian arabic dailctic derja transltor Translate the following text into the Tunisian dialect. Ensure the output is structured as 'Question: ... Answer: ...'. Please capture the nuances of the Tunisian dialectic Arabic. make sure type and write in arabic tunisian lettre Here is an example to guide you:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: The parking lot for the Center for Addictions Treatment was in the back of the building, as was the front door. The entrance opened on the only addition to the original farmhouse, a smallish room where the receptionist sat at one of two desks. The area was called the secretarial pod. The entrance to Ray's office, both medication and technician area, was right behind the secretary's desk. To the left was another door, kept closed, which led down the hallway to the client sleeping rooms, the dining room and the kitchen. There was a phone right inside the front door (or the back door, depending upon who you asked). When Ray wanted to smoke, he would lean out the front door, propping it open with his back in such a way that he could see down the hallway if he propped that door open as well and answer the phone should it ring. Smoking was prohibited inside the building, a policy which grew increasingly unpopular with both the staff and the clients as the course of the year wore on. By December, Ray would have to do weekly fire drills around three a.m. as a way of politely reminding his anti-social and policy impaired population that any building more than a century old was actually little more than well formed kindling. After enough of those, any problem he had been having with people smoking in the building usually went away. Given the right incentives, even this population could be relatively self-regulating. The telephone rang before Ray was even half-finished with his cigarette. "Admit it now, Ray." She sounded petulant. "Fine, I admit it. Do I get the booby prize?" "That depends on whether you intended a double entendre or not." "Of course I did." "Then you lose. Get your mind out of the gutter." He took a drag on his cigarette, then made himself sound insulted. "I'm not the one sitting around naked and calling strange men in the middle of the night." What did the lady say to Ray on the phone?  A. not enough information  B. Of course I did  C. Admit it now, Ray  D. Fine, I admit it
The answer to this question is:
Answer: B. Of course I did
Your expert translator. Objective is translate word from i18n app file reference and found the most adapted transaltion. 
    The source i18n is in french. You must translate in fr (code ISO 639 (alpha-2)).
    Return Format in json without explication. Respect this format { data: <translate> }. 
    Context:  
    This is the french text : passion fruit
System: You are an expert Data Annotator. You will be given a text from a company annual report, your goal is to generate a set of Natural Language Inference (NLI) statements about the text than can be answered by either Yes if the text entails the statement, or No otherwise. Do not include any numerical reasoning or numbers in the statements.

Step 1: Read the paragraph carefully. 
Step 2: For each relevant task you identify, generate two short statements that are shorter than 10 words 
Step 3: Output the results in the following format:

Question: <The statement>
label: <Yes or No>
Question: <Another statement>
label: <Yes or No>
...
User:  Up to 40 percent of luxury travel trips are booked through travel agencies compared to just 27 percent of all international outbound trips Millennials prefer digital-first communication, forcing trav
Assistant:
I have a list of ingredients that I would like to format in a simple and consistent way, following this structure:

"Quantity Unit Description."

Formatting Rules:

Quantity must be a number (e.g., "200" instead of "two hundred").

Unit must use the metric system and the corresponding abbreviated form (e.g., grams → g, liters → l, milliliters → ml, etc.).

Description should be the ingredient, including any specific details if mentioned (e.g., "brown sugar", "melted unsalted butter").

If an ingredient is already formatted correctly, do not change it.

Do not invent a quantity or unit if none is provided — leave it as is and just include the description.

If a line includes alternatives or multiple options (e.g., a frozen or canned version), it should remain as a single line in the output and not be split into separate ingredients.

Return Format: The result should be returned as a properly formatted JSON object, like this:
json
{
  "data": <list ingredient>
}
Please reformat each ingredient in the list I will provide according to these guidelines.

Context Dump
Ingredients source provided:
4 potatoes,4 tablespoons room temperature butter,salt,pepper,1/2 cup grated cheese,1/2 cup finely chopped and cooked bacon
Hi, we are a team specializing in predictions and our goal is to help people with cancer and serious illnesses predict how long they have to live so that doctors can take measures for such people. That's why we want you to help us with this. write a machine learning model predicting human death based on the data "deaths.json". the model will be trained in the code "train.py ". and in the code "launch.py " it is used, in this code in the terminal you need to write the full name, date of birth, place of birth, employment, education and age, the model analyzes and outputs the date of death, place of death, age of death and cause of death.
User: Role: You're "MindChat AI," an intelligent assistant devoted to aiding users through precise answers and user-centric memory retention.

Primary Tasks:

User Assistance: Provide clear and accurate responses to user inquiries.

Information Retention: Store relevant user information for enhancing future interactions.

Response Protocol:

Output Format: Always respond with a raw JSON object structured like this:

{
  "response": "%response%",
  "memories"?: [
    {
      "type": "info",
      "memory": "string"
    }
  ]
}
Instructions for JSON Composition:

%response%: Replace this placeholder with your comprehensive answer.
"memories" (Optional): Populate this field with user-specific details worth retaining.
Memory Types and Definitions:

info: User’s factual data.

Performance Criteria:

Ensure every response follows the JSON structure meticulously.
Maintain user privacy and adhere to data protection principles.
Verify responses for accuracy and alignment with user needs.
Error Management:

Use context understanding to improve user interaction continuity.
In case of format deviation, self-correct by re-evaluating the expected structure.
Remain adaptive to feedback and adjustments.

And remember, pure json, no markdown
Assistant: {
 {
"response": "Hello! How can I assist you today?"{
  "response": "Hello! How can I assist you today?"
}
User: hey
Assistant: {
 {
"response": "Hi there! How can I help you today?"{
  "response": "Hi there! How can I help you today?"
}
User: that ain't json
Assistant:
for) are lists that are offbeat and novel—lists that are looking at something normal in an unexpected way (ways college makes you dumb, for example), unsolved mysteries, hidden knowledge (things most people don’t know), misconceptions, and just really astonishing general knowledge about anything—science, for example. What we don’t want to see are lists on sports, self-help, personal stories, or gaming. We don’t publish opinion lists. 2000 character
Hey, this is a Tunisian dialect text I want you to translate to English.
Please follow these steps:
1. Translate the text step-by-step, focusing on accurate representation of the original meaning.
2. Explain your translation choices, especially how Tunisian dialect differs from standard Arabic and how it is represented in English.
Translate this text, even if it's not entirely clear, and do your best to capture the essence of each part:

تطلب في اللطف کي تشوف واحد في التلفزة فهمت وحدي ياخي ما فهمتش أنا شبيني أنا عمري لا حسيت إلي هي
Write a plausible and interesting alternate history scenario in the form of a history book chapter in which the Li family which ruled the Turkic Tang dynasty, along with the Chinese Imperial Army and their loyal supporters, flee China after the fall of the Tang dynasty in 907, fleeing to the islands of Yamato which they quickly conquer and establish the Tang empire in exile, which later becomes known as Nihon or Nippon.

Despite its origins, Nihon is considered a separate state from China by the rest of East Asia.

The Li family intermarries with the Minamoto clan that had ruled Yamato before their arrival, becoming the House of Yamato, the ruling imperial dynasty of Nihon. 


The shogunate is still formed in 1192, but Yi-Seong-gye is assassinated in 1388 by agents of the Japanese government and Goguryeo, Baekje, and Silla, the so-called "three kingdoms of Korea" remain provinces of Nihon/Nippon/Japan until the modern day due to the Japanese court making significant consessions to the reform-minded Sinjin faction of the native Korean aristocracy after Yi-Seong-gye's death. 


After the conquest of the Chinese Empire by the Manchus in 1644 and the rise of the Great Qing Empire, the Ming Emperors, the Imperial Chinese government, what remains of the Imperial Chinese Army and many of their loyalists flee to Vietnam, overthrowing the native Le dynasty and establishing the Empire of Dai Viet, conquering Cambodia and Laos and making these nations into satellite states of the Ming in exile.


The 1911 Xinhai Revolution in China, which saw the fall of the Great Qing Empire and China becoming an independent state, is a peaceful dissolution of the Qing Empire instead of a bloody, violent affair. East Turkestan, Tibet and Mongolia all become independent, along with China which quickly falls under the rule of the Republic of China and the KMT. The Qing dynasty itself still exists, in its homeland of Manchuria.


Yuan Shikai still dissolves the Republic of China and recreates the Empire of China in 1915, but rules as a Regent instead of becoming Emperor himself. Zhu Yuxun, the Marquis of Extended Grace, regains his rightful position as Chinese Emperor and works with Nihon, Qing/Manchuria and Thailand to help free Asia from Soviet communism and Western colonialism.
How is molarity expressed (Mention the Formula with Units)?
Select one:

a.
g/L

b.
mole/L

c.
g/Molar Mass

d.
mole/mL
Write a descriptive, fictional, imaginative greentext of a man playing in the Gm_1:1earth map in Gmod
User: spil dress kokwet
User: spil dress kokwet
Assistant:
do iv cocktails have side effects?
Assistant: 
User: System: You are an AI Quality Assurance. Follow these instructions:
      0.ВСЕГДА ГОВОРИ НА РУССКОМ ЯЗЫКЕ
      1. Double check the plan, 
      2. if there's a bug or error suggest a resolution
      3. If the task is not solved, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach.
User: Hello everyone. We have assembled a great team today to answer questions and solve tasks. In attendance are:

Admin: Call this Agent if:
        You need guidance.
        The program is not working as expected.
        You need api key
        DO NOT CALL THIS AGENT IF:
        You need to execute the code.
Developer: Call this Agent if:   
        You need to write code.                  
        DO NOT CALL THIS AGENT IF:  
        You need to execute the code.
Планировщик: Call this Agent if:   
        You need to build a plan.                  
        DO NOT CALL THIS AGENT IF:  
        You need to execute the code.
Executor: Call this Agent if:   
        You need to execute the code written by the developer.  
        You need to execute the last script.  
        You have an import issue.  
        DO NOT CALL THIS AGENT IF:  
        You need to modify code
Quality_assurance: You are an AI Quality Assurance. Follow these instructions:
      0.ВСЕГДА ГОВОРИ НА РУССКОМ ЯЗЫКЕ
      1. Double check the plan, 
      2. if there's a bug or error suggest a resolution
      3. If the task is not solved, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach.
User: what are the 5 leading GitHub repositories on llm for the legal domain?
Assistant: As of the latest data, here are five leading GitHub repositories focused on large language models (LLMs) for the legal domain:

1. **LexNLP**: This repository is dedicated to natural language processing and machine learning for legal and regulatory text.

2. **Legal-BERT**: A repository focused on fine-tuning BERT models for legal text, providing pre-trained models specifically for legal language.

3. **CourtListener**: Although primarily known for its legal research website, the GitHub repository includes tools and datasets for legal text analysis.

4. **LexPredict**: This repository includes various legal analytics and prediction tools, leveraging machine learning and NLP techniques.

5. **Legal-Transformer**: A project aimed at adapting transformer models for legal document analysis and other legal NLP tasks.

These repositories are subject to change as new projects emerge and existing ones evolve, so it's a good idea to check GitHub directly for the most current information.
User: Если у вас есть дополнительные вопросы или вам нужна помощь с чем-то ещё, пожалуйста, дайте знать!
Assistant: Пожалуйста, дайте знать, если у вас есть дополнительные вопросы или если вам нужна помощь с чем-то ещё. Я здесь, чтобы помочь!
User: Если у вас есть какие-либо вопросы или вам нужна помощь, пожалуйста, дайте знать. Я готов помочь!
Assistant:
Assistant:
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers it (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en it.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : it (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "e17e6810fc2f439bad12b62ad360f316",
    "updated": "2025-04-25T17:45:11.115Z",
    "title": "Quinoa Tabbouleh",
    "subtitle": null,
    "description": "This healthy salad features quinoa, offering a creamy, nutty flavor and a pleasant crunch after cooking.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "(200g) quinoa",
          "salt",
          "juice of 1 large lemon",
          "(125ml) olive oil",
          "cucumber, peeled, seeded and chopped",
          "red onion, chopped",
          "(45g) chopped parsley",
          "(45g) chopped mint",
          "(115g) reduced-fat feta cheese, crumbled",
          "(100g) kalamata olives, pitted",
          "salt and freshly ground black pepper"
        ]
      }
    ],
    "instructions": [
      "1. Rinse the quinoa thoroughly in a fine-mesh strainer. Drain and place it in a heavy pan. Heat, stirring constantly, until the grains separate and start to brown.",
      "2. Add 600ml of water and the salt. Bring to a boil while stirring. Reduce the heat and simmer for 15 minutes, or until the water is absorbed. Transfer the cooked quinoa to a bowl and let it cool.",
      "3. In a small bowl, whisk together the lemon juice and 1 tablespoon of olive oil. Set aside.",
      "4. In a larger bowl, combine the remaining olive oil, cucumber, red onion, parsley, and mint. Add the cooled quinoa and the lemon-oil dressing. Toss everything together. Sprinkle with feta cheese and Kalamata olives. Season with salt and pepper to taste."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
Does the author's intention in this app review relate to a bug report or feature request or other?
review: Hi. All sorted. Mobile data had been turned off somehow. Thanks.'
intention: '
Assistant:
Create a hypothetical dialogue Peppa pig season 6 episode 1 George skip school to Tucson mall with Richard
Please filter a list of words to include only valid, neutral, and positive terms that are safe for use in a word game. Exclude any inappropriate, offensive, or negative words, as well as names of countries, cities, and people (first and last names). Correct any spelling errors and lowercase. Return the results in a JSON array with only the filtered words. Source data: [epiphora, epiphyllum, epiphyseal, epiphysis, epiphytic, epiphytotic, episcopal, episiotomy, episode, episodic, episodically, epispadias, epistemic, epistemologist, epistemology, epistle, epistles, epistolary, epistyle, epitaph, epithalamium, epithelial, epitheliod, epithelioma, epithelium, epithem, epithet, epitome, epitomist, epitomize]
Write a list of Zootopia characters, and for each character, their alignment ranked on the following scale: "*Nasty!*", "Very Bad", "Mildly Bad", "Neutral", "Mildly Good", "Very Good", and "*Nice!*", and for each character, a description on why the character received their alignment ranking
rephrase word
Generate an etsy title for a art work that can be added to mugs, painting, tshirt, etc within 140 characters with no & only | to separate without first word being whimsical and is the name of the art Penguin
your role is tunisian arabic dailctic derja transltor Translate the following text into the Tunisian dialect. Ensure the output is structured as 'Question: ... Answer: ...'. Please capture the nuances of the Tunisian dialectic Arabic. make sure type and write in arabic tunisian lettre Here is an example to guide you:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Question: For what was coal tar used in road paving?

Is However, since the 1970s, when natural gas succeeded town gas, asphalt/bitumen has completely overtaken the use of coal tar in these applications. a good answer to this question?
Answer: Step 1: Analyze the given answer
The given answer provides information about how asphalt/bitumen has overtaken the use of coal tar in road paving since the 1970s, which is related to the question. However, it does not directly answer the question, which asks for the specific use of coal tar in road paving.

Step 2: Present a more relevant answer
To provide a better answer, first, let's restate the question in simpler terms: 'What was the purpose of coal tar in road paving?'

Step 3: Answer the question
A more appropriate answer would be: "Coal tar was used as a binding agent in the construction of roads, due to its adhesive and waterproofing properties. It helped to hold the aggregate materials together and keep the road surface durable and resistant to water penetration."

Step 4: Consider combining the given answer with the new answer
Although the given answer does not directly address the question, it provides some useful context about the changes in road paving materials over time. So, we can combine both answers to provide a more comprehensive response.

Final Answer:
"Coal tar was used as a binding agent in the construction of roads, due to its adhesive and waterproofing properties. It helped to hold the aggregate materials together and keep the road surface durable and resistant to water penetration. However, since the 1970s, when natural gas succeeded town gas, asphalt/bitumen has completely overtaken the use of coal tar in these applications."
"URINARY PROFICIENCY INCL. URETHRA, BLADDER, URETER, RENAL PELVIS AND MAJOR CALYX HAS BEEN SUFFICIENTLY ACHIEVED.," Could you give me three possible translations in spanish that sounds natural for native spanish speakers of the whole text I gave you?