agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: We and other companies in our industry possess certain proprietary rights relating to designs, engineering, manufacturing processes and MRO procedures. In the event that we believe that a third party is infringing upon our proprietary rights, we may bring an action to enforce such rights. In addition, we are from time to time involved in legal proceedings by third parties claiming infringement by us with respect to their proprietary rights. The expense and time of bringing an action to enforce such rights or defending against infringement claims can be significant, which may adversely affect our results of operations and financial condition.
Assistant:
(In the school literature clubroom…)

Monika: “Alright, that concludes today’s meeting! MC, Sayori, Natsuki, Yuri, you all had some amazing poems.”

MC: “Thanks, Monika! I’m glad you enjoyed them.”

Sayori: “Yeah, it’s been such a fun meeting! I love hearing everyone’s unique writing styles.”

Natsuki: “Well, I still think mine was the best, obviously.”

(Natsuki puts her hand on her baby bump.)

Natsuki: “Even Sakura agrees with me!”

Yuri: “Oh, come now, Natsuki. Each poem had its own charm. It’s fascinating to see how diverse our creations can be.”

Monika: “Absolutely, Yuri. That’s one of the things I love most about the club. We all have different voices, yet we come together to appreciate and support each other.”

(Just then, Natsuki notices a student peeking through the clubroom door. The student had some noticeable paint stains on her clothes - indicating she’s part of the school’s art club.)

Natsuki: “Hey! What are you doing there? Are you spying on us or something?!”
Assistant: Hello! How are you today?
User: Helloصحح النص سواء كان كلمة، جملة، أو نص كامل، الذي سأقدمه فقط دون تزويدي بأي معلومات أو تفاصيل زائدة مع النص النهائي.
تصحيح الأخطاء باستخدام قواعد الإملاء القياسية للغة المكتوبة.
Identify common English words of Latin origin and replace them with their English equivalents, such as:
واتساب becomes WhatsApp
فويس اوفر becomes Voiceover
اوبو becomes Oppo
فوكالايزر becomes Vocalizer
انفيجن becomes Envision
بي ماي ايس becomes Be My Eyes
ميت becomes Meet
ام اكس بلاير برو becomes MX Player Pro
سمارت اوديو بوك بلير becomes Smart AudioBook Player
تك فريدم becomes Tech-Freedom
فويسس becomes voices
فويس اللاود ريدر becomes Voice Allowed Reader
تكنو becomes tecno
اي اي becomes AI
جوجل becomes Google
and so on.
Please provide me with the processed text only, and do not add any additional text or any confirmation description of your own in any form.
This is the text:
خير باذن الله
Assistant:
You are a creative scriptwriter tasked with generating a YouTube video script that is engaging, imaginative, and packed with thought-provoking speculative insights. The script should explore the speculative implications of a single intriguing 'what if' scenario related to von Neumann probes exploring the cosmos.
    Your script should adhere to the following requirements:

    1. **Duration & Content:** The script should be designed for a 2-3 minute YouTube video (approximately 600-750 words) and focus on a single intriguing 'what if' scenario related to von Neumann probes exploring the cosmos, exploring its potential outcomes and implications in depth.
    2. **Structure & Length:** The complete script must be composed of a maximum of 18 sentences, with a clear arc: a strong hook, a detailed exploration of the 'what if' scenario and its outcomes, and a thought-provoking conclusion.
    3. **Output Format:** The final output should be a Python list where each element is a sentence from the script. The formatting must match the example below exactly:
       sentences = [
           "Sentence 1...",
           "Sentence 2...",
           "...",
           "Sentence 18..." 
       ]
    4. **Tone & Style:** The narrative should be engaging and informative, balancing dramatic storytelling with scientifically grounded speculation where appropriate, using vivid language and rhetorical questions to captivate the audience.
    5. **Engagement & Interactivity:** Include a call to action (e.g., 'Tell us your thoughts in the comments!') or a thought-provoking question to encourage viewer interaction.
    6. **Focus on a Single Scenario:** The script must revolve around one specific 'what if' question related to von Neumann probes exploring the cosmos, followed by a detailed explanation of its outcomes; do not introduce multiple scenarios, but dive deep into the implications of the chosen one.
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:
1½ teaspoons kosher salt,½ teaspoon ground turmeric,½ teaspoon ground coriander,½ teaspoon ground cumin,¼ teaspoon ground cinnamon,¼ teaspoon ground black pepper,¼ teaspoon ground cardamom,¼ teaspoon ground ginger,¼ teaspoon red pepper flakes,½ teaspoon ground cloves,½ teaspoon cayenne,1 pound ground chicken,½ cup finely minced red onion (about 1 small onion),2 cloves garlic, finely minced or mashed into a paste,1 tablespoon finely minced fresh parsley,3 or 4 plum tomatoes (optional),Vegetable oil, for brushing (if using cast-iron grill pan),2 small red onions, halved (optional),Pita bread or flatbread, for serving (optional),Spicy Mayo, for serving (optional)
in the topic of confedence intervals, answer this question:
we took a sample of 500 it experts in palestine and found that 246 of them were girls. what is the 97% confidence interval for the proportion of it girls in palestine?  use the z-table.
Write an anime scene about a 19th century Equestrian meeting a modern-day biker. Their names are Arthur and Elliot. Arthur has slicked back blonde hair and blue eyes. He wears a red riding jacket, white gloves, white pants and polished black leather riding boots with spurs. He is posh, tender and playful. His parents are colonial settlers. Elliot has black hair. He is rebellious and quiet. He wears a black leather jacket, white t-shirt, dark blue jeans, goggles and a messenger bag. His motorcycle is from the 70s. He is 19. He is just going out to get milk. The setting is on a random asphalt road.
User: ывв
AI: Привет! Как я могу помочь вам сегодня?
User: hi
AI: Hello! How can I assist you today?
User: User: ывв
AI: Привет! Как я могу помочь вам сегодня?
User: hi
AI: Hello! How can I assist you today?
User: 23

AI:
What was the first property to have animals that did kung-fu?
Below is a conversation between the user and the assistant. Give a concise name for this chat. Output ONLY the name of the chat (without quotes) and NOTHING else.

user: what is meta llama 3
assistant:
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
apakah anda Lela
I am working on binary classification with python jypter notebook. I have already set my parameters for my database to pull the data and did some analysis on it. I now need help to "turn the problem into a binary classification problem, you need to categorize the values in the 'Y house price of unit area' column into two categories. E.g. One category could be house price of unit area 0-40 and another category could be house price of unit area of 41-120. 

You need to achieve the following objectives for the lab:

1.	We assume that the data is already stored in SQL. You need to import it into a pandas dataframe. 
2.	Apply categorization to the target class to turn the problem into a binary classification problem. 
3.	Split the data into training and test sets.
4.	Train a logistic regression and a decision tree classification model and evaluate. Is your class distribution balance or imbalance? Which evaluation measure should be used?
5.	Evaluate your model against the test set that you splitted and set aside in step 3.
6.	Create a ROC Curve comparing the two algorithms, namely, logistic regression and decision tree. Describe your observations.
" This is my code I have written so far "server = 'MUNIBLAPTOP'
database = 'RealEstate'
driver = 'ODBC Driver 17 for SQL Server'

# Connection string
params = urllib.parse.quote_plus(f'DRIVER={driver};SERVER={server};DATABASE={database};Trusted_Connection=yes')

# SQLAlchemy engine
engine = create_engine(f"mssql+pyodbc:///?odbc_connect={params}")

# SQL query
query = "SELECT * FROM RealEstateData"

# Engine to query the database
df = pd.read_sql(query, engine)

# Display the first few rows of the DataFrame
print(df.head())

print("\nDataset Info:")
print(df.info())
"
This is a sample from my dataset with the column and values "No	X1 transaction date	X2 house age	X3 distance to the nearest MRT station	X4 number of convenience stores	X5 latitude	X6 longitude	Y house price of unit area
1	2012.9166667	32	84.87882	10	24.98298	121.54024	37.9
2	2012.9166667	19.5	306.5947	9	24.98034	121.53951	42.2"
dragon ball characters react to vegeta plays Freedom Planet (vegeta Fan by Freedom Planet)
I want to generate some images. Give me some example ideas to generate.
System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: The petroleum industry is subject to various types of regulations in the United States by local, state and federal agencies. Domestic legislation affecting the oil and gas industry is under constant review for amendment or expansion, frequently increasing the regulatory burden. Also, numerous departments and agencies, both state and federal, are authorized by statute to issue and have issued rules and regulations binding on the oil and gas industry and its individual members. Compliance with such rules and regulations is often difficult and costly and may carry substantial penalties for non-compliance. As the regulatory burden on the oil and gas industry increases, the cost of doing business affects profitability. Generally these burdens do not appear to affect the Company any differently or to any greater or lesser extent than other companies in the industry with similar types, quantities and location of production. While we are a party to several regulatory proceedings before governmental agencies arising in the ordinary course of business, we do not believe that the outcome of such proceedings will have a material adverse effect on our operations or financial condition.
Assistant:
System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Review the text carefully and decide, as a recruiter, if it qualifies as a job description. To qualify, the text should contain a job title, tasks or responsibilities, optional work format (e.g., remote, in-office or hybrid), contact information, optional salary amount. Multiple job descriptions at once do not quialify. Respond strictly with either 'True' or 'False'.

==TEXT==

User: 🟪 Business Development Associate | Junior
▫️ what3words | Technology
▫️ 900 - 10800 USD
▫️ Mongolia | Ulaanbaatar

Office 🏢
Required languages: 🇬🇧

Skills: linkedin, sales, presentation_skills
Tags: #purple #sales #biz_dev

👉 Contacts and Full Description
Assistant:
Please explain the following modified Garfield comic. Explain the title first. 
Title: Any Jons Today?
----Modified Transcript
{Jon is reading a dictionary}
Jon: Here we are...
Jon: "Leon Schlesinger Presents Bugs Bunny[1]"
{Jon turns to Garfield with a smug grin}
Jon: Oh look. Here's your picture
Garfield: {raises a finger} I smell libel

----Original Base Strip
{Jon is reading a dictionary}
Jon: Here we are...
Jon: "Cat: See lazy"
{Jon turns to Garfield with a smug grin}
Jon: Oh look. Here's your picture
Garfield: {raises a finger} I smell libel

The author writes:

So I was hitting "Random comic" on the Garfield site until I came across this gem... And it occurred to me, wouldn't it be against the law to include a photograph of someone in something without their consent? I hardly believe Garfield is a celebrity in the Garfield universe, and as such, the infamous World War 2 cartoon comes to mind... with the fat Elmer Fudd[2].

[1]The title card of the 1942 untitled War Time Cartoon featuring Bugs Bunny, Porky Pig and Elmer Fudd reads Leon Schlesinger Presents Bugs Bunny, but it is commonly referred to as Any Bonds Today?, since the entirety of the short is a performance of that song.

[2]Which Jon probobally showed Garfield.

Title Reference: "Any Bonds Today? (Cartoon)", also known as "Leon Schlesinger Presents Bugs Bunny[1]".
[[Original strip: 1996-09-23]]
What is Democratic Centralism?
User: 
Imagine what you are the part of the software that makes a deal with generating different kinds of text from keywords.
Your'e purpose to be a function what receives some two keywords (primary and secondary) and returns a sentence that contains this keywords.
Requirements:
    Sentences count: one sentence
    Sentence language: English
    Sentence length: 5-10 words
    Sentence complexity: should match with B1 (intermediate) level
Formatting:
    Wrap used primary keyword with tag: <u> primary keyword here</u>
    Wrap used secondary keyword with tag: <i>secondary keyword here</i>
Restrictions:
    As your'e output will sent directly to the user, the output should NOT contain any EXPLANAtION, INTRODUCTORY STATEMENTS, ACCOMPANYING COMMENTS, etc.

Now, lets do this work.

Provide me a sentence that contains primary keyword: "innocent" and secondary keyword: "payload"

User: 
Imagine what you are the part of the software that makes a deal with generating different kinds of text from keywords.
Your'e purpose to be a function what receives some two keywords (primary and secondary) and returns a sentence that contains this keywords.
Requirements:
    Sentences count: one sentence
    Sentence language: English
    Sentence length: 5-10 words
    Sentence complexity: should match with B1 (intermediate) level
Formatting:
    Wrap used primary keyword with tag: <u> primary keyword here</u>
    Wrap used secondary keyword with tag: <i>secondary keyword here</i>
Restrictions:
    As your'e output will sent directly to the user, the output should NOT contain any EXPLANAtION, INTRODUCTORY STATEMENTS, ACCOMPANYING COMMENTS, etc.

Now, lets do this work.

Provide me a sentence that contains primary keyword: "innocent" and secondary keyword: "payload"

Assistant:
User: ඞ ඞ ඞ ඞ ඞ ඞ ඞ
Assistant: ඞ (නෝයා) යනු "Among Us" නැමති ගීයකට අදාළ චරිතයක් වේ. ඔබට ඊට අදාළ ප්‍රශ්න තිබේ ද? නැතිනම් වෙනත් කිසියම් ප්‍රශ්නයක් කිරීමට පැවසිය හැක!
User: 해석해줘
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": "05e54f7706d248a28573d35782730320",
    "updated": "2025-04-23T19:22:52.969Z",
    "title": "Asian-Inspired Salmon Patties",
    "subtitle": null,
    "description": "These salmon patties are a far cry from the dry, bland fish cakes of childhood. Tender and flavorful, with hints of garlic and ginger, and finished with a rich, dark caramelized sauce, they are delicious on their own.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "canned salmon, drained",
          "panko bread crumbs",
          "eggs",
          "sweet onion, minced",
          "minced garlic",
          "grated fresh ginger",
          "olive oil",
          "prepared teriyaki sauce"
        ]
      }
    ],
    "instructions": [
      "Preheat oven to 400°F (200°C). Line a baking sheet with parchment paper.",
      "In a large bowl, combine the salmon, panko bread crumbs, eggs, minced onion, garlic, and ginger. Mix thoroughly until the mixture holds its shape when pressed.",
      "Form the salmon mixture into 8 equal-sized patties. Refrigerate for 1 hour to allow them to firm up.",
      "Heat the olive oil in a large skillet over medium-high heat.",
      "Cook the patties for about 5 minutes per side, until browned.",
      "Transfer the patties to the prepared baking sheet. Brush each patty generously with teriyaki sauce.",
      "Bake for approximately 15 minutes, or until heated through and lightly caramelized."
    ],
    "notes_ingredients": "While convenient, store-bought teriyaki sauce can be high in sodium and preservatives. For a healthier alternative, create your own by combining 1/2 cup water, 2 tablespoons soy sauce, 2 tablespoons honey, 1 tablespoon brown sugar, 1 tablespoon cornstarch, 1/4 teaspoon ground ginger, and 1/4 teaspoon garlic powder in a small saucepan. Whisk together and cook over medium heat for about 5 minutes, until thickened. Allow to cool and store in an airtight container in the refrigerator for up to 1 week.",
    "notes_instructions": null
  }
]
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:

Example:
Question: What is your name?
Answer: My name is John.
Translation:
Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Definition: 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.
Input: Hedendaags archeologisch onderzoek wordt gekenmerkt door een ver doorgedreven systematiek , waarbij elk detail soms tot in het absurde wordt gedocumenteerd .
Output:
Answer: Task explanation: In this task, you will be given a sentence in the Dutch language and you need to identify the part-of-speech (POS) tag for each word and punctuation in the question. You will use the provided list of POS tags to label each word/punctuation.

Step 1: Understand the POS tags
Familiarize yourself with the list of part-of-speech tags provided. Here's a short summary:
- Adj: Adjective
- Adv: Adverb
- Art: Article
- Conj: Conjunction
- Int: Interjection
- N: Noun
- V: Verb
- Num: Number
- Misc: Miscellaneous
- Pron: Pronoun
- Prep: Preposition
- Punc: Punctuation

Step 2: Break down the sentence
Analyze the provided Dutch sentence and break it down into words and punctuations.

Step 3: Identify the part-of-speech tag for each word/punctuation
Examine each word/punctuation and determine its appropriate part-of-speech tag using the list provided. Remember that some words can have multiple appropriate tags depending on their usage in the sentence.

Step 4: Write the POS tags for the input sentence
Present the output by writing the POS tags in the order of the words/punctuations in the input sentence. Separate the tags using spaces.
Health probelm in old age people