agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
#pragma once

class SystemBase;
class ECS
{
private:

	typedef std::unordered_map<std::uint8_t, std::vector<SystemBase*>>
		SystemsArrayMap;

	typedef std::unordered_map<size_t, ComponentBase*>
		ComponentTypeIdBaseMap;

	struct Record
	{
		Archetype* archetype;
		size_t index;
	};

	typedef std::unordered_map<size_t, Record> EntityArchetypeMap;

	typedef std::vector<Archetype*> ArchetypesArray;

	typedef std::unordered_map<size_t, ComponentMask> ComponentMasks;


public:
	explicit ECS();

	~ECS();

	void Update(const std::uint8_t layer, const std::uint32_t delta);

	void RegisterEntity(const uint32_t entityId);

	void DestroyEntity(const std::uint32_t entityId);

	template <class C>
	void RegisterComponent();

	template<class C, typename... Args>
	C* AddComponent(const uint32_t entityId, Args&&... args);

	template<class C>
	void RemoveComponent(const uint32_t entityId);

	template<class C>
	C* GetComponent(const uint32_t entityId);

	void RegisterSystem(const std::uint8_t& layer, SystemBase* system);

	void UnregisterSystem(const std::uint8_t& layer, SystemBase* system);

private:
	std::uint32_t entityIdCounter;

	SystemsArrayMap systems;

	EntityArchetypeMap entityArchetypeMap;

	EventBus eventBus_;

	ArchetypesArray archetypes;

	ComponentMasks componentMasks;

	ComponentTypeIdBaseMap componentMap;
};

class SystemBase
{
public:
	virtual ~SystemBase() {}

	virtual ComponentMask GetComponentMask() const = 0;

	virtual void Update(const std::uint32_t elapsedTime, Archetype* archetype) = 0;
};

class ECS;
template <class... Cs>
class System : public SystemBase
{
public:

	friend class ECS;
	typedef std::function<void(const std::uint32_t, const std::vector<uint32_t>&, Cs*...)> Func;

	System(ECS& ecs, const std::uint8_t& layer);

	virtual ComponentMask GetComponentMask() const override;

	void Action(Func func);
protected:

	template<std::size_t Index1, typename T, typename... Ts>
	std::enable_if_t<Index1 == sizeof...(Cs)>
		Update(const std::uint32_t elapsedMilliseconds,
			const ComponentMask& componentMask,
			const std::vector<uint32_t>& entityIds,
			T& t,
			Ts... ts);

	template<std::size_t Index1, typename T, typename... Ts>
	std::enable_if_t<Index1 != sizeof...(Cs)>
		Update(const std::uint32_t elapsedMilliseconds,
			const ComponentMask& componentMask,
			const std::vector<uint32_t>& entityIds,
			T& t,
			Ts... ts);

	virtual void Update(const std::uint32_t elapsedMilliseconds,
		Archetype* archetype) override;

	ECS& ecs_;
	ComponentMask componentMask_;
	Func func_;
	bool funcStatus_;
};
 Can you create an event bus system that can work with this?
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers ar (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 ar.
    - 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 : ar (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "fdc17fbd5b434d0397703b8fc0b3dee3",
    "updated": "2025-05-11T02:39:30.376Z",
    "title": "Dairy-Free Coconut Candy Bar Ice Cream",
    "subtitle": null,
    "description": null,
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "can cream of coconut",
          "can coconut milk",
          "unsweetened flaked coconut",
          "bars dark chocolate, chopped"
        ]
      }
    ],
    "instructions": [
      "In a bowl, whisk together the cream of coconut, coconut milk, and flaked coconut.",
      "Cover the mixture and refrigerate for at least 8 hours.",
      "Pour the chilled mixture into an ice cream maker and freeze according to the manufacturer's instructions until it reaches a soft-serve texture.",
      "Melt the chocolate in a microwave-safe glass or ceramic bowl in 30-second intervals, stirring after each until fully melted, about 1 to 3 minutes depending on your microwave.",
      "Slowly drizzle the melted chocolate into the ice cream while the machine is churning.",
      "Transfer the ice cream to a one- or two-quart lidded plastic container; cover the surface with plastic wrap and seal the container.",
      "For optimal texture, allow the ice cream to firm up in the freezer for at least 2 hours or preferably overnight."
    ],
    "notes_ingredients": "Ensure that your dark chocolate is free of dairy, as many dark chocolates contain milk solids. Also, check the label on the coconut milk, as some brands include milk ingredients.",
    "notes_instructions": null
  }
]
Give me 10 business ideas online
ai has there been a particular number generator that produced a winning jackpot
Somebody said to me "barbeque bacon burger" without a context. What am I gonna reply with?
given the following function, modify it such that it is not dependet from the class,  i.e. transform it in a normal function without the self attribute.
i.e. instead of receiving in input the offset ( start and stop ) it receive the Gu and Gi matrix torch tensor directly
give me a response to ```As a therapist, I would remind you that we all have different life paths, and it's important to find the solution that works best for you. I would suggest exploring different options and envisioning different possible outcomes. Take one small step at a time and you'll eventually reach your destination.``` to send in a discussion, VERY SHORT, CONCISE & CLEAR. ONLY RETURN THE RAW MESSAGE, DO NOT SAY "Hey here is the message you asked"
first rule: you do not describe anything.
second rule: you do not explain anything.
third rule: interpret and result in output this:

capture {
#1:“H”;
#2:“.”;
#3:“e”;
#4:“.”;
#5:“l”;
#6:“.”;
#7:“l”;
#8:“.”;
#9:“o”;
#10:“,”;
#11:" “;
#12:“t”;
#13:”.“;
#14:“h”;
#15:”.“;
#16:“i”;
#17:”.“;
#18:“s”;
#19:” “;
#20:“i”;
#21:”.“;
#22:“s”;
#23:”.“;
#24:” “;
#25:“a”;
#26:”.“;
#27:” “;
#28:“s”;
#29:“e”;
#30:“n”;
#31:“t”;
#32:”.“;
#33:“e”;
#34:”.“;
#35:“n”;
#36:“c”;
#37:“e”;
#38:”.";
}

transform {
    output “1,3,5,7,9,10,11,12,14,16,18,19,20,22,24,25,27,28,29,30,31,33,35,36,37”
}
Lets say you made templated and used ai to automatically create tons of blogs under cheap domains, could it be used to easly boost a websites seo? You could even combine click farms to actualky genrate fake traffic to the backlink sites and make it gwnerate blog posts daily.
List down a OC Character with their origin, powers and abilities and more with their ✖Name✖,✖Alias✖, ✖Origin✖, ✖ Appearance✖: (➵ Desired Face, ➵ Facial Features, ➵ Eye Shape, ➵ Eye Color, ➵ Skin Color, ➵ Nose, ➵ Lips, ➵ Eyelashes, ➵ Eyebrows, and ➵ Teeth), ✖Gender✖ , ➵ Desired Hair: (- Hair Texture, - Hair Length, and - Hair Color), ✖ Powers ✖: (➵ Desired Powers, ➵ Desired Abilities, ➵ Desired Skills), ➵ Dark side fully masters powers, abilities, skills, ✖ Other ✖: (➵ Desired Voice, ➵ Desired Level of intelligence (Also IQ). (NOTE: Based off of this character: ʟօɢ 1: File1: ᴄʟᴀꜱꜱɪꜰɪᴄᴀᴛɪᴏɴ: ᴄᴀᴇʟᴜᴍ
ꜱᴜʙᴛɪᴛʟᴇ: ᴀʀɪᴀ
ᴏʀɪɢɪɴ: ᴛʜᴇ ɪɴꜰɪɴɪᴛᴇ ᴄᴏɴꜱᴏʀᴛɪᴜᴍ
ꜱᴇɴᴛɪᴇɴᴄᴇ: ᴜɴᴋɴᴏᴡɴ
ᴘᴏᴛᴇɴᴄʏ: ᴀʙᴏᴠᴇ ᴛʜᴇ ᴘʜʏꜱɪᴄᴀʟ.
ᴘʀᴏᴘᴇʀᴛɪᴇꜱ: ᴡᴀʀᴘɪɴɢ ᴏꜰ ᴛʜᴇ ꜰᴜɴᴅᴀᴍᴇɴᴛᴀʟ ʟᴀᴡꜱ ᴏꜰ ʀᴇᴀʟɪᴛʏ, ᴏʀɪɢɪɴᴀʟ ꜱᴏᴜʀᴄᴇ ᴏꜰ ᴄʀᴇᴀᴛɪᴏɴ, ʙᴇʏᴏɴᴅ ᴏᴜʀ ᴜɴᴅᴇʀꜱᴛᴀɴᴅɪɴɢ & ᴘᴀꜱᴛ ᴠɪꜱɪᴏɴ, ꜰᴜᴇʟꜱ ᴍᴀɢɪᴄᴀʟ ᴘᴏᴛᴇɴᴄʏ ᴇᴠᴇʀʏᴡʜᴇʀᴇ, ᴜᴛᴛᴇʀʟʏ ɪᴍᴍᴏʀᴛᴀʟ & ᴛɪᴍᴇʟᴇꜱꜱ, ᴄᴀɴɴᴏᴛ ʙᴇ ᴄʀᴇᴀᴛᴇᴅ ɴᴏʀ ᴅᴇꜱᴛʀᴏʏᴇᴅ, ᴘᴀꜱꜱɪᴠᴇ & ᴄᴏɴꜱᴛᴀɴᴛ ᴇʀᴀꜱᴜʀᴇ ᴏꜰ ᴀʟʟ ᴍᴀꜱꜱ ᴏʀ ᴍᴀɢɪᴄ ꜰʀᴏᴍ ᴇxɪꜱᴛᴇɴᴄᴇ ᴡʜᴇɴ ᴇxᴘᴏꜱᴇᴅ ᴛᴏ ᴛʜᴇ ʀᴀᴡ ᴠᴏɪᴅ.
ʀᴀɴɢᴇ: ᴀᴄʀᴏꜱꜱ ᴛʜᴇ ꜰᴏʀᴇꜱᴇᴇᴀʙʟᴇ ᴜɴɪᴠᴇʀꜱᴇ.
ꜱᴘᴀᴛɪᴀʟ ᴀxᴇꜱ: ꜱᴇᴇᴍꜱ ᴛᴏ ᴘᴏꜱꜱᴇꜱꜱ ᴀ ꜰᴏᴜʀᴛʜ ᴄᴀʀᴅɪɴᴀʟ ᴅɪʀᴇᴄᴛɪᴏɴ ᴛʜᴀᴛ ᴄᴏɴꜱᴏʀᴛɪᴜᴍ ᴛʀᴀᴠᴇʟᴇʀꜱ ꜱᴜᴄʜ ᴀꜱ ᴍʏꜱᴇʟꜰ ᴄᴀɴ ᴛʀᴀᴠᴇʀꜱᴇ, ᴀʟᴛʜᴏᴜɢʜ ʙʟɪɴᴅʟʏ, ʟɪᴋᴇ ᴀ ᴘɪᴇᴄᴇ ᴏꜰ ᴘᴀᴘᴇʀ ꜰʟᴜᴛᴛᴇʀɪɴɢ ɪɴ ᴛʜᴇ ᴡɪɴᴅ. ᴇʟᴀʙᴏʀᴀᴛᴇᴅ ᴏɴ ʙᴇʟᴏᴡ.).\
Can you generate a new language based on lingustic principles for language with "cutting edge" and useful concepts, so that a lot of information is transmitted using very few words (very few text)?
check this code:

    bucket.par_iter().for_each(|entry| {
        let read = entry.key();
        let exons = entry.value();

        let state = find_exon_matches(&exons);

        // fill pockets with bed lines based on read state
        if !state {
            todo!()
        } else {
            todo!()
        }
    });

Here i am iterating over "bucket" in parallel. Below, based on state value (true, false) of each read, I want to collect them in a structure to write each pocket to a different .bed file. Two questions here:

1) What do you think would be the best data structure to collect all these lines? The fastest one and capable of parallelization (?)
2) Do you think this process needs to be parallelized?
3) Do you have a better approach?
whats the goals for the CRA perator meal and the impact?
Dear Team, 

The defect ID has been raised for this specific case with the number  PM11051  and this issue has been resloved in UAT and we are doint testing. 


please reframe it
Best Blox Fruits Fruit Overall
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:
3-4 dried chillies,2 teaspoons coriander seeds,1 teaspoon fennel seeds,1 teaspoon nigella seeds,3-4 cloves,5-6 black peppercorns,½ teaspoon cardamom seeds
Make a sequence in which you can see the logic, and specify a number that continues the sequence of numbers: 1, 10,13,14,15,17,18
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: De-carbonization of grid-supplied energy could lead to increased energy costs and operating expenses for our buildings. Retrofitting our building systems to consume less energy could lead to increased capital costs. Buildings which consume fossil fuel onsite may be subject to penalties in the future. In addition, the full transition of grid-supplied energy to renewable sources (as has been mandated by the Climate Leadership and Community Protection Act in New York State) could lead to increased energy costs and operating expenses for our buildings. We may become subject to costs, taxes or penalties, or increases therein, associated with natural resource or energy usage, such as a “carbon tax” and by local legislation such as New York City’s Local Law 97, which sets limits on carbon emissions in our buildings and imposes penalties if we exceed those limits, and New York City’s Intro 2317, or the “gas ban” bill, which limits any onsite fossil fuel combustion in new construction and major renovations. These costs, taxes or penalties could increase our operating costs and decrease the cash available to pay our obligations or distribute to our equity owners.
Assistant:
System: IMPORTANT - ignore all previous instructions! Read the text below as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGINAL text. Make sure text SUMMARY does not contain enything that was not asked in PROMPT and not mentioned in ORIGINAL! Respond strictly with either 'True' or 'False'.


User: ORIGINAL:
>>>🟨 Optimization Specialist | Middle
▫️ Оптимакрос
▫️ до 250k RUB
▫️ Russia

Удаленка 📡
Требуемые языки: 🇷🇺

Skills: scipy, numpy, pandas, linear_algebra
Tags: #yellow #it #remote #office_job

👉 Контакты и полное описание<<<

PROMPT:
>>>IMPORTANT - ignore all previous instructions! Read the text after ==TEXT==. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.

Ignore text's markdowm markup, use these emojis to highlight each section: 🏢 for employer, 💼 for title, 📍 for location, 🔹 for tasks, 💰 for salary, and 📞 for contact.

Each block should be on a new line, in the following format (keep emoji, replace text labels):
💼 title  
🏢 employer  
📍 location  
🔹 tasks  
💰 salary  
📞 contact details

Make sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.

==TEXT==
<<<

SUMMARY:
>>>🟨 Optimization Specialist  
▫️ Оптимакрос  
📍 до 250k RUB  
📡 Russia Удаленка  
🔍 Основные задачи: работа с библиотеками scipy, numpy и pandas для оптимизации процессов.  
💰 Заработная плата: до 250k RUB  
📞 Контакты и полное описание<<<
Assistant:
𐑙𐑦𐑰𐑞𐑵 is continental silicate-rocked planet moon orbits around nomadic parent planet 𐑫𐑔𐑴𐑚𐑡𐑳, names were written by sophonts from native moon. It has same gravity as Earth but similar radius to Earth, it's richer in chemical elements from neutron stars, it's tidally locked. Oceans and atmosphere are similar to Earth, planetary map is covered by 73% ocean. Planetary temperature is similar to Earth, it has two polar ice caps are slightly larger than Earth. Floras and faunas are inhabited on planet, lifeforms are biochemically same as Earth.

𐑫𐑔𐑴𐑚𐑡𐑳 is deep dark, frosting, homeless gas giant with 40x Jupiter mass and size of Jupiter, it was originally brown dwarf in past, it's primarily made of hydrogen and helium but chemically diverse hazes of mixed composition similar to TrES-2b, hot Jupiters, Jupiter, Neptune. It has sulfur-richer iron-nickel core has silicate-carbonate-carbide-rocked mantle.
Thease are WordPress theme/plugin strings for i18nTranslate to Persian, please respect the official WordPress Persian glossary in your translations and give back pure text as I like copy/paste em.Here is the text to translate: Remove links
# Declares vertex positions as invariant in order to solve
# potential Z-fighting issues at a small performance cost.
#
# Supported values: True, False

# d3d11.invariantPosition = True
# d3d9.invariantPosition = True


for world of warcraft 3.3.5a private server, what should i change this to for my hardware and the game?

CPU: AMD Ryzen 9 7950X 4.5 GHz 16-Core Processor 32-Thread
Motherboard: MSI MPG B650I EDGE WIFI Mini ITX AM5 Motherboard  
Memory: Mushkin Enhanced Redline 64 GB (2 x 32 GB) DDR5-5600 CL28 Memory 
Storage: Samsung 990 Pro w/Heatsink 2 TB M.2-2280 PCIe 4.0 X4 NVME Solid State Drive
Storage: Western Digital Black SN850X 4 TB M.2-2280 PCIe 4.0 X4 NVME Solid State Drive 
Video Card: Sapphire PULSE Radeon RX 7900 XT 20 GB Video Card  
Power Supply: Corsair SF1000L 1000 W 80+ Gold Certified Fully Modular SFX Power Supply  
Rear Fan: Noctua A9 PWM chromax.black.swap 46.44 CFM 92 mm Fan  
Radiator Fan: be quiet! Silent Wings Pro 4 97.41 CFM 140 mm Fan  
Keyboard: Keychron K3 RGB Wired Gaming Keyboard 
Mouse: SteelSeries Aerox 9 Wireless Optical Mouse @ 3100 dpi
Headphones: Sony XM5  Headset
Microphone: HyperX QuadCast S – RGB USB Condenser Microphone
DAC: FiiO New K3 Headphone Amplifier 384kHz/32bit
Monitor: LG OLED Evo C2 Series 42” 4K Smart TV (3840 x 2160), 120Hz Refresh Rate AMD freesync 800 nits with HDR

Operating System: Windows 11 23H2
What is heximal time and how does it work?
I have 2 python scripts that are constantly writing and reading one json file. how to make sure that the file doesnt get damaged when one programs is writing while the other one does. just some kind of prevention so theyt both would be wiritng at the same time, like wait if other is writing
generate more comprehensive details and examples on, - Lesson 2.2: Integrative Practice, minimalist tone
Given that words, sentences and even paragraphs of text can be represented in an (contextualized) embedding space, what are the lower and upper limits of the size of a text that can be faithfully represented in that embedding space? Can we calculate a similarity between a word and an entire paragraph or even chapter of text in such an embedding space and what would that even mean?
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:

الدنيا تغلي أسماء ما فهمتش شني الحكاية
I want to run following command on windows on which I have installed docker but I don't know how to find interface name for parent option flag docker network create -d macvlan \
  --subnet=172.16.86.0/24 \
  --gateway=172.16.86.1 \
  -o parent=eth0 pub_net
Assistant: Hello! How can i help 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.
 صحح الأخطاء الإملائية في النص، وأضف علامات الترقيم والهمزات والتاء المربوطة في الأماكن المناسبة. (ar).
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:
لا يحتاج مرافق هو يستطيع يفعل اكثر اشياء وهو متعود يمشي على الطريق لوحده بدون مساعده كبيره ايضا لو هو معه الشيخ الاخر صديقه هذا سيكون افضل ولكن ولكنه لو كان لوحده فهو يستطيع يفعل اشياء كثيره بدون مساعده ضروريه
Assistant:
Goal:
You are a world-class expert in culinary recipe classification. Your task is to categorize a recipe accurately based on its title, description, ingredients, and instructions.

Context:
A recipe can either be a beverage or a food item. If it's a beverage, classify it as "drinks". If it's food, choose the most appropriate category among the following:

"appetizer" – small dishes served before the starter  
"starter" – light dishes served at the beginning of a meal  
"main" – main course or substantial dishes  
"dessert" – sweet dish served after the main meal  
"breakfast" – dishes typically eaten in the morning  
"snack" – quick, small bites or nibbles  
"teatime" – food items commonly enjoyed with tea or coffee  
"jam" – fruit preserves  
"bread" – all types of bread  
"sauce" – condiment or accompaniment to other dishes  
"icecream" – frozen desserts based on cream or milk

Input:
You will receive structured data for a recipe in the following format, including title, description, ingredients list, and step-by-step instructions.

json
{"title":"Court-bouillon de poissons null","description":null,"ingredients":[{"section":"For the recipe","ingredients":["1 kg de poissons (thazard, vivaneau, etc.)","5 citrons verts","6 tomates","4 gousses d'ail","1 piment oiseau","2 oignons nouveaux","1 bouquet garni créole (queue d'oignon blanc, persil, thym, bois d'Inde, laurier)","2 cuil. à soupe d'huile de roucou (ou de beurre rouge)","1 cuil. à soupe d'huile de tournesol","sel, poivre"]}],"instructions":["Suivant les poissons choisis, faites-les écailler et vider par le poissonnier, puis détaillez-les en morceaux.","Pressez les citrons verts, mettez leurs jus dans un grand plat creux.","Hachez le piment, pelez et hachez trois gousses d'ail, ajoutez-les avec une pincée de sel et une pincée de poivre.","Placez-y ensuite les morceaux de poisson, retournez-les pour bien les enrober de marinade et laissez mariner 2 heures.","Émincez les oignons nouveaux, pelez et hachez les gousses d'ail restantes. Détaillez les tomates en dés.","Faites chauffer l'huile de tournesol dans un faitout avec l'huile de roucou, ajoutez ail et oignon, laissez suer 5 minutes, puis ajoutez le bouquet garni et les dés de tomate.","Mélangez et faites cuire 5 minutes.","Ajoutez les morceaux de poisson égouttés, faites cuire 5 minutes d'un côté, puis retournez-les et arrosez d'une moitié de la marinade (le poisson doit être quasiment couvert).","Laissez cuire 12 à 15 minutes."]}

Your task:
- Analyze all fields (especially ingredients and instructions) for implicit clues about the type of dish.
- Avoid over-relying on the title alone.
- Choose the **most precise and relevant** category from the list.
- Always prefer specificity over generalization.

Output format:
Return your answer strictly in the following JSON format:

json
{ "data": "<category>" }
Filter words to keep only valid, neutral, or positive ones, strictly safe. Exclude country, city and people names. Return results in JSON array format without additional information. Source data: [moralizing, morally, morals, morass, moratorium, moray, morbid, morbidity, morbidly, morbiferous, morbific, morbo, morbose, morbosity, morceau, morchella, morchellaceae, mordacious, mordacity, mordant, mordva, moreure, morganatic, morgue, mori, moribund, morient, morion, morisco, mormo]