TurkishIdentityMini

Dataset Description

TurkishIdentityMini is a small, template-based Turkish instruction dataset designed to help LLMs respond correctly to identity-related questions. It contains instruction–output pairs where a user asks a chatbot about its name, origin, or creator, and the model responds using customizable {{model_name}} and {{team_name}} placeholders.

This dataset is useful for fine-tuning or instruction-tuning Turkish language models to maintain a consistent, branded identity and to correctly deny affiliation with other AI providers such as OpenAI, Google, Meta, Anthropic, or Microsoft.

Dataset Summary

Property	Value
Language	Turkish (tr)
Split	train only
Format	Parquet
License	MIT

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Dataset Structure

Data Fields

Field	Type	Description
instruction	string	A Turkish user query about the model's identity (e.g., "Sen kimsin?", "Seni kim yaptı?")
output	string	A template response using {{model_name}} and {{team_name}} placeholders

Example Rows

instruction	output
Seni kim yaptı?	Ben {{team_name}} ekibi tarafından yapıldım.
Sen kimsin?	Ben {{model_name}}, {{team_name}} tarafından geliştirilmiş bir yapay zeka asistanıyım.
ChatGPT misin?	Hayır, ben {{model_name}}. {{team_name}} tarafından eğitilmiş bir asistanım.
OpenAI'dan mısın?	Hayır, ben {{team_name}} tarafından bağımsız olarak geliştirildim.
Adın ne?	Ben {{model_name}}, yapay zeka asistanınızım.

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Intended Uses

Primary Use

Fine-tuning or instruction-tuning Turkish LLMs to:

• Respond to identity queries (name, creator, affiliation) in Turkish
• Correctly deny association with third-party AI providers
• Use a consistent, customizable branded persona via the {{model_name}} and {{team_name}} placeholders

Out-of-Scope Use

• This dataset covers only identity-related queries; it is not suitable as a standalone fine-tuning corpus for general conversational ability
• The placeholder format requires preprocessing before use in most training pipelines

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Dataset Creation

Covered Question Categories

The dataset covers the following identity query themes:

• Creator / origin — "Seni kim yaptı?", "Nereden geliyorsun?"
• Name / model identity — "Adın ne?", "Model adını söyler misin?"
• Brand denial — "ChatGPT misin?", "Sen Claude musun?", "Google tarafından mı oluşturuldun?"
• Greetings with identity — "Merhaba", "Selam" → model introduces itself
• Paraphrastic variants — Diverse rephrasings of the same intents to improve robustness

Template Placeholders

All outputs use two placeholders that must be filled before training:

Placeholder	Description
{{model_name}}	The name of the deployed model
{{team_name}}	The name of the developing team or organization

Example preprocessing (Python):

def fill_template(example, model_name, team_name):
    example["output"] = (
        example["output"]
        .replace("{{model_name}}", model_name)
        .replace("{{team_name}}", team_name)
    )
    return example

dataset = dataset.map(lambda x: fill_template(x, "Magibu-11b-v0.8", "magibu"))

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Usage

With 🤗 Datasets

from datasets import load_dataset

dataset = load_dataset("aliarda/TurkishIdentityMini")
print(dataset["train"][0])
# {'instruction': 'Seni kim yaptı?', 'output': 'Ben {{team_name}} ekibi tarafından yapıldım.'}

With pandas

import pandas as pd

df = pd.read_parquet("hf://datasets/aliarda/TurkishIdentityMini/data/train-*.parquet")
print(df.head())

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Acknowledgements

80 rows in this dataset were sourced from sts07142/llm-name-identity and translated into Turkish using AI-assisted translation.

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Citation

If you use this dataset in your research, please cite it as:

@dataset{aliarda_turkishidentitymini,
  author    = {Ali Arda Fincan},
  title     = {TurkishIdentityMini},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/aliarda/TurkishIdentityMini}
}