README.md

---
language:
- tr
license: mit
task_categories:
- text-generation
- question-answering
tags:
- turkish
- identity
- instruction-tuning
- llm-alignment
- nlp
- chatbot
pretty_name: TurkishIdentityMini
size_categories:
- n<1K
dataset_info:
  features:
  - name: instruction
    dtype: string
  - name: output
    dtype: string
  splits:
  - name: train
    num_bytes: 41540
    num_examples: 481
  download_size: 13573
  dataset_size: 41540
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# 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 |

---

## 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.` |

---

## 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

---

## 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):**
```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"))
```

---

## Usage

### With 🤗 Datasets

```python
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

```python
import pandas as pd

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

---

## Acknowledgements

80 rows in this dataset were sourced from [`sts07142/llm-name-identity`](https://huggingface.co/datasets/sts07142/llm-name-identity) and translated into Turkish using AI-assisted translation.

---

## Citation

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

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