metadata
dataset_info:
features:
- name: id
dtype: int64
- name: title
dtype: string
- name: topic
dtype: string
splits:
- name: train
num_bytes: 40302
num_examples: 267
download_size: 20514
dataset_size: 40302
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language: ba
license: mit
tags:
- bashkir
- low-resource-language
- topic-classification
- news
- task-specific-tuning
pretty_name: Bashqort Topic Classification
size_categories:
- 100<n<1000
Bashqort Topic Classification
Description
A topic classification dataset for Bashkir news headlines. This dataset was created because no publicly available topic classification benchmark exists for Bashkir. It is intended for task‑specific fine‑tuning and evaluation of LLMs adapted to Bashkir.
Data Creation
- Source: Random sampling of headlines from bash.news
- Annotation: Manual labeling by Ilyas Khatipov (native speaker of Bashkir)
- Cleaning: Removed categories with fewer than 17 samples to improve class balance
Class Distribution (after cleaning)
| Topic | Count | Proportion |
|---|---|---|
| Culture (Мәҙәниәт) | 58 | 21.7% |
| Healthcare (Һаулыҡ һаҡлау) | 35 | 13.1% |
| Education (Мәғариф) | 32 | 12.0% |
| Social sphere (Социаль өлкә) | 25 | 9.4% |
| Politics (Сәйәсәт) | 25 | 9.4% |
| Sports (Спорт) | 21 | 7.9% |
| Military service (Хәрби хеҙмәт) | 18 | 6.7% |
| Economy (Иҡтисад) | 18 | 6.7% |
| Incidents (Ваҡиғалар) | 18 | 6.7% |
| Security (Хәүефһеҙлек) | 17 | 6.4% |
Total: 267 headlines (10 classes)
Format
The dataset is provided in CSV/JSON format with the following columns:
title: Bashkir news headline (string)topic: topic label (string, one of the 10 classes)
{
"title": "Өфөлә мәктәптәрҙә яңы уҡыу йылы башланды",
"topic": "Education"
}
Splits
No fixed train/test split. Users are encouraged to create their own splits (e.g., 80/20) for reproducibility.
Intended Use
Task‑specific fine‑tuning of LLMs for topic classification
Zero‑shot and few‑shot evaluation of Bashkir language understanding
Benchmark for future Bashkir NLP work
Licensing
MIT License
Citation
@misc{khudiakova2025bashqorttask,
author = {Khudiakova, Kseniia and Khatipov, Ilyas},
title = {Bashqort Topic Classification: News Headlines with 10 Topics},
year = {2025},
howpublished = {Hugging Face Datasets},
url = {https://huggingface.co/datasets/metuKKhud/bashqort-task}
}
Acknowledgements
Thanks to Ilyas Khatipov for native speaker validation and annotation.