This dataset contains 24,428 Bashkir-language news and analytical articles collected from various online sources. It is intended for clustering, representation learning, and unsupervised NLP tasks. Each text is accompanied by metadata such as title, source, date, and original category. The corpus is part of the BashkirNLP project, aiming to support low-resource language technology for Bashkir, a Turkic language spoken in Russia.

Curated by: Arabov Mullosharaf Kurbonovich, Khaybullina Svetlana Sergeevna (BashkirNLPWorld)
Language(s) (NLP): Bashkir (ba), Cyrillic script
License: other – see Licensing & Legal Notice below.

Licensing & Legal Notice

This dataset follows the practice established by large web‑crawled corpora such as HPLT and OSCAR:

Original source texts (news articles, analytical pieces) remain the property of their respective authors and publishers. They are not owned by the BashkirNLPWorld team and are not covered by the CC BY‑SA 4.0 license.
The structured compilation, metadata, and any original annotations created during dataset preparation are released under the CC BY‑SA 4.0 license.
Users are solely responsible for ensuring their use of the underlying texts complies with applicable copyright law. For commercial use of verbatim excerpts, permission from the original copyright holders may be required.
A notice‑and‑takedown procedure is in place: rights holders can request removal of specific content by contacting the dataset maintainers (see Dataset Card Contact). We commit to responding within 14 business days and removing disputed content in the next release.

Dataset Sources

Repository: https://huggingface.co/datasets/BashkirNLPWorld/bashkir-news-cluster
Related datasets:

Uses

Direct Use

This dataset is suitable for:

Training word or document embeddings (Word2Vec, FastText, BERT-like models)
Text clustering
Unsupervised topic modeling
Representation learning for downstream NLP tasks
Pre‑training language models for Bashkir

Out-of-Scope Use

The dataset should not be used for tasks requiring gold-standard labels (use the classification versions instead).
It is not intended for generating offensive content or for any unethical applications.
Redistribution of verbatim texts without permission from original copyright holders is prohibited.

Dataset Structure

Data Fields

Field	Type	Description
`content`	string	Full article text
`title`	string	Article title
`category`	string	Original category after normalization (one of 280 categories)
`source`	string	Source file name (e.g., `azatliqorg`, `amanat_articles`)
`content_length`	int64	Length of the text in characters
`resource`	string	Original URL or resource identifier (if available)
`date`	string	Publication date (when available)

Data Splits

The dataset contains a single split (train) with all 24,428 examples. No predefined train/validation/test split is provided; users are free to create their own.

Dataset Creation

Curation Rationale

The goal was to assemble a large, diverse corpus of modern Bashkir texts to support low‑resource NLP research. The collected articles cover a wide range of topics (news, culture, education, religion, sports, etc.), making them useful for general‑purpose language modeling and representation learning.

Source Data

Data Collection and Processing

Articles were collected from 14 Bashkir online sources, including news portals and magazines:

Agidel (журнал)
Akbuzat
Amanat
Azatliq
Bashkortostan gazete
Bashkizi
Henek
Shonkar
Tamasha
Tanburz
Uchbash
Yanshishma (two variants)
Ye102.ru

Processing steps:

Extracted JSONL files from raw HTML.
Removed texts shorter than 50 characters or longer than 10,000 characters.
Removed exact duplicates.
Normalized category names (e.g., яңалыклар → Яңылыҡтар).
Added metadata (source, content length, date where available).

Who are the source data producers?

The articles were originally written by journalists, authors, and contributors of the respective online publications. The BashkirNLPWorld team does not claim ownership of the content; it is used for non‑commercial research purposes under fair use.

Annotations

No manual annotations were added beyond the existing categories. The category field was automatically normalized using a rule‑based dictionary.

Personal and Sensitive Information

The texts are public news articles and do not contain personally identifiable information (PII) beyond what is already published. No additional personal data was collected.

Bias, Risks, and Limitations

Genre bias: The dataset is heavily skewed towards news and journalistic style; it may not represent colloquial or spoken Bashkir.
Source imbalance: Some sources (e.g., Azatliq) dominate the dataset, which may affect generalization.
Date incompleteness: Many articles lack publication dates.
Category normalization errors: Rule‑based normalization may contain inaccuracies.
Copyright constraints: The underlying texts are protected; users must respect original rights (see Licensing & Legal Notice).

Recommendations

Be aware of genre bias and consider balancing data for sub‑domain applications.
For tasks requiring high‑quality labels, use the classification versions of the dataset.
Verify dates if time‑based analysis is planned.
Respect original copyrights when redistributing excerpts.

Citation

BibTeX (dataset):

@dataset{arabov2026bashkircluster,
  author       = {Arabov, Mullosharaf Kurbonovich and Khaybullina, Svetlana Sergeevna},
  title        = {Bashkir News Cluster Dataset},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/BashkirNLPWorld/bashkir-news-cluster}
}

APA (dataset): Arabov, M. K., & Khaybullina, S. S. (2026). Bashkir News Cluster Dataset [Data set]. Hugging Face. https://huggingface.co/datasets/BashkirNLPWorld/bashkir-news-cluster

Glossary

Clustering – grouping similar items together without predefined labels.
Low-resource language – a language with limited digital resources and tools.
Embedding – a vector representation of text.

More Information

For questions, contributions, or feedback, please open an issue on the Hugging Face repository.

Dataset Card Authors

Arabov Mullosharaf Kurbonovich
Khaybullina Svetlana Sergeevna
BashkirNLPWorld

Dataset Card Contact

For questions, takedown requests, or collaboration, please open an issue on the Hugging Face repository:
https://huggingface.co/datasets/BashkirNLPWorld/bashkir-news-cluster/discussions
📧 Direct email: cool.araby@gmail.com

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