TajikNLPWorld/TajPersParallelCorpus

Dataset Card for Tajik–Persian Parallel Corpus

Dataset Details

Dataset Description

The Tajik–Persian Parallel Corpus is a large-scale parallel corpus containing 328,253 aligned Tajik–Persian sentence pairs collected from multiple sources, including news, poetry, prose, lexical resources, and named-entity lists. It is intended for machine translation, cross-lingual retrieval, linguistic analysis, tokenizer evaluation, and other NLP tasks.

• Curated by: TajikNLPWorld
• Language(s) (NLP): Tajik (tg), Persian (fa)
• 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 (sentence pairs, literary excerpts, news fragments, lexical items) remain the property of their respective authors and publishers. They are not owned by the TajikNLPWorld team and are not covered by the Apache 2.0 license.
• The structured compilation, metadata, and any original annotations created by TajikNLPWorld 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/TajikNLPWorld/TajPersParallelCorpus
• Papers:
  • Arabov, M. K. (2026). A Systematic Benchmark of Machine Transliteration Models for the Tajik‑Farsi Language Pair: A Comparative Study from Rule‑Based to Transformer Architectures. arXiv preprint arXiv:2605.02270.
  • Arabov, M. K. (2026). Character‑Level Transformer for Tajik‑Persian Transliteration with a Parallel Lexical Corpus. In Proceedings of the 2nd Workshop on NLP for Languages Using Arabic Script (AbjadNLP), pages 75–83, Rabat, Morocco. Association for Computational Linguistics.
  • Arabov, M. K. (2026). TajPersLexon: A Tajik‑Persian Lexical Resource and Hybrid Model for Cross‑Script Low‑Resource NLP. In Proceedings of the First Workshop on NLP and LLMs for the Iranian Language Family (SilkRoadNLP 2026), pages 29–37, Rabat, Morocco. Association for Computational Linguistics.

Uses

Direct Use

The dataset is intended for:

• Tajik–Persian machine translation
• Cross-lingual lexical studies
• Subword tokenization experiments
• Corpus linguistics
• Named-entity and domain adaptation research
• Sentence similarity and cross-lingual retrieval

Out-of-Scope Use

• Redistribution of verbatim sentence pairs without permission from original copyright holders.
• Any use that violates the rights of content creators whose texts are included.
• Creation of misleading or harmful content based on the corpus.

Dataset Structure

Data Fields

Field	Type	Description
farsi	string	Persian side of the aligned pair
tajik	string	Tajik side of the aligned pair
category	string	File-based category (e.g., poetry_parts, prose_parts, words)
source	string	Optional source label if available

Data Splits

The dataset contains a single split (train) with all 328,253 records.

Category Distribution

Category	Count	Share
poetry_parts	154,891	47.19%
masnavi	38,972	11.87%
unique_tajik_words	38,151	11.62%
shahnameh	24,819	7.56%
prose_parts	23,936	7.29%
paranames_per	20,101	6.12%
words	14,292	4.35%
paranames_loc	9,586	2.92%
dr	1,542	0.47%
jj	803	0.24%
paranames_org	722	0.22%
bbc	438	0.13%

Dataset Creation

Curation Rationale

The corpus was created to address the lack of large-scale parallel resources for the Tajik–Persian language pair. It aggregates data from poetry, prose, news, lexical resources, and named-entity lists to support machine translation, transliteration, and cross-lingual research.

Source Data

Data Collection and Processing

Data were collected from publicly available sources. Processing steps included:

1. Alignment of Tajik and Persian sentence pairs.
2. Cleaning and normalization of text.
3. Classification into categories based on source file.
4. Deduplication and quality filtering.

Who are the source data producers?

The original texts were produced by poets, writers, journalists, and lexicographers. The compilation and alignment were performed by TajikNLPWorld.

Annotations

No additional manual annotations were added. The category field was derived from the original source files.

Personal and Sensitive Information

The corpus consists of publicly available literary, news, and lexical content. No personal or sensitive information is intentionally included.

Bias, Risks, and Limitations

• The corpus is heterogeneous and domain-imbalanced.
• Some categories (especially poetic and literary text) are much larger than others.
• Token counts are based on whitespace tokenization.
• Source labels are mostly unavailable (unknown).

Recommendations

• Use appropriate sampling or weighting to handle domain imbalance.
• Respect original copyrights when redistributing excerpts (see Licensing & Legal Notice).
• For translation tasks, consider filtering by category to match the target domain.

Citation

BibTeX (dataset):

@dataset{tajpersparallelcorpus,
  title        = {Tajik–Persian Parallel Corpus},
  author       = {TajikNLPWorld},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/TajikNLPWorld/TajPersParallelCorpus}
}

APA (dataset): TajikNLPWorld. (2026). Tajik–Persian Parallel Corpus [Data set]. Hugging Face. https://huggingface.co/datasets/TajikNLPWorld/TajPersParallelCorpus

Related Publications

BibTeX:

@article{arabov2026transliteration,
  author = {Arabov, Mullosharaf K.},
  title = {A Systematic Benchmark of Machine Transliteration Models for the Tajik-Farsi Language Pair: A Comparative Study from Rule-Based to Transformer Architectures},
  journal = {arXiv preprint arXiv:2605.02270},
  year = {2026}
}

@inproceedings{arabov2026character,
  author = {Arabov, Mullosharaf K.},
  title = {Character-Level Transformer for Tajik-Persian Transliteration with a Parallel Lexical Corpus},
  booktitle = {Proceedings of the 2nd Workshop on NLP for Languages Using Arabic Script (AbjadNLP)},
  pages = {75--83},
  year = {2026},
  address = {Rabat, Morocco},
  publisher = {Association for Computational Linguistics}
}

@inproceedings{arabov2026tajperslexon,
  author = {Arabov, Mullosharaf K.},
  title = {TajPersLexon: A Tajik-Persian Lexical Resource and Hybrid Model for Cross-Script Low-Resource NLP},
  booktitle = {Proceedings of the First Workshop on NLP and LLMs for the Iranian Language Family (SilkRoadNLP 2026)},
  pages = {29--37},
  year = {2026},
  address = {Rabat, Morocco},
  publisher = {Association for Computational Linguistics}
}

APA:

• Arabov, M. K. (2026). A Systematic Benchmark of Machine Transliteration Models for the Tajik‑Farsi Language Pair: A Comparative Study from Rule‑Based to Transformer Architectures. arXiv preprint arXiv:2605.02270.
• Arabov, M. K. (2026). Character‑Level Transformer for Tajik‑Persian Transliteration with a Parallel Lexical Corpus. In Proceedings of the 2nd Workshop on NLP for Languages Using Arabic Script (AbjadNLP) (pp. 75–83). Association for Computational Linguistics.
• Arabov, M. K. (2026). TajPersLexon: A Tajik‑Persian Lexical Resource and Hybrid Model for Cross‑Script Low‑Resource NLP. In Proceedings of the First Workshop on NLP and LLMs for the Iranian Language Family (SilkRoadNLP 2026) (pp. 29–37). Association for Computational Linguistics.

Glossary

• Parallel corpus – a collection of aligned texts in two or more languages.
• Transliteration – conversion of text from one script to another.

More Information

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

Dataset Card Authors

• TajikNLPWorld (community)

Dataset Card Contact

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