toiar/english-pnar-parallel-corpus-100k

English–Pnar Parallel Corpus (100k)

The English–Pnar Parallel Corpus is a bilingual dataset designed to support the development of Natural Language Processing (NLP) tools for the Pnar language. The dataset contains 109,122 aligned sentence pairs between English and Pnar.

Pnar is an Austroasiatic language spoken mainly in the Jaintia Hills region of Meghalaya, India. Due to the limited availability of digital linguistic resources, this dataset aims to help researchers build and evaluate translation systems and other NLP models for this low-resource language.

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Overview

Property	Value
Creator	Toiarbor Mawlieh
Languages	English (en) ⇄ Pnar (pbv)
Sentence Pairs	109,122
Intended Task	Machine Translation

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Dataset Structure

A typical row in the dataset contains a single parallel sentence pair:

{
  "english": "They are learning new skills to improve their future.",
  "pnar": "Dang sikai ki ya ki sap wa thymme wow pynbha ya ka mynried yong ki."
}

Fields

Field	Description
english	Sentence written in English
pnar	Corresponding translation in Pnar

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Applications

This dataset can be used for:

• Training English ↔ Pnar machine translation models
• Developing multilingual language models
• Building cross-lingual embeddings
• Linguistic research for low-resource Austroasiatic languages
• Supporting digital resources for the Pnar language

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Known Limitations

• The dataset primarily contains general domain text.
• Coverage of specialized vocabulary (legal, medical, technical) is limited.
• Some translations may follow literal structure rather than idiomatic phrasing.
• Sentence lengths are mostly short to moderate.

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Citation

If you use this dataset for research or projects, please cite it as follows:

@dataset{toiar_eng_pnar_corpus_100K_2026,
  title     = {English-Pnar Parallel Corpus (100k)},
  author    = {Toiarbor Mawlieh},
  year      = {2026},
  publisher = {Hugging Face},
  license   = {CC BY-NC 4.0},
  url       = {https://huggingface.co/datasets/toiar/english-pnar-parallel-corpus-100k}
}