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Arabic Sentence Segmentation Across Genres and Punctuation Conditions

What it is about

Arabic sentence boundaries are hard to find because punctuation is sparse, inconsistent or absent in many texts, and clauses are often joined by conjunctions such as wa- and fa-. The authors build ARASEG, a corpus of 2,187 documents, about 121,600 sentences and 1.45M tokens from 30 sources in eight genres (children, education, literature, media, poetry, politics, religion, wiki), split at document level. Segmentation is a binary decision per token, tested under four settings that keep or remove punctuation and paragraph breaks. They compare rule and frequency baselines, a fine-tuned CAMeLBERT, dependency-parser models trained on silver trees, and LLMs. Lightweight supervised encoders beat the LLMs, most clearly under the hardest conditions. About 39% of boundaries are word-based (no punctuation mark); a full stop is reliable in wiki and literature but not in poetry or religious text.

Ideas

For Mova

I1 and I2 belong to a future Arabic sentence splitter, planned beside tools/langseg (which cuts by script and language, not by sentence). I3 is a test for gparse. I4 is the evaluation rule for treebanks/ar. Mova has no Arabic grammar chapters yet, so nothing goes into languages/.

Cite

The paper itself, not this card. BibTeX from the library's record of the work. arXiv 2606.08025

@misc{elkholy2026arabic,
  title = {{Arabic Sentence Segmentation Across Genres and Punctuation Conditions}},
  author = {Elkholy, Mohammed and Elmadani, Khalid N. and Habash, Nizar and Alhafni, Bashar},
  year = {2026},
  eprint = {2606.08025},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2606.08025}
}

References

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