---
title: "AdabNER — paper by Mourad and Jarrar (2026)"
description: "Arabic NER research has relied mostly on news, Wikipedia, and social media. 44 references."
authors: ["Aya Mourad", "Mustafa Jarrar"]
year: 2026
venue: "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)"
source: "https://aclanthology.org/2026.acl-long.1541/"
doi: "10.18653/v1/2026.acl-long.1541"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/mourad-2026-adabner-arabic-digital-archive-books/"
---
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# AdabNER: Arabic Digital Archive Books with Nested Entity Recognition

**Authors:** Aya Mourad and [Mustafa Jarrar](https://md.research.elamur.ai/free/en/authors/mustafa-jarrar/) · **Year:** 2026 · **Venue:** [Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)](https://md.research.elamur.ai/free/en/venues/acl/) ([ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.acl-long.1541/) · [PDF](https://aclanthology.org/2026.acl-long.1541.pdf) · [DOI 10.18653/v1/2026.acl-long.1541](https://doi.org/10.18653/v1/2026.acl-long.1541) · [OpenAlex](https://openalex.org/W7166813604)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Arabic NER research has relied mostly on news, Wikipedia, and social media. Literary and non-fiction books, with their historical names, archaic units, and layered entity structures, have had no dedicated resource. The authors fill this gap with AdabNER, a nested NER corpus built from Modern Standard Arabic books in the Hindawi Library. They annotated the opening 6,000 words of 138 books from ten genres published between the 1880s and the 2020s. The annotation scheme extends the Wojood nested framework to 21 entity types. It reinstates the OntoNotes categories WORK_OF_ART and NORP and adjusts several definitions for the literary domain.

For baselines, the authors fine-tuned five Arabic BERT encoders and tested five LLMs with 5-shot prompting. Fine-tuned encoders clearly beat in-context learning. Models trained on AdabNER transferred poorly to Wojood, and the reverse was also true. Training on both corpora together nearly erased this gap. The resource fills a domain gap in Arabic NER, and the transfer results suggest that robust systems need training data from several domains.

## Key points
- Corpus size: about 876K tokens, 78,530 entity mentions, 21 entity types, and 18.96% of mentions nested. The corpus and its guidelines are openly available on Zenodo (DOI 10.5281/zenodo.19468385).
- Best supervised model: AraBERTv2 reached micro-F1 0.86 on stratified splits and 0.83 on leave-book-out splits.
- LLM baselines: Gemini 3 Pro scored highest among the LLMs at F1 0.59, well below the fine-tuned encoders.
- Domain shift: Maximum Mean Discrepancy analysis found the largest shift between AdabNER and Wojood for PERCENT (0.480) and LAW (0.445), and the smallest for TIME (0.152) and PERS (0.161).
- Joint training: training AraBERTv2 on both AdabNER and Wojood kept the F1 drop under 1% relative to in-domain results on each test set. This was tested on only one domain pair, since Wojood is the sole MSA nested benchmark.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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## Cite

Cite as: Aya Mourad and Mustafa Jarrar. 2026. AdabNER: Arabic Digital Archive Books with Nested Entity Recognition. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

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

```bibtex
@inproceedings{mourad2026adabner,
  title = {{AdabNER: Arabic Digital Archive Books with Nested Entity Recognition}},
  author = {Aya Mourad and Mustafa Jarrar},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.1541},
  url = {https://doi.org/10.18653/v1/2026.acl-long.1541}
}
```

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*Updated 1 November 2026*