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# Camelira: An Arabic Multi-Dialect Morphological Disambiguator

**Authors:** [Ossama Obeid](https://md.mova.elamur.ai/free/en/docs/papers/authors/ossama-obeid/); [Go Inoue](https://md.mova.elamur.ai/free/en/docs/papers/authors/go-inoue/); [Nizar Habash](https://md.mova.elamur.ai/free/en/docs/papers/authors/nizar-habash/) · **Year:** 2022 · **Venue:** Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations **Link:** [aclanthology.org/2022.emnlp-demos.32](https://aclanthology.org/2022.emnlp-demos.32/) · library `aclbulk-2022-obeid-camelira-arabic-multi-dialect-morphological` · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**11** citations](https://openalex.org/works?filter=cites:W4385573074) openalex · 2026-10-18[**17** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2022-obeid-camelira-arabic-multi-dialect-morphological/) of the 140673 papers whose bibliographies we read[Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations](https://aclanthology.org/volumes/2022.emnlp-demos/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/2022.emnlp-demos.32/)
- [PDF](https://aclanthology.org/2022.emnlp-demos.32.pdf)
- [DOI 10.18653/v1/2022.emnlp-demos.32](https://doi.org/10.18653/v1/2022.emnlp-demos.32)
- [OpenAlex](https://openalex.org/W4385573074)

**Authors (3)**

1. [Ossama Obeid](https://openalex.org/A5080300851) h 12 · 765 citations · 30 works
2. [Go Inoue](https://openalex.org/A5112548463) h 7 · 147 citations · 22 works
3. [Nizar Habash](https://openalex.org/A5084517393) [ORCID](https://orcid.org/0000-0002-1831-3457) · h 57 · 12233 citations · 359 works

Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart.

## What it is about

Camelira is a public web interface that disambiguates Arabic sentences in four varieties: MSA, Egyptian, Gulf and Levantine. Its disambiguator is an existing tagger (Inoue et al., 2022) on top of a morphological analyzer. A dialect identifier, a reimplementation of Salameh et al. (2018), picks the variety-specific disambiguator when the user does not name one. Unlike MADAMIRA or Farasa, the interface shows every analysis of a word with its score, not only the top one. On the DEV split, full-tag accuracy is 95.9% for MSA, 90.5% for Egyptian, 93.8% for Gulf and 85.5% for Levantine (POS-only: 98.7, 94.0, 96.6, 92.7). The dialect identifier reaches 93.5% on TEST, against 93.6% for the original. It is a demonstration paper and reports no new model.

## Ideas

- I1. Keep the alternatives. The interface lists every analysis with its disambiguation score. When Mova's segmenter or parser has a second-best reading, the explanation should return it with its score, so a wrong choice can be seen and checked.
- I2. Route by variety. A small identifier chooses which disambiguator runs. For Aramaic, `tools/langseg` already labels segments (arc, arc-x-targum, tmr, jpa, arc-x-zohar); a rule-based or small statistical identifier could choose the variety-specific lexicon and tests.
- I3. Report two levels per variety. The paper gives full-tag and POS accuracy separately for each variety, and the gap between varieties (85.5 against 95.9 for full tags) is itself a finding. Mova's tests for `tools/hbo` and the Aramaic tools should report the same two levels per variety.

## For Mova

I1 is for `world` and the explanation of parses. I2 is for `tools/langseg` and the variety choice in `languages/arc/`. I3 is a measurement table for `tools/hbo` and [Aramaic in Mova: what it would need](https://md.mova.elamur.ai/free/en/docs/languages/arc/mova/).

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/2022.emnlp-demos.32](https://doi.org/10.18653/v1/2022.emnlp-demos.32)

```
@inproceedings{obeid2022camelira,
  title = {{Camelira: An Arabic Multi-Dialect Morphological Disambiguator}},
  author = {Obeid, Ossama and Inoue, Go and Habash, Nizar},
  booktitle = {Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  year = {2022},
  doi = {10.18653/v1/2022.emnlp-demos.32},
  url = {https://doi.org/10.18653/v1/2022.emnlp-demos.32}
}
```

- [← previous Transfer Learning for Less-Resourced Semitic Languages Speech Recognition: the Case of Amharic](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2020-woldemariam-transfer-learning-less-resourced-semitic/)
- [next → Beyond Concatenative Morphology: Applying OntoLex-Morph to Maltese](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2023-ionov-beyond-concatenative-morphology-applying-ontolex/)
- [↑ back to Semitic languages](https://md.mova.elamur.ai/free/en/docs/papers/sem/)

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