Abstract
Arabic dialects present a special problem for natural language processing because there are few resources, they have no standard orthography, and have not been studied much. However, as more and more written dialectal Arabic is found in social media, NLP for Arabic dialects becomes an important goal. We present a methodology for creating a morphological analyzer and a morphological tagger for dialectal Arabic, and we illustrate it on Egyptian and Levantine Arabic. To our knowledge, these are the first analyzer and tagger for Levantine.- Anthology ID:
- C16-1326
- Volume:
- Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Editors:
- Yuji Matsumoto, Rashmi Prasad
- Venue:
- COLING
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 3455–3465
- Language:
- URL:
- https://aclanthology.org/C16-1326
- DOI:
- Cite (ACL):
- Ramy Eskander, Nizar Habash, Owen Rambow, and Arfath Pasha. 2016. Creating Resources for Dialectal Arabic from a Single Annotation: A Case Study on Egyptian and Levantine. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 3455–3465, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Creating Resources for Dialectal Arabic from a Single Annotation: A Case Study on Egyptian and Levantine (Eskander et al., COLING 2016)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/C16-1326.pdf