Using Ambiguity Detection to Streamline Linguistic Annotation
Wajdi Zaghouani, Abdelati Hawwari, Sawsan Alqahtani, Houda Bouamor, Mahmoud Ghoneim, Mona Diab, Kemal Oflazer
Abstract
Arabic writing is typically underspecified for short vowels and other markups, referred to as diacritics. In addition to the lexical ambiguity exhibited in most languages, the lack of diacritics in written Arabic adds another layer of ambiguity which is an artifact of the orthography. In this paper, we present the details of three annotation experimental conditions designed to study the impact of automatic ambiguity detection, on annotation speed and quality in a large scale annotation project.- Anthology ID:
- W16-4115
- Volume:
- Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Editors:
- Dominique Brunato, Felice Dell’Orletta, Giulia Venturi, Thomas François, Philippe Blache
- Venue:
- CL4LC
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 127–136
- Language:
- URL:
- https://aclanthology.org/W16-4115
- DOI:
- Cite (ACL):
- Wajdi Zaghouani, Abdelati Hawwari, Sawsan Alqahtani, Houda Bouamor, Mahmoud Ghoneim, Mona Diab, and Kemal Oflazer. 2016. Using Ambiguity Detection to Streamline Linguistic Annotation. In Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC), pages 127–136, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Using Ambiguity Detection to Streamline Linguistic Annotation (Zaghouani et al., CL4LC 2016)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/W16-4115.pdf