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:
Bibkey:
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)
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PDF:
https://preview.aclanthology.org/nschneid-patch-1/W16-4115.pdf