Abstract
We investigate the tasks of general morphological tagging, diacritization, and lemmatization for Arabic. We show that for all tasks we consider, both modeling the lexeme explicitly, and retuning the weights of individual classifiers for the specific task, improve the performance.
Original language | English (US) |
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Pages (from-to) | 117-120 |
Number of pages | 4 |
Journal | Proceedings of the Annual Meeting of the Association for Computational Linguistics |
State | Published - 2008 |
Event | 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL 2008 - Columbus, United States Duration: Jun 16 2008 → Jun 17 2008 |
ASJC Scopus subject areas
- Computer Science Applications
- Linguistics and Language
- Language and Linguistics