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2010

Arabic Named Entity Recognition: Using Features Extracted from Noisy Data

9 years 3 months ago
Arabic Named Entity Recognition: Using Features Extracted from Noisy Data
Building an accurate Named Entity Recognition (NER) system for languages with complex morphology is a challenging task. In this paper, we present research that explores the feature space using both gold and bootstrapped noisy features to build an improved highly accurate Arabic NER system. We bootstrap noisy features by projection from an Arabic-English parallel corpus that is automatically tagged with a baseline NER system. The feature space covers lexical, morphological, and syntactic features. The proposed approach
Yassine Benajiba, Imed Zitouni, Mona T. Diab, Paol
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where ACL
Authors Yassine Benajiba, Imed Zitouni, Mona T. Diab, Paolo Rosso
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