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ACL
2008

Semantic Role Labeling Systems for Arabic using Kernel Methods

9 years 3 months ago
Semantic Role Labeling Systems for Arabic using Kernel Methods
There is a widely held belief in the natural language and computational linguistics communities that Semantic Role Labeling (SRL) is a significant step toward improving important applications, e.g. question answering and information extraction. In this paper, we present an SRL system for Modern Standard Arabic that exploits many aspects of the rich morphological features of the language. The experiments on the pilot Arabic Propbank data shows that our system based on Support Vector Machines and Kernel Methods yields a global SRL F1 score of 82.17%, which improves the current state-of-the-art in Arabic SRL.
Mona T. Diab, Alessandro Moschitti, Daniele Pighin
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ACL
Authors Mona T. Diab, Alessandro Moschitti, Daniele Pighin
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