SEEN: a semantic dependency analyzer for Chinese

Authors:
Jiajun Yan;David B. Bracewell;Fuji Ren;Shingo Kuroiwa
Affiliations:
Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, Tokushima-shi, Japan;Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, Tokushima-shi, Japan;Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, Tokushima-shi, Japan and School of Information Engineering, Beijing University of Po ...;Department of Information Science and Intelligent Systems, Faculty of Engineering, The University of Tokushima, Tokushima-shi, Japan
Venue:
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Year:
2006

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Abstract

Determining the semantic structure of sentences is a difficult but desired task. In this paper, we propose a system for determining semantic dependency in Chinese sentences. The system is composed of 3 main modules; Syntactic analysis, headword assignment, and semantic dependency assignment. For the semantic dependency module, many classifiers are tested. The best is able to achieve an accuracy of just under 84%.