An alignment-based approach to semi-supervised relation extraction including multiple arguments

Authors:
Seokhwan Kim;Minwoo Jeong;Gary Geunbae Lee;Kwangil Ko;Zino Lee
Affiliations:
Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea;Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea;Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea;Alticast Corp., Seoul, Korea;Alticast Corp., Seoul, Korea
Venue:
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Year:
2008

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Abstract

We present an alignment-based approach to semi-supervised relation extraction task including more than two arguments. We concentrate on improving not only the precision of the extracted result, but also on the coverage of the method. Our relation extraction method is based on an alignment-based pattern matching approach which provides more flexibility of the method. In addition, we extract all relationships including two or more arguments at once in order to obtain the integrated result with high quality. We present experimental results which indicate the effectiveness of our method.