A Novel Composite Kernel Approach to Chinese Entity Relation Extraction

Authors:
Ji Zhang;You Ouyang;Wenjie Li;Yuexian Hou
Affiliations:
Department of Computing, The Hong Kong Polytechnic University, Hong Kong and School of Computer Science and Technology, Tianjin University, China;Department of Computing, The Hong Kong Polytechnic University, Hong Kong;Department of Computing, The Hong Kong Polytechnic University, Hong Kong;School of Computer Science and Technology, Tianjin University, China
Venue:
ICCPOL '09 Proceedings of the 22nd International Conference on Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy
Year:
2009

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Abstract

Relation extraction is the task of finding semantic relations between two entities from the text. In this paper, we propose a novel composite kernel for Chinese relation extraction. The composite kernel is defined as the combination of two independent kernels. One is the entity kernel built upon the non-content-related features. The other is the string semantic similarity kernel concerning the content information. Three combinations, namely linear combination, semi-polynomial combination and polynomial combination are investigated. When evaluated on the ACE 2005 Chinese data set, the results show that the proposed approach is effective.