Tree kernel-based semantic relation extraction with rich syntactic and semantic information

被引:44
|
作者
Zhou Guodong [1 ]
Qian Longhua [1 ]
Fan Jianxi [1 ]
机构
[1] Soochow Univ, Sch Comp Sci & Technol, Suzhou 215006, Peoples R China
基金
中国国家自然科学基金;
关键词
Semantic relation extraction; Tree kernel-based methods; Context-sensitive convolution tree kernel; Rich semantic relation tree structure; Semantic information; Syntactic information;
D O I
10.1016/j.ins.2009.12.006
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a novel tree kernel-based method with rich syntactic and semantic information for the extraction of semantic relations between named entities. With a parse tree and an entity pair, we first construct a rich semantic relation tree structure to integrate both syntactic and semantic information. And then we propose a context-sensitive convolution tree kernel, which enumerates both context-free and context-sensitive sub-trees by considering the paths of their ancestor nodes as their contexts to capture structural information in the tree structure. An evaluation on the Automatic Content Extraction/Relation Detection and Characterization (ACE RDC) corpora shows that the proposed tree kernel-based method outperforms other state-of-the-art methods. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:1313 / 1325
页数:13
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