Event argument extraction based on CRF

Authors:
Libin Hou;Peifeng Li;Qiaoming Zhu;Yuan Cao
Affiliations:
Natural Language Processing Lab, Soochow University, Suzhou, Jiangsu, China, School of Computer Science & Technology, Soochow University, Suzhou, Jiangsu, China;Natural Language Processing Lab, Soochow University, Suzhou, Jiangsu, China, School of Computer Science & Technology, Soochow University, Suzhou, Jiangsu, China;Natural Language Processing Lab, Soochow University, Suzhou, Jiangsu, China, School of Computer Science & Technology, Soochow University, Suzhou, Jiangsu, China;Natural Language Processing Lab, Soochow University, Suzhou, Jiangsu, China, School of Computer Science & Technology, Soochow University, Suzhou, Jiangsu, China
Venue:
CLSW'12 Proceedings of the 13th Chinese conference on Chinese Lexical Semantics
Year:
2012

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Abstract

Event argument extraction is an important component of event extraction which plays a decisive role in whether event extraction can be applied to the actual. This paper proposes a method of event argument extraction based on Conditional Random Fields (CRFs). After employing frequently used features, we summarize all the features into five categories, i.e., lexical, semantic, dependency, syntactic and relative-position. More importantly, we propose using semantic role as a specific feature. Great efforts have been made to evaluate the performance by exploring various features and their combination. Experimental results show that semantic role is a good indicator for event argument extraction.