Joint modeling of argument identification and role determination in Chinese event extraction with discourse-level information

Authors:
Peifeng Li;Qiaoming Zhu;Guodong Zhou
Affiliations:
School of Computer Science & Technology, Soochow University, Suzhou, China;School of Computer Science & Technology, Soochow University, Suzhou, China;School of Computer Science & Technology, Soochow University, Suzhou, China
Venue:
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Year:
2013

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Abstract

Argument extraction is a challenging task in event extraction. However, most of previous studies focused on intra-sentence information and failed to extract inter-sentence arguments. This paper proposes a discourse-level joint model of argument identification and role determination to infer those inter-sentence arguments in a discourse. Moreover, to better represent the relationship among relevant event mentions and the relationship between an event mention and its arguments in a discourse, this paper introduces various kinds of corpus-based and discourse-based constraints in the joint model, either automatically learned or linguistically motivated. Evaluation on the ACE 2005 Chinese corpus justifies the effectiveness of our joint model over a strong baseline in Chinese argument extraction, in particular argument identification.