CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms
Shulin Liu1,2; Yubo Chen1,2; Kang Liu1; Jun Zhao1,2
2017
Conference NameAnnual Meeting of Association for Computational Linguistics (ACL 2017)
Conference Date2017-03
Conference PlaceVancouver, Canada
Abstract

This paper tackles the task of event
detection (ED), which involves identifying
and categorizing events. We argue
that arguments provide significant
clues to this task, but they are either
completely ignored or exploited in an
indirect manner in existing detection
approaches. In this work, we propose to
exploit argument information explicitly
for ED via supervised attention mechanisms.
In specific, we systematically
investigate the proposed model under
the supervision of different attention
strategies. Experimental results show
that our approach advances state-ofthe-
arts and achieves the best F1 score
on ACE 2005 dataset.

KeywordEvent Extraction Event Detection Attention Mechanism
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14522
Collection模式识别国家重点实验室_自然语言处理
Corresponding AuthorKang Liu
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Shulin Liu,Yubo Chen,Kang Liu,et al. Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms[C],2017.
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