Journal of Natural Language Processing
Online ISSN : 2185-8314
Print ISSN : 1340-7619
ISSN-L : 1340-7619
Paper
Acquiring Event Relation Knowledge by Learning Cooccurrence Patterns and Fertilizing Cooccurrence Samples
Shuya AbeKentaro InuiYuji Matsumoto
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JOURNAL FREE ACCESS

2009 Volume 16 Issue 5 Pages 5_79-5_100

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Abstract
Aiming at acquiring semantic relations between events from a large corpus, this paper proposes several extensions to a state-of-the-art method originally designed for entity relation extraction. First, expressions of events are defined to specify the class of the acquisition task. Second, the templates of co-occurrence patterns are extended so that they can capture semantic relations between event mentions. Experiments on a Japanese Web corpus show that (a) there are indeed specific co-occurrence patterns useful for event relation acquisition, and (b) For action-effect relation, at least five thousand relation instances are acquired from a 500M-sentence Web corpus with a precision of about 66%.
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© 2009 The Association for Natural Language Processing
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