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ACL
2007

Detecting Semantic Relations between Named Entities in Text Using Contextual Features

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Detecting Semantic Relations between Named Entities in Text Using Contextual Features
This paper proposes a supervised learning method for detecting a semantic relation between a given pair of named entities, which may be located in different sentences. The method employs newly introduced contextual features based on centering theory as well as conventional syntactic and word-based features. These features are organized as a tree structure and are fed into a boosting-based classification algorithm. Experimental results show the proposed method outperformed prior methods, and increased precision and recall by 4.4% and 6.7%.
Toru Hirano, Yoshihiro Matsuo, Gen-ichiro Kikui
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ACL
Authors Toru Hirano, Yoshihiro Matsuo, Gen-ichiro Kikui
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