A novel feature-based approach to Chinese entity relation extraction

Wenjie Li; Peng Zhang; Furu Wei; Yuexian Hou; Qin Lu

A novel feature-based approach to Chinese entity relation extraction

Wenjie Li, Peng Zhang, Furu Wei, Yuexian Hou, Qin Lu

Research output: Journal article publication › Conference article › Academic research › peer-review

Abstract

Relation extraction is the task of finding semantic relations between two entities from text. In this paper, we propose a novel feature-based Chinese relation extraction approach that explicitly defines and explores nine positional structures between two entities. We also suggest some correction and inference mechanisms based on relation hierarchy and co-reference information etc. The approach is effective when evaluated on the ACE 2005 Chinese data set.

Original language	English
Pages (from-to)	89-92
Number of pages	4
Journal	Proceedings of the Annual Meeting of the Association for Computational Linguistics
Publication status	Published - 2008
Event	46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL 2008 - Columbus, United States Duration: 16 Jun 2008 → 17 Jun 2008

ASJC Scopus subject areas

Computer Science Applications
Linguistics and Language
Language and Linguistics

Cite this

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title = "A novel feature-based approach to Chinese entity relation extraction",

abstract = "Relation extraction is the task of finding semantic relations between two entities from text. In this paper, we propose a novel feature-based Chinese relation extraction approach that explicitly defines and explores nine positional structures between two entities. We also suggest some correction and inference mechanisms based on relation hierarchy and co-reference information etc. The approach is effective when evaluated on the ACE 2005 Chinese data set.",

author = "Wenjie Li and Peng Zhang and Furu Wei and Yuexian Hou and Qin Lu",

note = "Publisher Copyright: {\textcopyright} 2008 Association for Computational Linguistics.; 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL 2008 ; Conference date: 16-06-2008 Through 17-06-2008",

year = "2008",

language = "English",

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journal = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",

issn = "0736-587X",

publisher = "Association for Computational Linguistics (ACL)",

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TY - JOUR

T1 - A novel feature-based approach to Chinese entity relation extraction

AU - Li, Wenjie

AU - Zhang, Peng

AU - Wei, Furu

AU - Hou, Yuexian

AU - Lu, Qin

PY - 2008

Y1 - 2008

N2 - Relation extraction is the task of finding semantic relations between two entities from text. In this paper, we propose a novel feature-based Chinese relation extraction approach that explicitly defines and explores nine positional structures between two entities. We also suggest some correction and inference mechanisms based on relation hierarchy and co-reference information etc. The approach is effective when evaluated on the ACE 2005 Chinese data set.

AB - Relation extraction is the task of finding semantic relations between two entities from text. In this paper, we propose a novel feature-based Chinese relation extraction approach that explicitly defines and explores nine positional structures between two entities. We also suggest some correction and inference mechanisms based on relation hierarchy and co-reference information etc. The approach is effective when evaluated on the ACE 2005 Chinese data set.

UR - http://www.scopus.com/inward/record.url?scp=85119986969&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85119986969

SN - 0736-587X

SP - 89

EP - 92

JO - Proceedings of the Annual Meeting of the Association for Computational Linguistics

JF - Proceedings of the Annual Meeting of the Association for Computational Linguistics

T2 - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL 2008

Y2 - 16 June 2008 through 17 June 2008

ER -

A novel feature-based approach to Chinese entity relation extraction

Abstract

ASJC Scopus subject areas

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