Chinese Open Relation Extraction for Knowledge Acquisition

Yuen Hsien Tseng; Lung Hao Lee; Shu Yen Lin; Bo Shun Liao; Mei Jun Liu; Hsin Hsi Chen; Oren Etzioni; Anthony Fader

Chinese Open Relation Extraction for Knowledge Acquisition

Yuen Hsien Tseng, Lung Hao Lee, Shu Yen Lin, Bo Shun Liao, Mei Jun Liu, Hsin Hsi Chen, Oren Etzioni, Anthony Fader

電機工程學系

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

42 引文斯高帕斯（Scopus）

摘要

This study presents the Chinese Open Relation Extraction (CORE) system that is able to extract entity-relation triples from Chinese free texts based on a series of NLP techniques, i.e., word segmentation, POS tagging, syntactic parsing, and extraction rules. We employ the proposed CORE techniques to extract more than 13 million entity-relations for an open domain question answering application. To our best knowledge, CORE is the first Chinese Open IE system for knowledge acquisition.

原文	???core.languages.en_GB???
主出版物標題	EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
發行者	Association for Computational Linguistics (ACL)
頁面	12-16
頁數	5
ISBN（電子）	9781937284992
出版狀態	已出版 - 2014
事件	14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014 - Gothenburg, Sweden 持續時間: 26 4月 2014 → 30 4月 2014

出版系列

名字	EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

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???event.eventtypes.event.conference???	14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014
國家/地區	Sweden
城市	Gothenburg
期間	26/04/14 → 30/04/14

引用此

Tseng, Y. H., Lee, L. H., Lin, S. Y., Liao, B. S., Liu, M. J., Chen, H. H., Etzioni, O., & Fader, A. (2014). Chinese Open Relation Extraction for Knowledge Acquisition. 於 EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference (頁 12-16). (EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference). Association for Computational Linguistics (ACL).

Tseng, Yuen Hsien ; Lee, Lung Hao ; Lin, Shu Yen 等. / Chinese Open Relation Extraction for Knowledge Acquisition. EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics (ACL), 2014. 頁 12-16 (EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference).

@inproceedings{861757757dad4b7eb08fc8483889ca25,

title = "Chinese Open Relation Extraction for Knowledge Acquisition",

abstract = "This study presents the Chinese Open Relation Extraction (CORE) system that is able to extract entity-relation triples from Chinese free texts based on a series of NLP techniques, i.e., word segmentation, POS tagging, syntactic parsing, and extraction rules. We employ the proposed CORE techniques to extract more than 13 million entity-relations for an open domain question answering application. To our best knowledge, CORE is the first Chinese Open IE system for knowledge acquisition.",

author = "Tseng, {Yuen Hsien} and Lee, {Lung Hao} and Lin, {Shu Yen} and Liao, {Bo Shun} and Liu, {Mei Jun} and Chen, {Hsin Hsi} and Oren Etzioni and Anthony Fader",

note = "Publisher Copyright: {\textcopyright} 2014 Association for Computational Linguistics; 14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014 ; Conference date: 26-04-2014 Through 30-04-2014",

year = "2014",

language = "???core.languages.en_GB???",

series = "EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference",

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

pages = "12--16",

booktitle = "EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference",

}

Tseng, YH, Lee, LH, Lin, SY, Liao, BS, Liu, MJ, Chen, HH, Etzioni, O & Fader, A 2014, Chinese Open Relation Extraction for Knowledge Acquisition. 於 EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, Association for Computational Linguistics (ACL), 頁 12-16, 14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014, Gothenburg, Sweden, 26/04/14.

Chinese Open Relation Extraction for Knowledge Acquisition. / Tseng, Yuen Hsien; Lee, Lung Hao; Lin, Shu Yen 等.
EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics (ACL), 2014. p. 12-16 (EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference).

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

TY - GEN

T1 - Chinese Open Relation Extraction for Knowledge Acquisition

AU - Tseng, Yuen Hsien

AU - Lee, Lung Hao

AU - Lin, Shu Yen

AU - Liao, Bo Shun

AU - Liu, Mei Jun

AU - Chen, Hsin Hsi

AU - Etzioni, Oren

AU - Fader, Anthony

PY - 2014

Y1 - 2014

N2 - This study presents the Chinese Open Relation Extraction (CORE) system that is able to extract entity-relation triples from Chinese free texts based on a series of NLP techniques, i.e., word segmentation, POS tagging, syntactic parsing, and extraction rules. We employ the proposed CORE techniques to extract more than 13 million entity-relations for an open domain question answering application. To our best knowledge, CORE is the first Chinese Open IE system for knowledge acquisition.

AB - This study presents the Chinese Open Relation Extraction (CORE) system that is able to extract entity-relation triples from Chinese free texts based on a series of NLP techniques, i.e., word segmentation, POS tagging, syntactic parsing, and extraction rules. We employ the proposed CORE techniques to extract more than 13 million entity-relations for an open domain question answering application. To our best knowledge, CORE is the first Chinese Open IE system for knowledge acquisition.

UR - http://www.scopus.com/inward/record.url?scp=84923132098&partnerID=8YFLogxK

M3 - 會議論文篇章

AN - SCOPUS:84923132098

T3 - EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

SP - 12

EP - 16

BT - EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

PB - Association for Computational Linguistics (ACL)

T2 - 14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014

Y2 - 26 April 2014 through 30 April 2014

ER -

Tseng YH, Lee LH, Lin SY, Liao BS, Liu MJ, Chen HH 等. Chinese Open Relation Extraction for Knowledge Acquisition. 於 EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics (ACL). 2014. p. 12-16. (EACL 2014 - 14th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference).

Chinese Open Relation Extraction for Knowledge Acquisition

摘要

出版系列

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指紋

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