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
N1 - Publisher Copyright:
© 2014 Association for Computational Linguistics
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
UR - http://www.scopus.com/inward/citedby.url?scp=84923132098&partnerID=8YFLogxK
M3 - Conference contribution
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 -