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

研究成果: 書貢獻/報告類型會議論文篇章

39 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.

原文英語
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
出版狀態已發佈 - 2014
事件14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014 - Gothenburg, 瑞典
持續時間: 2014 4月 262014 4月 30

出版系列

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

會議

會議14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014
國家/地區瑞典
城市Gothenburg
期間2014/04/262014/04/30

ASJC Scopus subject areas

  • 計算機理論與數學
  • 軟體
  • 語言和語言學

指紋

深入研究「Chinese Open Relation Extraction for Knowledge Acquisition」主題。共同形成了獨特的指紋。

引用此