CASIA OpenIR  > 综合信息系统研究中心
A Joint Framework for Entity Discovery and Linking in Chinese Questions
Ziqi Lin1,2; Wancheng Ni1; Haidong Zhang1; Yu Liu1; Yiping Yang1
2017-12
Conference Name2017 International Conference on Asian Language Processing (IALP)
Conference Date2017-12
Conference Place新加坡
Abstract

Entity discovery and linking can help to understand the questions semantics and infer answers in question answering systems. In this paper, we study the characteristics of Chinese questions and propose a joint
framework that leverages the mutual dependency between entity discovery and linking to enhance their performances. It jointly connects a joint parsing method based on concept knowledge tree for entity discovery, with candidate entity generation of entity linking. And we also investigate conditional random fields to detect entity mentions and filter
them with candidate entity generation. Experiments show that our proposed method outperforms state-of-the-art methods on a real dataset.

KeywordEntity Discovery Entity Linking Joint Method Question Representation Concept Knowledge Tree
MOST Discipline Catalogue工学::计算机科学与技术(可授工学、理学学位)
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/26219
Collection综合信息系统研究中心
Corresponding AuthorWancheng Ni
Affiliation1.Integrated Information System Research Center, CASIA,
2.University of Chinese Academy of Science
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Ziqi Lin,Wancheng Ni,Haidong Zhang,et al. A Joint Framework for Entity Discovery and Linking in Chinese Questions[C],2017.
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