Using Coreference and Surrounding Contexts for Entity Linking

被引:0
|
作者
Huynh, Huy M. [1 ,2 ,3 ]
Nguyen, Trong T. [2 ]
Cao, Tru H. [1 ,2 ]
机构
[1] Univ Technol VNUHCM, Ho Chi Minh City, Vietnam
[2] John Von Neumann Inst VNUHCM, Ho Chi Minh City, Vietnam
[3] Ton Duc Thang Univ, Ho Chi Minh City, Vietnam
来源
PROCEEDINGS OF 2013 IEEE RIVF INTERNATIONAL CONFERENCE ON COMPUTING AND COMMUNICATION TECHNOLOGIES: RESEARCH, INNOVATION, AND VISION FOR THE FUTURE (RIVF) | 2013年
关键词
entity disambiguation; wikification; coreference; machine learning;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Ambiguity in meanings of words or phrases in a document is considered one of the most primary barriers in natural language processing. In this work, we address the task of identifying and linking mentions of entities into correct referents described in a given knowledge base. To deal with it, we propose a supervised learning method for ranking candidate entities in combination with exploiting a heuristic and coreference relations among mentions in a document. Furthermore, another advantage of our method is its simplicity and effectiveness with using much fewer features than other systems. The results from evaluation on TAC-KBP 2012 datasets show that our combination is efficient and this method has a comparable performance to the state-of-the-art ones.
引用
收藏
页码:1 / 5
页数:5
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