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XLink: An Unsupervised Bilingual Entity Linking System

  • Jing Zhang
  • Yixin Cao
  • Lei Hou
  • Juanzi LiEmail author
  • Hai-Tao Zheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10565)

Abstract

Entity linking is a task of linking mentions in text to the corresponding entities in a knowledge base. Recently, entity linking has received considerable attention and several online entity linking systems have been published. In this paper, we build an online bilingual entity linking system XLink, which is based on Wikipeida and Baidu Baike. XLink conducts two steps to link the mentions in the input document to entities in knowledge base, namely mention parsing and entity disambiguation. To eliminate dependency of language, we conduct mention parsing without any named entity recognition tools. To ensure the correctness of linking results, we propose an unsupervised generative probabilistic method and utilize text and knowledge joint representations to perform entity disambiguation. Experiments show that our system gets a state-of-the-art performance and a high time efficiency.

Keywords

Entity linking system Entity disambiguation Mention detection 

Notes

Acknowledgements

The work is supported by 973 Program (No. 2014CB340504), NSFC key project (No. 61533018, 61661146007), Fund of Online Education Research Center, Ministry of Education (No. 2016ZD102), THUNUS NExT Co-Lab, National Natural Science Foundation of China (Grant No. 61375054) and Natural Science Foundation of Guangdong Province (Grant No. 2014A030313745).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jing Zhang
    • 1
  • Yixin Cao
    • 1
  • Lei Hou
    • 1
  • Juanzi Li
    • 1
    Email author
  • Hai-Tao Zheng
    • 1
  1. 1.Department of Computer Science and TechnologyTsinghua UniversityBeijingPeople’s Republic of China

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