Entity Linking in Web Tables with Multiple Linked Knowledge Bases

  • Tianxing WuEmail author
  • Shengjia Yan
  • Zhixin Piao
  • Liang Xu
  • Ruiming Wang
  • Guilin Qi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10055)


The World-Wide Web contains a large scale of valuable relational data, which are embedded in HTML tables (i.e. Web tables). To extract machine-readable knowledge from Web tables, some work tries to annotate the contents of Web tables as RDF triples. One critical step of the annotation is entity linking (EL), which aims to map the string mentions in table cells to their referent entities in a knowledge base (KB). In this paper, we present a new approach for EL in Web tables. Different from previous work, the proposed approach replaces a single KB with multiple linked KBs as the sources of entities to improve the quality of EL. In our approach, we first apply a general graph-based algorithm to EL in Web tables with each single KB. Then, we leverage the existing and newly learned “sameAs” relations between the entities from different KBs to help improve the results of EL in the first step. We conduct experiments on the sampled Web tables with, which consists of three linked encyclopedic KBs. The experimental results show that our approach outperforms the state-of-the-art table’s EL methods in different evaluation metrics.


Entity linking Web tables Linked knowledge bases 



This work is supported in part by the National Natural Science Foundation of China (NSFC) under Grant No. 61272378, the 863 Program under Grant No. 2015AA015406 and the Research Innovation Program for College Graduates of Jiangsu Province under Grant No. KYLX16_0295.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Tianxing Wu
    • 1
    Email author
  • Shengjia Yan
    • 1
  • Zhixin Piao
    • 1
  • Liang Xu
    • 1
  • Ruiming Wang
    • 1
  • Guilin Qi
    • 1
  1. 1.School of Computer Science and EngineeringSoutheast UniversityNanjingChina

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