Entity disambiguation with linkless knowledge bases

Yang Li, Shulong Tan, Huan Sun, Jiawei Han, Dan Roth, Xifeng Yan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Named Entity Disambiguation is the task of disambiguating named entity mentions in natural language text and link them to their corresponding entries in a reference knowledge base (e.g. Wikipedia). Such disambiguation can help add semantics to plain text and distinguish homonymous entities. Previous research has tackled this problem by making use of two types of context-Aware features derived from the reference knowledge base, namely, the context similarity and the semantic relatedness. Both features heavily rely on the cross-document hyperlinks within the knowledge base: The semantic relatedness feature is directly measured via those hyperlinks, while the context similarity feature implicitly makes use of those hyperlinks to expand entity candidates' descriptions and then compares them against the query context. Unfortunately, cross-document hyperlinks are rarely available in many closed domain knowledge bases and it is very expensive to manually add such links. Therefore few algorithms can work well on linkless knowledge bases. In this work, we propose the challenging Named Entity Disambiguation with Linkless Knowledge Bases (LNED) problem and tackle it by leveraging the useful disambiguation evidences scattered across the reference knowledge base. We propose a generative model to automatically mine such evidences out of noisy information. The mined evidences can mimic the role of the missing links and help boost the LNED performance. Experimental results show that our proposed method substantially improves the disambiguation accuracy over the baseline approaches.

Original languageEnglish (US)
Title of host publication25th International World Wide Web Conference, WWW 2016
PublisherInternational World Wide Web Conferences Steering Committee
Pages1261-1270
Number of pages10
ISBN (Electronic)9781450341431
DOIs
StatePublished - Jan 1 2016
Event25th International World Wide Web Conference, WWW 2016 - Montreal, Canada
Duration: Apr 11 2016Apr 15 2016

Publication series

Name25th International World Wide Web Conference, WWW 2016

Other

Other25th International World Wide Web Conference, WWW 2016
CountryCanada
CityMontreal
Period4/11/164/15/16

Keywords

  • Entity Disambiguation
  • Evidence Mining
  • Generative Model
  • Linkless Knowledge Bases

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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