Linking named entities to any database

  • Authors:

  • Avirup Sil;Ernest Cronin;Penghai Nie;Yinfei Yang;Ana-Maria Popescu;Alexander Yates

  • Affiliations:

  • Temple University, Philadelphia, PA;St. Joseph's University, Philadelphia, PA;St. Joseph's University, Philadelphia, PA;St. Joseph's University, Philadelphia, PA;Yahoo! Labs, Sunnyvale, CA;Temple University, Philadelphia, PA

  • Venue:
  • EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
  • Year:
  • 2012

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Abstract

Existing techniques for disambiguating named entities in text mostly focus on Wikipedia as a target catalog of entities. Yet for many types of entities, such as restaurants and cult movies, relational databases exist that contain far more extensive information than Wikipedia. This paper introduces a new task, called Open-Database Named-Entity Disambiguation (Open-DB NED), in which a system must be able to resolve named entities to symbols in an arbitrary database, without requiring labeled data for each new database. We introduce two techniques for Open-DB NED, one based on distant supervision and the other based on domain adaptation. In experiments on two domains, one with poor coverage by Wikipedia and the other with near-perfect coverage, our Open-DB NED strategies outperform a state-of-the-art Wikipedia NED system by over 25% in accuracy.