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Entity Linking in Queries: Efficiency vs. Effectiveness

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Advances in Information Retrieval (ECIR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10193))

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Abstract

Identifying and disambiguating entity references in queries is one of the core enabling components for semantic search. While there is a large body of work on entity linking in documents, entity linking in queries poses new challenges due to the limited context the query provides coupled with the efficiency requirements of an online setting. Our goal is to gain a deeper understanding of how to approach entity linking in queries, with a special focus on how to strike a balance between effectiveness and efficiency. We divide the task of entity linking in queries to two main steps: candidate entity ranking and disambiguation, and explore both unsupervised and supervised alternatives for each step. Our main finding is that best overall performance (in terms of efficiency and effectiveness) can be achieved by employing supervised learning for the entity ranking step, while tackling disambiguation with a simple unsupervised algorithm. Using the Entity Recognition and Disambiguation Challenge platform, we further demonstrate that our recommended method achieves state-of-the-art performance.

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Notes

  1. 1.

    http://webscope.sandbox.yahoo.com/.

  2. 2.

    It is important to note that Y-ERD contains queries that have been reformulated (often only slightly so) during the course of a search session; we ensure that queries from the same session are assigned to the same fold when using cross-validation.

  3. 3.

    Carmel et al. [3] do not report on the efficiency of the approaches and the online leaderboard is no longer available, hence we present only effectiveness results from Cornolti et al. [6].

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Authors and Affiliations

  1. Norwegian University of Science and Technology, Trondheim, Norway

    Faegheh Hasibi & Svein Erik Bratsberg

  2. University of Stavanger, Stavanger, Norway

    Krisztian Balog

Authors
  1. Faegheh Hasibi
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  2. Krisztian Balog
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  3. Svein Erik Bratsberg
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Corresponding author

Correspondence to Faegheh Hasibi .

Editor information

Editors and Affiliations

  1. University of Glasgow , Glasgow, United Kingdom

    Joemon M Jose

  2. TU Delft - EWI/ST/WIS , Delft, The Netherlands

    Claudia Hauff

  3. Middle East Technical University , Ankara, Turkey

    Ismail Sengor Altıngovde

  4. Open University , Milton Keynes, United Kingdom

    Dawei Song

  5. Signal Media , London, United Kingdom

    Dyaa Albakour

  6. Toronto, Canada

    Stuart Watt

  7. JohnTait.net Ltd. and BCS IRSG , Sunderland, United Kingdom

    John Tait

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Hasibi, F., Balog, K., Bratsberg, S.E. (2017). Entity Linking in Queries: Efficiency vs. Effectiveness. In: Jose, J., et al. Advances in Information Retrieval. ECIR 2017. Lecture Notes in Computer Science(), vol 10193. Springer, Cham. https://doi.org/10.1007/978-3-319-56608-5_4

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  • DOI: https://doi.org/10.1007/978-3-319-56608-5_4

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  • Online ISBN: 978-3-319-56608-5

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