EARL: Joint entity and relation linking for question answering over knowledge graphs

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

Many question answering systems over knowledge graphs rely on entity and relation linking components in order to connect the natural language input to the underlying knowledge graph. Traditionally, entity linking and relation linking have been performed either as dependent sequential tasks or as independent parallel tasks. In this paper, we propose a framework called EARL, which performs entity linking and relation linking as a joint task. EARL implements two different solution strategies for which we provide a comparative analysis in this paper: The first strategy is a formalisation of the joint entity and relation linking tasks as an instance of the Generalised Travelling Salesman Problem (GTSP). In order to be computationally feasible, we employ approximate GTSP solvers. The second strategy uses machine learning in order to exploit the connection density between nodes in the knowledge graph. It relies on three base features and re-ranking steps in order to predict entities and relations. We compare the strategies and evaluate them on a dataset with 5000 questions. Both strategies significantly outperform the current state-of-the-art approaches for entity and relation linking.

Original languageEnglish
Title of host publicationThe Semantic Web – ISWC 2018 : 17th International Semantic Web Conference, Monterey, CA, USA, October 8–12, 2018 : proceedings
EditorsDenny Vrandecic, Kalina Bontcheva, Mari Carmen Suárez-Figueroa, Valentina Presutti, Irene Celino, Marta Sabou, Lucie-Aimee Kaffee, Elena Simperl
Number of pages19
Volume1
Place of PublicationCham
PublisherSpringer Schweiz
Publication date18.09.2018
Pages108-126
ISBN (print)978-3-030-00670-9
ISBN (electronic)978-3-030-00671-6
DOIs
Publication statusPublished - 18.09.2018
Externally publishedYes
Event17th International Semantic Web Conference - ISWC 2018 - Asilomar Conference Grounds, Monterey, United States
Duration: 08.10.201812.10.2018
Conference number: 17
http://iswc2018.semanticweb.org/

Bibliographical note

Funding Information:
Acknowledgement. This work is supported by the funding received from the EU H2020 projects WDAqua (ITN, GA. 642795) and HOBBIT (GA. 688227).

Funding Information:
This work is supported by the funding received from the EU H2020 projects WDAqua (ITN, GA. 642795) and HOBBIT (GA. 688227).

Publisher Copyright:
© Springer Nature Switzerland AG 2018.

    Research areas

  • Entity linking, GTSP, Question answering, Relation linking
  • Informatics

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