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Constraint-based question answering with knowledge graph

  • Harbin Institute of Technology
  • Microsoft USA
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

WebQuestions and SimpleQuestions are two benchmark data-sets commonly used in recent knowledge-based question answering (KBQA) work. Most questions in them are 'simple' questions which can be answered based on a single relation in the knowledge base. Such data-sets lack the capability of evaluating KBQA systems on complicated questions. Motivated by this issue, we release a new data-set, namely ComplexQuestions1 aiming to measure the quality of KBQA systems on 'multi-constraint' questions which require multiple knowledge base relations to get the answer. Beside, we propose a novel systematic KBQA approach to solve multi-constraint questions. Compared to state-of-the-art methods, our approach not only obtains comparable results on the two existing benchmark data-sets, but also achieves significant improvements on the ComplexQuestions.

Original languageEnglish
Title of host publicationCOLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016
Subtitle of host publicationTechnical Papers
PublisherAssociation for Computational Linguistics, ACL Anthology
Pages2503-2514
Number of pages12
ISBN (Print)9784879747020
StatePublished - 2016
Event26th International Conference on Computational Linguistics, COLING 2016 - Osaka, Japan
Duration: 11 Dec 201616 Dec 2016

Publication series

NameCOLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016: Technical Papers

Conference

Conference26th International Conference on Computational Linguistics, COLING 2016
Country/TerritoryJapan
CityOsaka
Period11/12/1616/12/16

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