ZORE: A Syntax-based System for Chinese Open Relation Extraction

Likun Qiu

Published 2014 in Conference on Empirical Methods in Natural Language Processing

ABSTRACT

Open Relation Extraction (ORE) overcomes the limitations of traditional IE techniques, which train individual extractors for every single relation type. Systems such as ReVerb, PATTY, OLLIE, and Exemplar have attracted much attention on English ORE. However, few studies have been reported on ORE for languages beyond English. This paper presents a syntax-based Chinese (Zh) ORE system, ZORE, for extracting relations and semantic patterns from Chinese text. ZORE identifies relation candidates from automatically parsed dependency trees, and then extracts relations with their semantic patterns iteratively through a novel double propagation algorithm. Empirical results on two data sets show the effectiveness of the proposed system.

PUBLICATION RECORD

  • Publication year

    2014

  • Venue

    Conference on Empirical Methods in Natural Language Processing

  • Publication date

    2014-10-01

  • Fields of study

    Computer Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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