Composing distributed representations of relational patterns

Sho Takase, Naoaki Okazaki, Kentaro Inui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Learning distributed representations for relation instances is a central technique in downstream NLP applications. In order to address semantic modeling of relational patterns, this paper constructs a new dataset that provides multiple similarity ratings for every pair of relational patterns on the existing dataset (Zeichner et al, 2012). In addition, we conduct a comparative study of different encoders including additive composition, RNN, LSTM, and GRU for composing distributed representations of relational patterns. We also present Gated Additive Composition, which is an enhancement of additive composition with the gating mechanism. Experiments show that the new dataset does not only enable detailed analyses of the different encoders, but also provides a gauge to predict successes of distributed representations of relational patterns in the relation classification task.

Original languageEnglish
Title of host publication54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages2276-2286
Number of pages11
ISBN (Electronic)9781510827585
Publication statusPublished - 2016 Jan 1
Event54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Berlin, Germany
Duration: 2016 Aug 72016 Aug 12

Publication series

Name54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers
Volume4

Other

Other54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
CountryGermany
CityBerlin
Period16/8/716/8/12

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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    Takase, S., Okazaki, N., & Inui, K. (2016). Composing distributed representations of relational patterns. In 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers (pp. 2276-2286). (54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers; Vol. 4). Association for Computational Linguistics (ACL).