Issues in evaluating semantic spaces using word analogies

Tal Linzen

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

    Abstract

    The offset method for solving word analogies has become a standard evaluation tool for vector-space semantic models: It is considered desirable for a space to represent semantic relations as consistent vector offsets. We show that the method's reliance on cosine similarity conflates offset consistency with largely irrelevant neighborhood structure, and propose simple baselines that should be used to improve the utility of the method in vector space evaluation.

    Original languageEnglish (US)
    Title of host publicationProceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP, RepEval 2016 at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
    PublisherAssociation for Computational Linguistics (ACL)
    Pages13-18
    Number of pages6
    ISBN (Electronic)9781945626142
    DOIs
    StatePublished - 2016
    Event1st Workshop on Evaluating Vector-Space Representations for NLP, RepEval 2016 at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Berlin, Germany
    Duration: Aug 7 2016 → …

    Publication series

    NameProceedings of the Annual Meeting of the Association for Computational Linguistics
    ISSN (Print)0736-587X

    Conference

    Conference1st Workshop on Evaluating Vector-Space Representations for NLP, RepEval 2016 at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
    Country/TerritoryGermany
    CityBerlin
    Period8/7/16 → …

    ASJC Scopus subject areas

    • Computer Science Applications
    • Linguistics and Language
    • Language and Linguistics

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