A framework for Distributional Formal Semantics

Noortje J. Venhuizen, Petra Hendriks, Matthew Crocker, Harm Brouwer

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

    4 Citations (Scopus)
    157 Downloads (Pure)

    Abstract

    Formal semantics and distributional semantics offer complementary strengths in capturing the meaning of natural language. As such, a considerable amount of research has sought to unify them, either by augmenting formal semantic systems with a distributional component, or by defining a formal system on top of distributed representations. Arriving at such a unified framework has, however, proven extremely challenging. One reason for this is that formal and distributional semantics operate on a fundamentally different `representational currency': formal semantics defines meaning in terms of models of the world, whereas distributional semantics defines meaning in terms of linguistic co-occurrence. Here, we pursue an alternative approach by deriving a vector space model that defines meaning in a distributed manner relative to formal models of the world. We will show that the resulting Distributional Formal Semantics offers probabilistic distributed representations that are also inherently compositional, and that naturally capture quantification and entailment. We moreover show that, when used as part of a neural network model, these representations allow for capturing incremental meaning construction and probabilistic inferencing. This framework thus lays the groundwork for an integrated distributional and formal approach to meaning.
    Original languageEnglish
    Title of host publicationLogic, Language, Information, and Computation
    Subtitle of host publication26th International Workshop, WoLLIC 2019 Utrecht, The Netherlands, July 2-5, 2019 Proceedings
    EditorsRosalie Iemhoff, Michael Moortgat, Ruy de Queiroz
    Place of PublicationBerlin
    PublisherSpringer
    Pages633-646
    Number of pages14
    ISBN (Electronic)978-3-662-59533-6
    ISBN (Print)978-3-662-59532-9
    DOIs
    Publication statusPublished - Jun-2019

    Publication series

    NameLecture Notes in Computer Science
    Volume11541
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

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