NOPE: A Corpus of Naturally-Occurring Presuppositions in English

Alicia Parrish, Sebastian Schuster, Alex Warstadt, Omar Agha, Soo Hwan Lee, Zhuoye Zhao, Samuel Bowman, Tal Linzen

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

    Abstract

    Understanding language requires grasping not only the overtly stated content, but also making inferences about things that were left unsaid. These inferences include presuppositions, a phenomenon by which a listener learns about new information through reasoning about what a speaker takes as given. Presuppositions require complex understanding of the lexical and syntactic properties that trigger them as well as the broader conversational context. In this work, we introduce the Naturally-Occurring Presuppositions in English (NOPE) Corpus to investigate the context-sensitivity of 10 different types of presupposition triggers and to evaluate machine learning models’ ability to predict human inferences. We fnd that most of the triggers we investigate exhibit moderate variability. We further fnd that transformer-based models draw correct inferences in simple cases involving presuppositions, but they fail to capture the minority of exceptional cases in which human judgments reveal complex interactions between context and triggers.

    Original languageEnglish (US)
    Title of host publicationCoNLL 2021 - 25th Conference on Computational Natural Language Learning, Proceedings
    EditorsArianna Bisazza, Omri Abend
    PublisherAssociation for Computational Linguistics (ACL)
    Pages349-366
    Number of pages18
    ISBN (Electronic)9781955917056
    StatePublished - 2021
    Event25th Conference on Computational Natural Language Learning, CoNLL 2021 - Virtual, Online
    Duration: Nov 10 2021Nov 11 2021

    Publication series

    NameCoNLL 2021 - 25th Conference on Computational Natural Language Learning, Proceedings

    Conference

    Conference25th Conference on Computational Natural Language Learning, CoNLL 2021
    CityVirtual, Online
    Period11/10/2111/11/21

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Human-Computer Interaction
    • Linguistics and Language

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