A fast unified model for parsing and sentence understanding

Samuel R. Bowman, Raghav Gupta, Jon Gauthier, Christopher D. Manning, Abhinav Rastogi, Christopher Potts

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

    Abstract

    Tree-structured neural networks exploit valuable syntactic parse information as they interpret the meanings of sentences. However, they suffer from two key technical problems that make them slow and unwieldy for large-scale NLP tasks: they usually operate on parsed sentences and they do not directly support batched computation. We address these issues by introducing the Stack-augmented Parser-Interpreter Neural Network (SPINN), which combines parsing and interpretation within a single tree-sequence hybrid model by integrating tree-structured sentence interpretation into the linear sequential structure of a shiftreduce parser. Our model supports batched computation for a speedup of up to 25x over other tree-structured models, and its integrated parser can operate on unparsed data with little loss in accuracy. We evaluate it on the Stanford NLI entailment task and show that it significantly outperforms other sentence-encoding models.

    Original languageEnglish (US)
    Title of host publication54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers
    PublisherAssociation for Computational Linguistics (ACL)
    Pages1466-1477
    Number of pages12
    ISBN (Electronic)9781510827585
    DOIs
    StatePublished - 2016
    Event54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Berlin, Germany
    Duration: Aug 7 2016Aug 12 2016

    Publication series

    Name54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers
    Volume3

    Other

    Other54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
    Country/TerritoryGermany
    CityBerlin
    Period8/7/168/12/16

    ASJC Scopus subject areas

    • Language and Linguistics
    • Linguistics and Language

    Fingerprint

    Dive into the research topics of 'A fast unified model for parsing and sentence understanding'. Together they form a unique fingerprint.

    Cite this