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Verb Phrase Ellipsis Resolution Using Discriminative and Margin-Infused Algorithms

Kian Kenyon-Dean,J. Cheung,Doina Precup

Published 2016 in Conference on Empirical Methods in Natural Language Processing

ABSTRACT

Verb Phrase Ellipsis (VPE) is an anaphoric construction in which a verb phrase has been elided. It occurs frequently in dialogue and informal conversational settings, but despite its evident impact on event coreference resolution and extraction, there has been relatively little work on computational methods for identifying and resolving VPE. Here, we present a novel approach to detecting and resolving VPE by using supervised discriminative machine learning techniques trained on features extracted from an automatically parsed, publicly available dataset. Our approach yields state-of-the-art results for VPE detection by improving F1 score by over 11%; additionally, we explore an approach to antecedent identifi-cation that uses the Margin-Infused-Relaxed-Algorithm, which shows promising results.

PUBLICATION RECORD

  • Publication year

    2016

  • Venue

    Conference on Empirical Methods in Natural Language Processing

  • Publication date

    2016-11-01

  • Fields of study

    Linguistics, Computer Science

  • Identifiers
    DOI 10.18653/v1/D16-1179
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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