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A Multilingual Paradigm for Automatic Verb Classification

Paola Merlo,S. Stevenson,V. Tsang,Gianluca Allaria

Published 2002 in Annual Meeting of the Association for Computational Linguistics

ABSTRACT

We demonstrate the benefits of a multilingual approach to automatic lexical semantic verb classification based on statistical analysis of corpora in multiple languages. Our research incorporates two interrelated threads. In one, we exploit the similarities in the crosslinguistic classification of verbs, to extend work on English verb classification to a new language (Italian), and to new classes within that language, achieving an accuracy of 86.4% (baseline 33.9%). Our second strand of research exploits the differences across languages in the syntactic expression of semantic properties, to show that complementary information about English verbs can be extracted from their translations in a second language (Chinese). The use of multilingual features improves classification performance of the English verbs, achieving an accuracy of 83.5% (baseline 33.3%).

PUBLICATION RECORD

  • Publication year

    2002

  • Venue

    Annual Meeting of the Association for Computational Linguistics

  • Publication date

    2002-07-06

  • Fields of study

    Linguistics, Computer Science

  • Identifiers
    DOI 10.3115/1073083.1073119
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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