Towards a representation of verbal semantics - An approach based on near synonyms

Mei Chih Tsai, Chu Ren Huang, Keh Jiann Chen, Kathleen Ahrens

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In this paper we propose using the distributional differences in the syntactic patterns of near-synonyms to deduce the relevant components of verb meaning. Our method involves determining the distributional differences in syntactic patterns, deducing the semantic features from the syntactic phenomena, and testing the semantic features in new syntactic frames. We determine the distributional differences in syntactic patterns through the following five ways: First, we search for all instances of the verb in the corpus. Second, we classify each of these instances into its type of syntactic function. Third, we classify each of these instances into its argument structure type. Fourth, we determine the aspectual type that is associated with each verb. Lastly, we determine each verb's sentential type. Once the distributional differences have been determined, then the relevant semantic features are postulated. Our goal is to tease out the lexical semantic features as the explanation, and as the motivation of the syntactic contrasts.

Original languageEnglish
Title of host publicationProceedings of the 10th Research on Computational Linguistics International Conference
EditorsKeh-Jiann Chen, Chu-Ren Huang, Richard Sproat
PublisherThe Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
Pages34-48
Number of pages15
Publication statusPublished - Aug 1997
Externally publishedYes
Event10th Research on Computational Linguistics International Conference, (ROCLING 1997) - Taipei, Taiwan
Duration: 22 Aug 199724 Aug 1997

Conference

Conference10th Research on Computational Linguistics International Conference, (ROCLING 1997)
Country/TerritoryTaiwan
CityTaipei
Period22/08/9724/08/97

ASJC Scopus subject areas

  • Language and Linguistics
  • Speech and Hearing

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