Semantic Inference for Anaphora Resolution: Toward a Framework in Machine Translation

  • Authors:

  • Samuel W. K. Chan;Benjamin K. T'Sou

  • Affiliations:

  • Department of Decision Sciences and Managerial Economics, The Chinese University of Hong Kong, Hong Kong, China. E-mail: swkchan@cuhk.edu.hk;Language Information Sciences Research Centre, City University of Hong Kong, Hong Kong, China. E-mail: rlbtsou@uxmail.cityu.edu.hk

  • Venue:
  • Machine Translation
  • Year:
  • 1999

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Abstract

Anaphora is a discourse-level linguistic phenomenon.There is consensus that anaphora resolution shouldrely on prior sentences within the context of thediscourse. We propose to cast anaphora resolution asa semantic inference process in which a combination ofmultiple strategies, each exploiting different aspectsof linguistic knowledge, is employed to provide acoherent resolution of anaphora. A framework whichencompasses several salient linguistic parameters suchas grammatical role, proximity, repetition, sentencerecency and semantic cues is demonstrated. This workalso shows how an anaphora-resolution algorithm can beembedded within a framework which captures all theabove salient parameters, as well as remedies some ofthe inadequacies found in any monolithic resolutionsystem. A language-neutral semantic representationcharacterized by semantic cues is presented in orderto capture the distilled information after resolution.The effectiveness of the language-neutralrepresentation, both for machine translation andanaphora resolution, is demonstrated through a set ofsimulations and evaluations.