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

Anaphora is a discourse-level linguistic phenomenon. There is consensus that anaphora resolution should rely on prior sentences within the context of the discourse. We propose to cast anaphora resolution as a semantic inference process in which a combination of multiple strategies, each exploiting d...

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Bibliographic Details
Published in:Machine translation 1999-01, Vol.14 (3/4), p.163-190
Main Authors: Chan, Samuel W. K., T'Sou, Benjamin K.
Format: Article
Language:English
Subjects:
Anaphora
Computational linguistics
Inference
Linguistics
Matrices
Pronouns
Referents
Semantics
Syntactical antecedents
Syntactics
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Summary:Anaphora is a discourse-level linguistic phenomenon. There is consensus that anaphora resolution should rely on prior sentences within the context of the discourse. We propose to cast anaphora resolution as a semantic inference process in which a combination of multiple strategies, each exploiting different aspects of linguistic knowledge, is employed to provide a coherent resolution of anaphora. A framework which encompasses several salient linguistic parameters such as grammatical role, proximity, repetition, sentence recency and semantic cues is demonstrated. This work also shows how an anaphora-resolution algorithm can be embedded within a framework which captures all the above salient parameters, as well as remedies some of the inadequacies found in any monolithic resolution system. A language-neutral semantic representation characterized by semantic cues is presented in order to capture the distilled information after resolution. The effectiveness of the language-neutral representation, both for machine translation and anaphora resolution, is demonstrated through a set of simulations and evaluations.
ISSN:0922-6567
1573-0573
DOI:10.1023/a:1011138323599