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Conference Papers Year : 2003

Lexical Knowledge Representation with Contexonyms

Abstract

Inter-word associations like stagger - drunken, or intra-word sense divisions (e.g. write a diary vs. write an article) are difficult to compile using a traditional lexicographic approach. As an alternative, we present a model that reflects this kind of subtle lexical knowledge. Based on the minimal sense of a word clique), the model (1) selects contextually related words (contexonyms) and (2) classifies them in a multi-dimensional semantic space. Trained on very large corpora, the model provides relevant, organized contexonyms that reflect the fine-grained connotations and contextual usage of the target word, as well as the distinct senses of homonyms and polysemous words. Further study on the neighbor effect showed that the model can handle the data sparseness problem.

Domains

Linguistics
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Dates and versions

hal-00933207 , version 1 (20-01-2014)

Identifiers

  • HAL Id : hal-00933207 , version 1

Cite

Ji Hyungsuk, Sabine Ploux, Eric Wehrli. Lexical Knowledge Representation with Contexonyms. 9th MT summit Machine Translation, Sep 2003, New Orleans, United States. pp.194-201. ⟨hal-00933207⟩
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