Word sense disambiguation using a second language monolingual corpus (original) (raw)
This paper presents a new approach for resolving lexical ambiguities in one language using statis-tical data from a monolingual corpus of another language. This approach exploits the differences between mappings of words to senses in different languages. The paper concentrates on the prob-lem of target word selection in machine translation, for which the approach is directly applicable. The presented algorithm identifies syntactic relations between words, using a source language parser, and maps the alternative interpretations of these relations to the target language, using a bilingual lexicon. The preferred senses are then selected according to statistics on lexical relations in the target language. The selection is based on a statistical model and on a constraint prop-agation algorithm, which simultaneously handles all ambiguities in the sentence. The method was evaluated using three sets of Hebrew and German examples and was found to be very use-ful for disambiguation. The paper...
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