Abstract
This paper presents an unsupervised, all-words, word sense disambiguation system for English. The system associates a word with its meaning in a given context using an electronic dictionary as a tagged corpora in order to extract semantic disambiguation rules. The methodology attempts to avoid the data acquisition bottleneck observed in word sense disambiguation techniques. Semantic rules are used as input of a semantic application program encoding a linguistic strategy in order to select the best rule to apply. The semantic rule extraction process as well as the application program is described. The methodology is developed in a client/server architecture, which enables the treatment of large corpora. The evaluation of the system is then detailed and some possible extensions and perspectives are finally proposed.
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