Using a probabilistic class-based lexicon for lexical ambiguity resolution
Detlef Prescher, Stefan Riezler, Mats Rooth · 2000
This paper presents the use of probabilistic class-based lexica for disambiguation in target-word selection. Our method employs minimal but precise contextual information for disam-biguation. That is, only information provided by the target-verb, enriched by the condensed information of a probabilistic class-based lexi-con, is used. Induction of classes and ne-tuning to verbal arguments is done in an unsupervised manner by EM-based clustering techniques. The method shows promising results in an evaluation on real-world translations. 1