Paper: Using A Probabilistic Class-Based Lexicon For Lexical Ambiguity Resolution

ACL ID C00-2094
Title Using A Probabilistic Class-Based Lexicon For Lexical Ambiguity Resolution
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2000
Authors

This paper presents the use of prot)abilistie class-based lexica tbr dismnbiguati(m in target- woxd selection. Our method emlfloys nfinimal 1)llt; 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 fine-tuning to verbal arguments is done in an unsupervised manner by EM-lmsed clustering techniques. The method shows pronlising results in an evaluation on real-world translations.