Using a Probabilistic Class-Based Lexicon for Lexical Ambiguity Resolution

This paper presents the use of probabilistic class-based lexica for disambiguation in targetword selection. Our method employs minimal but precise contextual information for disambiguation. That is, only information provided by the target-verb, enriched by the condensed information of a probabilistic class-based lexicon, 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.

• Type: Conference
• Year: 2000
• Where: COLING
• Authors: Detlef Prescher, Stefan Riezler, Mats Rooth
• Keywords: COLING 2000, COLING 2008, Precise Contextual Information, Probabilistic Class-based Lexica, Probabilistic Class-based Lexicon