Using a Probabilistic Class-Based Lexicon for Lexical
Ambiguity Resolution. Detlef Prescher, Stefan Riezler, and Mats Rooth.
In Proceedings of the 18th International Conference on
Computational Linguistics (COLING 2000), 2000, Saarbrücken.
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presents the use of probabilistic class-based lexica
for disambiguation in target-word selection.
This 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 fine-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. You can get our:
