Extracting Hidden Sense Probabilities from Bitexts
We propose a probabilistic model that is inspired by Diab & Resnik’s algorithm to extract disambiguation information from aligned bilingual texts. Like Diab & Resnik’s, the proposed model uses WordNet and the fact that word ambiguities are not always the same in the two languages. The generative model introduces a dependency between two translated words through a common ancestor in WordNet’s ontology. Unlike Diab & Resnik’s algorithm it does not suppose that the translation in the source language has a single meaning.