Abstract

yarowsky~unagi, ci s. upenn, edu This paper presents an unsupervised learning algorithm for sense disambiguation that, when trained on unannotated English text, rivals the performance of supervised techniques that require time-consuming hand annotations. The algorithm is based on two powerful constraints- that words tend to have one sense per discourse and one sense per collocation- exploited in an iterative bootstrapping procedure. Tested accuracy exceeds 96%. 1

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