1995 UnsupWSDRivalingSupervMethods

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Subject Headings: Unsupervised Word Sense Disambiguation Algorithm, Word Sense Disambiguation Algorithm, Yarowsky Algorithm.


Cited By




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%.


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
1995 UnsupWSDRivalingSupervMethodsDavid YarowskyUnsupervised Word Sense Disambiguation Rivaling Supervised MethodsProceedings of the 33rd annual meeting on Association for Computational Linguisticshttp://acl.ldc.upenn.edu//P/P95/P95-1026.pdf10.3115/981658.9816841995