Deriving an Ambiguous Word's Part-of-Speech Distribution from Unannotated Text
نویسنده
چکیده
A distributional method for part-of-speech induction is presented which, in contrast to most previous work, determines the part-of-speech distribution of syntactically ambiguous words without explicitly tagging the underlying text corpus. This is achieved by assuming that the word pair consisting of the left and right neighbor of a particular token is characteristic of the part of speech at this position, and by clustering the neighbor pairs on the basis of their middle words as observed in a large corpus. The results obtained in this way are evaluated by comparing them to the part-of-speech distributions as found in the manually tagged Brown corpus.
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