ML p(r)ior | Automatic Error Detection in Part of Speech Tagging
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Automatic Error Detection in Part of Speech Tagging

1994-10-21
9410013 | cmp-lg
A technique for detecting errors made by Hidden Markov Model taggers is described, based on comparing observable values of the tagging process with a threshold. The resulting approach allows the accuracy of the tagger to be improved by accepting a lower efficiency, defined as the proportion of words which are tagged. Empirical observations are presented which demonstrate the validity of the technique and suggest how to choose an appropriate threshold.
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