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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.