Automatic Error Detection in Part of Speech Tagging
<|reference_start|>Automatic Error Detection in Part of Speech Tagging: 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.<|reference_end|>
@article{elworthy1994automatic,
    title={Automatic Error Detection in Part of Speech Tagging},
    author={David Elworthy (Sharp Laboratories of Europe)},
    journal={arXiv preprint arXiv:cmp-lg/9410013},
    year={1994},
    archivePrefix={arXiv},
    eprint={cmp-lg/9410013},
    primaryClass={cmp-lg cs.CL}
}