Abstract
Automatic morphosyntactic tagging of corpora is usually imperfect. Wrong or strange tagging may be automatically repeated following some patterns. It is usually hard to manually detect all these errors, as corpora may contain millions of tags. This paper presents an approach to detect sequences of part-of-speech tags that have an internal cohesiveness in corpora. Some sequences match to syntactic chunks or correct sequences, but some are strange or incorrect, usually due to systematically wrong tagging. The amount of time spent in separating incorrect bigrams and trigrams from correct ones is very small, but it allows us to detect 70% of all tagging errors in the corpus.
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Rocio, V., Silva, J., Lopes, G. (2007). Detection of Strange and Wrong Automatic Part-of-Speech Tagging. In: Neves, J., Santos, M.F., Machado, J.M. (eds) Progress in Artificial Intelligence. EPIA 2007. Lecture Notes in Computer Science(), vol 4874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77002-2_57
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DOI: https://doi.org/10.1007/978-3-540-77002-2_57
Publisher Name: Springer, Berlin, Heidelberg
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