Correcting a POS-Tagged Corpus Using Three Complementary Methods

The quality of the part-of-speech (PoS) annotation in a corpus is crucial for the development of PoS taggers. In this paper, we experiment with three complementary methods for automatically detecting errors in the PoS annotation for the Icelandic Frequency Dictionary corpus. The first two methods are language independent and we argue that the third method can be adapted to other morphologically complex languages. Once possible errors have been detected, we examine each error candidate and hand-correct the corresponding PoS tag if necessary. Overall, based on the three methods, we hand-correct the PoS tagging of 1,334 tokens (0.23% of the tokens) in the corpus. Furthermore, we re-evaluate existing state-of-the-art PoS taggers on Icelandic text using the corrected corpus.

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