After some theoretical discussion on the issue of representativity of a corpus, this paper presents a simple yet very efficient technique serving for (semi-) automatic detection of those positions in a part-of-speech tagged corpus where an error is to be suspected. The approach is based on the idea of learning and application of “invalid bigrams”, i.e. on the search for pairs of adjacent tags which constitute an incorrect configuration in a text of a particular language (in English, e.g., the bigram ARTICLE - VERB). Further, the paper describes the generalization of the “invalid bigrams” into “extended invalid bigrams of length n”, for any natural n, which provides a powerful tool for error detection in a corpus. The approach is illustrated by English, German and Czech examples.
CITATION STYLE
Květoň, P., & Oliva, K. (2002). Achieving an almost correct PoS-tagged corpus. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2448, pp. 19–26). Springer Verlag. https://doi.org/10.1007/3-540-46154-x_3
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