Abstract
This paper brings a new method for acquisition of syntactic patterns capable of detecting errors in annotated corpora. These patterns are acquired semi-automatically, by means of an inductive logic programming (relational data mining) system followed by a human expert supervision. The patterns acquired have been used for automatic detection and subsequent manual correction of the annotation errors found in DESAM, a morphologically annotated corpus of written Czech. Preliminary results show efficiency of the method: more than 7000 annotation errors in the corpus have been successfully detected and corrected so far.
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Nepil, M. (2003). Detecting Annotation Errors in a Corpus by Induction of Syntactic Patterns. In: Matoušek, V., Mautner, P. (eds) Text, Speech and Dialogue. TSD 2003. Lecture Notes in Computer Science(), vol 2807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39398-6_11
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DOI: https://doi.org/10.1007/978-3-540-39398-6_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20024-6
Online ISBN: 978-3-540-39398-6
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