Detecting Annotation Errors in a Corpus by Induction of Syntactic Patterns

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Authors

NEPIL Miloslav

Year of publication 2003
Type Article in Proceedings
Conference Text, Speech and Dialogue: Sixth International Conference, TSD 2003
MU Faculty or unit

Faculty of Informatics

Citation
Field Informatics
Keywords error detection; morphological tagging; relational rule induction; syntactic patterns
Description 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.
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