he Possibilities of Automatic Detection/Correction of Errors in Tagged Corpora: A Pilot Study on a German Corpus
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2166)
The performance of taggers is usuallye valuated bytheir percentual success rate. Because of the pure quantitativity of such an approach, all errors committed bythe tagger are treated on a par for the purpose of the evaluation. This paper takes a different, qualitative stand on the topic, arguing that the previous viewpoint is not linguisticallyadequate: the errors (might) differ in severity. General implications for tagging are discussed, and a simple method is proposed and exemplified, able to
Some encouraging results achieved bya verysimple, manuallyperformed test and evaluation on a small sample of a corpus are given.
detect and in some cases even rectifythe most severe errors and thus
contribute to arriving finally at a better tagged corpus.
KeywordsAmbiguity Resolution Subordinate Clause Relative Pronoun Test Corpus German Corpus
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Unable to display preview. Download preview PDF.
© Springer-Verlag Berlin Heidelberg 2001