Abstract
The published experiments with shallow parsing for Slavic languages are characterised with small size of the corpora used. With the publication of the National Corpus of Polish (NCP), a new opportunity was opened: to test several chunking algorithms on the 1-million token manually annotated subcorpus of the NCP. We test three Machine Learning techniques: Decision Tree induction, Memory-Based Learning and Conditional Random Fields. We also investigate the influence of tagging errors on the overall chunker performance, which happens to be quite substantial.
This work was financed by the National Centre for Research and Development (NCBiR) project SP/I/1/77065/10.
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Radziszewski, A., Pawlaczek, A. (2012). Large-Scale Experiments with NP Chunking of Polish. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science(), vol 7499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32790-2_17
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DOI: https://doi.org/10.1007/978-3-642-32790-2_17
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