Abstract
Accuracy of a Named Entity Recognition algorithm based on the Hidden Markov Model is investigated. The algorithm was limited to recognition and classification of Named Entities representing persons. The algorithm was tested on two small Polish domain corpora of stock exchange and police reports. Comparison with the base lines algorithms based on the case of the first letter and a gazetteer is presented. The algorithm expressed 62% precision and 93% recall for the domain of the training data. Introduction of the simple hand-written post-processing rules increased precision up to 89%. We discuss also the problem of the method portability. A model of the combined knowledge sources is sketched also as a possible way to overcome the portability problem.
Work financed by European Union within Innovative Economy Programme project POIG.01.01.02-14-013/09.
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Marcińczuk, M., Piasecki, M. (2010). Study on Named Entity Recognition for Polish Based on Hidden Markov Models. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2010. Lecture Notes in Computer Science(), vol 6231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15760-8_19
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DOI: https://doi.org/10.1007/978-3-642-15760-8_19
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