Study on Named Entity Recognition for Polish Based on Hidden Markov Models

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%in conclusions as a possible way to overcome the portability problem.
Year:
2010
Type of Publication:
In Proceedings
Keywords:
Named Entity Recognition; Machine Learning; HiddenMarkov Model; Polish
Editor:
Sojka, Petr and Horák, Aleš and Kopecek, Ivan and Pala, Karel
Volume:
6231
Book title:
Text, Speech and Dialogue
Series:
Lecture Notes in Computer Science
Pages:
142-149
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