Study on named entity recognition for Polish based on hidden Markov models

Authors:
Michał Marcińczuk;Maciej Piasecki
Affiliations:
Institute of Informatics, Wrocław University of Technology, Wrocław, Poland;Institute of Informatics, Wrocław University of Technology, Wrocław, Poland
Venue:
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
Year:
2010

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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.