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

  • Michał Marcińczuk
  • Maciej Piasecki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6231)

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.

Keywords

named entity recognition machine learning Hidden Markov Model Polish 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Michał Marcińczuk
    • 1
  • Maciej Piasecki
    • 1
  1. 1.Institute of InformaticsWrocław University of TechnologyWrocławPoland

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