Part of Speech Tagging for Polish: State of the Art and Future Perspectives

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9623)


In this paper we discuss the intricacies of Polish language part of speech tagging, present the current state of the art by comparing available taggers in detail and show the main obstacles that are a limiting factor in achieving an accuracy of Polish POS tagging higher than 91% of correctly tagged word segments. As this result is not only lower than in the case of English taggers, but also below those for other highly inflective languages, such as Czech and Slovene, we try to identify the main weaknesses of the taggers, their underlying algorithms, the training data, or difficulties inherent to the language to explain this difference. For this purpose we analyze the errors made individually by each of the available Polish POS taggers, an ensemble of the taggers and also by a publicly available well-known OpenNLP tagger, adapted to Polish tagset. Finally, we propose further steps that should be taken to narrow down the gap between Polish and English POS tagging performance.


Speech Tagging OpenNLP English Taggers Correct Tag Morphosyntactic Lexicon 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Work partly financed by the Polish Ministry of Science and Higher Education, a program in support of scientific units involved in the development of a European research infrastructure for the humanities and social sciences in the scope of the CLARIN ERIC consortium and partly financed by Polish National Science Center grant 2014/15/B/HS2/03119.


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Authors and Affiliations

  1. 1.Institute of Computer Science, Polish Academy of SciencesWarszawaPoland

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