@InProceedings{mitrofan-ion:2017:BioNLP,
  author    = {Mitrofan, Maria  and  Ion, Radu},
  title     = {Adapting the TTL Romanian POS Tagger to the Biomedical Domain},
  booktitle = {Proceedings of the Biomedical NLP Workshop associated with RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {8--14},
  abstract  = {This paper presents the adaptation of the Hidden Markov Models-based TTL
	part-of-speech tagger to the biomedical domain. TTL is a text processing
	platform that performs sentence splitting, tokenization, POS tagging, chunking 
	and Named Entity Recognition (NER) for a number of languages, including
	Romanian. The POS tagging accuracy obtained by the TTL POS tagger exceeds 97\%
	when TTL's baseline model is updated with training information from a Romanian
	biomedical corpus. This corpus is developed in the context of the CoRoLa (a
	reference corpus for the contemporary Romanian language) project. Informative
	description and statistics of the Romanian biomedical corpus are also provided.},
  url       = {https://doi.org/10.26615/978-954-452-044-1_002}
}