Automatic Morphological Analysis for Russian : a Comparative Study

@inproceedings{dereza2016AutomaticMA,
  title={Automatic Morphological Analysis for Russian : a Comparative Study},
  author={Dereza O. V. oksana. dereza},
  year={2016}
}
  • Dereza O. V. oksana. dereza
  • Published 2016
In this paper we present a comparison of ten systems for automatic morphological analysis: TreeTagger, TnT, HunPos, Lapos, Citar, Morfette, Mystem, Pymorhy, Stanford POS tagger and SVMTool. Different training and tagging approaches are discussed together with the strengths and weaknesses of each system. Probabilistic taggers were trained and tested on the Russian National Disambiguated Corpus and achieved accuracy scores as high as 96,94% on POS tags and 92,56% on the whole tagset. However… CONTINUE READING