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Russian Tagging and Dependency Parsing Models for Stanford CoreNLP Natural Language Toolkit

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Knowledge Engineering and Semantic Web (KESW 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 786))

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Abstract

The paper concerns implementing maximum entropy tagging model and neural net dependency parser model for Russian language in Stanford CoreNLP toolkit, an extensible pipeline that provides core natural language analysis. Russian belongs to morphologically rich languages and demands full morphological analysis including annotating input texts with POS tags, features and lemmas (unlike the case of case-, person-, etc. insensitive languages when stemming and POS-tagging give enough information about grammatical behavior of a word form). Rich morphology is accompanied by free word order in Russian which adds indeterminacy to head finding rules in parsing procedures. In the paper we describe training data, linguistic features used to learn the classifiers, training and evaluation of tagging and parsing models.

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Notes

  1. 1.

    https://github.com/MANASLU8/CoreNLP.

  2. 2.

    https://github.com/MANASLU8/CoreNLPRusModels.

  3. 3.

    http://universaldependencies.org/.

  4. 4.

    https://ufal.mff.cuni.cz/udpipe.

  5. 5.

    http://universaldependencies.org/u/pos/all.html.

  6. 6.

    Examples were taken from Ilya Kormiltsev poetry, therefore, English translations in the figures footnotes are approximate and do not preserve the author’s syntax.

  7. 7.

    https://nlp.stanford.edu/software/tagger.html.

  8. 8.

    https://nlp.stanford.edu/software/nndep.shtml.

  9. 9.

    https://nlp.stanford.edu/nlp/javadoc/javanlp/.

  10. 10.

    http://www.ruscorpora.ru/.

  11. 11.

    https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-1983.

  12. 12.

    http://universaldependencies.org/docs/format.html.

  13. 13.

    http://odict.ru/.

  14. 14.

    http://statmt.org/.

  15. 15.

    https://github.com/dialogue-evaluation/morphoRuEval-2017.

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Acknowledgment

This work was financially supported by the Russian Fund of Basic Research (RFBR), Grant No. 16-36-60055.

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Authors and Affiliations

  1. ITMO University, Saint-petersburg, Russia

    Liubov Kovriguina, Ivan Shilin, Alexander Shipilo & Alina Putintseva

  2. SPbSU, Saint-petersburg, Russia

    Alexander Shipilo

Authors
  1. Liubov Kovriguina
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  2. Ivan Shilin
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  3. Alexander Shipilo
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  4. Alina Putintseva
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Correspondence to Liubov Kovriguina .

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Editors and Affiliations

  1. West Pomeranian University of Technology in Szczecin, Szczecin, Poland

    Przemysław Różewski

  2. University of Bonn, Bonn, Germany

    Christoph Lange

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Kovriguina, L., Shilin, I., Shipilo, A., Putintseva, A. (2017). Russian Tagging and Dependency Parsing Models for Stanford CoreNLP Natural Language Toolkit. In: Różewski, P., Lange, C. (eds) Knowledge Engineering and Semantic Web. KESW 2017. Communications in Computer and Information Science, vol 786. Springer, Cham. https://doi.org/10.1007/978-3-319-69548-8_8

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  • DOI: https://doi.org/10.1007/978-3-319-69548-8_8

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