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Lexical Analysis of Serbian with Conditional Random Fields and Large-Coverage Finite-State Resources

  • Mathieu ConstantEmail author
  • Cvetana Krstev
  • Duško Vitas
Conference paper
  • 282 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10930)

Abstract

This article describes a joint approach to lexical tagging in Serbian, combining three fundamental natural language processing tasks: part-of-speech tagging, compound and named entity recognition. The proposed system relies on conditional random fields that are trained from a newly released annotated corpus and finite-state lexical resources used in an existing symbolic Serbian tagging system. Experimental results show that a joint strategy is more robust than pipeline ones and that the use of lexical resources has a significant positive impact on tagging, in particular on out-of-domain texts.

Notes

Acknowledgments

This research was partly supported by the Serbian Ministry of Education and Science under grant #47003 and by the French National Research Agency (ANR) through the project PARSEME-FR (ANR-14-CERA-0001).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Mathieu Constant
    • 1
    Email author
  • Cvetana Krstev
    • 2
  • Duško Vitas
    • 2
  1. 1.ATILF UMR 7118Université de Lorraine/CNRSNancyFrance
  2. 2.University of BelgradeBelgradeSerbia

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