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

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Human Language Technology. Challenges for Computer Science and Linguistics (LTC 2015)

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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.

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Notes

  1. 1.

    For the purpose of this article, we define a compound as a contiguous sequence of tokens that has a non-compositional meaning. Compounds form a subclass of multiword expressions. We exclude multiword named entities from it.

  2. 2.

    Note that these tasks can also be jointly combined with parsing: e.g. CR [6, 10, 18] or NER [9].

  3. 3.

    The Unitex software system: http://unitexgramlab.org/.

  4. 4.

    The disambiguation was done by a special tool integrated into Unitex system that facilitates manual disambiguation http://tln.li.univ-tours.fr/Tln_Colloques/Tln_JUnitex2014/Communications/Vitas.pdf.

  5. 5.

    Note that it does not correspond to a strict combination of the three types of annotations, as we do not tag the internal elements of the multiword lexical units.

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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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Authors and Affiliations

  1. ATILF UMR 7118, Université de Lorraine/CNRS, Nancy, France

    Mathieu Constant

  2. University of Belgrade, Belgrade, Serbia

    Cvetana Krstev & Duško Vitas

Authors
  1. Mathieu Constant
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  2. Cvetana Krstev
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  3. Duško Vitas
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Correspondence to Mathieu Constant .

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Editors and Affiliations

  1. Adam Mickiewicz University, Poznań, Poland

    Zygmunt Vetulani

  2. LIMSI-CNRS, Orsay Cedex, France

    Joseph Mariani

  3. Adam Mickiewicz University, Poznań, Poland

    Marek Kubis

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Constant, M., Krstev, C., Vitas, D. (2018). Lexical Analysis of Serbian with Conditional Random Fields and Large-Coverage Finite-State Resources. In: Vetulani, Z., Mariani, J., Kubis, M. (eds) Human Language Technology. Challenges for Computer Science and Linguistics. LTC 2015. Lecture Notes in Computer Science(), vol 10930. Springer, Cham. https://doi.org/10.1007/978-3-319-93782-3_20

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  • DOI: https://doi.org/10.1007/978-3-319-93782-3_20

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