Maximum Entropy Model for Disambiguation of Rich Morphological Tags

  • Mārcis Pinnis
  • Kārlis Goba
Part of the Communications in Computer and Information Science book series (CCIS, volume 100)


In this work we describe a statistical morphological tagger for Latvian, Lithuanian and Estonian languages based on morphological tag disambiguation. These languages have rich tagsets and very high rates of morphological ambiguity. We model distribution of possible tags with an exponential probabilistic model, which allows to select and use features from surrounding context. Results show significant improvement in error rates over the baseline, the same as the results for Czech. In comparison with the simplified parameter estimation method applied for Czech, we show that maximum entropy weight estimation achieves considerably better results.


Tagger maximum entropy inflective languages Estonian Latvian Lithuanian 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Berger, A., Della Pietra, S., Della Pietra, V.: A Maximum Entropy Approach to Natural Language Processing. Computational Linguistics 22(1), 39–71 (1996)Google Scholar
  2. 2.
    Hajič, J., Vidová-Hladká, B.: Tagging Inflective Languages: Prediction of Morphological Categories for a Rich, Structured Tagset. In: Proceedings of the COLING-ACL Conference, Montreal, Canada, pp. 483–490 (1998)Google Scholar
  3. 3.
    Halácsy, P., Kornai, A., Oravec, C.: HunPos — an Open Source Trigram Tagger. In: Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions, pp. 209–212. Association for Computational Linguistics, Prague (2007)Google Scholar
  4. 4.
    Malouf, R.: A Comparison of Algorithms for Maximum Entropy Parameter Estimation. In: Proceedings of CoNLL 2002, pp. 49–55 (2002)Google Scholar
  5. 5.
    Benson, S., More, J.: A Limited Memory Variable Metric Method in Subspaces and Bound Constrained Optimization Problems. In: Technical Report ANL/MCS-P909-0901, Argonne National Laboratory (2001)Google Scholar
  6. 6.
    Kaalep, H.-J.: An Estonian Morphological Analyser and the Impact of a Corpus on its Development. Computers and Humanities 31, 115–133 (1997)CrossRefGoogle Scholar
  7. 7.
    MULTEXT-East: Multilingual Text Tools and Corpora for Central and Eastern European Languages,
  8. 8.
    A Simple C++ Library for Maximum Entropy Classification,
  9. 9.
    Morphologically Disambiguated Estonian Corpus,

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mārcis Pinnis
    • 1
  • Kārlis Goba
    • 1
  1. 1.TildeRigaLatvia

Personalised recommendations