Skip to main content

Improvements in Part-of-Speech Tagging with an Application to German

  • Chapter
Natural Language Processing Using Very Large Corpora

Part of the book series: Text, Speech and Language Technology ((TLTB,volume 11))

Abstract

Work on part-of-speech tagging has concentrated on English in the past, since a lot of manually tagged training material is available for English and results can be compared to those of other researchers. It was assumed that methods which have been developed for English would work for other languages as well.1

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  • Brill, E. 1992. A simple rule-based part of speech tagger. In Proceedings of the Third Conference on Applied Natural Language Processing, Trento, Italy, pp. 152–155.

    Google Scholar 

  • Brill, E. 1999. Unsupervised learning of disambiguation rules for part of speech tagging. This volume, pp. 27–42.

    Google Scholar 

  • Church, K. W. and Gale, W. A. 1991. A comparison of the enhanced Good-Turing and deleted estimation methods for estimating probabilities of English bigrams. Computer Speech and Language, 5: 19–54.

    Article  Google Scholar 

  • Cutting, D., Kupiec, J., Pedersen, J. and Sibun, P. 1992. A practical part-of-speech tagger. In Proceedings of the Third Conference on Applied Natural Language Processing, Trento, Italy pp. 133–140.

    Google Scholar 

  • Feldweg, H. 1999. Implementation and evaluation of a German HMM for POS disambiguation. This volume, pp. 1–12.

    Google Scholar 

  • Jelinek, F. and Mercer, R. L. 1980. Interpolated estimation of Markov source parameters from sparse data. In Workshop on Pattern Recognition in Practice,pp. 381–397, Amsterdam.

    Google Scholar 

  • Katz, S. 1987. Estimation of probabilities from sparse data for the language model component of a speech recognizer. IEEE Transactions on ASSP,34(3), pp. 400401.

    Google Scholar 

  • Marcus, M. P., Santorini, B. and Marcinkiewicz, M. A. 1993. Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics, 19 (2), pp. 313–330.

    Google Scholar 

  • Merialdo, B. 1994. Tagging English text with a probabilistic model. Computational Linguistics, 20 (2), pp. 155–171.

    Google Scholar 

  • Pereira, F. C., Singer, Y. and Tishby, N. 1999. Beyond word N-grams. This volume, pp. 121–136.

    Google Scholar 

  • Quinlan, J. R. 1983. Learning efficient classification procedures and their application to chess end games. In Michalski, Carbonell, and Mitchell (eds), Machine Learning: An artificial intelligence approach, pp. 463–482. Morgan Kaufmann, San Mateo, CA.

    Google Scholar 

  • Quinlan, J. R. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.

    Google Scholar 

  • Schiller, A. 1995. DMOR: Benutzeranleitung. Technical report, Institut für maschinelle Sprachverarbeitung, Universität Stuttgart. (in German).

    Google Scholar 

  • Schmid, H. 1994. Probabilistic part-of-speech tagging using decision trees. In International Conference on New Methods in Language Processing, pp. 44–49, Manchester, UK.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Schmid, H. (1999). Improvements in Part-of-Speech Tagging with an Application to German. In: Armstrong, S., Church, K., Isabelle, P., Manzi, S., Tzoukermann, E., Yarowsky, D. (eds) Natural Language Processing Using Very Large Corpora. Text, Speech and Language Technology, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-2390-9_2

Download citation

  • DOI: https://doi.org/10.1007/978-94-017-2390-9_2

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5349-7

  • Online ISBN: 978-94-017-2390-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics