Skip to main content

POS Tagging

  • Reference work entry
Encyclopedia of Machine Learning

Synonyms

Grammatical tagging; Morphosyntactic disambiguation; Part of speech tagging; Tagging

Definition

Part-of-speech tagging (POS tagging) is a process in which each word in a text is assigned its appropriate morphosyntactic category (for example noun-singular, verb-past, adjective, pronoun-personal, and the like). It therefore provides information about both morphology (structure of words) and syntax (structure of sentences). This disambiguation process is determined both by constraints from the lexicon (what are the possible categories for a word?) and by constraints from the context in which the word occurs (which of the possible categories is the right one in this context?). For example, a word like table can be a noun-singular, but also a verb-present (as in I table this motion). This is lexical knowledge. It is the context of the word that should be used to decide which of the possible categories is the correct one. In a sentence like Put it on the table, the fact that table...

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

Access this chapter

Institutional subscriptions

Recommended Reading

  • Brants, T. (2000). TnT – A statistical part-of-speech tagger. In Proceedings of the sixth applied natural language processing conference ANLP-2000. Seattle, WA.

    Google Scholar 

  • Brill, E. (1995a). Transformation-based error-driven learning and natural language processing: a case study in part-of-speech tagging. Computional Linguistics, 21(4), 543–565.

    Google Scholar 

  • Brill, E. (1995b). Unsupervised learning of disambiguation rules for part of speech tagging. In Proceedings of the third workshop on very large corpora (pp. 1–13). Ohio State University, Ohio.

    Google Scholar 

  • Cussens, J. (1997). Part-of-speech tagging using progol. In N. Lavrac, & S. Dzeroski (Eds.), Proceedings of the seventh international workshop on inductive logic programming, Lecture Notes in Computer Science (Vol. 1297 pp. 93–108). London: Springer.

    Google Scholar 

  • Daelemans, W., Zavrel, J., Berck, P., & Gillis, S. (1996). MBT: A memory-based part of speech tagger generator. In Proceedings of the fourth workshop on very large corpora (pp. 14–27). Copenhagen, Denmark

    Google Scholar 

  • Garside, R., & Smith, N. (1997). A hybrid grammatical tagger: CLAWS4. In R. Garside, G. Leech, & A. McEnery (Eds.), Corpus annotation: Linguistic information from computer text corpora (pp. 102–121). London: Longman.

    Google Scholar 

  • Jurafsky, D., & Martin, J. (2008). Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition (2nd ed.). Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Karlsson, F., Voutilainen, A., Heikkilä, J., & Anttila, A. (1995). Constraint grammar. A language-independent system for parsing unrestricted text (p. 430). Berlin and New York: Mouton de Gruyter.

    Google Scholar 

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

    Google Scholar 

  • Ratnaparkhi, A. (1996). A maximum entropy part of speech tagger. In Proceedings of the ACL-SIGDAT conference on empirical methods in natural language processing (pp. 17–18). Philadelphia, PA.

    Google Scholar 

  • Schmid, H. (1994a). Part-of-speech tagging with neural networks. In Proceedings of COLING-94 (pp. 172–176). Kyoto, Japan.

    Google Scholar 

  • Schmid, H. (1994b). Probabilistic part-of-speech tagging using decision trees. In Proceedings of the international conference on new methods in language processing (NeMLaP), (pp. 44–49). Manchester, UK.

    Google Scholar 

  • Schutze, H. (1995). Distributional part-of-speech tagging. In Proceedings of EACL 7 (pp. 141–148). Dublin, Ireland.

    Google Scholar 

  • Shen, L., Satta, G., & Joshi, A. (2007). Guided learning for bidirectional sequence classification. In Proceedings of the 45th annual meetings of the association of computational linguistics (ACL 2007) (pp. 760–767). Prague, Czech Republic.

    Google Scholar 

  • Ushioda, A. (1996). Hierarchical clustering of words and applications to NLP tasks. In Proceedings of the fourth workshop on very large corpora (pp. 28–41). Somerset, NJ.

    Google Scholar 

  • van Halteren, H. (Ed.). (1999). Syntactic wordclass tagging. Boston: Kluwer Academic Publishers.

    MATH  Google Scholar 

  • van Halteren, H. Zavrel, J., & Daelemans, W. (2001) Improving accuracy in NLP through combination of machine learning systems. Computational Linguistics, 27(2), 199–229.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media, LLC

About this entry

Cite this entry

Daelemans, W. (2011). POS Tagging. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_643

Download citation

Publish with us

Policies and ethics