Abstract
I examine what would be necessary to move part-of-speech tagging performance from its current level of about 97.3% token accuracy (56% sentence accuracy) to close to 100% accuracy. I suggest that it must still be possible to greatly increase tagging performance and examine some useful improvements that have recently been made to the Stanford Part-of-Speech Tagger. However, an error analysis of some of the remaining errors suggests that there is limited further mileage to be had either from better machine learning or better features in a discriminative sequence classifier. The prospects for further gains from semi-supervised learning also seem quite limited. Rather, I suggest and begin to demonstrate that the largest opportunity for further progress comes from improving the taxonomic basis of the linguistic resources from which taggers are trained. That is, from improved descriptive linguistics. However, I conclude by suggesting that there are also limits to this process. The status of some words may not be able to be adequately captured by assigning them to one of a small number of categories. While conventions can be used in such cases to improve tagging consistency, they lack a strong linguistic basis.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Toutanova, K., Klein, D., Manning, C.D., Singer, Y.: Feature-rich part-of-speech tagging with a cyclic dependency network. In: NAACL 3, pp. 252–259 (2003)
Shen, L., Satta, G., Joshi, A.: Guided learning for bidirectional sequence classification. In: ACL 2007 (2007)
Spoustová, D.j., Hajič, J., Raab, J., Spousta, M.: Semi-supervised training for the averaged perceptron POS tagger. In: Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009), pp. 763–771 (2009)
Søgaard, A.: Simple semi-supervised training of part-of-speech taggers. In: Proceedings of the ACL 2010 Conference Short Papers, pp. 205–208 (2010)
Subramanya, A., Petrov, S., Pereira, F.: Efficient graph-based semi-supervised learning of structured tagging models. In: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pp. 167–176 (2010)
Collins, M.: Discriminative training methods for Hidden Markov Models: Theory and experiments with perceptron algorithms. In: EMNLP 2002 (2002)
Marcus, M.P., Santorini, B., Marcinkiewicz, M.A.: Building a large annotated corpus of English: The Penn treebank. Computational Linguistics 19, 313–330 (1993)
Finkel, J., Dingare, S., Manning, C., Nissim, M., Alex, B., Grover, C.: Exploring the boundaries: Gene and protein identification in biomedical text. BMC Bioinformatics 6 (suppl. 1) (2005)
Collins, M.: Ranking algorithms for named entity extraction: Boosting and the voted perceptron. In: ACL 40, pp. 489–496 (2002)
Tsuruoka, Y., Tsujii, J.: Bidirectional inference with the easiest-first strategy for tagging sequence data. In: Proceedings of HLT/EMNLP 2005, pp. 467–474 (2005)
Clark, A.: Combining distributional and morphological information for part of speech induction. In: EACL 2003, pp. 59–66 (2003)
Klein, D., Manning, C.D.: Accurate unlexicalized parsing. In: ACL 41, pp. 423–430 (2003)
MacKinlay, A.: The effects of part-of-speech tagsets on tagger performance. Honours thesis, Department of Computer Science and Software Engineering, University of Melbourne (2005)
Church, K.W.: Current practice in part of speech tagging and suggestions for the future. In: Mackie, A.W., McAuley, T.K., Simmons, C. (eds.) For Henry Kučera: Studies in Slavic Philology and Computational Linguistics. Papers in Slavic philology, vol. 6, pp. 13–48. Michigan Slavic Studies, Ann Arbor (1992)
Magerman, D.M.: Natural language parsing as statistical pattern recognition. PhD thesis, Stanford University (1994)
Ratnaparkhi, A.: A maximum entropy model for part-of-speech tagging. In: EMNLP 1, pp. 133–142 (1996)
Abney, S., Schapire, R.E., Singer, Y.: Boosting applied to tagging and PP attachment. In: Fung, P., Zhou, J. (eds.) Proceedings of the 1999 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, pp. 38–45 (1999)
Voutilainen, A., Järvinen, T.: Specifying a shallow grammatical representation for parsing purposes. In: 7th Conference of the European Chapter of the Association for Computational Linguistics, pp. 210–214 (1995)
Samuelsson, C., Voutilainen, A.: Comparing a linguistic and a stochastic tagger. In: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics, pp. 246–253 (1997)
Dickinson, M., Meurers, W.D.: Detecting errors in part-of-speech annotation. In: Proceedings of the 10th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2003 (2003)
Levy, R., Andrew, G.: Tregex and Tsurgeon: tools for querying and manipulating tree data structures. In: 5th International Conference on Language Resources and Evaluation, LREC 2006 (2006)
Rohde, D.L.T.: Tgrep2 user manual. ms. MIT, Cambridge (2005)
Santorini, B.: Part-of-speech tagging guidelines for the Penn treebank project. 3rd Revision, 2nd printing, February 1995. University of Pennsylvania (1990)
Moore, D.S.: Statistics: Concepts and Controversies, 3rd edn. W. H. Freeman, New York (1991)
Ross, J.R.: A fake NP squish. In: Bailey, C.J.N., Shuy, R.W. (eds.) New Ways of Analyzing Variation in English, pp. 96–140. Georgetown University Press, Washington (1973)
Quirk, R., Greenbaum, S., Leech, G., Svartvik, J.: A Comprehensive Grammar of the English Language. Longman, London (1985)
Aarts, B.: Syntactic gradience: the nature of grammatical indeterminacy. Oxford University Press, Oxford (2007)
Abney, S.: Statistical methods and linguistics. In: Klavans, J., Resnik, P. (eds.) The Balancing Act. MIT Press, Cambridge (1996)
Maling, J.: Transitive adjectives: A case of categorial reanalysis. In: Heny, F., Richards, B. (eds.) Linguistic Categories: Auxiliaries and Related Puzzles, vol. 1, pp. 253–289. D. Reidel, Dordrecht (1983)
Harnad, S. (ed.): Categorical perception: the groundwork of cognition. Cambridge University Press, Cambridge (1987)
Radford, A.: Transformational Grammar. Cambridge University Press, Cambridge (1988)
Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Boston (1999)
Bies, A., Ferguson, M., Katz, K., MacIntyre, R. (colleagues): Bracketing guidelines for Treebank II style: Penn treebank project. ms, University of Pennsylvania (1995)
Huddleston, R.D., Pullum, G.K.: The Cambridge Grammar of the English Language. Cambridge University Press, Cambridge (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Manning, C.D. (2011). Part-of-Speech Tagging from 97% to 100%: Is It Time for Some Linguistics?. In: Gelbukh, A.F. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6608. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19400-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-19400-9_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19399-6
Online ISBN: 978-3-642-19400-9
eBook Packages: Computer ScienceComputer Science (R0)