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Selecting Decomposable Models for Word-Sense Disambiguation: TheGrling-Sdm System

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Abstract

This paper describes the grling-sdm system, which is asupervised probabilistic classifier that participated in the 1998SENSEVAL competition for word-sense disambiguation. This systemuses model search to select decomposable probability models describingthe dependencies among the feature variables.These types of models have been found to be advantageous in terms ofefficiency and representational power. Performance on the SENSEVALevaluation data is discussed.

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References

  • Bruce, R. and J. Wiebe. "Decomposable modeling in natural language processing". Computational Linguistics 25(2) (1999), 195–207.

    Google Scholar 

  • Jurafsky, D. and J. H. Martin. Speech and Language Processing. Upper Saddle River, NJ: Prentice-Hall. 1999.

    Google Scholar 

  • Koller, D. and M. Sahami Hierarchically classifying documents using very few words". Proc. 14th International Conference on Machine Learning (ICML-97). Nashville, Tennessee, 1997, pp. 170–178.

  • Mooney, R. "Comparative experiments on disambiguating word senses: An illustration of the role of bias in machine learning". Proc. Conference on Empirical Methods in Natural Language Processing (EMNLP-96). Philadelphia, Pennsylvania, 1996, pp. 82–91.

  • Ng, H. T. and H. B. Lee. "Integrating multiple knowledge sources to disambiguate word sense: an exemplar-based approach". Proc. of the 31st Annual Meeting of the Association for Computational Linguistics (ACL-96). Santa Cruz, California, 1996, pp. 40–47.

  • O'Hara, T., J.Wiebe and R. Bruce. "Selecting decomposable models for word-sense disambiguation: the grling-sdm system". Notes of SENSEVAL Workshop. Sussex, England, September 1998.

  • Pedersen, T. and R. Bruce. "A new supervised learning algorithm for word sense disambiguation". Proc. of the 14th National Conference on Artificial Intelligence (AAAI-97). Providence, Rhode Island, 1997, pp. 604–609.

  • Pedersen, T. and R. Bruce. "Knowledge-lean word-sense disambiguation". Proc. of the 15th National Conference on Artificial Intelligence (AAAI-98). Madison, Wisconsin, 1998, pp. 800–805.

  • Wiebe, J., K. McKeever and R. Bruce. "Mapping collocational properties into machine learning features". Proc. 6th Workshop on Very Large Corpora (WVLC-98). Association for Computational Linguistics SIGDAT, Montreal, Quebec, Canada, 1998.

    Google Scholar 

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O'Hara, T., Wiebe, J. & Bruce, R. Selecting Decomposable Models for Word-Sense Disambiguation: TheGrling-Sdm System. Computers and the Humanities 34, 159–164 (2000). https://doi.org/10.1023/A:1002439708427

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  • DOI: https://doi.org/10.1023/A:1002439708427

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