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mySENSEVAL: Explaining WSD System Performance Using Target Word Features

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Natural Language Processing and Information Systems (NLDB 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3513))

Abstract

Word sense disambiguation (WSD) is an unsolved problem in NLP. The field has produced a variety of methods but none of them potent enough to reach high, human-tagger accuracy in demanding NLP applications. Our contribution to WSD is mySENSEVAL, an error analyzer using SENSEVAL evaluation scores (in mySQL database) to find significant correlations between WSD system types and lexico-conceptual features (from WordNet and SUMO).

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References

  1. Edmonds, P., Kilgarriff, A.: Introduction to the Special Issue on evaluating word sense disambiguation programs. Journal of Natural Language Engineering 8(4) (2002)

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  2. Hoste, V., Hendrickx, I., Daelemans, W., van den Bosch, A.: Parameter optimization for machine-learning of word sense disambiguation. Journal of Natural Language Engineering 8(4) (2002)

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  3. Mihalcea, R., Kilgarriff, A., Chklovski, T.: The SENSEVAL-3 English lexical sample task. In: Proceedings of SENSEVAL-3 Workshop at ACL-2004, Barcelona, Spain (2004)

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  4. Niles, I., Pease, A.: Towards a standard upper ontology. In: Welty, C., Smith, B. (eds.) Proceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS-2001), Ogunquit, Maine, October 17-19 (2001)

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  5. Saarikoski, H.: Using SENSEVAL system scores to optimize lexical resources for WSD and knowledge Acquisition. In: Proceedings of IBERAMIA, IX Ibero-American Conference for Artificial Intelligence, Puebla, Mexico (2004)

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  6. SENSEVAL-3 evaluation workshop of WSD systems 2004. Proceedings of SENSEVAL-3 Workshop at ACL-2004, Barcelona, Spain (July 2004)

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© 2005 Springer-Verlag Berlin Heidelberg

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Saarikoski, H.M.T. (2005). mySENSEVAL: Explaining WSD System Performance Using Target Word Features. In: Montoyo, A., Muńoz, R., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2005. Lecture Notes in Computer Science, vol 3513. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428817_39

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  • DOI: https://doi.org/10.1007/11428817_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26031-8

  • Online ISBN: 978-3-540-32110-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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