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Verb Analysis in a Highly Inflective Language with an MFF Algorithm

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Computational Processing of the Portuguese Language (PROPOR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7243))

Abstract

We introduce the MFF algorithm for the task of verbal inflection analysis. This algorithm follows an heuristics that decide for the most frequent inflection feature bundle given the set of admissible feature bundles for a verb input form. This algorithm achieves a significantly better level of accuracy than the ones offered by current stochastic tagging technology commonly used for the same task.

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References

  1. Branco, A., Costa, F., Nunes, F.: The Processing of Verbal Inflection Ambiguity: Characterization of the Problem Space. In: Actas do XXI Encontro Anual da Associação Portuguesa de Linguística (2007)

    Google Scholar 

  2. Barreto, F., Branco, A., Ferreira, E., Mendes, A., Nascimento, M.F., Nunes, F., Silva, J.: Open Resources and Tools for the Shallow Processing of Portuguese: The TagShare Project. In: Proceedings of the 5th International Conference on Language Resources and Evaluation, LREC 2006 (2006)

    Google Scholar 

  3. Brants, T.: TnT - A Statistical Part-of-Speech Tagger. In: Proceedings of the 6th Applied Natural Language Processing Conference (ANLP 2000), pp. 224–231 (2000)

    Google Scholar 

  4. Chanod, J.-P., Tapanainen, P.: Tagging French – Comparing a Statistical and a Constraint-based Method. In: Proceedings of the 7th Conference of the European Chapter of the Association for Computational Linguistics (EACL 1995), pp. 149–156 (1995)

    Google Scholar 

  5. Chklovski, T., Mihalcea, R.: Exploiting Agreement and Disagreement of Human Annotators for Word Sense Disambiguation. In: Proceedings of the Conference on Recent Advances on Natural Language Processing, RANLP 2003 (2003)

    Google Scholar 

  6. Cucerzan, S., Yarowsky, D.: Bootstrapping a Multilingual Part-of-speech Tagger in One Person-day. In: Proceedings of The Sixth Conference on Natural Language Learning (CoNLL 2002), pp. 132–138 (2002)

    Google Scholar 

  7. Elworthy, D.: Tagset Design and Inflected Languages. In: Procedings of EACL SIGDAT Workshop From Texts to Tags: Issues in Multilingual Language Analysis, pp. 1–10 (1995)

    Google Scholar 

  8. Ezeiza, N., Aduriz, I., Alegria, I., Arriola, J., Urizar, R.: Combining Stochastic and Rule-Based Methods for Disambiguation in Agglutinative Languages. In: Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and the 17th Intemational Conference on Computational Linguistic (ACL-COLING 1998), pp. 380–384 (1998)

    Google Scholar 

  9. Hajič, J., Hladká, B.: Tagging Inflective Languages: Prediction of Morphological Categories for a Rich, Structured Tagset. In: Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and the 17th Intemational Conference on Computational Linguistic (ACL-COLING 1998), pp. 483–490 (1998)

    Google Scholar 

  10. Hakkani-Tür, D., Oflazer, K., Tür, G.: Statistical Morphological Disambiguation for Agglutinative Languages. In: Proceedings of the 18th International Conference on Computational Linguistics (COLING 2000), pp. 285–291 (2000)

    Google Scholar 

  11. Mihalcea, R., Edmonds, P. (eds.): Proceedings of Senseval-3: The Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text. Association for Computational Linguistics (2004)

    Google Scholar 

  12. Pedersen, T., Mihalcea, R.: Advances in Word Sense Disambiguation, Annual Conference of the Association for Computational Linguistcis, ACL 2005, Tutorial notes (2005)

    Google Scholar 

  13. Reichenbach, H.: Elements of Symbolic Logic. Macmillan, New York (1947)

    Google Scholar 

  14. Trushkina, J., Hinrichs, E.: A Hybrid Model for Morphosyntactic Annotation of German with a Large Tagset. In: Proceedings of Empirical Methods in Natural Language Processing (EMNLP 2004), pp. 238–246 (2004)

    Google Scholar 

  15. Tufis, D.: Tiered Tagging and Combined Language Models Classifiers. In: Matoušek, V., Mautner, P., Ocelíková, J., Sojka, P. (eds.) TSD 1999. LNCS (LNAI), vol. 1692, pp. 28–33. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

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Branco, A., Nunes, F. (2012). Verb Analysis in a Highly Inflective Language with an MFF Algorithm. In: Caseli, H., Villavicencio, A., Teixeira, A., Perdigão, F. (eds) Computational Processing of the Portuguese Language. PROPOR 2012. Lecture Notes in Computer Science(), vol 7243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28885-2_1

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  • DOI: https://doi.org/10.1007/978-3-642-28885-2_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28884-5

  • Online ISBN: 978-3-642-28885-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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