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Harmonization and Development of Resources and Tools for Italian Natural Language Processing within the PARLI Project pp 161–171Cite as

Simple Voting Algorithms for Italian Parsing

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 589))

Abstract

This paper presents an ensemble system for dependency parsing of Italian: three parsers are separately trained and combined by means of a majority vote. The three parsers are the MATE parser, version 2.0, the DeSR parser, and the MALT parser. We present three experiments showing that a simple voting combination further improves the performances of the parsers.

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Notes

  1. 1.

    http://code.google.com/p/mate-tools/

  2. 2.

    http://sites.google.com/site/desrparser/

  3. 3.

    http://maltparser.org/

  4. 4.

    In this paper we use the term word in a general sense, as synonym of token.

  5. 5.

    File: it_isst_train.splet.

  6. 6.

    File: it_isst_test.splet.

  7. 7.

    File: it_isst_train.splet and it_isst_test.splet.

  8. 8.

    File: it_EULaw_test_blind.splet.

  9. 9.

    File: it_isst_train.splet and it_isst_test . splet.

  10. 10.

    File: it_NatRegLaw_test_blind.splet.

  11. 11.

    File: evalita201_ train.conll.

  12. 12.

    File: evalita2011_ test.conll.

  13. 13.

    The same consideration hold for COM2: in the second experiment there are just \(8\) corrupted trees.

  14. 14.

    http://www.parsit.it.

  15. 15.

    The UniPi parser is the DeSR parser tuned for this specific competition.

  16. 16.

    The FBKirst parser is an ensemble combination of the MALT parser.

References

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Authors and Affiliations

  1. Dipartimento di Informatica, Università di Torino, Corso Svizzera 185, 101049, Torino, Italy

    Alessandro Mazzei

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  1. Alessandro Mazzei
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Correspondence to Alessandro Mazzei .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Systems and Production, University of Rome Tor Vergata, Rome, Italy

    Roberto Basili

  2. Department of Computer Science, University of Turin, Turin, Italy

    Cristina Bosco

  3. Department of Language and Cultural Studies, Department of Computer Science, Ca’ Foscari University of Venice, Venezia, Italy

    Rodolfo Delmonte

  4. Department of Computer Science and Information Engineering, University of Trento, Trento, Italy

    Alessandro Moschitti

  5. Department of Computer Science, University of Pisa, Pisa, Italy

    Maria Simi

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Mazzei, A. (2015). Simple Voting Algorithms for Italian Parsing. In: Basili, R., Bosco, C., Delmonte, R., Moschitti, A., Simi, M. (eds) Harmonization and Development of Resources and Tools for Italian Natural Language Processing within the PARLI Project. Studies in Computational Intelligence, vol 589. Springer, Cham. https://doi.org/10.1007/978-3-319-14206-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-14206-7_8

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