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Towards a Mention-Pair Model for Coreference Resolution in Portuguese

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Progress in Artificial Intelligence (EPIA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10423))

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Abstract

The aim of coreference resolution is to automatically determine all linguistic expressions included in a piece of text that refer to the same entity. Following the mention-pair model, we employ machine learning techniques to address coreference resolution from text written in Portuguese. Based on a modest annotated corpus, we highlight the impact that different training-set creation strategies have on the quality of the predictions made by the system. We conclude that enriching the system with semantic-based features significantly improves the overall performance of the system.

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Notes

  1. 1.

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Acknowledgments

The first author is partially supported by a doctoral grant from Doctoral Program in Informatics Engineering (ProDEI) from the Faculty of Engineering of the University of Porto (FEUP).

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Authors and Affiliations

  1. LIACC/DEI, Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Gil Rocha & Henrique Lopes Cardoso

Authors
  1. Gil Rocha
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  2. Henrique Lopes Cardoso
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Corresponding author

Correspondence to Gil Rocha .

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Editors and Affiliations

  1. Universidade do Porto, Porto, Portugal

    Eugénio Oliveira

  2. Universidade do Porto, Porto, Portugal

    João Gama

  3. Polytechnic Institute of Porto, Porto, Portugal

    Zita Vale

  4. Universidade do Porto, Porto, Portugal

    Henrique Lopes Cardoso

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Rocha, G., Lopes Cardoso, H. (2017). Towards a Mention-Pair Model for Coreference Resolution in Portuguese. In: Oliveira, E., Gama, J., Vale, Z., Lopes Cardoso, H. (eds) Progress in Artificial Intelligence. EPIA 2017. Lecture Notes in Computer Science(), vol 10423. Springer, Cham. https://doi.org/10.1007/978-3-319-65340-2_69

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  • DOI: https://doi.org/10.1007/978-3-319-65340-2_69

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65339-6

  • Online ISBN: 978-3-319-65340-2

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