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A Rule-Based AMR Parser for Portuguese

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Advances in Artificial Intelligence - IBERAMIA 2018 (IBERAMIA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11238))

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Abstract

Semantic parsers help to better understand a language and may produce better computer systems. They map natural language statements into meaning representations. Abstract Meaning Representation (AMR) is a new semantic representation designed to capture the meaning of a sentence, representing it as a single rooted acyclic directed graph with labeled nodes (concepts) and edged (relations) among them. Although it is receiving growing attention in the Natural Language Processing community, most of the works have focused on the English language due to the lack of large annotated corpora for other languages. Thus, the task of developing parsers becomes difficult, producing a gap between English and other languages. In this paper, we introduce an approach for a rule-based parser with generic rules in order to overcome this gap. We evaluate the parser on a manually annotated corpus in Portuguese, achieving promising results and outperforming one of the current parser development strategies in the area.

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Notes

  1. 1.

    Although PALAVRAS is a typical syntactical parser, it also produces some shallow semantic annotation.

  2. 2.

    It is important to notice that this rule was designed for Portuguese, in which the noun-adjective order is the most common ordering.

  3. 3.

    https://amr.isi.edu/download.html.

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Acknowledgments

The authors are grateful to FAPESP and IFPI for supporting this work.

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Authors and Affiliations

  1. Interinstitutional Center for Computational Linguistics (NILC), Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, Brazil

    Rafael Torres Anchiêta & Thiago Alexandre Salgueiro Pardo

Authors
  1. Rafael Torres Anchiêta
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  2. Thiago Alexandre Salgueiro Pardo
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Corresponding author

Correspondence to Rafael Torres Anchiêta .

Editor information

Editors and Affiliations

  1. Universidad Nacional del Sur, Bahía Blanca, Buenos Aires, Argentina

    Guillermo R. Simari

  2. University of Madeira, Funchal, Portugal

    Eduardo Fermé

  3. Universidad Nacional de Piura, Castilla-Piura, Peru

    Flabio Gutiérrez Segura

  4. Universidad Nacional de Trujillo, Trujillo, Peru

    José Antonio Rodríguez Melquiades

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Anchiêta, R.T., Pardo, T.A.S. (2018). A Rule-Based AMR Parser for Portuguese. In: Simari, G., Fermé, E., Gutiérrez Segura, F., Rodríguez Melquiades, J. (eds) Advances in Artificial Intelligence - IBERAMIA 2018. IBERAMIA 2018. Lecture Notes in Computer Science(), vol 11238. Springer, Cham. https://doi.org/10.1007/978-3-030-03928-8_28

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  • DOI: https://doi.org/10.1007/978-3-030-03928-8_28

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