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Abstract Meaning Representation Parsing for the Brazilian Portuguese Language

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Computational Processing of the Portuguese Language (PROPOR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13208))

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Abstract

Abstract Meaning Representation (AMR) is a semantic formalism that has been widely adopted in the area for semantic parsing. We present in this paper our contribution to the task for Portuguese. We investigated semantic parsing methods of different paradigms, producing state of the art results for this language. We also introduced the first AMR-annotated corpus for Portuguese, a novel and better semantic parsing evaluation measure, and a new AMR-based alignment method.

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References

  1. Anchiêta, R., Pardo, T.: Towards AMR-BR: a SemBank for Brazilian Portuguese language. In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation, pp. 974–979. European Languages Resources Association, Miyazaki, Japan, May 2018

    Google Scholar 

  2. Anchiêta, R., Pardo, T.: Semantically inspired AMR alignment for the Portuguese language. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pp. 1595–1600. Association for Computational Linguistics, Online, November 2020

    Google Scholar 

  3. Anchiêta, R.T., Cabezudo, M.A.S., Pardo, T.A.S.: SEMA: an extended semantic evaluation metric for AMR. In: (To appear) Proceedings of the 20th International Conference on Computational Linguistics and Intelligent Text Processing, La Rochelle, France, April 2019

    Google Scholar 

  4. Anchiêta, R.T., Pardo, T.A.S.: A rule-based AMR parser for Portuguese. In: Simari, G.R., Fermé, E., Gutiérrez Segura, F., Rodríguez Melquiades, J.A. (eds.) IBERAMIA 2018. LNCS (LNAI), vol. 11238, pp. 341–353. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03928-8_28

    Chapter  Google Scholar 

  5. Banarescu, L., et al.: Abstract meaning representation for sembanking. In: Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse, pp. 178–186. Association for Computational Linguistics, Sofia, Bulgaria, August 2013

    Google Scholar 

  6. Bick, E.: The Parsing System “Palavras”: Automatic Grammatical Analysis of Portuguese in a Constraint Grammar Framework. Aarhus Universitetsforlag (2000)

    Google Scholar 

  7. Bos, J.: Squib: expressive power of abstract meaning representations. Comput. Linguist. 42(3), 527–535 (2016)

    Article  MathSciNet  Google Scholar 

  8. Cai, S., Knight, K.: Smatch: an evaluation metric for semantic feature structures. In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 748–752. Association for Computational Linguistics, Sofia, Bulgaria, August 2013

    Google Scholar 

  9. Caseli, H., Nunes, M.: Sentence alignment of Brazilian Portuguese and English parallel texts. In: Proceedings of the Argentine Symposium on Artificial Intelligence, pp. 1–11. Buenos Aires, Argentine (2003)

    Google Scholar 

  10. Damonte, M., Cohen, S.B.: Cross-lingual abstract meaning representation parsing. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 1146–1155. Association for Computational Linguistics, New Orleans, Louisiana, June 2018

    Google Scholar 

  11. Damonte, M., Cohen, S.B., Satta, G.: An incremental parser for abstract meaning representation. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pp. 536–546. Association for Computational Linguistics, Valencia, Spain, April 2017

    Google Scholar 

  12. Duran, M.S., Martins, J.P., Aluísio, S.M.: Um repositório de verbos para a anotação de papéis semânticos disponível na web. In: Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology, pp. 168–172. Sociedade Brasileira de Computação, Fortaleza, Brazil, October 2013

    Google Scholar 

  13. Flanigan, J., Thomson, S., Carbonell, J., Dyer, C., Smith, N.A.: A discriminative graph-based parser for the abstract meaning representation. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1426–1436. Association for Computational Linguistics, Baltimore, Maryland, June 2014

    Google Scholar 

  14. Hartmann, N., Fonseca, E., Shulby, C., Treviso, M., Silva, J., Aluísio, S.: Portuguese word embeddings: Evaluating on word analogies and natural language tasks. In: Proceedings of the 11th Brazilian Symposium in Information and Human Language Technology, pp. 122–131. Sociedade Brasileira de Computação, Uberlândia, Brazil, October 2017

    Google Scholar 

  15. Hartmann, N.S., Duran, M.S., Aluísio, S.M.: Automatic semantic role labeling on non-revised syntactic trees of journalistic texts. In: Silva, J., Ribeiro, R., Quaresma, P., Adami, A., Branco, A. (eds.) PROPOR 2016. LNCS (LNAI), vol. 9727, pp. 202–212. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41552-9_20

    Chapter  Google Scholar 

  16. Kingsbury, P., Palmer, M.: From TreeBank to PropBank. In: Proceedings of the Third International Conference on Language Resources and Evaluation. European Language Resources Association, Las Palmas, Canary Islands - Spain, May 2002

    Google Scholar 

  17. Kusner, M., Sun, Y., Kolkin, N., Weinberger, K.: From word embeddings to document distances. In: Proceedings of the 32nd International Conference on Machine Learning, pp. 957–966. PMLR, Lille, France, July 2015

    Google Scholar 

  18. Liu, Y., Che, W., Zheng, B., Qin, B., Liu, T.: An AMR aligner tuned by transition-based parser. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 2422–2430. Association for Computational Linguistics, Brussels, Belgium, October–November 2018

    Google Scholar 

  19. Pourdamghani, N., Gao, Y., Hermjakob, U., Knight, K.: Aligning English strings with abstract meaning representation graphs. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 425–429. Association for Computational Linguistics, Doha, Qatar, October 2014

    Google Scholar 

  20. Wang, C., Xue, N., Pradhan, S.: A transition-based algorithm for AMR parsing. In: Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 366–375. Association for Computational Linguistics, Denver, Colorado, May–June 2015

    Google Scholar 

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Acknowledgments

The authors are grateful to USP Research Office (PRP #668), USP/IBM/FAPESP Center for Artificial Intelligence (#2019/07665-4), and Instituto Federal do Piauí.

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Correspondence to Rafael Torres Anchiêta .

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Anchiêta, R.T., Pardo, T.A.S. (2022). Abstract Meaning Representation Parsing for the Brazilian Portuguese Language. In: Pinheiro, V., et al. Computational Processing of the Portuguese Language. PROPOR 2022. Lecture Notes in Computer Science(), vol 13208. Springer, Cham. https://doi.org/10.1007/978-3-030-98305-5_41

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  • DOI: https://doi.org/10.1007/978-3-030-98305-5_41

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