Towards Uniform Meaning Representation for Brazilian Portuguese: Building a First UMR-Annotated Dataset
Resumo
This paper presents the first Brazilian Portuguese dataset annotated for Uniform Meaning Representation (UMR). It contains 96 sentences from the Brazilian Portuguese portion of the Parallel Universal Dependencies treebank, parallel to existing UMR annotations in English, Czech, and Italian. The sentences were parsed with PortParser, revised in Arborator-Grew, converted from CoNLL-U into preliminary sentence-level UMR graphs, and manually revised in PENMAN format. The results show that CoNLL-U is a useful starting point, but semantic graph construction requires manual interpretation and language-specific lexical resources. The dataset expands multilingual UMR coverage and supports future Portuguese semantic annotation.
Referências
Banarescu, L., Bonial, C., Cai, S., Georgescu, M., Griffitt, K., Hermjakob, U., Knight, K., Koehn, P., Palmer, M., and Schneider, N. (2013). Abstract Meaning Representation for sembanking. In Pareja-Lora, A., Liakata, M., and Dipper, S., editors, Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse, pages 178–186, Sofia, Bulgaria. Association for Computational Linguistics.
Bonn, J., Buchholz, M. J., Chun, J., Cowell, A., Croft, W., Denk, L., Ge, S., Hajic, J., Lai, K., Martin, J. H., et al. (2024). Building a broad infrastructure for uniform meaning representations. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 2537–2547.
Bonn, J., Myers, S., E. L. Van Gysel, J., Denk, L., Vigus, M., Zhao, J., Cowell, A., Croft, W., Hajič, J., H. Martin, J., Palmer, A., Palmer, M., Pustejovsky, J., Urešová, Z., Vallejos, R., and Xue, N. (2023). Mapping AMR to UMR: Resources for adapting existing corpora for cross-lingual compatibility. In Dakota, D., Evang, K., Kübler, S., and Levin, L., editors, Proceedings of the 21st International Workshop on Treebanks and Linguistic Theories (TLT, GURT/SyntaxFest 2023), pages 74–95, Washington, D.C. Association for Computational Linguistics.
Buchholz, M. J., Bonn, J., Post, C. B., Cowell, A., and Palmer, A. (2024). Bootstrapping UMR annotations for Arapaho from language documentation resources. In Calzolari, N., Kan, M.-Y., Hoste, V., Lenci, A., Sakti, S., and Xue, N., editors, Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 2447–2457, Torino, Italia. ELRA and ICCL.
de Marneffe, M.-C., Manning, C. D., Nivre, J., and Zeman, D. (2021). Universal Dependencies. Computational Linguistics, 47(2):255–308.
Duran, M. and Aluísio, S. (2015). Automatic generation of a lexical resource to support semantic role labeling in Portuguese. In Palmer, M., Boleda, G., and Rosso, P., editors, Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics, pages 216–221, Denver, Colorado, USA. Association for Computational Linguistics.
Duran, M. S., Martins, J. P., and Aluísio, S. M. (2013). Um repositório de verbos para a anotação de papéis semânticos disponível na web (a verb repository for semantic role labeling bavailable in the web) [in Portuguese]. In Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology.
Gamba, F., Palmer, A., and Zeman, D. (2025). Bootstrapping UMRs from Universal Dependencies for scalable multilingual annotation. In Peng, S. and Rehbein, I., editors, Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025), pages 126–136, Vienna, Austria. Association for Computational Linguistics.
Guibon, G., Courtin, M., Gerdes, K., and Guillaume, B. (2020). When collaborative treebank curation meets graph grammars. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5291–5300.
Lopatková, M., Hledíková, H., Štěpánek, J., and Zeman, D. (2025). From the prague dependency treebank to the uniform meaning representation: Gold-standard czech umr data and partial automatic conversion.
Lopes, L. and Pardo, T. (2024). Towards portparser - a highly accurate parsing system for Brazilian Portuguese following the Universal Dependencies framework. In Gamallo, P., Claro, D., Teixeira, A., Real, L., Garcia, M., Oliveira, H. G., and Amaro, R., editors, Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1, pages 401–410, Santiago de Compostela, Galicia/Spain. Association for Computational Lingustics.
Pardo, T. A. S., Duran, M. S., Lopes, L., Di Felippo, A., Roman, N. T., and Nunes, M. d. G. V. (2021). Porttinari: a large multi-genre treebank for brazilian portuguese. In Anais do XIII Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana, Porto Alegre, RS, Brasil. SBC.
Rademaker, A., Chalub, F., Real, L., Freitas, C., Bick, E., and de Paiva, V. (2017). Universal dependencies for portuguese. In Proceedings of the Fourth International Conference on Dependency Linguistics (Depling 2017), pages 197–206.
Van Gysel, J. E., Vigus, M., Chun, J., Lai, K., Moeller, S., Yao, J., O’Gorman, T., Cowell, A., Croft, W., Huang, C.-R., et al. (2021). Designing a uniform meaning representation for natural language processing. KI-Künstliche Intelligenz, 35(3):343–360.
Zeman, D., Popel, M., Straka, M., Hajič, J., Nivre, J., Ginter, F., Luotolahti, J., Pyysalo, S., Petrov, S., Potthast, M., Tyers, F., Badmaeva, E., Gokirmak, M., Nedoluzhko, A., Cinková, S., Hajič jr., J., Hlaváčová, J., Kettnerová, V., Urešová, Z., Kanerva, J., Ojala, S., Missilä, A., Manning, C. D., Schuster, S., Reddy, S., Taji, D., Habash, N., Leung, H., de Marneffe, M.-C., Sanguinetti, M., Simi, M., Kanayama, H., de Paiva, V., Droganova, K., Martínez Alonso, H., Çöltekin, Ç., Sulubacak, U., Uszkoreit, H., Macketanz, V., Burchardt, A., Harris, K., Marheinecke, K., Rehm, G., Kayadelen, T., Attia, M., Elkahky, A., Yu, Z., Pitler, E., Lertpradit, S., Mandl, M., Kirchner, J., Alcalde, H. F., Strnadová, J., Banerjee, E., Manurung, R., Stella, A., Shimada, A., Kwak, S., Mendonça, G., Lando, T., Nitisaroj, R., and Li, J. (2017). CoNLL 2017 shared task: Multilingual parsing from raw text to Universal Dependencies. In Hajič, J. and Zeman, D., editors, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 1–19, Vancouver, Canada. Association for Computational Linguistics.
Bonn, J., Buchholz, M. J., Chun, J., Cowell, A., Croft, W., Denk, L., Ge, S., Hajic, J., Lai, K., Martin, J. H., et al. (2024). Building a broad infrastructure for uniform meaning representations. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 2537–2547.
Bonn, J., Myers, S., E. L. Van Gysel, J., Denk, L., Vigus, M., Zhao, J., Cowell, A., Croft, W., Hajič, J., H. Martin, J., Palmer, A., Palmer, M., Pustejovsky, J., Urešová, Z., Vallejos, R., and Xue, N. (2023). Mapping AMR to UMR: Resources for adapting existing corpora for cross-lingual compatibility. In Dakota, D., Evang, K., Kübler, S., and Levin, L., editors, Proceedings of the 21st International Workshop on Treebanks and Linguistic Theories (TLT, GURT/SyntaxFest 2023), pages 74–95, Washington, D.C. Association for Computational Linguistics.
Buchholz, M. J., Bonn, J., Post, C. B., Cowell, A., and Palmer, A. (2024). Bootstrapping UMR annotations for Arapaho from language documentation resources. In Calzolari, N., Kan, M.-Y., Hoste, V., Lenci, A., Sakti, S., and Xue, N., editors, Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 2447–2457, Torino, Italia. ELRA and ICCL.
de Marneffe, M.-C., Manning, C. D., Nivre, J., and Zeman, D. (2021). Universal Dependencies. Computational Linguistics, 47(2):255–308.
Duran, M. and Aluísio, S. (2015). Automatic generation of a lexical resource to support semantic role labeling in Portuguese. In Palmer, M., Boleda, G., and Rosso, P., editors, Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics, pages 216–221, Denver, Colorado, USA. Association for Computational Linguistics.
Duran, M. S., Martins, J. P., and Aluísio, S. M. (2013). Um repositório de verbos para a anotação de papéis semânticos disponível na web (a verb repository for semantic role labeling bavailable in the web) [in Portuguese]. In Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology.
Gamba, F., Palmer, A., and Zeman, D. (2025). Bootstrapping UMRs from Universal Dependencies for scalable multilingual annotation. In Peng, S. and Rehbein, I., editors, Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025), pages 126–136, Vienna, Austria. Association for Computational Linguistics.
Guibon, G., Courtin, M., Gerdes, K., and Guillaume, B. (2020). When collaborative treebank curation meets graph grammars. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5291–5300.
Lopatková, M., Hledíková, H., Štěpánek, J., and Zeman, D. (2025). From the prague dependency treebank to the uniform meaning representation: Gold-standard czech umr data and partial automatic conversion.
Lopes, L. and Pardo, T. (2024). Towards portparser - a highly accurate parsing system for Brazilian Portuguese following the Universal Dependencies framework. In Gamallo, P., Claro, D., Teixeira, A., Real, L., Garcia, M., Oliveira, H. G., and Amaro, R., editors, Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1, pages 401–410, Santiago de Compostela, Galicia/Spain. Association for Computational Lingustics.
Pardo, T. A. S., Duran, M. S., Lopes, L., Di Felippo, A., Roman, N. T., and Nunes, M. d. G. V. (2021). Porttinari: a large multi-genre treebank for brazilian portuguese. In Anais do XIII Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana, Porto Alegre, RS, Brasil. SBC.
Rademaker, A., Chalub, F., Real, L., Freitas, C., Bick, E., and de Paiva, V. (2017). Universal dependencies for portuguese. In Proceedings of the Fourth International Conference on Dependency Linguistics (Depling 2017), pages 197–206.
Van Gysel, J. E., Vigus, M., Chun, J., Lai, K., Moeller, S., Yao, J., O’Gorman, T., Cowell, A., Croft, W., Huang, C.-R., et al. (2021). Designing a uniform meaning representation for natural language processing. KI-Künstliche Intelligenz, 35(3):343–360.
Zeman, D., Popel, M., Straka, M., Hajič, J., Nivre, J., Ginter, F., Luotolahti, J., Pyysalo, S., Petrov, S., Potthast, M., Tyers, F., Badmaeva, E., Gokirmak, M., Nedoluzhko, A., Cinková, S., Hajič jr., J., Hlaváčová, J., Kettnerová, V., Urešová, Z., Kanerva, J., Ojala, S., Missilä, A., Manning, C. D., Schuster, S., Reddy, S., Taji, D., Habash, N., Leung, H., de Marneffe, M.-C., Sanguinetti, M., Simi, M., Kanayama, H., de Paiva, V., Droganova, K., Martínez Alonso, H., Çöltekin, Ç., Sulubacak, U., Uszkoreit, H., Macketanz, V., Burchardt, A., Harris, K., Marheinecke, K., Rehm, G., Kayadelen, T., Attia, M., Elkahky, A., Yu, Z., Pitler, E., Lertpradit, S., Mandl, M., Kirchner, J., Alcalde, H. F., Strnadová, J., Banerjee, E., Manurung, R., Stella, A., Shimada, A., Kwak, S., Mendonça, G., Lando, T., Nitisaroj, R., and Li, J. (2017). CoNLL 2017 shared task: Multilingual parsing from raw text to Universal Dependencies. In Hajič, J. and Zeman, D., editors, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 1–19, Vancouver, Canada. Association for Computational Linguistics.
Publicado
19/10/2026
Como Citar
PAGANO, Adriana S.; DURAN, Magali; GAMBA, Federica; ZEMAN, Daniel.
Towards Uniform Meaning Representation for Brazilian Portuguese: Building a First UMR-Annotated Dataset. In: SIMPÓSIO BRASILEIRO DE TECNOLOGIA DA INFORMAÇÃO E DA LINGUAGEM HUMANA (STIL), 17. , 2026, Cuiabá/MT.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 285-296.
DOI: https://doi.org/10.5753/stil.2026.26607.
