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English Information

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Authors
# Name
1 Karina Fróes(karina.froes@ime.usp.br)
2 Kelly Rosa Braghetto(kellyrb@ime.usp.br)

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Reference
# Reference
1 Attard, J., Orlandi, F., Scerri, S., and Auer, S. (2015). A systematic review of open government data initiatives. Government Information Quarterly, 32(4):399–418.
2 Brasil. Ministerio da Educacao (2026). Plano Nacional de Educacao 2026–2036. https://www2.camara.leg.br/legin/fed/lei/2026/ lei-15388-14-abril-2026-798950-normaatualizada-pl.pdf. Documento preparatorio do novo Plano Nacional de Educacao (PNE 2026–2036). Acesso em: 20 maio 2026.
3 Costa, L., Dutra, M. T., Oliveira, G., Silva, M., Soares, D. C., de Cassia Silva Faria, L., Jr., W. M., and Pappa, G. (2024). Ciencia de dados e transparencia: Experiencias com dados publicos do sicom. In Anais Estendidos do XXXIX Simposio Brasileiro de Bancos de Dados, pages 246-252, Porto Alegre, RS, Brasil. SBC.
4 Data.gov (2009). The home of the U.S. Government's open data. https://data.gov/. Acesso em: 20 mai. 2026.
5 Froes, K. d. C. and Braghetto, K. R. (2025). Exploring temporal Text-to-SQL challenges in brazilian portuguese: Lessons from educational data. Anais do 40o Simposio Brasileiro de Banco de Dados (SBBD), pages 963-969.
6 INEP (2026). Microdados do Censo Escolar da Educacao Basica. Disponivel em: https://www.gov.br/inep/pt-br/acesso-a-informacao/dados-abertos/microdados/censo-escolar. Acesso em: 26 mai. 2026.
7 Li, J. et al. (2024). Can LLM already serve as a database interface? a big bench for large-scale database grounded Text-to-SQLs. Advances in Neural Information Processing Systems, 36.
8 Oliveira, A. H., Martins, S., Rocha, D., and Nascimento, L. R. (2025). InSANdB: Base de dados integrada por municipio brasileiro para estudos da inseguranca alimentar e nutricional no brasil. In Simposio Brasileiro de Sistemas de Informacao.
9 Open Government Partnership (2011). The open gov challenge. https://www.opengovpartnership.org/. Acesso em: 20 mai. 2026.
10 Pourreza, M. and Rafiei, D. (2024). Din-SQL: Decomposed in-context learning of text-to-SQL with self-correction. Advances in Neural Information Processing Systems, 36.
11 Rodrigues, I., Reis, J., Queiroz, B., and Benevenuto, F. (2025). BRAZIL DATA COMMONS: Plataforma unificada para analise de dados publicos de diferentes repositorios. In Anais do XX Simposio Brasileiro de Sistemas Colaborativos, pages 308-316, Porto Alegre, RS, Brasil. SBC.
12 Sun, R. et al. (2023). SQL-PaLM: Improved large language model adaptation for Text-to-SQL (extended). arXiv preprint arXiv:2306.00739.
13 Visperas, M. et al. (2023). On modern Text-to-SQL semantic parsing methodologies for natural language interface to databases: A comparative study. In 2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), pages 390-396. IEEE.
14 Yu, T. and et al. (2018). Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and Text-to-SQL task. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 3911-3921, Brussels, Belgium. Association for Computational Linguistics.
15 Zhong, V., Xiong, C., and Socher, R. (2017). Seq2sql: Generating structured queries from natural language using reinforcement learning. arXiv preprint arXiv:1709.00103.