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English Information

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Authors
# Name
1 Juan Marciano(juan.morysson@ifpi.edu.br)
2 Arlino Magalhaes(arlino@ufpi.edu.br)
3 Vinicius Ponte(vinicius@ufpi.edu.br)

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Reference
# Reference
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2 Bommarito, M. J., Katz, D. M., and Detterman, E. M. (2020). Lexnlp: Natural language processing and information extraction for legal and regulatory texts. In Research Hand- book on Big Data Law. Edward Elgar Publishing.
3 Brandt, M. B. e. a. (2018). Modelo de dados abertos conectados para informac¸ ˜ao legisla- tiva. Informac¸ ˜ao & Sociedade: Estudos, 28(2):149–161.
4 Brasil (2011). Lei nº 12.527, de 18 de novembro de 2011. https://www.planalto. gov.br/ccivil_03/_ato2011-2014/2011/lei/l12527.htm. Di´ario Oficial da Uni˜ao, Bras´ılia, DF, 18 nov. 2011. Acesso em: 2 jun. 2025.
5 Breitman, K. e. a. (2012). Open government data in brazil. IEEE Intelligent Systems, 27(3):45–49.
6 Cavalcante, G. V., Sousa, F. R. d., Vaz, R. C. R., and Araujo, C. H. G. (2016). Dados abertos legislativos: o parlamento e o cidad˜ao. Anais da VIII Jornada de Pesquisa e Extens˜ao.
7 Chebolu, S. U. S., Dernoncourt, F., Lipka, N., and Solorio, T. (2023). A review of datasets for aspect-based sentiment analysis. In Proceedings of the 13th International Joint Conference on Natural Language Processing (IJCNLP 2023) and the 3rd Conference of the Asia-Pacific Chapter of the ACL (Volume 1: Long Papers), pages 611–628, Nusa Dua, Bali, Indonesia. Association for Computational Linguistics.
8 Dalenogare, L. G. C. and Ara´ujo, M. A. D. d. (2019). Abordagens te´oricas em dados governamentais abertos. Revista Gest˜ao e Tecnologia, 19(5):296–314.
9 Dzikrullah, F. and Rinjani, M. A. (2017). A framework design to develop integrated data system for smart e-government based on big data technology. Bulletin of Social Informatics Theory and Application, 1(2):41–51.
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11 Janssen, K. (2011). The influence of the psi directive on open government data. Govern- ment Information Quarterly, 28(4):446–456.
12 Janssen, M., Charalabidis, Y., and Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29(4):258–268.
13 Li, A., Hua, X., Liao, Y., and Bansal, M. (2023). Stance detection on social media with background knowledge. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), pages 14252–14270, Singapore. As- sociation for Computational Linguistics.
14 Mumcuo˘glu, E. e. a. (2021). Natural language processing in law: Prediction of outcomes in the higher courts of turkey. Information Processing & Management, 58(6):102684.
15 Nay, J. (2018). Natural language processing and machine learning for law and policy texts. Technical Report 3438276, Social Science Research Network (SSRN). Acesso em: 2 jun. 2025.
16 Oliveira, G. P., Silva, M. O., Costa, L. G. L., Dutra, M. T., and Pappa, G. L. (2024). Icpset: Um conjunto de dados estruturados de itens de compras p’ublicas. In Proceedings of the VI Dataset Showcase Workshop (DSW), pages 103–113, Florian’opolis, SC, Brazil. SBC.
17 Rolim, T. V., ´Avila, C. V. S., Freitas, R., Mariano, R. G., and Vidal, V. M. P. (2024). Construc¸ ˜ao do dataset semˆantico de pessoas jur´ıdicas. In Proceedings of the VI Dataset Showcase Workshop (DSW), pages 41–52, Florian´opolis, SC, Brazil. SBC.
18 Ruijer, E., Grimmelikhuijsen, S., and Meijer, A. (2017). Open data for democracy: Deve- loping a theoretical framework for open data use. Government Information Quarterly, 34(1):45–52.
19 Testa, G., Mesquita, L., and Bolognesi, B. (2024). Do fisiologismo ao centro do poder: as reformas eleitorais e o centr˜ao 2.0. Caderno CRH, 37(100):e024003.
20 Wilkinson, M. D. e. a. (2016). The fair guiding principles for scientific data management and stewardship. Scientific Data, 3.