LegalNLP - Natural Language Processing methods for the Brazilian Legal Language - Polo, Felipe Maia; Mendonça, Gabriel Caiaffa Floriano; Parreira, Kauê Capellato J.; Gianvechio, Lucka; Cordeiro, Peterson; Ferreira, Jonathan Batista; Lima, Leticia Maria Paz de; Maia, Antônio Carlos do Amaral; Vicente, Renato (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC); 2021: Anais do XVIII Encontro Nacional de Inteligência Artificial e ComputacionalDO - 10.5753/eniac.2021.18301, 2021)
We present and make available pre-trained language models (Phraser, Word2Vec, Doc2Vec, FastText, and BERT) for the Brazilian legal language, a Python package with functions to facilitate their use, and a set of demonstrations/tutorials containing some applications involving them. Given that our material is built upon legal texts coming from several Brazilian courts, this initiative is extremely helpful for the Brazilian legal field, which lacks other open and specific tools and language models. Our main objective is to catalyze the use of natural language processing tools for legal texts analysis by the Brazilian industry, government, and academia, providing the necessary tools and accessible material.