Open AccessLegalNLP - Natural Language Processing methods for the Brazilian Legal Language
Author(s) -
Felipe Maia Polo,
Gabriel Caiaffa Floriano Mendonça,
Kauê Capellato J. Parreira,
Lucka de Godoy Gianvechio,
Peterson Cordeiro,
Jonathan Batista Ferreira,
Leticia Maria Paz de Lima,
Antônio Carlos do Amaral Maia,
Renato Vicente
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/eniac.2021.18301
Subject(s) - computer science , word2vec , python (programming language) , natural language processing , government (linguistics) , natural language , artificial intelligence , field (mathematics) , set (abstract data type) , world wide web , programming language , linguistics , philosophy , mathematics , pure mathematics
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.