LegalNLP -- Natural Language Processing methods for the Brazilian Legal Language
This addresses a domain-specific problem for the Brazilian legal field, providing incremental tools to facilitate NLP adoption in industry, government, and academia.
The authors tackled the lack of open NLP tools for Brazilian legal language by releasing pre-trained models (e.g., BERT, Word2Vec) and a Python package based on texts from Brazilian courts, resulting in accessible resources for legal text analysis.
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.