LegalNLP -- Natural Language Processing methods for the Brazilian Legal Language
Felipe Maia Polo, Gabriel Caiaffa Floriano Mendon\c{c}a, Kau\^e, Capellato J. Parreira, Lucka Gianvechio, Peterson Cordeiro, Jonathan Batista, Ferreira, Leticia Maria Paz de Lima, Ant\^onio Carlos do Amaral Maia, Renato, Vicente
TL;DR
This paper introduces pre-trained language models and tools tailored for Brazilian legal texts, aiming to facilitate NLP applications in the legal domain for Brazilian institutions and researchers.
Contribution
It provides the first set of open-source NLP models and a Python package specifically designed for Brazilian legal language analysis.
Findings
Availability of multiple pre-trained models for legal texts
Development of a Python package with functions and tutorials
Facilitates NLP research and applications in Brazilian legal domain
Abstract
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.
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Taxonomy
TopicsArtificial Intelligence in Law · Comparative and International Law Studies · Natural Language Processing Techniques