The increasing use of artificial intelligence methods in the legal field has sparked interest in
applying Natural Language Processing techniques to handle legal tasks and reduce the …

Legislative houses all over the world are adopting tools based on artificial intelligence to
support their work. The incorporation of these tools can improve the analysis of the text of the …

Abstract Named Entity Recognition (NER) is a challenging Natural Language Processing
task for a language as rich as Portuguese. When applied in a scenario appropriate to …

A large amount of legal and legislative documents are generated every year with highly
specialized content and significant repercussions on society. Besides technical, the …

This work investigates the application of Natural Language Processing (NLP) in the legal
context for the Portuguese language, emphasizing the importance of adapting pre-trained …

Obtaining relevant legal documents fast, from very large datasets, is essential for the proper
functioning of justice and legislative institutions. Nevertheless, legacy systems currently …

Abstract Named Entity Recognition (NER) is the task of identifying and classifying tokens in
texts corresponding to a set of pre-defined categories, such as names of people …

This study presents UlyssesNERQ, a system designed to improve Information Retrieval for
Brazilian Portuguese legislative documents. It uses Named Entity Recognition in Query …

Even if technology has made legislative documents more accessible, they are often written
in jargon that makes them hard to understand for ordinary citizens, researchers, journalists …

Este trabalho trata do vazamento de dados no treinamento de modelos de Reconhecimento
de Entidades Nomeadas (NER) em textos legislativos em português brasileiro, resultante de …