Work

Brazilian Consumer Protection Code: a methodology for a dataset to Question-Answer (QA) Models

Year: 2024

Type: conference-paper

Abstract: This work introduces the methodology for building a new dataset based onthe Brazilian Consumer Protection Code (CDC), focusing on question-answer (QA) models. The dataset collected legal data, including CDC articles, legal summaries, and court rulings from the Superior Court of Justice (STJ). Automated data extraction techniques using Python were employed, and advanced language models such as Llama3-8b-8192, Gemma2-9b-it, and GPT-4o-mini were used to generate question-answer (QA) structures. This work presents our methodology for creating such a dataset to be used by language models for training in the legal domain, particularly in the CDC domain.

DOI: 10.5753/stil.2024.31168

Authors: Aline Athaydes, Lucas Krug Bulcao, Caio Sacramento, Babacar Mane, Daniela Barreiro Claro, Marlo Souza, Robespierre Pita

Institution: Universidade Federal da Bahia

Language: English

Topic: Artificial Intelligence in Law

Subfield: Political Science and International Relations

Field: Social Sciences

Domain: Social Sciences

SDG: Peace, justice, and strong institutions

Open Access status: gold

Funders: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Fundação de Amparo à Pesquisa do Estado da Bahia

OpenAlex ID: W4405168416

FWCI: 10.53

Cites: 4

Cited by: 4

Related to: 10