Evaluation of a Hybrid Approach to Legal Entity Recognition - Lopes, Fernando Hurias; Garcia, Luís Paulo Faina (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC), 2025)
The Brazilian judiciary system’s extensive volume of documents and technical language necessitates efficient methods for automating legal text analysis, where Legal Entity Recognition (LER) presents a significant challenge. This study evaluated the performance of LER models within the Brazilian legal domain through a comprehensive assessment across all publicly available Portuguese legal datasets: LeNER-BR, CDJur-BR, and UlyssesNER-BR. Eleven models were evaluated, encompassing classical-based, transformer-based, and hybrid approaches. Using Precision, Recall, and F1-Score metrics, the evaluation indicated that hybrid approaches consistently outperform both classicalbased and standalone transformer-based approaches in legal entity extraction tasks.