ANPC Panel: A Hybrid Framework for Legal Information Extraction, Transparency, and Human-on-the-Loop Validation - Santos, Vitória S.; Bortolanza, Francisco; Dorneles, Carina F. (Anais Estendidos do Simpósio Brasileiro de Banco de Dados (SBBD); 2026: Anais Estendidos do XLI Simpósio Brasileiro de Bancos de Dados, 2026)
Legal document analysis plays an important role in supporting institutional oversight and public governance; however, manual extraction of information from large document collections is time-consuming and difficult to scale. This paper presents the ANPC Panel, a hybrid framework that combines Large Language Models (LLMs), retrieval-based extraction, and complementary rule-based strategies to transform Civil Non-Prosecution Agreements (ANPCs) into structured representations for institutional monitoring and large-scale analysis. Beyond automated extraction, the system incorporates algorithmic transparency and Human-on-the-Loop validation mechanisms, allowing users to inspect, contextualize, and audit AI-generated outputs. By combining automated information extraction, transparent analytics, and human supervision, the proposed approach contributes to strengthening efficiency, accountability, and evidence-based decision-making in public-sector environments.