从大型巴西基金监管 PDF 中提取结构化数据的挑战（230 千字符，22 种实体类型）

Hi! I'm Reinaldo Chaves, a data journalist from Brazil. I'm building an open-source tool to extract structured information from Brazilian investment fund regulation PDFs using LangExtract + Gemini. These are standardized documents (CVM Resolution 175/2022) with ~100 pages / 230K characters each, containing 22 entity types (fund name, CNPJ, administrator, manager, fees, duration, risk factors, liquidation events, legal forum, etc.). **Project repo:** https://GitHub.com/reichaves/langextract-fundos The goal is to enable investigative journalists to systematically analyze thousands of fund regulations for transparency and accountability purposes.