Using Google’s LangExtract and Gemma for Structured Data Extraction

Google's LangExtract framework, when combined with its Gemma 3 large language model, provides a powerful method for pulling structured information from dense, unstructured documents. The framework is specifically designed to handle long texts by using smart chunking to preserve context, parallel processing for speed, and multiple extraction passes to maximize recall. This process leverages Gemma 3, a lightweight yet capable open-source model that can run locally, ensuring data privacy and reducing reliance on cloud services. A practical demonstration shows these tools effectively parsing a real insurance policy, turning complex clauses and exclusions into organized, traceable data points.