The Untaught Lessons of RAG Question Parsing: Structure Before You Search

Many Retrieval-Augmented Generation (RAG) systems falter by treating a user's question as a simple search query, which often results in incomplete answers. A more robust approach first parses the question into a structured format, analyzing its keywords, scope, and expected answer shape before any search occurs. This structured data then generates two separate briefs: one tailored for the retrieval process and another for the final answer generation. This method systematically handles complex, multi-part questions by identifying their underlying patterns and can use expert-curated dictionaries to map user language to document terminology more reliably than embeddings alone.