Simple Python Gate Can Catch Unsupported Claims in RAG-Generated Answers

Retrieval-Augmented Generation (RAG) systems can cite real documents while still making claims those documents do not actually support. A developer has outlined a lightweight, deterministic citation-verification approach using a Python dataclass that checks whether required terms appear in cited source text. The method intentionally avoids semantic reasoning, making it easy to inspect but suitable only as a first-pass filter rather than a final verifier. Best practices suggested include splitting answers into atomic claims, storing full source metadata, and normalizing numeric terms before applying any entailment model. The core takeaway is that a citation functions as an address, not as proof, and verification requires its own dedicated step.