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This invention describes a method for automatically discovering and defining rules for a database using artificial intelligence. It works by feeding database information to a large language model (LLM), asking it questions, and then using the model's responses to generate more specific questions or to formulate the actual database rules. The process specifically involves using prior AI answers to refine subsequent questions and filling in templates with concrete data values.
Why it matters: The core challenge of reliably deriving precise database constraints from LLM outputs remains significant. While LLMs continue to advance, their inherent probabilistic nature still poses hurdles for deterministic rule generation, which was already a known issue when this was filed in 2025.
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