This invention discloses a document
information extraction method,
system, and program product that combines logical constraints and
reinforcement learning, relating to the fields of
artificial intelligence and
intelligent document processing technology. Firstly, by explicitly incorporating arithmetic rules into the reward function, this invention significantly reduces "numerical illusions" and substantially improves logical consistency. Secondly, it solves the problem of extracting borderless tables, deriving the table structure through semantic content and logical constraints instead of relying on visual dividing lines, making it particularly suitable for borderless complex tables such as medical invoices. Thirdly, this invention uses
reinforcement learning to transform discrete business rules into dense supervisory signals to guide the optimization of the document
information extraction model. Furthermore, the document
information extraction model of this invention directly outputs
JSON format conforming to the
database schema, eliminating the need for complex post-
processing steps and achieving direct conversion from images to a queryable
database.