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Constraint-Guided Enterprise Data Mapping with Large Language Models

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Enterprise entity alignment must handle semi-structured records, implicit attributes, and unit or granularity mismatches. Manual matching is still common in practice, but does not scale as schemas and providers evolve. LLM-only matching improves semantic recall, yet can violate structural and physical invariants, producing fluent yet operationally invalid correspondences. We propose constraint-guided mapping (CGM), a neuro-symbolic method with three stages: (i) schema-grounded admissibility constraints with metadata mc = , where tau_c denotes the constraint type and delta_c provides executable

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