Semantic Field Analysis

Large governed knowledge systems accumulate claims, assumptions, constraints, evidence, refusals, and typed relationships whose interactions cannot be understood by document retrieval alone. Semantic Field Analysis (SFA) is a proposed diagnostic method for examining those interactions as versioned, governed graph projections. SFA does not treat basins, convergence, collapse, or drift as intrinsic properties of an undifferentiated corpus. Each result is relative to a declared projection: node and edge types, identity resolution, jurisdiction, time, standing, evidence policy, lens, thresholds, and treatment of uncertainty. Under such a projection, SFA can propose support-cohesion regions, tension boundaries, admissible paths, dependency-sensitive convergence candidates, and version-to-version structural changes. These outputs are diagnostic candidates, not truth, authority, or automatic governance decisions. Dense agreement may reflect duplicated sources or shared error. Contradiction may be scoped rather than globally inconsistent. Change may be correction rather than drift. The paper defines a typed field model, repairs the invariant-preserving path condition, integrates SFA with the Governed Meaning Base (GMB), universal GSM, semantic cartography, binding quality, fragmentation analysis, and governed semantic compilation, and specifies countertests and an evaluation program.