Semantic Knowledge Production

Abstract

Semantic knowledge is increasingly produced through combinations of human expertise, computational processing, external knowledge resources, and artificial intelligence. This paper develops an architectural account of semantic knowledge production for systems in which assertions may depend on different forms of evidence, competence, inference, and prior semantic states while remaining incomplete, contested, or revisable. The framework distinguishes four semantic roles—Evidence, Knowledge, Provenance, and Normative consequence—and treats knowledge production as a progressive process of observation, interpretation, review, inference, and stabilisation. Stabilised semantic states are operationally reusable without being treated as epistemically final, while provenance preserves the lineage and warrant of knowledge-producing activities. A running cultural-heritage example illustrates how heterogeneous evidence and human and computational activities can participate in this process. A developing companion paper, The Review Algebra, formalises candidate generation, review, and finalisation as provenance-bearing transformations between semantic states.