SAGE 2026 proposes a workshop at SEMANTiCS focused on semantic architectures that make AI systems governed, explainable, and evidence-driven. Despite rapid progress in machine learning and large language models, most systems remain prediction-centric, weakly auditable, and difficult to align with governance requirements. Meanwhile, the Semantic Web community provides mature foundations for knowledge representation, constraint validation, provenance, and reasoning. However, these strands remain fragmented and rarely integrated into end-to-end reasoning systems. SAGE addresses this gap by bringing together researchers working on knowledge graphs, ontologies, rules, provenance, causal reasoning, and hybrid LLM+KG pipelines. The workshop will focus on architectural principles, evaluation practices, and community-building outcomes for trustworthy semantic systems.
SAGE 2026: Semantic Architectures for Governance and Explainability