Educating AI: Ontologies That Help AI Reason Better and Hallucinate Less

These slides accompany the webinar: Educating AI: Ontologies That Help AI Reason Better and Hallucinate Less

Large Language Models are powerful — but they hallucinate, and they can't be trusted to act autonomously without structured guidance. In this session, Graham McLeod explains how ontologies provide the knowledge layer that helps AI reason reliably, make deterministic decisions, and reduce hallucinations in enterprise environments.

Recorded at the Educating AI webinar hosted by Ecosystem.ai on 5 August 2026.

We cover:

• What ontologies are and why enterprises need them

• Core building blocks: types, relationships, roles, properties, and constraints

• Key standards: OWL, RDF, SHACL, Turtle, and SPARQL

• How knowledge graphs enable trustworthy AI agents

• Avoiding vendor lock-in from platforms like Palantir, Google, and Microsoft Fabric

• The Accessible Enterprise Ontology (AON) initiative

• Sapiento: a graph-based modeling and execution tool

• The open-source "Flow" platform for vendor-agnostic SQL queries

Perfect for enterprise architects, AI engineers, and anyone exploring how structured knowledge can make LLMs more reliable.

🌐 Ecosystem.ai — Real-time AI personalization and prediction platform
https://ecosystem.ai

Semantic Technologies and the Web of Meaning: An Introduction for Enterprise Practitioners

What are semantic technologies, how do they work, and why do they matter for enterprise architecture and information management?

The World Wide Web was built to share documents between humans — but semantic technologies, as Tim Berners-Lee foresaw from the outset, make it possible to share and query meaning between machines at web scale. This 2011 lecture by Graham McLeod, delivered at the University of Cape Town, provides a thorough and accessible introduction to the semantic web stack for enterprise practitioners.

Starting from first principles — what semantics means, and why the distinction between syntax and meaning matters — the lecture works through the core W3C standards: RDF as a graph-based data model where every fact is uniquely addressable via a URI, SPARQL as the query language that can span multiple distributed datasets as a single conceptual database, OWL as the web ontology language that enables classification, inferencing, and richer knowledge organisation, and linked open data as the practical realisation of these ideas at internet scale.

A particularly illuminating section demonstrates how two independently published datasets about the same book — one in English, one in French — can be automatically merged and queried together simply by sharing a common URI and a few bridging statements, illustrating the power of the approach for enterprise data integration. Real-world applications covered include Siri, DBPedia, semantic video indexing, and geo-spatial data integration.

For enterprise architects and information architects grappling with data integration, knowledge management, or the foundations of AI-driven systems, this lecture provides both the conceptual grounding and the practical vocabulary needed to engage seriously with semantic technologies.

Originally presented by Graham McLeod as a guest lecture at the University of Cape Town, June 2011.