Legal codes, such as the Uniform Commercial Code (UCC) examined in this article, are good points of entry for AI and ontology work because of their more straightforward adaptability to relationship linking and rules-based encoding. However, approaches relying on encoding solely on formal code structure are incomplete, missing the rich experience of practitioner expertise that identifies key relationships and decision criteria often supplied by experienced practitioners and process experts from various disciplines (e.g., sociology, political economics, logistics, operations research). This research focuses on the UCC because it transcends the limitations of a formal code, functioning essentially as a composite. AI work can benefit from real-world codes like the UCC, which are essentially formal codes enlightened from a more realistic experience-base from centuries of development in international commercial transactions settings. This paper then describes our initial work in converting an expert system on the U.S. law governing the sale of goods from Article II of the Uniform Commercial Code (UCC), into a knowledge-based system using the Web Ontology Language OWL.