This article explores how to represent sentences as graphs, moving beyond traditional semantic modeling to a more natural-language oriented approach using reification and context graphs. It demonstrates how to translate sentences into RDF, Turtle, Open Cypher, and JSON-LD, highlighting the benefits of reification for capturing nuanced information and creating cleaner, more intuitive knowledge representations.
An introduction to semantic model-driven AI, exploring how SHACL (Shape Constraint Language) can improve the reliability of LLM responses by providing structure and constraints to data.
