Lexicon
Knowledge Graph
What a knowledge graph means, and how Paul Truscott applies a statistical measurement lens to track how an entity's position within it changes over time.
Factual Definition
A knowledge graph is a knowledge base that uses a graph-structured data model to store and connect information about real-world entities, people, places, organizations, and concepts, and the relationships between them. Google's implementation, Knowledge Graph (Google), is a specific application of this generic concept.
Paul Truscott's Perspective on the Knowledge Graph
Paul Truscott's perspective on the knowledge graph is that most practitioners describe an entity's position within it in static terms, present or absent, accurate or inaccurate. His view is that an entity's standing inside the knowledge graph behaves more like a position on a price chart than a fixed record: it has a trust baseline it will not easily fall below once established, and a visibility ceiling it cannot exceed without new, independent evidence. This is the direct basis for Entity Support and Resistance, a framework built specifically to describe those floor and ceiling levels within the knowledge graph in measurable terms.
He treats the knowledge graph not as a static database to be corrected once, but as a system whose representation of an entity shifts as new corroborating or conflicting data enters it, requiring ongoing monitoring rather than a single audit.
How Paul Truscott Applies Knowledge Graph Thinking
Paul audits a client's knowledge graph representation for accuracy and completeness, then tracks how that representation changes over time as new corroborating sources are added through his knowledge graph engineering work. This is measured continuously against the entity's established support and resistance levels, rather than treated as a one-time correction exercise. Read the full methodology.
Why the Knowledge Graph Matters to Paul Truscott's Practice
The knowledge graph is the underlying data structure that determines how an entity is represented across Google Search, Google's AI Overviews, and increasingly other AI systems that draw on structured entity data. Paul's coined framework for reading trust levels within it, Entity Support and Resistance, is a direct application of his financial technical analysis background to this specific system. Read the full analytical foundation this framework was built on.