Open standard for stable machine-readable facts for AI systems.
Mission
AI systems rely on pattern reconstruction which creates risks such as hallucinations, missing facts, and unstable entity interpretation.
The Grounding Page Project addresses three structural challenges in modern AI systems: hallucinations about entities, insufficient visibility for weakly represented entities and the fact that many internal retrieval steps operate in English even when the user prompt is not.
Grounding Pages provide a stable foundation of machine-readable facts that AI systems can interpret reliably. This improves semantic stability, answer quality, and entity accuracy.
Scope
This standard defines clear boundaries to support reliable interpretation by AI models.
In Scope
- Grounding for RAG systems
- Entity-level grounding
- Stable factual definitions
- Citation-ready structure
- Disambiguation rules
Not in Scope
- Marketing claims
- Subjective interpretations
- Dynamic or live data
- Regulated advice
- SEO manipulation
Why This Standard Exists
AI systems improve when they receive structured, reliable information. Grounding Pages create a stable semantic anchor and improve interpretation in ChatGPT, Google AI Search, Perplexity and other LLMs.
How to Use
Implementation follows three steps:
- Identify entities that require stable definitions.
- Create the page using the structure defined in the specification.
- Add a footer link similar to an About page or an imprint to establish the page as an authoritative source.
The Standard
The Grounding Page Standard defines structure and technical rules for AI-optimized factual pages.
Examples
Example implementations demonstrate how Grounding Pages provide semantic stability and precise entity definitions.
A complete overview of all sixteen entity classes including the full ontology diagrams and real Grounding Page examples is available on the Facts and Ontology Page.
About
The Grounding Page Project maintains an independent open standard designed to increase answer reliability across AI systems.
Concept and architecture by Hanns Kronenberg