It is a common confusion in our industry: “GEO” often refers to “Generative Engine Optimization.” But for the scientific community, GEO means Geology. And interestingly, geological data provides one of the best case studies for how to ground Large Language Models in physical reality.

The Hallucination of Physical Space

Ask an ungrounded LLM “What is the soil composition of the specific plot at [Lat, Long]?” and it will likely hallucinate a generic answer based on the region. “It’s probably clay.” It averages the data.

Geological features are named entities. “Mount Everest” is an entity. “The San Andreas Fault” is an entity. “The Pierre Shale Formation” is an entity.

For researchers in the geospatial domain, linking your content to these distinct entities is the bedrock of MCP-SEO.

Disambiguation via Wikidata

“Paris” is a city in France. “Paris” is also a city in Texas. “Paris” is also a rock formation (hypothetically). To ensure an AI understands you are talking about the rock formation, you must link to its Wikidata ID (e.g., Q12345).