Knowledge Vault: Google's Predicted Fact Database
Knowledge Vault is Googles research prototype for building a massive database of facts about entities, combining extraction with automated prediction.
Knowledge Vault is Google's research prototype database that predicts and stores facts about entities.
What It Is
Knowledge Vault was Googles research effort to build a vast database of facts by automatically extracting claims from the web and scoring how confident it was in each one.
Unlike manual curation, the system predicted facts and assigned a probability to each, feeding the Knowledge Graph and related systems.
How It Works
- Extracts candidate facts from billions of web pages.
- Combines text patterns, existing graph data, and statistics.
- Assigns a confidence score to every extracted fact.
- Stores only facts that pass a confidence threshold.
Why It Matters
- It shows how Google builds and checks the entities behind search results.
- Fact-based understanding powers panels, snippets, and AI answers.
- Websites that present facts clearly are easier for these systems to digest.
Implications for SEO
- Publish consistent, well-structured factual content.
- Use schema markup to label entities and facts.
- Keep entities and claims aligned across your site and listings.
Before: a brand makes claims scattered across a PDF with no structure.
After: the same facts live in clean HTML with schema markup.
The result: systems can extract, score, and trust the information.
The lesson: structure facts so machines can verify them.
Quick Tip
Mark up entity facts with schema.org markup so fact-extraction systems can read them without guessing.
Frequently Asked Questions
Knowledge Vault, in Short
Google is constantly turning the web into machine-readable facts.
Present facts clearly and consistently and systems will trust them.