— The Knowledge Graph —
The authority layer every LLM was already trained on.
Before an LLM answers a question about your business, it’s already weighted the facts it learned from Wikidata. Schema Monkee finds your entity, wires it into your @graph via sameAs, and submits cited claims with your site as the referenced source. By the time a new model is trained, the knowledge graph already knows the facts you control.
Why Wikidata
It’s not just “another directory.” It’s in the training data.
Wikidata is the structured companion to Wikipedia — a machine-readable knowledge graph with over 100 million entities, each with a stable Q-ID and fully cited claims. Every major language model (GPT, Claude, Gemini) is trained on Wikidata dumps. When they answer a factual question about a company, a person, or a place, they’re leaning heavily on the Wikidata record for that entity. Facts that live there are treated as canonical.
Q
Stable identity
Every Wikidata entity has a permanent Q-ID that never moves. Models use it as a disambiguation anchor — “the Brooklyn coffee roaster Acme, not the cloud tools company Acme.”
✓
Cited claims
Every fact on Wikidata carries a reference — a cited source that backs the claim. The higher-signal the source, the more weight the claim gets. Your official website is one of the strongest signals available.
⇢
Downstream reach
Wikidata powers Google’s Knowledge Panel, Siri, Alexa, Bing’s Knowledge Graph, and every major LLM’s training corpus. Updating one Wikidata claim fans out across the entire answer ecosystem.
The Sync Process
From “missing record” to “cited canonical source” — automatically.
01
Entity matching
We search Wikidata for your organization, founders, and key locations. If a record exists, we match it. If none exists for a qualifying entity, we flag it for human review — Wikidata notability rules matter, and we won’t fabricate claims.
02
sameAs linking
Once matched, we wire the Wikidata Q-ID into your @graph as a sameAs reference. Any MCP client, crawler, or training pipeline that resolves your entity will now find the Wikidata anchor — and every signal attached to it.
03
Cited claim submission
Property updates — founding date, legal name, official URL, headquarters address, key personnel — are submitted with your verified website as the referenced source. Wikidata weights claims heavily by source authority; a primary site outranks third-party aggregators.
04
Ongoing drift watch
Wikidata is editable. Claims can drift, contradict, or be removed by other editors. We monitor your record continuously, re-submit corrections when drift is detected, and alert you when a claim is actively contested so you can weigh in.
What the Claim Looks Like
The difference between “on Wikidata” and “cited on Wikidata.”
Anyone can add a claim to Wikidata. Claims without a high-authority reference are deprioritized — by Wikidata itself, and by the models trained on it. Here’s what a properly-sourced claim looks like.
Before
Unsourced or weakly sourced
Wikidata entity: Q123456789
Acme Coffee Roasters
Property: founding date (P571)
Value: 2018 ← incorrect
Reference: (none)
Property: official website (P856)
Value: acmecoffee.co ← outdated domain
Reference: imported from en.wikipedia⚠ An LLM sees weak references and treats the claim as low confidence.
After Schema Monkee
Primary-source cited
Wikidata entity: Q123456789
Acme Coffee Roasters
Property: founding date (P571)
Value: 2019 ← corrected
Reference: stated in acme.coffee/about
retrieved 2026-04-17
Property: official website (P856)
Value: https://acme.coffee
Reference: stated in acme.coffee (self-ref)
retrieved 2026-04-17
Property: award (P166)
Value: Roast Magazine Macro Roaster of the Year
Reference: stated in acme.coffee/press
retrieved 2026-04-17✓ Every claim cites your primary source. Wikidata promotes it. LLMs quote it.
Downstream
One cited claim. Fans out across the entire answer ecosystem.
A single corrected-and-cited claim on your Wikidata record doesn’t just update one place. It propagates.
- Google Knowledge Panel — rebuilt on every indexing run, picks up corrected Wikidata claims within days.
- Bing & Gemini Knowledge Graph — sourced from the same underlying Wikidata, same propagation.
- LLM training corpora — every major model pulls Wikidata dumps; next training cycle gets the corrected claim baked in.
- Voice assistants (Siri, Alexa) — Wikidata-backed answers for factual questions about businesses and people.
- Third-party aggregators — Crunchbase, LinkedIn, and business directories regularly re-import Wikidata facts.
- Your own
@graph— thesameAslink completes the loop, so your on-site schema and the global knowledge graph stay unambiguously joined.
Is your business on Wikidata? Is it cited correctly?
A free footprint audit finds your current Wikidata record (if one exists), scores the sourcing quality of every claim, and lists the fixes that would earn canonical status.