Part of the AEO / GEO / AI-search audit tool stack. See the pillar post for the full catalog of sibling audits and where this one fits in the lineup.
AI retrievers (Perplexity, ChatGPT Browse, Claude with web, Gemini) increasingly query the entity graph before they trust a source. The entity graph is the structured cross-reference layer built from Wikidata (primary), Wikipedia, LinkedIn, Crunchbase, official company registries, and the sameAs property in your own schema.
If your site says the CEO is Jane Smith and Wikidata says the CEO is John Jones, one of those is wrong — and the retriever will usually prefer Wikidata because it's a curated source with edit history.
If your site has no Organization schema, or the schema has no sameAs property, you are not in the graph. AI retrievers can still rank you, but they can't verify you, which means they treat you as a lower-confidence source.
The Cross-Domain Entity Consistency tool reconciles both sides.
What it does
- Fetches your page
- Extracts the Organization JSON-LD (or Person schema, for author entities)
- Queries Wikidata's search API for a matching entity by name
- Fetches the matched Wikidata entity's full properties
- Compares each claim:
- Legal name
- Founding date
- Founders / CEO
- Headquarters location
- Industry (ISIC code)
- Website URL
- Social-media handles (
sameAs) - LinkedIn company page
- Crunchbase ID
- Reports matches, mismatches, and missing-on-your-side vs. missing-on-Wikidata-side
The three failure modes
1. "No Wikidata entity exists"
You haven't been listed yet. Fix: create a Wikidata entity manually (account + notability criteria apply) OR get listed in a reference source that feeds into Wikidata (Crunchbase, Forbes list, industry association directory).
2. "Entity exists but your site's schema is missing sameAs"
Your Organization JSON-LD lacks the sameAs array pointing at Wikidata QID, LinkedIn, X, Crunchbase. Fix: add the sameAs block.
3. "Both exist but disagree"
The hardest. Your site says founding year 2015, Wikidata says 2016. One is wrong — probably your site, since Wikidata is generally curated against primary sources. Fix: verify the truth, update the wrong source.
Why entity consistency is about to matter a lot more
IBM's GEO playbook names "entity presence" as one of the top-three signals. Perplexity's citation preference leans on entity-resolvable sources. Google's E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) evaluates via a mixed human/algorithmic read that includes whether the named entities resolve to real-world verified identities.
Sites with clean entity graphs get cited. Sites with no entity graph get cited less. And the difference widens as more of traffic shifts from 10-blue-links to conversational answers with inline citations.
How to use it
- Go to /tools/cross-domain-entity-consistency/
- Paste your site's URL (or your About / Team page)
- Tool fetches + queries Wikidata's public API
- Read the cross-reference report
- Copy fix prompt — emits a corrected Organization JSON-LD with sameAs URLs populated
Related reading
- Entity Citation Radar — which entities currently cite you
- Schema Graph Visualizer — your internal schema relationships
- E-E-A-T Analyzer — credibility-signal audit
Fact-check notes and sources
- Wikidata public API: Wikidata Query Service / wbsearchentities.
- schema.org Organization and sameAs: schema.org/Organization, schema.org/sameAs.
- IBM GEO playbook (entity layer): Search Engine Land — IBM GEO Playbook.
- Google E-E-A-T guidelines: Google Search Central — Creating helpful, reliable content.
This post is informational, not SEO-consulting or legal advice. Mentions of Google, Wikidata, Wikipedia, LinkedIn, Crunchbase, Perplexity, OpenAI, ChatGPT, Anthropic, Claude, Google Gemini, IBM, and similar products are nominative fair use. No affiliation is implied.
