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MARKETING · 2026-05-28

Entity recognition for B2B brands: the Wikidata + Knowledge Graph play

AI Overview disproportionately cites brands Google recognizes as named entities. Entity recognition is built through four signals: a Wikidata entry, presence in trusted databases (Crunchbase, LinkedIn), consistent NAP (name, address, phone) across the web, and Schema.org sameAs linking your assertions back to those external sources. The whole playbook runs in about 8 hours of work and pays off for years.

By Nazar Mazur · 5 min read

Why entity recognition matters for AEO

Google Knowledge Graph is a structured database of entities (people, organizations, places, products). When AI Overview synthesizes an answer, it weights cited sources by entity status: a citation from a recognized entity is more trustworthy than a citation from an unknown publisher. This is true across AI Overview, Bing/Copilot grounding, and (to varying degrees) ChatGPT Search and Perplexity.

A B2B brand under 50 employees typically has weak entity signals: no Wikidata entry, sparse Crunchbase data, inconsistent NAP across the web, Person schema without sameAs. Fixing this is the highest-leverage entity-recognition work available.

Signal 1: Wikidata entry

Wikidata is the structured database that feeds Google Knowledge Graph directly. A Wikidata Q-item with referenced statements is the strongest single signal for entity recognition.

Setup (60 minutes):

  1. Register at wikidata.org. Use a personal username, not the brand name (community is skeptical of brand accounts).
  2. Create a Q-item for the company with: instance of (business), industry (your category), country, headquarters location, founded by, founding date, official website.
  3. Every statement needs a reference URL. Your own /team or /llm-info pages count. The more diverse the references, the stronger.
  4. Create a separate Q-item for the founder linked via founded by / chief executive officer.
  5. Add external IDs: LinkedIn (P6634), X (P2002), Crunchbase (P2087) once those exist.

Wikidata moderation: 4-14 days for pass-rate ~90% if statements have references. Knowledge Graph pickup: 4-12 weeks after Wikidata acceptance.

Signal 2: Trusted database presence

After Wikidata, the highest-trust databases for B2B entity confirmation:

  • Crunchbase — high DA, B2B-focused, often appears in Knowledge Panel. Free account, 30 minutes to set up.
  • LinkedIn Company Page — Google reads LinkedIn extensively for entity disambiguation.
  • Industry-specific databases for your category (e.g., G2 / Capterra for SaaS, Clutch for agencies, AngelList for startup-stage).
  • Bloomberg / Reuters / Pitchbook — high-trust but typically require press coverage to populate.

Submit to 3-5 high-trust databases in your category. Do not mass-submit to 200 directories — Google now down-weights mass-submission signals.

Signal 3: Consistent NAP

Name, Address, Phone consistency across the web is checked by Google as part of entity disambiguation. For B2B brands, this also includes founders, founding date, headquarters location.

Check that the following match exactly:

  • Your /team page
  • LinkedIn company page
  • LinkedIn founder profile (employer = company name exactly)
  • Crunchbase
  • Wikidata statements
  • Schema.org Organization and Person on your site

Common drift: founding year off by one, address abbreviated differently, founder name with vs. without middle initial. Each inconsistency is a small signal-loss; aggregate they materially reduce entity confidence.

Signal 4: Schema.org sameAs links

Your own Organization and Person schemas should have sameAs arrays linking to LinkedIn, Crunchbase, Wikidata, X, and the founder's profile sources. This creates a verifiable graph Google can traverse to confirm entity claims.

Common gap: sameAs exists but lists only LinkedIn and Twitter. Adding Crunchbase, Wikidata Q-item URL, and (for founder) a personal LinkedIn doubles signal strength at zero ongoing cost.

Important: sameAs URLs must actually resolve to pages about the same entity. Pointing sameAs to a placeholder LinkedIn URL that does not yet exist creates a broken signal. Wait until the profile is created.

Order of execution

If starting from zero:

  1. Wikidata first — slowest moderation cycle, set it up first.
  2. Crunchbase + LinkedIn Company Page same day — fast setup, parallel.
  3. NAP consistency audit and fixes — 1-2 hours.
  4. Schema.org sameAs additions — 30 minutes, deploy with next regular release.
  5. Wait 6-12 weeks. Check for Knowledge Panel appearance. Iterate.

The whole sequence is roughly one day of focused work. The compound effect — being recognized as an entity by AI Overview — runs for years.

Frequently asked questions

How long does Knowledge Panel take to appear after Wikidata?

Typical range is 4-12 weeks after Wikidata moderation passes, sometimes faster if you have strong external signals (Crunchbase, LinkedIn, brand mentions). Some brands wait longer; if 4 months pass without Knowledge Panel, the signal stack needs strengthening (more backlinks, more entity references on .gov/.edu).

Can I edit my own Wikidata entry?

Yes. Self-editing is common and accepted as long as statements are factual and referenced. The Wikidata community will edit out any promotional language or unreferenced claims. Resist the temptation to phrase things like marketing copy.

Do I need a Wikipedia page too?

Not initially. Wikidata feeds Knowledge Graph directly without Wikipedia. Wikipedia notability requirements are much higher than Wikidata. Most B2B brands under 100 employees do not qualify for Wikipedia but do qualify for Wikidata.

Does this work for personal brands (founder, executive) as well?

Yes. The same playbook applies to people. Personal Wikidata Q-item + LinkedIn + named author schema across your content creates entity recognition for the person, which compounds with company entity recognition.

Where Logitelia fits

Logitelia's Growth team executes the full entity recognition stack — Wikidata draft, Crunchbase submission, NAP audit, sameAs schema upgrades — as part of every Growth Team subscription. Starting at €4,500/month, cancel monthly. Book a call and we will audit your current entity recognition signals on the call.

Want to see how Logitelia ships this kind of work for your team?

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