- Entity resolution is Stage 2 of the AI visibility build sequence: a model can't reliably attach a citation, review, or stat to a brand it hasn't confidently disambiguated from near-duplicates.
- The single highest-value fix: one canonical brand-name string, used identically across your own site, Wikidata, G2, Capterra, Crunchbase, and LinkedIn. "Acme Corp," "Acme Corp.," and "ACME" read as three different entities to a knowledge graph, not one.
- Wikidata is the highest-impact single entry, because it feeds directly into Google's Knowledge Graph rather than being one signal among several. Worth prioritizing if you qualify under its notability standard.
- Organization schema needs a validated sameAs array (check with Google's Rich Results Test and the Schema.org Validator) pointing at every authoritative profile you control, plus an
@idanchoring your own site's schema to one node. A dead or redirected sameAs link is worse than no link, since it signals an entity that used to resolve and no longer does. - This whole audit is mechanical, checkable by eye, and realistically completable in under an hour. It doesn't require a paid tool or an agency engagement.
A model doesn't cite a name. It cites an entity it has some confidence it has correctly resolved: the right company, the right category, the right facts attached. Get the entity wrong and every downstream signal (a review, a press mention, a stat someone cites about you) has a real chance of attaching to the wrong node, or not attaching at all. That's Stage 2 of the five-stage sequence, and unlike the access check in Stage 1, it doesn't need a server-log dig. It needs about an hour and a browser.
How do you run the name-consistency check (10 minutes)?
Open, side by side: your own homepage and legal/footer text, your Wikidata entry if you have one, your G2 or Capterra profile, your Crunchbase page, and your LinkedIn company page. Write down the exact brand-name string used on each.
"Acme Corp," "Acme Corp.," and "ACME" are three different entity nodes from a knowledge graph's perspective, not stylistic variants of one. Pick a single canonical string (including whether you use a legal suffix, spacing, or capitalization) and treat every other version as a bug to fix, not a minor inconsistency to leave alone. This single fix is the highest-value item on the whole list, because it's the precondition every other item in this audit depends on.
How do you run the Wikidata check (15 minutes)?
Search Wikidata for your brand. If an entry exists, verify: the official website property is set and points to your actual domain, the label matches your canonical name exactly, and the entry isn't stale (an old product name, a former legal entity, outdated leadership).
If no entry exists, check Wikidata's notability standard before creating one. It requires the subject to be a clearly identifiable entity describable with serious, publicly available references (a registry entry, an authority record, a database profile counts; a lower and different bar than Wikipedia's press-coverage standard, covered in full in Wikidata for brands). If you don't qualify yet, don't force it; a Wikidata entry created to game the system is worse than no entry, because it can get flagged and removed, and that history is itself a negative signal. Come back to this once you have the qualifying references that would make you eligible on its own merits.
Also worth the two minutes: check Google's own Knowledge Graph Search API (or the no-code Knowledge Graph Explorer) for whether Google has already resolved your brand as a distinct entity. This checks the actual output of entity resolution rather than inferring it from your inputs. If a Knowledge Panel already exists, claim and verify it (via Search Console or a linked YouTube channel) rather than leaving it unclaimed and out of date.
How do you run the schema check (15 minutes)?
Check whether your site has a validated Organization schema block, using Google's Rich Results Test (checks rich-result eligibility specifically) and the Schema.org Markup Validator (checks full schema.org spec compliance). The two are checking different things, so run both rather than treating a pass on one as confirmation of the other.
Specifically confirm two properties: a sameAs array, the property that tells a machine "this profile and that profile describe the identical entity," pointing to every authoritative profile you actually control (Wikidata, LinkedIn, Crunchbase, G2 or Capterra), and an @id, the property that actually anchors a single canonical node across your own site's schema. sameAs only links outward to other profiles; @id is what keeps every mention of the brand within your own schema resolving back to one entity instead of several unlinked ones.
Check each sameAs URL by actually clicking it. A dead link or a redirect to a different page is worse than no sameAs entry at all. It signals an entity that used to resolve cleanly and no longer does, which is a more confusing signal to a model than simply having gaps.
How do you run the profile-alignment check (15 minutes)?
For each third-party profile in your sameAs array (G2, Capterra, Crunchbase, LinkedIn) check that the basic facts agree with what your own site says: founding year, headquarters, category, and especially the canonical name string from step one. These platforms are exactly the kind of third-party sources AI models weight heavily for earned-media citations, so a disagreement here isn't cosmetic. It's the entity-resolution layer failing at the exact place a citation would otherwise land.
What doesn't this fix?
This checklist gets you a cleanly resolvable entity. It doesn't get you cited on its own. Entity resolution is a precondition for the citations, reviews, and third-party proof covered in later stages to actually attach correctly; it's not a substitute for earning them. If your entity is clean and your citation rate is still low, the gap is almost certainly further down the sequence, in content extractability or earned off-site presence, not here.
Frequently asked questions
What's the fastest way to check if my brand's entity is consistent?
Pull up your own homepage, your Wikidata entry (if you have one), your G2 or Capterra profile, your Crunchbase page, and your LinkedIn company page side by side, and compare the exact brand name string on each. If they don't match character-for-character, that's the fastest, single highest-value fix available, and it costs nothing but time.
Do I need a Wikidata entry?
If you qualify for one under Wikidata's notability standard, yes. It's the single highest-impact entry point, because it feeds directly into Google's Knowledge Graph rather than being one signal among many. If you don't yet qualify, don't fabricate notability to get one; fix the rest of the checklist first and revisit later.
What's a "sameAs" link and why does it matter?
It's a schema.org property that tells a machine "this profile and that profile describe the identical entity," pointing your Organization schema's sameAs array at your Wikidata, LinkedIn, Crunchbase, and G2 profiles. A dead or redirected sameAs link is worse than no link at all, because it signals an entity that was once resolvable and no longer is.
How long does entity resolution take to show up in AI answers?
Not rigorously measured anywhere in the industry as of mid-2026. Treat any vendor's specific day-count promise here skeptically, the same caution that applies to any AI-visibility timeline claim. What's measurable is the work itself, which is mechanical and largely completable in the hour this piece describes; the propagation lag afterward isn't something anyone has published real data on yet.
Sources referenced
- Google Search Central: Organization structured data
- Wikidata: Notability policy
- Schema.org: sameAs property
- Google Knowledge Graph Search API
- Google: Claim your Knowledge Panel
This piece assumes the sequencing in the five stages for winning in the AI search era and the access-layer check in how to check AI crawler access. Do that one first; entity work on a site AI crawlers can't reach is wasted effort.
