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sameAs: which profiles actually help an entity resolve

sameAs is a list of claims, not a link dump. What counts as corroboration, what counts as padding, and why the scanner's two-point check does not fetch a single profile.

By Alex Xu10 min read

sameAs is the most misunderstood property in structured data. It is not a place to put every social account the company owns, and it is not a ranking signal. It is a claim of identity: this URL is another page that refers to the same thing the current node describes. The useful version of that claim is short, verifiable and boring. The useless version is long, self-referential and never checked.

This article is about which profiles actually help an entity resolve, which ones are decoration, and how to audit the list you have. It is not a list of platforms to sign up for; it is a filter for the ones worth linking.

What sameAs actually claims

Schema.org defines sameAs as a URL of a reference page that unambiguously indicates the identity of the entity. The word that does the work is unambiguously: the destination has to identify the same thing, not merely mention it or be run by the same person. A link to a company’s own homepage is a self-reference, not corroboration. A link to an unrelated profile with the same name is worse than nothing.

The property is a list of claims, and a claim is only useful when someone can check it. That is why the quality of the destination matters more than the number of links: an engine resolving an entity is looking for independent pages that agree, not for a package of links the entity published about itself.

A hierarchy that is actually useful

TierExamplesWhy it helps
Authoritative / registryWikidata, a company registry, CrunchbaseRecords the entity independently of its own site; the strongest corroboration when it exists.
Code and productGitHub organisation or repository, package registriesFor a software product, the repository is verifiable evidence that the thing exists and who publishes it.
Professional profileLinkedIn company page, a founder profileNames the entity on a platform the entity does not control, usually with a back-link and a consistent name.
Directories and reviewsG2, AI-tool directories, Product HuntUseful corroboration for a product, weaker than a registry, and sometimes promotional in tone.
Social accountsX, Bluesky, a YouTube channelFine as a contact surface; the profile has to actually name the entity to count as identity.
NoiseLink farms, unrelated profiles, self-referential site pagesAdds links without adding corroboration; can make the claim less credible.

The ordering is about independence, not prestige. A small directory that clearly names the product and links to the site can be more useful than a large social account that never mentions it. The test is the same for every row: if a stranger opened the URL, would they know which entity it describes?

What this site does

LLMention’s Organization node lists three profiles: the author’s GitHub profile, the public repository for the scanner, and an AI-agents directory listing. They are in the list because each one exists, names the project, and can be opened and checked. The site deliberately does not list every account or a placeholder profile that has not been created — a link to a page that does not exist is not an identity claim.

The Person node carries its own profile link, and the WebSite and WebPage nodes point back to the Organization with @id references rather than repeating the list. One entity, one list, referenced from the places that need it.

The mistakes that make the list worthless

  • Self-reference. sameAs pointing at your own homepage or another page on your own site is circular; it corroborates nothing.
  • Profiles that do not mention the brand. A personal account with no reference to the company is not evidence that the company exists. If the profile is personal, attach it to the Person node, not the Organization.
  • Fabricated or dead profiles. A 404 or a redirect to an unrelated page is a broken claim. The scanner does not fetch the list, so this passes the check and fails the reader.
  • Name drift. The profile says one name, the site says another, and the JSON-LD says a third. Consistency across the three is the whole point.
  • Padding. Fifteen links where four would do makes the credible ones harder to find, for a person and for a model.
  • The wrong node. A company profile attached to a Personnode (or the reverse) sends the reader to the wrong entity to resolve.

How to audit your own list

Fetch the JSON-LD from the response, extract every sameAs value, and check each one by hand. The commands are deliberately boring; the judgement is the work.

# 1. List the sameAs URLs in the server response
curl -sS https://your-domain.com/ \
  | python -c "import sys,json,re; html=sys.stdin.read(); \
      blocks=re.findall(r'<script[^>]*application/ld\\+json[^>]*>(.*?)</script>', html, re.S); \
      [print(u) for b in blocks for u in re.findall(r'\"sameAs\"\s*:\s*\[?\"([^\"]+)\"', b)]"

# 2. Check every one returns 200 and is not a redirect to somewhere else
#    (run once per URL)
curl -sS -o /dev/null -w "%{http_code} %{url_effective}\n" https://profile.example.com/brand

For each URL that survives, answer three questions: does the page name the entity clearly, is it on a platform the entity does not fully control, and does it link back to the canonical site. Three yeses is a good profile. Two is acceptable. One or zero is a link, not corroboration.

What the scanner scores — and why the score is low

The rule is sameas, worth 2 points in the trust and authority dimension. The condition is only that parsed JSON-LD contains a non-empty sameAs. The rule page is explicit about the limit: the profiles are not fetched, so a list of accounts that no longer exist passes.

That is the right level for a cheap check. Presence is a one-line assertion; verification is work. Treat a pass as a reminder to do the work, not as evidence that the entity has been resolved. The same is true of every markup check on this site: the score describes the page, and the page is only as good as the claims in it.

What it changes, and what it does not

A short, verifiable sameAs list makes entity resolution cheaper: it gives a model or a person a few independent places to confirm that the brand on this site is the same brand on GitHub, in the directory, or in the registry. That reduces a specific kind of error — merging two same-named things, or treating a product and its company as unrelated.

It does not guarantee a citation, a ranking or even correct resolution. Identity is inferred from many signals, and one list is one input. The honest goal is narrower and achievable: make the claim checkable, then keep it true.

Questions about sameAs

How many sameAs profiles should I have?

A handful of profiles that actually identify the entity, not every account the company owns. Three to five verified profiles — a code host, a professional profile, a registry or directory — are usually more useful than fifteen links, because each link is a claim that has to be corroborated rather than noise.

Does sameAs have to be on the Organization node?

No. The scanner accepts a sameAs property anywhere in the parsed graph, because a Person or WebSite node can identify the same entity. Putting the strongest list on the node that represents the entity a reader is trying to resolve is the cleaner structure, but it is not a hard rule.

Do these profiles have to link back to my site?

It helps, and it is the cheapest form of corroboration: a profile that is controlled by a third party and points at the canonical site is harder to fake than a profile that merely exists. A link back is not required for schema validity; it is what makes the claim verifiable to a person.

Evidence and sources

GEO can boost visibility by up to 40% overall in generative engine responses, and in the paper's Table 1 the best of the tested methods improve on the no-optimization baseline by 41% and 28%. — Generative Engine Optimization, KDD 2024

Every figure in this piece comes from the published study or from the rule set the scanner executes; both are linked, and both can be re-run.

Primary sources

Alex Xu — Maintainer, LLMention

I build and maintain LLMention: the scanner, the rule set and the study behind it. The work is published as source, so the method can be checked rather than taken on trust.

How this site is written and funded →

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