The authority network is the machine-readable layer that lets a search engine or language model understand what a page is about and connect it to a known entity: valid JSON-LD structured data, Organization and Person nodes with sameAs links to Wikidata, LinkedIn and other corroborating profiles, consistent name and address data, and off-site mentions that agree with the on-site story. Google's Knowledge Graph holds about 54 billion entities, and a brand that is not one of them is invisible to entity-based retrieval. This hub links the Entity Authority framework, the Schema Scanner, the Knowledge Graph gap analysis and the pillar-four audit checks.
Before a machine can cite you it has to know who you are and trust it has the right entity. This pillar is the machine-readable layer: schema validity, entity and Knowledge Graph signals, consistent sameAs references and off-site corroboration. Third-largest commercial-intent cluster, led by schema markup and knowledge graph demand.
Which frameworks explain schema markup and entity authority?
Which free tools and lab builds cover schema markup and entity authority?
AEO Schema Scanner
A free Chrome extension that reads any page’s structured data and shows three things: what is detected, what Google has deprecated or demoted, and what is missing to be the trusted answer in AI search. It also flags incomplete Organization and Person entities (missing sameAs, @id, logo, knowsAbout, jobTitle). The scan is 100% on-device. Open source.
Knowledge Graph Gap Analysis
A method for finding what is missing in a knowledge base by visualising it as a graph and identifying structural holes, dense clusters of related ideas that are not connected to each other. Bridging a structural hole tends to produce original, non-generic insight, because the territory between two developed clusters is by definition under-explored.
What has Laurelin published on schema markup and entity authority?
Which of the 330 audit checks belong to schema markup and entity authority?
59 checks in the Authority Network pillar of the 330-check AEO audit, each cited to a primary source. The most consulted first.
- Invalid JSON-LD syntax
- Unparseable / bad escaping
- Missing required properties
- Missing recommended properties
- Wrong @type
- Markup for invisible content
- Structured data on noindex page
- Inconsistent vocabularies
- Microdata/RDFa conflicting with JSON-LD
- Unstable/duplicate @id
- Deprecated types/properties
- Schema stuffing
- Conflicting duplicate entities
- No Organization schema
- No WebSite schema/SearchAction
- No Article markup on editorial
- Article missing author/date/headline
- Product missing price/availability/currency
- Product missing/invalid review/rating
- Offer missing priceValidUntil
- Missing BreadcrumbList
- FAQ/QA markup misused
- No LocalBusiness for a local business
- LocalBusiness missing geo/hours/address
Frequently asked questions about schema markup and entity authority
What is entity authority?
The degree to which a brand, product or person exists as a distinct, verified entity in the knowledge graphs that search engines and AI models draw on. It is built by consistent structured data, resolvable sameAs identifiers, a Wikidata item where the notability rules allow one, and third-party mentions that corroborate the same facts.
Which schema types matter most for AI search?
Organization and Person with sameAs (entity resolution), Article or TechArticle with author, dates and about (provenance), FAQPage and speakable (passage extraction), and BreadcrumbList (site hierarchy). Types the page is not genuinely eligible for add nothing and can trigger a manual action.