Wikidata is the underrated lever in entity SEO. While everyone talks about Wikipedia, Wikidata does the actual knowledge-graph work — structured, machine-readable, ingested directly by Google's KG engine, Bing, LLMs and knowledge aggregators. A maintained Wikidata item is often more valuable for entity SEO than a weak Wikipedia stub that Google does not weight as an authority signal.

The anatomy of Wikidata

Every Wikidata entity has a Q-ID (e.g., Q2283 for Microsoft, Q42 for Douglas Adams). The ID is the stable reference that never changes. The item carries labels in many languages, descriptions for disambiguation, aliases for alternative spellings and a set of statements. A statement consists of a property (P-code) + value + references. Example: P31 (instance of) + Q4830453 (business) + reference to a commercial register entry.

The quality of a Wikidata item is directly visible in the density and quality of its statements. An item with five properties and no references is weak. An item with thirty properties, all referenced to independent sources, is strong. That density acts directly on Google's KG confidence and LLM entity resolution.

Q-ID

stable identifier — foundation for the @id graph and sameAs

20+

properties as the target threshold for a strong item

References

required per statement — without refs, a weak signal

The property set for companies

Required properties: P31 (instance of → business / company / startup), P17 (country), P571 (inception date), P856 (official website), P1454 (legal form).

Strong properties: P112 (founded by — reference to a founder item), P169 (chief executive officer), P452 (industry), P361 (part of — for group structures), P159 (headquarters location), P1128 (employees).

Identifiers: P1320 (OpenCorporates), P2611 (LEI code), P5385 (Crunchbase), P4264 (LinkedIn), P2013 (Facebook ID), P2002 (X handle), P2003 (Instagram), P2397 (YouTube channel). This identifier chain is the single most important LLM entity-resolution lever.

The property set for people

Required: P31 (human), P106 (occupation), P569 (date of birth), P27 (country of citizenship), P21 (sex or gender).

Strong properties: P108 (employer), P69 (educated at), P463 (member of), P1416 (affiliation), P800 (notable work), P166 (awards).

Identifiers: P6379 (ORCID), P4264 (LinkedIn), P214 (VIAF), P244 (LoC ID), P245962 (GitHub username), P2003 (Instagram), P2002 (X), P2850 (Apple Music ID).

Wikidata property matrix for companies and people
CategoryCompany (property)Person (property)Priority
Instance typeP31 instance of → businessP31 instance of → humanRequired
Location / originP17 country, P159 HQP27 citizenship, P19 place of birthRequired
Occupation / industryP452 industryP106 occupationRequired
DateP571 inceptionP569 date of birthRequired
LeadershipP112 founded by, P169 CEOP108 employerRecommended
Official websiteP856 official websiteP856 official websiteRequired
LinkedInP4264 company IDP4264 personal IDRecommended
Academia / ORCIDP6379 ORCIDYMYL-required
Identifier codeP2611 LEI, P5385 CrunchbaseP214 VIAFStrengthening
EducationP69 educated atRecommended
Mid-read · Wikidata status

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Reference discipline

Wikidata recognizes three reference types: stated in (source is a structured database such as VIAF), reference URL (a web URL), imported from (from another project). Every substantive statement should carry at least one reference URL — ideally from an independent, authoritative source. The own website as reference for self-description is acceptable; for facts like revenue, headcount, founding date, external sources should dominate.

Maintaining Wikidata in steady state

Wikidata items are never "finished". A quarterly review across four dimensions: (1) add new publications as references, (2) reflect personnel and organizational changes, (3) update external identifiers (LinkedIn URL changes, new Crunchbase profiles), (4) drift control — identify and correct incorrect edits by third parties. Tool recommendation: a watchlist plus Wikimedia Toolforge utilities for structured reviews.

Conclusion: Wikidata is the lever beneath Wikipedia

For 80% of brands, Wikidata is the right first entity step — not Wikipedia. Lower hurdles, directly machine-readable, ingested directly by Google, Bing and LLMs. Brands that maintain and reference 20+ properties cleanly hold a knowledge-graph asset that pays off measurably across all three entity-SEO dimensions (identifiability, consistency, corroboration).