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opendata402 Wikidata Entity Lookup
x402
opendata402 Wikidata Entity Lookup is a paid API for AI agents from opendata402.com, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-15).
Returns key facts (label, description, type, location, dates, identifiers, and more) about any entity from Wikidata by name or Q-id.
Price / call$0.001
Success—
StatusUnknown
How this service works
Key facts about any thing, place, person or company from Wikidata, by name or Q-id: label, description, Wikidata id and the most useful properties (type, country, location, population, coordinates, inception, birth/death dates, occupation, website, headquarters, industry, revenue, employees, ticker). Use it for entity lookup, enrichment and disambiguation. CC0.
Output
A structured JSON object containing the entity's Wikidata Q-id, label, and description, plus a curated set of the most useful properties: type, country, location coordinates, population, inception or birth/death dates, occupation, official website, headquarters, industry, revenue, employee count, and stock ticker — whichever are available for the entity.
Example use cases
Enrich company records with Wikidata
“I have a list of company names — can you pull each one's Wikidata entry and add the industry, headquarters country, revenue, and employee count to my spreadsheet?”
Disambiguate a historical figure
“I need to know which 'Alexander Hamilton' is the Founding Father — can you look him up on Wikidata by Q-id Q178903 and confirm his birth and death dates and occupation?”
Geocode a city for mapping
“Can you find the coordinates and population of Kyoto, Japan from Wikidata so I can plot it on a map?”
Technical details
Endpoint
GEThttps://opendata402.com/v1/wikidata?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need fast, structured, CC0-licensed facts about a named entity — person, place, company, or thing — drawn from Wikidata's knowledge graph. It is ideal for entity enrichment pipelines, disambiguation, and quick fact lookups without scraping Wikipedia or calling the full Wikidata SPARQL API. Prefer it over Wikipedia scraping when you need machine-readable structured fields like coordinates, tickers, or founding dates.
Side effects
- Entity not found in Wikidata — returns empty or error if the name is too ambiguous or nonexistent
- Ambiguous name may resolve to the wrong entity — use Q-id for precision
- Missing properties — not all entities have all fields; absent properties are omitted
- Language code not supported — falls back to English or returns error
- Query too short or too long — rejected by the 2–120 character length constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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