Wikidata Entity & Company Enrichment: Facts & IDs · Apify
Wikidata Entity & Company Enrichment (facts, IDs, links) avatar

Wikidata Entity & Company Enrichment (facts, IDs, links)

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Wikidata Entity & Company Enrichment (facts, IDs, links)

Wikidata Entity & Company Enrichment (facts, IDs, links)

Try for free

Resolve Wikidata QIDs, names and Wikipedia URLs into useful entity facts and links. Valid entities enter results; failed lookups stay in Diagnostics. Batch and Standby HTTP API, with result-budget checks and requested-language labels.

Pricing

from $0.60 / 1,000 results

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Murat Uzun

Murat Uzun

Maintained by Community

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7 days ago

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Business

Lead generation

AI

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Limited permissionsSingle-tenantServer interface

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Wikidata Entity & Company Enrichment turns a QID (Q95), a name (Apify), or a Wikipedia article URL (https://en.wikipedia.org/wiki/Stripe,_Inc.) into a structured record of facts pulled straight from Wikidata, the free, editable knowledge base behind Wikipedia's infoboxes. Give it a list of companies, people, or places and get back one useful result per successfully enriched entity, using Wikidata public APIs.

Quality policy (0.35): upstream/API errors, missing entities and identity-only records never enter the result dataset. Open Quality report in Output for accepted/diagnostic counts and the first diagnostic key; full failed records are in KV Diagnostics. An all-rejected batch ends FAILED; mixed batches retain valid results. Counts cover the current process attempt, and restarting/resurrecting a run does not provide deduplication of previous dataset rows.

Standby API: GET / is readiness; GET /?entity=Q95 or /?entities=Q95,Q312 enriches up to 100 entities. Failed lookups appear as separate diagnostics, not result rows. No usable result returns HTTP502; an exhausted result-event budget returns402 before upstream work. Mixed and budget-truncated responses include partial/skipped/diagnostic counts. Unconfirmed dataset delivery returns503 and stops further data work and terminates that process after sending the error response; inspect the run dataset before retrying to avoid duplicate results. Standby remains enabled.

What data does Wikidata Entity & Company Enrichment extract?

FieldDescription
qid, label, descriptionThe resolved Wikidata item, its requested-language label and description, with English fallback
matchConfidence1.0 for a direct QID/Wikipedia URL; 0.9/0.6/0.4 for a name search, by match quality
instanceOf, entityTypeWhat kind of thing it is (P31), bucketed into company/person/place/product
country, headquarters, inceptionP17, P159, P571
founders, ceo, employees, employeesAsOfP112, P169, P1128 (latest count by its point-in-time qualifier)
revenue, revenueCurrency, revenueAsOfP2139, latest by point-in-time qualifier
website, industries, parentOrganization, legalFormP856, P452, P749, P1454
isin, crunchbaseId, linkedinIdP946, P2088, P4264
twitter, facebook, instagram, youtubeChannelIdP2002, P2013, P2003, P1651
coordinates, imageUrl, logoUrlP625, and Commons URLs built from P18/P154
wikipediaUrl, wikidataUrlThe enwiki sitelink and the canonical Wikidata item link

Pricing: see the current Pricing tab for event prices and plan tiers. Only useful result dataset rows create result events. Failed lookups remain in Diagnostics; actor-start fees and applicable platform usage may still apply.

Every claim missing on a given entity comes back as null rather than an error — a person has no revenue, a startup has no ISIN, and that is expected.

How to use Wikidata Entity & Company Enrichment

  1. Click Try for free (or Start) on this Actor's page.
  2. In Entities, list what you want resolved: QIDs, company/person names, or Wikipedia URLs — one per line.
  3. Optionally set Language (default en), an Entity type filter to prefer a company/person/place/product match on ambiguous name searches, and Max concurrency.
  4. Run the Actor. Each entity becomes one dataset row.
  5. Open the Dataset tab and export as JSON, CSV, Excel, or HTML — or pull it via the API into your CRM or enrichment pipeline.

Example input

{
    "entities": ["Q95", "Apify", "https://en.wikipedia.org/wiki/Stripe,_Inc."],
    "language": "en",
    "entityType": "any",
    "maxConcurrency": 5
}

Example output

{
    "query": "Apify",
    "qid": "Q112502991",
    "label": "Apify",
    "description": "Czech tech startup",
    "matchConfidence": 0.9,
    "entityType": "company",
    "country": "Czech Republic",
    "headquarters": "Prague",
    "employees": 66,
    "employeesAsOf": "2021-01-01",
    "revenue": 298000000,
    "revenueCurrency": "Czech koruna",
    "website": "https://apify.com/",
    "wikidataUrl": "https://www.wikidata.org/wiki/Q112502991",
    "scrapedAt": "2026-09-12T18:44:51.519Z"
}

Input parameters

  • Entities (entities, required) — QIDs, names, or Wikipedia URLs to resolve. Default ["Q95"].
  • Language (language) — Wikidata/Wikipedia language code for labels and search. Default en.
  • Entity type filter (entityType) — any, company, person, place, or product; nudges name-search matching toward that instance-of type. Default any.
  • Max concurrency (maxConcurrency) — parallel entities processed at once, 1-20. Default 5.

Pricing

Current prices are shown in the Pricing tab. Standard PPE and Standby can have different platform-usage treatment; the run options and Pricing tab show the applicable charges. Set Maximum cost per run before starting.

Wikidata Entity & Company Enrichment vs. a manual Wikidata lookup

Looking up one company on wikidata.org and copying its infobox takes a minute; doing it for a list of 500 leads does not scale. This Actor batches the same lookups — search, entity fetch, and label resolution for every referenced ID — behind one input list, on a schedule if you want it, and exports straight to CSV or your CRM via Apify's integrations (Zapier, Make, n8n).

Using Wikidata Entity & Company Enrichment with AI agents

The Actor is built pay-per-event so it is callable through the Apify MCP server or any agent framework: pass an entity name or QID, get back a structured company/person profile an LLM can reason over (industry, HQ, employee count, official links) without the model having to parse a Wikipedia infobox itself.

FAQ

Is this legal? Yes — Wikidata is public-domain (CC0) structured data, and this Actor only calls Wikidata's own public API endpoints (wbsearchentities, Special:EntityData, wbgetentities) plus Wikipedia's pageprops endpoint, at a modest rate.

Why is a field null? Wikidata simply has no statement for that property on that entity — a common, expected outcome, not a bug.

Can I search by company name instead of QID? Yes — plain names go through wbsearchentities; matchConfidence tells you how sure the match is (1.0 exact QID/URL, 0.9 exact label match, 0.6 best-guess first result, 0.4 a lower-ranked type-matched result).

Something looks wrong or missing. Open an issue on the Actor's Issues tab with the entity you tried — Wikidata's data model has edge cases (multiple CEOs, deprecated statements) this Actor resolves with best-rank/latest-by-date heuristics.

Part of the webdatatools web-intelligence suite — every Actor is pay-per-event, reads public data without a login, and returns one clean row per entity:

Browse the whole suite at webdatatools, or call ten of these Actors straight from Claude, Cursor or Cline with the webdatatools MCP server.

Website & domain intelligence

Content for AI, LLMs and RAG

Search, video and social

Leads, jobs and company data

Developer, app and research data

Support

Found a bug or want a feature (more properties, more languages, bulk CSV upload)? Use the Issues tab on this Actor's Apify Store page — it is the fastest way to reach the maintainer.

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