Wikidata Entity Scraper — Labels, Claims & Sitelinks | from $0.50/1K

Built for knowledge-graph builders, entity-resolution pipelines, and AI agents that need structured Wikidata records by Q-ID or keyword. Official APIs only — no proxy, no auth, zero COGS.

Extract structured data from Wikidata entities via the official public APIs. No proxy, no authentication required.

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What you get

For each entity (fetched by Q-ID or discovered via search):

Field	Description
entity_id	Wikidata Q-ID (e.g. Q42)
label	Human-readable name in requested language
description	Short description (e.g. "British science fiction writer")
aliases	Known alternative names
instance_of	What type of entity this is (Q-IDs from P31)
key_claims	Selected property values (dates, genders, occupations, nationalities…)
sitelinks_count	Number of Wikipedia editions this entity has an article on
url	Canonical Wikidata entity URL
parse_confidence	0.0–1.0 quality score; 1.0 = all expected fields present
warnings	List of field-level quality warnings

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Inputs

Basic

Parameter	Type	Description	Default
entityIds	array	Wikidata Q-IDs to fetch directly	["Q42", "Q937"]
searchQueries	array	Full-text search queries	[]
language	string	Language code for labels/descriptions	"en"
maxItems	integer	Max total entities to return (0 = unlimited)	50
maxSearchResults	integer	Max results per search query (1–50)	10

Advanced

Parameter	Type	Description	Default
claimProperties	array	P-value property IDs to extract	["P31","P21","P27","P569","P570","P19","P106"]
maxClaimsPerProperty	integer	Max values per property (0 = all)	5

Default properties extracted:

• P31 — instance of (what kind of thing this is)
• P21 — sex or gender
• P27 — country of citizenship
• P569 — date of birth
• P570 — date of death
• P19 — place of birth
• P106 — occupation

Other useful properties: P18 (image), P856 (website), P17 (country), P131 (located in), P625 (coordinates).

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Example

Input:

{
  "entityIds": ["Q42", "Q7186"],
  "language": "en",
  "claimProperties": ["P31", "P569", "P570", "P106"]
}

Output record for Q42:

{
  "entity_id": "Q42",
  "label": "Douglas Adams",
  "description": "British science fiction writer and humorist (1952–2001)",
  "aliases": ["Douglas Noel Adams"],
  "instance_of": ["Q5"],
  "key_claims": {
    "P31": ["Q5"],
    "P569": ["1952-03-11T00:00:00Z"],
    "P570": ["2001-05-11T00:00:00Z"],
    "P106": ["Q214917", "Q28389", "Q6625963"]
  },
  "sitelinks_count": 132,
  "url": "https://www.wikidata.org/wiki/Q42",
  "language": "en",
  "query": "Q42",
  "source": "entity_id",
  "scraped_at": "2026-05-31T10:00:00Z",
  "parse_confidence": 1.0,
  "warnings": []
}

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Notes on claim values

Claim values are decoded to human-readable strings:

• wikibase-item → Q-ID string ("Q5", "Q6581097")
• time → ISO date string ("1952-03-11T00:00:00Z")
• string / external-id → raw string
• quantity → "42 Q11573" (amount + unit Q-ID)

To look up what a Q-ID means (e.g. "Q5" = human, "Q145" = United Kingdom), search it on wikidata.org.

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Pricing

Pay per entity: from $0.50 / 1,000 entities (PPE). Apify automatically charges the run owner. No monthly subscription. The first few seconds of each run are covered by Apify.

Volume	Cost
100 entities	~$0.05
1,000 entities	~$0.50
10,000 entities	~$5.00

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FAQ

Do I need a proxy or API key? No. Wikidata is a fully public API — no credentials, no proxy required.

What output formats are available? JSON (default), CSV, and Excel — downloadable from the Apify dataset UI or via the REST API.

Can I schedule this to run automatically? Yes. Apify's scheduler runs this on any cron schedule and can push results via webhook to your pipeline automatically.

What if a Q-ID doesn't exist or returns empty? The actor logs a warning and skips the entity — no crash. Missing Q-IDs appear in the OUTPUT.failedDetails summary at the end of the run.

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Why this actor

• Official APIs only — EntityData REST + Action API. No DOM scraping, no parsing fragility.
• Zero cost — Wikidata is public, no proxy or authentication needed.
• Configurable properties — extract exactly the P-values you need.
• parse_confidence field — machine-detectable data quality in every row.
• Multi-language — labels and descriptions in any Wikidata language.

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Not affiliated with Wikimedia Foundation. Uses the official Wikidata public APIs.

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Use with AI agents (MCP)

This actor is available as an MCP tool for Claude, GPT-4, and other AI agents that support the Model Context Protocol:

https://mcp.apify.com/?tools=bovi/wikidata-scraper

Feed any Q-ID or search term and get back structured entity data — ideal for knowledge-graph enrichment, entity disambiguation, and AI research pipelines.

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vs. competitors

	This actor	Typical Wikidata scraper
Data source	Official Wikidata REST + Action APIs	HTML / DOM scraping
P-values (claims)	Configurable selection	Rarely exposed
parse_confidence	✓	No
Proxy needed	No	Often required
Price	from $0.50/1K	$2–5/1K

Integrations

Built for knowledge-graph builders and entity-resolution pipelines consuming structured Wikidata records by Q-ID or keyword — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.