Wikidata Scraper

hipersoft/wikidata-scraper

Search Wikidata and export structured knowledge data: entity ID, label, description, aliases, Wikipedia link and statements (claims) in any language. Search by keyword or fetch specific Q-IDs. One clean row per entity as JSON, CSV or Excel.

Run this scraper →See the API call

Total users

Monthly users

Total runs

Per entity scraped

$0.002

Last rebuilt

Oct 26, 2026

Overview

Search Wikidata and export structured knowledge data. Look up entities by keyword or fetch specific Q-IDs, and get one row per entity with its ID, label, description, aliases, Wikipedia link, sitelink count and full statements (claims) — in any language. Export to JSON, CSV or Excel, or pull straight from the API.

Perfect for knowledge graphs, data enrichment, entity linking, research, reference datasets, and feeding structured facts to LLMs and RAG pipelines.

What you get

One flat, ready-to-use record per entity:

Field	Description
`id`	Wikidata entity ID (e.g. `Q42`)
`type`	Entity type (item / property)
`label`	Label in your chosen language
`description`	Short description
`aliases`	Alternative names
`url`	Wikidata page
`wikipediaTitle` / `wikipediaUrl`	Linked Wikipedia article
`siteLinkCount`	Number of linked wikis
`claims`	Statements as a map of property ID → values (e.g. `P31` = instance of)
`query`	The search term that produced the row
`collectedAt`	When the row was scraped

How to use

1. By search term or Q-ID

{
  "searchQueries": ["Douglas Adams", "Berlin"],
  "entityIds": ["Q42"],
  "language": "en",
  "resultsPerQuery": 5,
  "includeClaims": true,
  "maxItems": 200
}

Search terms — each returns its top matching entities.
Entity IDs — fetch specific Q-IDs (or Wikidata URLs) directly.
Language — labels/descriptions/aliases in this language (falls back to English).
Results per search term — how many entities per term.
Include statements (claims) — add the property → values map.
Max entities — cap the total (0 = no limit).

Example output

{
  "id": "Q42",
  "label": "Douglas Adams",
  "description": "British science fiction writer and humourist",
  "aliases": ["Douglas Noël Adams"],
  "url": "https://www.wikidata.org/wiki/Q42",
  "wikipediaUrl": "https://en.wikipedia.org/wiki/Douglas_Adams",
  "siteLinkCount": 140,
  "claims": { "P31": ["Q5"], "P106": ["Q36180", "Q6625963"] },
  "collectedAt": "2026-09-20T16:00:00.000Z"
}

Common use cases

Knowledge graphs — build or enrich graphs with entities and their relationships.
Data enrichment — resolve names to canonical IDs, labels and facts.
Entity linking — map your data to Wikidata IDs and Wikipedia articles.
Research & reference — pull structured facts across many entities at once.
LLMs & RAG — feed clean, structured knowledge into models and pipelines.

Frequently asked questions

Do I need any login, account or key? No. Just add search terms or Q-IDs and run.

Can I get data in other languages? Yes — set the Language field (it falls back to English when a label is missing).

What are claims? Wikidata statements, returned as a map of property ID (like P31 = "instance of") to its values. Turn off "Include statements" for a lighter output.

Can I fetch exact entities? Yes — put their Q-IDs (or Wikidata URLs) in Entity IDs.

What format is the data? A flat table you can export as JSON, CSV or Excel, or fetch from the Apify API.

Related scrapers

Building a knowledge or research toolkit? Check out our other data and content scrapers on Apify Store — all with the same clean, one-row-per-item output.

Input

Field	Type	Description
`searchQueries` Search terms	array	Names or terms to look up on Wikidata — e.g. 'Douglas Adams', 'Berlin', 'photosynthesis'. Each term returns its top matching entities.
`entityIds` Entity IDs (Q-IDs)	array	Specific Wikidata entity IDs or URLs to fetch directly — e.g. 'Q42', 'https://www.wikidata.org/wiki/Q64'.
`language` Language	string	Language code for labels, descriptions and aliases (falls back to English). E.g. en, es, fr, de, ja. Default: `"en"`
`resultsPerQuery` Results per search term	integer	How many top entities to return for each search term. Default: `5`
`includeClaims` Include statements (claims)	boolean	Include the entity's statements as a map of property ID → values (e.g. P31 = instance of). Default: `true`
`maxItems` Max entities	integer	Maximum number of entities to collect (0 = no limit). Default: `100`

API

curl -X POST "https://api.apify.com/v2/acts/hipersoft~wikidata-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "searchQueries": [
    "Douglas Adams"
  ]
}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("hipersoft/wikidata-scraper").call(run_input={
    "searchQueries": [
        "Douglas Adams"
    ]
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('hipersoft/wikidata-scraper').call({
  "searchQueries": [
    "Douglas Adams"
  ]
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Pricing

Event	Price	Paid plans from
Entity scraped Charged for each Wikidata entity returned.	$0.002	$0.001

You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.

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