# Wikidata Entities & Knowledge Graph Scraper (`scrapers_lat/wikidata-entities-scraper`) Actor
Search Wikidata and export matching entities as clean structured data. Get each entity's label, description, aliases, type, country, official website, inception date and industry, plus the Wikidata URL. Great for research and KYB enrichment. Export to JSON, CSV or Excel.
- **URL**: https://apify.com/scrapers\_lat/wikidata-entities-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** Developer tools, Business, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $12.75 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## Wikidata Entities & Knowledge Graph Scraper
> Search Wikidata and export matching entities as clean structured data. Get each entity's label, description, aliases, type, country, official website, inception date and industry, plus its Wikidata URL. Ideal for research, entity resolution and KYB enrichment.
Label & description plus aliases
Key facts country, website, industry
JSON / CSV / Excel output formats
### What you get
Each record is one Wikidata entity, ready for enrichment, a graph or a spreadsheet:
- **qid**: the stable Wikidata identifier (for example Q95)
- **label**: the entity name in English
- **description**: the short description
- **aliases**: other names the entity is known by
- **instanceOf**: what kind of thing it is (company, human, chemical element and so on)
- **country**: associated country when set
- **industry**: the industry when set
- **headquarters**: headquarters location when set
- **website**: the official website when set
- **inception**: founding or creation date when set
- **url**: a direct link to the Wikidata page
- **observedAt**: when the record was collected
### Who is it for
| Use case | Who benefits |
|---|---|
| KYB and enrichment | Teams matching companies and people to a stable identifier |
| Research and data science | Analysts pulling structured facts for entities at scale |
| Knowledge graphs | Builders seeding a graph with labels, types and relations |
| Reference and content | Editors resolving names, aliases and descriptions |
### How to use it
1. Enter a **search query** (a keyword, company, person, place or concept).
2. Set **Max Items** for how many matching entities to collect.
3. Run and export as JSON, CSV or Excel, or pull it through the Apify API.
### Frequently Asked Questions
**What is a QID?**
A QID is the permanent identifier Wikidata gives every entity (for example `Q95` for Google). It is the safest way to link records across data sets.
**Why are some fields empty?**
Wikidata is community maintained, so not every entity has a website, country or inception date. Missing facts are returned as null while label and description are always present.
**Can I search for people, places or products?**
Yes. Any entity type works. The type is returned in the `instanceOf` field so you can filter to companies, humans, cities and more.
**What language are the results in?**
Labels and descriptions are returned in English. Aliases are the English aliases recorded for the entity.
### Related scrapers
- [Crossref Works Scraper](https://apify.com/scrapers_lat/crossref-scraper)
- [Company Research Enrichment Tool](https://apify.com/scrapers_lat/company-research-enrichment-tool)
- [arXiv Papers Scraper](https://apify.com/scrapers_lat/arxiv-papers-scraper)
### More scrapers at scrapers.lat
This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish scrapers for public platforms: finance, news, real estate, jobs, e-commerce and government data. Browse the full catalog or ask us for a custom scraper at [scrapers.lat](https://scrapers.lat).
---
> This actor is an independent tool and has no affiliation with Wikidata or the Wikimedia Foundation. It only accesses publicly available open data. Use the results in accordance with the source's terms.
# Actor input Schema
## `maxEntities` (type: `integer`):
Maximum number of entities to collect. Optional.
## `searchQuery` (type: `string`):
The keyword or entity name to search for on Wikidata (for example 'Google', 'Albert Einstein', 'lithium').
## Actor input object example
```json
{
"maxEntities": 50,
"searchQuery": "Google"
}
````
# Actor output Schema
## `results` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"maxEntities": 50,
"searchQuery": "Google"
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/wikidata-entities-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"maxEntities": 50,
"searchQuery": "Google",
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/wikidata-entities-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"maxEntities": 50,
"searchQuery": "Google"
}' |
apify call scrapers_lat/wikidata-entities-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/wikidata-entities-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Wikidata Entities & Knowledge Graph Scraper",
"description": "Search Wikidata and export matching entities as clean structured data. Get each entity's label, description, aliases, type, country, official website, inception date and industry, plus the Wikidata URL. Great for research and KYB enrichment. Export to JSON, CSV or Excel.",
"version": "0.1",
"x-build-id": "sTdkDvDlpr9ZvAsN3"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~wikidata-entities-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-wikidata-entities-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~wikidata-entities-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-wikidata-entities-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~wikidata-entities-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-wikidata-entities-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"maxEntities": {
"title": "Max entities",
"minimum": 1,
"maximum": 5000,
"type": "integer",
"description": "Maximum number of entities to collect. Optional."
},
"searchQuery": {
"title": "Search query",
"type": "string",
"description": "The keyword or entity name to search for on Wikidata (for example 'Google', 'Albert Einstein', 'lithium')."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```