# Wikipedia Scraper - Wikidata Facts, Summaries & Images (`plotpointtech/wikipedia-wikidata-entity-extractor`) Actor

Turn names into structured records from Wikipedia and Wikidata: summary, image, founding date, HQ, CEO, website, revenue, employees, birth dates, coordinates and population. Official APIs. $1 per 1,000 entities.

- **URL**: https://apify.com/plotpointtech/wikipedia-wikidata-entity-extractor.md
- **Developed by:** [Plot Point Technologies](https://apify.com/plotpointtech) (community)
- **Categories:** AI, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.62 / 1,000 entities

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Wikipedia Scraper: Wikidata Facts, Summaries and Images

**Turn a list of names into clean, structured records for companies, people, places and any other topic on Wikipedia.** Give it article titles, Wikipedia links, Wikidata IDs or a search term, and get the article summary, image, categories and the key facts from Wikidata in plain, ready-to-use fields. All data comes from the official Wikipedia and Wikidata APIs. **$1 per 1,000 entities.**

### What can this Wikipedia scraper do?

- **Look up anything** by title (`Apple Inc.`), Wikipedia URL in any language, Wikidata ID (`Q312`) or search term.
- **Return readable facts, not codes:** a CEO or headquarters city comes back as a name.
- **Pick the right value:** preferred values first, the most recent dated value for employees, revenue and population, and current office holders for CEO and chair.
- **Work in any language edition**, with labels falling back to English.
- **Add any extra Wikidata property** you need, such as `P1448` (official name) or `P2002` (X username).

### What data do you get?

| Group | Fields |
|---|---|
| Identity | `label`, `description`, `aliases`, `entityType`, `instanceOf`, `wikidataId`, `wikidataUrl`, `title`, `pageUrl`, `language` |
| Article | `summary`, `thumbnail`, `originalImage`, `categories`, `lastModified` |
| Organizations | `founded`, `foundedBy`, `headquarters`, `industry`, `officialWebsite`, `ceo`, `chairperson`, `parentOrganization`, `employees`, `revenue`, `netIncome`, `stockExchange`, `isin`, `country`, `logo` |
| People | `birthDate`, `deathDate`, `birthPlace`, `deathPlace`, `occupation`, `nationality`, `educatedAt`, `awards` |
| Places | `country`, `locatedIn`, `capital`, `coordinates`, `population`, `area` |
| Extras | `extraProperties`, `license` |

### Who uses it?

- **Sales and market research teams** enriching company lists with founding year, HQ, industry, CEO, website, employees and revenue.
- **Data and AI teams** building knowledge bases, entity-linking tables or training data with stable Wikidata IDs.
- **Publishers, educators and researchers** who need short, reliable summaries and images.
- **Analysts** joining their data to Wikidata IDs, ISINs, coordinates or population figures.

### How to use it

1. Click **Try for free** (or **Start**).
2. Paste **Articles or entities**, one per line, and/or a **Search term**.
3. Choose the **Wikipedia language** (default `en`).
4. Run it and export to Excel, CSV or JSON.

### Input example

```json
{
  "items": [
    "Apple Inc.",
    "Marie Curie",
    "Q90",
    "https://de.wikipedia.org/wiki/Siemens"
  ],
  "searchTerm": "electric vehicle manufacturer",
  "maxSearchResults": 5,
  "language": "en"
}
```

### Output example

```json
{
  "input": "Apple Inc.",
  "language": "en",
  "title": "Apple Inc.",
  "pageUrl": "https://en.wikipedia.org/wiki/Apple_Inc.",
  "wikidataId": "Q312",
  "wikidataUrl": "https://www.wikidata.org/wiki/Q312",
  "label": "Apple Inc.",
  "description": "American multinational technology company based in Cupertino, California",
  "aliases": [
    "Apple (company)"
  ],
  "entityType": "organization",
  "instanceOf": [
    "enterprise",
    "business",
    "public company"
  ],
  "summary": "Apple Inc. is an American multinational technology company headquartered in Cupertino, California, in Silicon Valley, and known for consumer electronics, software and online services. Founded in 1976 as Apple Computer Co...",
  "thumbnail": "https://thumb.wikimedia.org/wikipedia/commons/thumb/f/fa/Apple_logo_black.svg/500px-Apple_logo_black.svg.png?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail",
  "originalImage": "https://upload.wikimedia.org/wikipedia/commons/f/fa/Apple_logo_black.svg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=original",
  "founded": "1976-04-01",
  "foundedBy": [
    "Steve Wozniak",
    "Ronald Wayne",
    "Steve Jobs"
  ],
  "headquarters": [
    "Cupertino"
  ],
  "industry": [
    "software industry",
    "consumer electronics industry",
    "digital distribution"
  ],
  "officialWebsite": "https://apple.com/",
  "ceo": [
    "John Ternus"
  ],
  "chairperson": [
    "Arthur D. Levinson"
  ],
  "employees": 164000,
  "revenue": 416161000000,
  "netIncome": 112010000000,
  "stockExchange": [
    "Nasdaq",
    "Tokyo Stock Exchange"
  ],
  "isin": [
    "US0378331005"
  ],
  "awards": [
    "National Design Awards"
  ],
  "country": [
    "United States"
  ],
  "image": "https://commons.wikimedia.org/wiki/Special:FilePath/Apple_park_cupertino_2019.jpg",
  "logo": "https://commons.wikimedia.org/wiki/Special:FilePath/Apple_logo_black.svg",
  "employeesYear": "2022",
  "revenueCurrency": "United States dollar",
  "revenueYear": "2025",
  "netIncomeCurrency": "United States dollar",
  "netIncomeYear": "2025",
  "lastModified": "2026-10-28T12:58:11Z",
  "license": "Wikipedia text: CC BY-SA 4.0 (attribute Wikipedia contributors, link pageUrl). Wikidata facts: CC0."
}
```

### How much does it cost?

**$1 per 1,000 entities** ($0.001 each), plus a $0.00005 start fee per run.

| You look up | You pay |
|---|---|
| 500 company names | $0.50 |
| 10,000 Wikidata IDs refreshed monthly | $10.00 a month |

Inputs that do not exist are logged, skipped and not charged.

**Volume discounts on higher Apify plans.** The prices above are for the Apify Free plan. On paid plans the per-result price drops automatically: about 15% lower on Bronze, 25% lower on Silver and 38% lower on Gold and above.

### Use it via API, Make, Zapier, n8n or an AI agent

**Apify API.** Start a run and get the results back in one HTTP request (replace `YOUR_API_TOKEN` with the token from Apify Console > Settings > Integrations):

```bash
curl -X POST "https://api.apify.com/v2/acts/plotpointtech~wikipedia-wikidata-entity-extractor/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"items": ["Apple Inc.", "Marie Curie", "Q90", "https://de.wikipedia.org/wiki/Siemens"], "searchTerm": "electric vehicle manufacturer", "maxSearchResults": 5, "language": "en"}'
```

For longer jobs, start the run asynchronously and read the dataset when it finishes. Official `apify-client` libraries exist for Python and JavaScript; the **API** tab on this page has ready-made code.

**No-code automation.** Connect the tool to **Make, Zapier, n8n, Google Sheets, Slack, Airtable** or any webhook with Apify integrations, and use **Schedules** in Apify Console to run it hourly, daily or weekly.

**AI agents (MCP).** Give Claude, ChatGPT, Cursor, VS Code or any MCP-compatible agent direct access to this tool through the hosted Apify MCP server. Add this server URL to your client:

```
https://mcp.apify.com?tools=plotpointtech/wikipedia-wikidata-entity-extractor
```

The agent can then call the tool with the same input fields shown above and read the results.

### FAQ

**Is it legal to use Wikipedia and Wikidata data?**
Yes, under their licences. Wikidata facts are CC0 (public domain). Wikipedia summaries are CC BY-SA 4.0: if you republish them, credit "Wikipedia contributors", link to the article (`pageUrl`) and share adaptations under the same licence. Images have their own licences on Wikimedia Commons. The tool follows Wikimedia's API etiquette.

**Why are some fields empty?**
Fields appear only when Wikidata has a value. Coverage is excellent for well-known entities and thinner for small companies.

**Can I use other languages?**
Yes. Set the Wikipedia language (`de`, `fr`, `es`, `ja`...), or paste URLs from any language edition.

**What if a title is ambiguous?**
Redirects are followed automatically. For exact matches, use a Wikidata ID or the full Wikipedia URL.

**Is this good for AI and RAG?**
Yes. Each record has a stable `wikidataId`, a clean summary and a source URL for citations.

### Related tools from Plot Point Technologies

- [Website to Markdown Crawler for AI, LLM & RAG - $1/1K](https://apify.com/plotpointtech/website-to-markdown-crawler): any website as clean Markdown for LLMs and RAG.
- [AI Web Scraper - Extract Any Website to JSON in Plain English](https://apify.com/plotpointtech/ai-page-extractor): describe the fields you want and get JSON from any web page.
- [News Scraper - Worldwide News Search by Keyword, 65+ Languages](https://apify.com/plotpointtech/worldwide-news-search): news articles worldwide by keyword, country and language.
- [WHOIS & Domain Lookup - Bulk RDAP, DNS, SSL & Mail Provider](https://apify.com/plotpointtech/bulk-domain-lookup): registrar, expiry, DNS, email provider and SSL for any domain list.

Plot Point Technologies is not affiliated with the Wikimedia Foundation, Wikipedia or Wikidata.

***

If this tool saved you time, we would be grateful for a short review on this page; it helps other people find it. If something did not work as expected, please open an issue on the **Issues** tab and we will look into it quickly.

# Actor input Schema

## `items` (type: `array`):

Wikipedia article titles (e.g. Apple Inc.), Wikipedia URLs (any language), Wikidata IDs (e.g. Q312) or Wikidata URLs.

## `searchTerm` (type: `string`):

Also look up the top Wikipedia articles matching this search, e.g. 'electric vehicle manufacturers'.

## `maxSearchResults` (type: `integer`):

How many articles to take from the search.

## `language` (type: `string`):

Language code of the Wikipedia edition for titles and search, e.g. en, de, fr, es, ja. Labels fall back to English when not available. URLs keep their own language.

## `includeCategories` (type: `boolean`):

Return the article's visible Wikipedia categories.

## `extraProperties` (type: `array`):

Additional Wikidata property IDs to return, e.g. P2002 (X username), P1448 (official name), P3608 (EU VAT number). Linked items are returned as labels.

## `maxItems` (type: `integer`):

Stop after this many entities.

## Actor input object example

```json
{
  "items": [
    "Apple Inc.",
    "Marie Curie",
    "Q90"
  ],
  "maxSearchResults": 10,
  "language": "en",
  "includeCategories": true,
  "extraProperties": [],
  "maxItems": 1000
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "items": [
        "Apple Inc.",
        "Marie Curie",
        "Q90"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("plotpointtech/wikipedia-wikidata-entity-extractor").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "items": [
        "Apple Inc.",
        "Marie Curie",
        "Q90",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("plotpointtech/wikipedia-wikidata-entity-extractor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "items": [
    "Apple Inc.",
    "Marie Curie",
    "Q90"
  ]
}' |
apify call plotpointtech/wikipedia-wikidata-entity-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,plotpointtech/wikipedia-wikidata-entity-extractor"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/qLN8Uw45sOwOeGa4g/builds/XUZzPHgfVfKvMbUA8/openapi.json