# Wikidata Entity Scraper - Knowledge Graph Data (`thirdwatch/wikidata-entity-scraper`) Actor

Search or fetch Wikidata entities with labels, descriptions, aliases, claims, statement counts, sitelinks, and Wikipedia URLs in structured form.

- **URL**: https://apify.com/thirdwatch/wikidata-entity-scraper.md
- **Developed by:** [Thirdwatch](https://apify.com/thirdwatch) (community)
- **Categories:** AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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 Entity Scraper

> Search or fetch Wikidata knowledge-graph entities with labels, aliases, claims, statements, sitelinks, and Wikipedia URLs.

### What you get

Turn names, concepts, or exact Q-IDs into structured knowledge-graph rows. Search in a chosen language, fetch exact entities without injecting an unrelated default search, and enrich every match through Wikidata's entity API. Output includes human-readable metadata, simplified claim values, counts for statements and sitelinks, and direct Wikidata and language-matched Wikipedia links.

### Output fields

| Field | Description |
|---|---|
| `id`, `label`, `description` | Entity identity and readable metadata |
| `aliases` | Alternative names in the requested language |
| `matched_text`, `matched_type` | Search-match context when applicable |
| `claims` | Property IDs mapped to simplified statement values |
| `statements_count`, `sitelinks_count` | Entity richness indicators |
| `wikipedia_url`, `entity_url` | Language Wikipedia and Wikidata links |
| `source`, `license` | Wikidata attribution and CC0 license |

### Example output

```json
{"id":"Q7259","label":"Ada Lovelace","description":"English mathematician","aliases":["Augusta Ada King"],"license":"CC0 1.0"}
```

### Input parameters

| Parameter | Required | Description |
|---|---|---|
| `queries` | No | Entity names or concepts; empty permits exact-only lookup |
| `entityIds` | No | Exact IDs such as Q42 or Q7259 |
| `language` | No | Language code for search and labels; defaults to `en` |
| `maxResultsPerQuery` | No | Maximum search matches per query; defaults to 10 |

### Use cases

- Data teams can enrich names with durable knowledge-graph identifiers.
- Publishers can connect topics to Wikipedia and multilingual references.
- Researchers can inspect statement and sitelink coverage across entities.
- Developers can seed entity-resolution and taxonomy workflows.

### Limitations

Wikidata is community-maintained, so labels, descriptions, claims, and sitelinks can change and may contain errors or gaps. Claim values are simplified for portability: complex qualifiers, ranks, references, calendars, precision, and units are not expanded into a full RDF model. Search relevance belongs to Wikidata. The Actor retrieves items, not MediaWiki pages or arbitrary SPARQL result sets.

### Compared to alternatives

This Actor combines `wbsearchentities` and `wbgetentities` in one bounded Apify workflow. Unlike plain search output, it adds claims and richness counts. Unlike a SPARQL query builder, it requires no query-language knowledge and works naturally with saved Tasks, schedules, webhooks, and datasets.

### FAQ

#### Can I fetch exact Q-IDs without a search?

Yes. Leave `queries` empty and provide `entityIds`. The Actor will not inject a default query.

#### Can I reuse the output commercially?

Wikidata structured data is published under CC0. Review Wikimedia's current reuse guidance for your application and preserve useful source links.

Explore [Wikidata Entity Scraper on thirdwatch.dev](https://thirdwatch.dev/scrapers/wikidata-entity-scraper). Related Actors: [OpenAlex Research Scraper](https://apify.com/thirdwatch/openalex-research-scraper), [Crossref DOI Scraper](https://apify.com/thirdwatch/crossref-doi-scraper), and [Google Search Scraper](https://apify.com/thirdwatch/google-search-scraper).

Last verified: 2026-07

# Actor input Schema

## `queries` (type: `array`):

Names or concepts to search. Leave empty for exact entity IDs only.

## `entityIds` (type: `array`):

Wikidata IDs such as Q42 or Q7259.

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

Language code for search, labels, descriptions, aliases, and Wikipedia URL.

## `maxResultsPerQuery` (type: `integer`):

Maximum search matches saved for each query. Exact IDs are always requested.

## Actor input object example

```json
{
  "queries": [
    "artificial intelligence",
    "Ada Lovelace"
  ],
  "entityIds": [
    "Q42",
    "Q7259"
  ],
  "language": "en",
  "maxResultsPerQuery": 10
}
```

# 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 = {
    "queries": [
        "artificial intelligence",
        "Ada Lovelace"
    ],
    "entityIds": [
        "Q42",
        "Q7259"
    ],
    "language": "en",
    "maxResultsPerQuery": 10
};

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

# Prepare the Actor input
run_input = {
    "queries": [
        "artificial intelligence",
        "Ada Lovelace",
    ],
    "entityIds": [
        "Q42",
        "Q7259",
    ],
    "language": "en",
    "maxResultsPerQuery": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("thirdwatch/wikidata-entity-scraper").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 '{
  "queries": [
    "artificial intelligence",
    "Ada Lovelace"
  ],
  "entityIds": [
    "Q42",
    "Q7259"
  ],
  "language": "en",
  "maxResultsPerQuery": 10
}' |
apify call thirdwatch/wikidata-entity-scraper --silent --output-dataset

```

## MCP server setup

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

```

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/dzfr1usyZeHft27pa/builds/Cu8JVaCfzSRCRSxFV/openapi.json