📚 Wikipedia Article Summary Scraper

🚀 Pull Wikipedia article summaries with thumbnail, extract, coordinates, Wikidata link, revision ID, and language. Lookup or search modes.

🕒 Last updated: 2026-05-08 · 📊 25 fields per record · 60M+ Wikipedia pages · 300+ languages · summary extract, thumbnail, coords, Wikidata, revision · lookup or search

The Wikipedia Article Summary Scraper pulls structured summaries from Wikipedia's REST API. Output includes thumbnail and original-image URLs (with widths and heights), page ID, title and display title, normalized + canonical title, description and description source, summary extract (plain text + HTML), page type, namespace, Wikibase item ID, language code and direction, last-modified timestamp, revision ID, geographic coordinates, and desktop / mobile / edit / revisions URLs.

Two modes in one Actor: lookup by title (one per line), and search (using Wikipedia's opensearch). The dataset covers Wikipedia in any of 300+ languages. Set the language input to es, fr, de, etc.

🎯 Target Audience	💡 Primary Use Cases
Knowledge-graph builders, content marketers, ML researchers, journalists, encyclopedia apps, education platforms	Knowledge-graph extraction, encyclopedic-content displays, summary embeddings, fact-card UIs, education content

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📋 What the Wikipedia Article Summary Scraper does

Five filtering workflows in a single run:

• 🔍 Lookup mode. One title per line, returns rich summary per page.
• 🔍 Search mode. Wikipedia's opensearch with ranked matches.
• 🌐 300+ languages. Switch language with a single input.
• 🗺️ Coordinates included. Lat / lng for places, when the page is geo-tagged.
• 🔗 Wikidata link. Direct Wikibase item ID for cross-language joins.

💡 Why it matters: clean, server-side filtering and fresh data on every run.

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🎬 Full Demo

🚧 Coming soon: a 3-minute walkthrough showing how to go from sign-up to a downloaded dataset.

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⚙️ Input

Input	Type	Default	Behavior
maxItems	integer	10	Records to return. Free plan caps at 10, paid plan up to 1,000,000.
mode	string	"lookup"	lookup or search.
titles	string	""	Newline-separated titles (lookup mode).
query	string	""	Search term (search mode).
language	string	"en"	Wikipedia language code (e.g. `en`, `es`, `fr`, `de`, `ja`).

Example: look up famous scientists.

{
    "maxItems": 50,
    "mode": "lookup",
    "titles": "Albert Einstein\nMarie Curie\nIsaac Newton\nCharles Darwin\nGalileo Galilei",
    "language": "en"
}

Example: search topic in Spanish.

{
    "maxItems": 20,
    "mode": "search",
    "query": "fotografía",
    "language": "es"
}

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📊 Output

Each record contains 25 fields. Download as CSV, Excel, JSON, or XML.

🧾 Schema

Field	Type	Example
🖼️ thumbnailUrl	string	"https://upload.wikimedia.org/.../thumb.jpg"
🆔 pageId	number	736
📛 title	string	"Albert Einstein"
📛 displayTitle	string	"Albert Einstein"
📛 normalizedTitle	string	"Albert Einstein"
📛 canonicalTitle	string	"Albert_Einstein"
📜 description	string	"German-born theoretical physicist (1879-1955)"
📝 extract	string	"Albert Einstein was a German-born theoretical physicist..."
📝 extractHtml	string	"<p><b>Albert Einstein</b> was a German-born theoretical physicist..."
🏷️ type	string	"standard"
🌐 language	string	"en"
🔤 languageCode	string	"en"
🔗 wikibaseItem	string	"Q937"
🗺️ coordinatesLat	number	52.5
🗺️ coordinatesLng	number	13.4
📅 timestamp	string	"2026-04-29T14:32:11Z"
🆔 revisionId	number	1238762345
🌐 desktopUrl	string	"https://en.wikipedia.org/wiki/Albert_Einstein"
📱 mobileUrl	string	"https://en.m.wikipedia.org/wiki/Albert_Einstein"
✏️ editDesktopUrl	string	"https://en.wikipedia.org/wiki/Albert_Einstein?action=edit"

📦 Sample records

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✨ Why choose this Actor

	Capability
🔗	Wikidata link. Wikibase item ID lets you join across languages and other knowledge graphs.
🌍	300+ languages. Same Actor pulls summaries from any Wikipedia language.
🗺️	Geo coordinates. Lat / lng exposed when the page is geo-tagged.
📜	Plain + HTML extracts. Both formats per record.
🆓	No auth. Wikipedia REST is open.

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📈 How it compares to alternatives

Approach	Cost	Coverage	Refresh	Filters	Setup
⭐ This Actor	$5 free credit	60M+ pages	Live per run	2 modes	⚡ 2 min
Wikipedia REST direct	Free	Same	Live	DIY	🐢 Code
DBpedia / Wikidata	Free	Triplestore	Live	SPARQL	🐢 Hours
Manual scraping	Free	All	Live	DIY	🐢 Days

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🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Find the Wikipedia Article Summary Scraper on the Apify Store.
3. 🎯 Set input. Pick filters and maxItems.
4. 🚀 Run it. Click Start.
5. 📥 Download. Grab results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to dataset: 3-5 minutes. No coding required.

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💼 Business use cases

📚 Knowledge + Education Encyclopedia-app summaries Quiz / trivia content Reference card UIs Reading-comprehension exercises	🤖 ML + Search Summary embeddings Fine-tune QA models Knowledge-graph seeding Multilingual training data
📰 Journalism + Content Background fact cards Multi-language coverage Topic-page generation Subject-A vs subject-B comparisons	🌐 Localization Multi-language content seeding Cross-language entity matching Translated summaries Localized SEO content

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🔌 Automating Wikipedia Article Summary Scraper

Control the scraper programmatically:

• 🟢 Node.js. Install the apify-client NPM package.
• 🐍 Python. Use the apify-client PyPI package.
• 📚 See the Apify API documentation for full details.

The Apify Schedules feature lets you trigger this Actor on any cron interval.

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🌟 Beyond business use cases

Data like this powers more than commercial workflows.

🎓 Research and academia Reproducible Wikipedia corpora Cross-language entity studies Educational fact-card content Knowledge-graph research	🎨 Personal and creative Personal study aids Trivia apps Side projects with summary data Reading-list backbones
🤝 Non-profit and civic Free encyclopedic content Library reference tools Heritage knowledge preservation Educational outreach	🧪 Experimentation Train summarization models Prototype QA systems Build entity-disambiguation tools Test multilingual pipelines

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🤖 Ask an AI assistant about this scraper

Open a ready-to-send prompt in the AI of your choice:

• 💬 ChatGPT
• 🧠 Claude
• 🔍 Perplexity
• 🅒 Copilot

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❓ Frequently Asked Questions

🧩 How does it work?

Pick lookup or search mode and supply titles or a query. The Actor calls the Wikipedia REST API and returns one record per page.

📊 How many fields per record?

25, including thumbnail, page ID, title fields, description, extract (plain + HTML), type, language metadata, Wikibase item, coordinates, timestamps, and URLs.

🌍 Which languages are supported?

Any Wikipedia language. Set the language input to the standard code (en, es, fr, de, ja, zh, ar, etc).

🗺️ Are geo-coordinates always present?

Only on geo-tagged pages (places, landmarks). Other pages have null.

🔗 What's the wikibaseItem field?

The Wikidata Q-number for the entity. Lets you join across languages and other knowledge bases.

📜 Is the full article body returned?

No, only the summary extract (lead section). Use Wikipedia's full-content API for the entire body.

🆓 Do I need an API key?

No. Wikipedia REST is open.

🔁 Can I schedule runs?

Yes. Schedule daily to refresh summaries.

⚖️ Is this data free to use?

Yes. Wikipedia content is licensed CC-BY-SA. Attribution required for redistribution.

💳 Do I need a paid Apify plan?

No. The free plan covers preview runs (10 records).

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🔌 Integrate with any app

Wikipedia Article Summary Scraper connects to any cloud service via Apify integrations:

• Make - Automate multi-step workflows
• Zapier - Connect with 5,000+ apps
• Slack - Get run notifications
• Airbyte - Pipe data into your warehouse
• GitHub - Trigger runs from commits
• Google Drive - Export datasets to Sheets

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• 🌍 REST Countries Reference Data - Every country with flag, capital, currency, languages
• 📊 Stack Exchange Questions - Search 170+ Stack Exchange Q&A sites
• 🌍 GeoNames Places + Postal Codes - 12M+ places with admin hierarchy, lat/lng, alternate names

💡 Pro Tip: browse the complete ParseForge collection for more reference-data scrapers.

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🆘 Need Help? Open our contact form to request a new scraper, propose a custom data project, or report an issue.

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⚠️ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by the Wikimedia Foundation, Wikipedia editors, or any cited reference work. All trademarks mentioned are the property of their respective owners. Only publicly available open data is collected.