Wikipedia Page Summaries Scraper
Pricing
from $8.00 / 1,000 result items
Wikipedia Page Summaries Scraper
Pull Wikipedia article summaries via REST API. Returns title, description, extract (plain + HTML), thumbnail, lang, page ID, content URLs (desktop + mobile + edit), coordinates, page type, timestamps. Look up specific titles or get search results.
Pricing
from $8.00 / 1,000 result items
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0.0
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ParseForge
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2
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1
Monthly active users
6 days ago
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📚 Wikipedia Article Summary Scraper
🚀 Pull Wikipedia article summaries with thumbnail, extract, coordinates, Wikidata link, revision ID, and language. Lookup or search modes.
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 |
📋 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.
📊 Data fields
Each record includes: description, desktopUrl, extract, language, pageId, thumbnailUrl, timestamp, title. These field names come straight from the actor's dataset schema, so what you see here is what lands in your dataset.
🚀 How to use
- 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
- 🌐 Open the Actor. Find the Wikipedia Article Summary Scraper on the Apify Store.
- 🎯 Set input. Pick filters and
maxItems. - 🚀 Run it. Click Start.
- 📥 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.
🔗 Recommended Actors
- 🌐 Wikidata Entity Search - 100M+ open knowledge-graph entities
- 🌍 Wikivoyage Travel Articles - Wikivoyage city and country articles with image, geo
- 🌍 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.
⚠️ 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.
🆘 Need Help?
If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.
For faster answers, join our Discord. It's the best place to get support and suggest new actors.
