Wikipedia Scraper for Infoboxes, Citations, and Sections
Organize Wikipedia Articles for Research
Keep article facts, infobox values, citations, and section context in separate fields.
Extract Wikipedia Data in One Click
It proposes columns for the page you open and completes the capture in one run. Adjust or rename fields in natural language, then run again if you like.
Work Across Different Wikipedia Page Types
The agent reads visible labels, headers, and section titles to map values on the page you can access. If a field isn’t present, the column stays blank.
Export Wikipedia Data Directly
Continue the research in Google Sheets, Excel, Airtable, Notion, or a downloaded CSV.
Collect Wikipedia Research Data Without Building a Scraper
Cut selector upkeep for Wikipedia research.
Manual or selector-based setup
Time spent maintaining rulesThunderbit AI Agent
Field suggestions and a single runColumns for article facts, infobox, citations, and sections
Columns appear only when shown on the page you can access.
- page_title
- page_url
- lead_paragraph
- first_sentence
- infobox_image_url
- infobox_image_caption
- birth_name
- birth_date
- death_date
- birth_place
- death_place
- nationality
- occupation
- years_active
- employer
- alma_mater
- spouse
- children
- website
- notable_works
- latitude
- longitude
- categories
- reference_titles
- reference_links
- external_links
- article_sections
- table_of_contents
- hatnotes
- page_last_edited_date
See researchers capture structured facts from open pages
In user-recorded videos, researchers pick page facts, check the rows, and move the result into their own tools.
Questions about Wikipedia research runs
Short answers for Agent Mode on Wikipedia.
When your research spans Wikimedia projects
Pair Wikipedia articles with Wikidata items, Commons groups, or media pages.
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Learn more ->Ready to supercharge your data extraction?
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