Counting Documents Is Not Counting Text: Unit Bias in Web-PDF Corpus Statistics
PDF corpora advertise their size in tokens, but every rate they publish (coverage, OCR routing, re-fetch recovery, language mix) is computed per document, and none decomposes its token total. Because PDF length is extremely skewed, the two units can describe the same corpus very differently. We ask how the headline statistics of a web-PDF corpus change when each document is weighted by the text it contributes rather than counted once. We used CC-MAIN-2021-31-PDF-UNTRUNCATED (7.9M Common Crawl PDFs, 32.6B tokens), the one public corpus that pairs the fragments Common Crawl stored with the re-fetched originals. Text mass is highly concentrated: 3.02% of text-bearing documents hold half the ...
| Authors | Luca Foppiano |
|---|---|
| Primary category | cs.CL |
| Published | 17 August 2026 |
| Last updated at source | 21 September 2026 |
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