Archive · Document AI · Family history

The Buck Ends Here

My grandfather, Ivan D.E. Beaumont, wrote a column for the Nebraska City News-Press for about twenty years. I wanted every word of it back in readable text.

1959–1979 [N] columns PDF scans → clean text Visit the archive →
[Column headline]The county board met Tuesday evening to talk over the new bridge, and as usual the discussion ran longer than the agenda.
Placeholder text. Swap in a real passage and its real OCR output.

Why I built it

Grandpa ran and wrote for the Nebraska City paper for decades. His column was scattered across scanned pages in the county's digital archive: technically preserved, but practically unreadable. I wanted the family, and anyone else, to be able to sit down and actually read him again.

[Add your own line here, about what his writing means to you.]

What was hard

Standard OCR fell apart on decades-old newsprint: narrow columns, bleed-through, faded type, broken hyphenation. The output wasn't clean enough to read, let alone search.

Switching from plain OCR to an AI transcription step changed the quality completely. After that, the remaining work was a cleanup pass for what it still missed, and finding which piece on each page was actually his.

How it works

  1. 01CollectPull page PDFs from the county's digital archive.
  2. 02Find the column[How you located his column on each page.]
  3. 03Transcribe[Name of the transcription endpoint] instead of plain OCR.
  4. 04Clean & publishFix leftovers, date each piece, and publish the archive.

What I think now

This started as a family project, but the bigger lesson is that a huge amount of local history is stuck in scans nobody can search. Reading and cleaning old documents is now cheap enough to do at archive scale, whether for a county paper, a school, or a company's old records.

Have boxes of old documents that need to become text?

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