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New Pipeline Extracts Billions of Tokens from Historical Newspapers

By PulseAugur Editorial · [1 sources] ·

Researchers have developed the Institutional Newspapers Pipeline, a modular system designed to extract high-quality, structured data from historical newspaper scans. This pipeline, created in collaboration with the Boston Public Library, processes scans through segmentation, OCR, and various text analysis steps to classify types, detect reading order, recognize named entities, and generate embeddings. The system was applied to over 1.4 million public domain newspaper scans published between 1795 and 1930, yielding 16.3 billion tokens and resulting in an open dataset. AI

IMPACT Enables large-scale analysis of historical text data, potentially uncovering new insights from digitized archives.

RANK_REASON The item is a research paper describing a new pipeline for data extraction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Pipeline Extracts Billions of Tokens from Historical Newspapers

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The item is a research paper describing a new pipeline for data extraction. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Matteo Cargnelutti, Catherine Brobston, Eben English, Jake Sadow, Kacie Bailey, Greg Leppert, Amanda Watson, Jessica Chapel, Jonathan Zittrain ·

    Institutional Newspapers Pipeline: Deriving billions of high quality tokens from historical newspapers

    arXiv:2608.18972v1 Announce Type: new Abstract: Historical newspapers are an abundant record of public life, but their dense, irregular and sometimes noisy layouts make computational access to these materials both challenging and limited. We present the Institutional Newspapers P…

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