Quid est VERITAS? A Modular Framework for Archival Document Analysis

TL;DR

VERITAS is a modular framework that enhances digitisation of historical documents by integrating transcription, layout analysis, and semantic enrichment, improving accuracy and efficiency.

Contribution

It introduces a schema-driven, integrated workflow for archival document analysis, combining multiple stages into a flexible, model-agnostic pipeline.

Findings

Achieved 67.6% reduction in word error rate over commercial OCR.

Reduced end-to-end processing time threefold with manual correction.

Demonstrated utility in historical inquiry through retrieval-augmented generation.

Abstract

The digitisation of historical documents has traditionally been conceived as a process limited to character-level transcription, producing flat text that lacks the structural and semantic information necessary for substantive computational analysis. We present VERITAS (Vision-Enhanced Reading, Interpretation, and Transcription of Archival Sources), a modular, model-agnostic framework that reconceptualises digitisation as an integrated workflow encompassing transcription, layout analysis, and semantic enrichment. The pipeline is organised into four stages - Preprocessing, Extraction, Refinement, and Enrichment - and employs a schema-driven architecture that allows researchers to declaratively specify their extraction objectives. We evaluate VERITAS on the critical edition of Bernardino Corio's Storia di Milano, a Renaissance chronicle of over 1,600 pages. Results demonstrate that the pipeline achieves a 67.6% relative reduction in word error rate compared to a commercial OCR baseline, with a threefold reduction in end-to-end processing time when accounting for manual correction. We further illustrate the downstream utility of the pipeline's output by querying the transcribed corpus through a retrieval-augmented generation system, demonstrating its capacity to support historical inquiry.