Quid est VERITAS? A Modular Framework for Archival Document Analysis
This addresses the need for more efficient and accurate computational analysis of archival documents for historical researchers, though it is incremental as it builds on existing digitization methods.
The paper tackles the problem of digitizing historical documents by introducing VERITAS, a modular framework that integrates transcription, layout analysis, and semantic enrichment, resulting in a 67.6% relative reduction in word error rate and a threefold reduction in processing time compared to a commercial OCR baseline.
The digitisation of historical documents has traditionally been conceived as a process limited to character-level transcription, producing flat text that lacks the structural and semantic information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.