The digitisation of historical documents has traditionally been conceived as a process limited to character-level transcription, producing flat text that lacks the structural and semantic information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.

Quid est VERITAS? A Modular Framework for Archival Document Analysis / L. Bassanini, L.B. - In: Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities / [a cura di] A. Montejo-Ráez, C. Grisot. - [s.l] : European Language Resources Association (ELRA), 2026. - pp. 57-66 (( LLMs4SSH Proceedings : May, 11th - 16th Palma de Mallorca 2026 [10.63317/3ec9hbgdgs8x].

Quid est VERITAS? A Modular Framework for Archival Document Analysis

L. Bassanini
Primo
;
L. Biancardi
Secondo
;
A. Ferrara;A. Gamberini;S. Picascia
Penultimo
;
F. Vaglienti
Ultimo
2026

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The digitisation of historical documents has traditionally been conceived as a process limited to character-level transcription, producing flat text that lacks the structural and semantic information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.
vision language models; document layout analysis; historical document digitisation; digital humanities;
Settore INFO-01/A - Informatica
Settore HIST-04/C - Archivistica, bibliografia e biblioteconomia
2026
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1259398
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