Mining the Nineteenth Century for the Thirteenth: Register-Scale Forced Alignment and HTR Bootstrapping via Legacy Regesta and Antiquarian Editions
Read the original on arXiv Computation and Language →The study evaluates how nineteenth‑century scholarship—specifically Pressutti’s regesta and partial editions—can aid handwritten text recognition (HTR) of Pope Honorius III’s registers beyond the limited modern expert transcriptions available for regnal years 1‑2. By aligning legacy layers with modern source lines, the authors demonstrate that projection onto curial spelling with replay reduces word‑error rate by 1.50 points, that a legacy lexicon covers 82.2 % of out‑of‑vocabulary words and flags errors with 66.7 % precision, and that a distilled medieval NER model achieves an F1 of 82.1 % on a validated benchmark. Additionally, Pressutti’s regesta and related topological data recover 73.9 % of entry starts and suggest a character‑error rate of 7.80 % beyond folio 203, indicating that antiquarian scholarship can steer, check, and segment HTR rather than replace modern transcription.
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