ALMA: Automated Alignment of Ancient Texts using Linguistic and Semantic Analysis
TL;DR
This paper introduces ALMA, a new pipeline that integrates lexical, grammatical, and semantic analysis to perform automatic textual alignment on four manuscripts of the Gospel of John, two in Latin and two in Greek.
Abstract
Textual criticism, the task of reconstructing a text as close as possible to its original form based on multiple ancient copies, is a central concern of philologists studying ancient literature. After identifying and cataloging the available manuscripts, scholars align the texts to produce a list of variants, a process known as collation . Automating this task has been one of the earliest areas of interest for applying computational methods to the humanities. Most current approaches rely on sequence alignment algorithms, originally developed for bioinformatics. However, recent advances in mono and multilingual neural alignment, capable of modeling semantic, syntactic, and grammatical relationships, remain largely underutilized in this field. In this paper, we introduce ALMA ( A lignment and L earning for M anuscript A nalysis). This new pipeline integrates lexical, grammatical, and semantic analysis to perform automatic textual alignment. We evaluate ALMA against three established alignment methods, each representing a different paradigm, on four manuscripts of the Gospel of John, two in Latin and two in Greek. ALMA achieves