A New Framework for Error Analysis in Computational Paleographic Dating of Greek Papyri

Giuseppe De Gregorio, Lavinia Ferretti, Rodrigo C. G. Pena, Isabelle Marthot-Santaniello, Maria Konstantinidou, John Pavlopoulos
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Abstract

The study of Greek papyri from ancient Egypt is fundamental for understanding Graeco-Roman Antiquity, offering insights into various aspects of ancient culture and textual production. Palaeography, traditionally used for dating these manuscripts, relies on identifying chronologically relevant features in handwriting styles yet lacks a unified methodology, resulting in subjective interpretations and inconsistencies among experts. Recent advances in digital palaeography, which leverage artificial intelligence (AI) algorithms, have introduced new avenues for dating ancient documents. This paper presents a comparative analysis between an AI-based computational dating model and human expert palaeographers, using a novel dataset named Hell-Date comprising securely fine-grained dated Greek papyri from the Hellenistic period. The methodology involves training a convolutional neural network on visual inputs from Hell-Date to predict precise dates of papyri. In addition, experts provide palaeographic dating for comparison. To compare, we developed a new framework for error analysis that reflects the inherent imprecision of the palaeographic dating method. The results indicate that the computational model achieves performance comparable to that of human experts. These elements will help assess on a more solid basis future developments of computational algorithms to date Greek papyri.
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希腊纸质古籍计算年代误差分析新框架
研究古埃及的希腊纸莎草纸是了解古希腊罗马古代的基础,可以深入了解古代文化和文字制作的各个方面。传统上用于确定这些手稿年代的古文字学依赖于识别手写风格中与年代相关的特征,但缺乏统一的方法,导致专家之间的主观解释和不一致。数字考古学的最新进展利用人工智能(AI)算法,为确定古代文献的年代提供了新的途径。本文利用一个名为 Hell-Date 的新数据集,对基于人工智能的计算年代模型和人类古文字学专家进行了比较分析,该数据集由希腊化时期的希腊纸莎草纸组成,具有可靠的细粒度年代。该方法包括对来自 Hell-Date 的视觉输入进行卷积神经网络训练,以预测纸莎草纸的精确日期。此外,专家们还提供了古文字学的年代,以供比较。为了进行比较,我们开发了一个新的误差分析框架,以反映古文字学定年方法固有的不精确性。结果表明,计算模型的性能可与人类专家相媲美。这些要素将有助于在更坚实的基础上评估未来希腊纸莎草纸年代计算算法的发展。
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