Logion: Machine Learning for Greek Philology

Autor:	Cowen-Breen, Charlie, Brooks, Creston, Haubold, Johannes, Graziosi, Barbara
Rok vydání:	2023
Předmět:	Computer Science - Computation and Language Computer Science - Machine Learning I.2.7
Druh dokumentu:	Working Paper
Popis:	This paper presents machine-learning methods to address various problems in Greek philology. After training a BERT model on the largest premodern Greek dataset used for this purpose to date, we identify and correct previously undetected errors made by scribes in the process of textual transmission, in what is, to our knowledge, the first successful identification of such errors via machine learning. Additionally, we demonstrate the model's capacity to fill gaps caused by material deterioration of premodern manuscripts and compare the model's performance to that of a domain expert. We find that best performance is achieved when the domain expert is provided with model suggestions for inspiration. With such human-computer collaborations in mind, we explore the model's interpretability and find that certain attention heads appear to encode select grammatical features of premodern Greek. Comment: 14 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2305.01099 Zobrazit plný text záznamu View this record from Arxiv