2025
NAACL
NAACL 2025
Towards an Integrated Methodology of Dating Biblical Texts: The Case of the Book of Jeremiah
Abstract
AbstractIn this paper we describe our research project on dating the language of the Book of Jeremiah using a combination of traditional biblical scholarship and machine learning. Jeremiah is a book with a long history of composing and editing, and the historical background of many of the sections in the book are unclear. Moreover, redaction criticism and historical linguistics are mostly separate fields within the discipline of Biblical Studies. With our approach we want to integrate these areas of research and make new strides in uncovering the compositional history of Book of Jeremiah.
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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning and Natural Language Processing
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Keyword Pioneer
— biblical scholarship
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning
Machine Learning > Core Methods > Classification
Natural Language Processing > Applications > Text Classification
Interdisciplinary > Linguistics > Computational Linguistics
Interdisciplinary > Digital Humanities
Interdisciplinary > Social > Digital Humanities
Machine Learning > Learning Types > Machine Learning