@inproceedings{mcgovern-etal-2024-detecting,
title = "Detecting Narrative Patterns in Biblical {H}ebrew and {G}reek",
author = "McGovern, Hope and
Sirin, Hale and
Lippincott, Tom and
Caines, Andrew",
editor = "Pavlopoulos, John and
Sommerschield, Thea and
Assael, Yannis and
Gordin, Shai and
Cho, Kyunghyun and
Passarotti, Marco and
Sprugnoli, Rachele and
Liu, Yudong and
Li, Bin and
Anderson, Adam",
booktitle = "Proceedings of the 1st Workshop on Machine Learning for Ancient Languages (ML4AL 2024)",
month = aug,
year = "2024",
address = "Hybrid in Bangkok, Thailand and online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.ml4al-1.26",
pages = "269--279",
abstract = "We present a novel approach to extracting recurring narrative patterns, or type-scenes, in Biblical Hebrew and Biblical Greek with an information retrieval network. We use cross-references to train an encoder model to create similar representations for verses linked by a cross-reference. We then query our trained model with phrases informed by humanities scholarship and designed to elicit particular kinds of narrative scenes. Our models can surface relevant instances in the top-10 ranked candidates in many cases.Through manual error analysis and discussion, we address the limitations and challenges inherent in our approach. Our findings contribute to the field of Biblical scholarship by offering a new perspective on narrative analysis within ancient texts, and to computational modeling of narrative with a genre-agnostic approach for pattern-finding in long, literary texts.",
}
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%0 Conference Proceedings
%T Detecting Narrative Patterns in Biblical Hebrew and Greek
%A McGovern, Hope
%A Sirin, Hale
%A Lippincott, Tom
%A Caines, Andrew
%Y Pavlopoulos, John
%Y Sommerschield, Thea
%Y Assael, Yannis
%Y Gordin, Shai
%Y Cho, Kyunghyun
%Y Passarotti, Marco
%Y Sprugnoli, Rachele
%Y Liu, Yudong
%Y Li, Bin
%Y Anderson, Adam
%S Proceedings of the 1st Workshop on Machine Learning for Ancient Languages (ML4AL 2024)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Hybrid in Bangkok, Thailand and online
%F mcgovern-etal-2024-detecting
%X We present a novel approach to extracting recurring narrative patterns, or type-scenes, in Biblical Hebrew and Biblical Greek with an information retrieval network. We use cross-references to train an encoder model to create similar representations for verses linked by a cross-reference. We then query our trained model with phrases informed by humanities scholarship and designed to elicit particular kinds of narrative scenes. Our models can surface relevant instances in the top-10 ranked candidates in many cases.Through manual error analysis and discussion, we address the limitations and challenges inherent in our approach. Our findings contribute to the field of Biblical scholarship by offering a new perspective on narrative analysis within ancient texts, and to computational modeling of narrative with a genre-agnostic approach for pattern-finding in long, literary texts.
%U https://aclanthology.org/2024.ml4al-1.26
%P 269-279
Markdown (Informal)
[Detecting Narrative Patterns in Biblical Hebrew and Greek](https://aclanthology.org/2024.ml4al-1.26) (McGovern et al., ML4AL-WS 2024)
ACL
- Hope McGovern, Hale Sirin, Tom Lippincott, and Andrew Caines. 2024. Detecting Narrative Patterns in Biblical Hebrew and Greek. In Proceedings of the 1st Workshop on Machine Learning for Ancient Languages (ML4AL 2024), pages 269–279, Hybrid in Bangkok, Thailand and online. Association for Computational Linguistics.