@inproceedings{pavlopoulos-etal-2023-dating,
title = "Dating {G}reek Papyri with Text Regression",
author = "Pavlopoulos, John and
Konstantinidou, Maria and
Marthot-Santaniello, Isabelle and
Essler, Holger and
Paparigopoulou, Asimina",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.556",
doi = "10.18653/v1/2023.acl-long.556",
pages = "10001--10013",
abstract = "Dating Greek papyri accurately is crucial not only to edit their texts but also to understand numerous other aspects of ancient writing, document and book production and circulation, as well as various other aspects of administration, everyday life and intellectual history of antiquity. Although a substantial number of Greek papyri documents bear a date or other conclusive data as to their chronological placement, an even larger number can only be dated tentatively or in approximation, due to the lack of decisive evidence. By creating a dataset of 389 transcriptions of documentary Greek papyri, we train 389 regression models and we predict a date for the papyri with an average MAE of 54 years and an MSE of 1.17, outperforming image classifiers and other baselines. Last, we release date estimations for 159 manuscripts, for which only the upper limit is known.",
}
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%0 Conference Proceedings
%T Dating Greek Papyri with Text Regression
%A Pavlopoulos, John
%A Konstantinidou, Maria
%A Marthot-Santaniello, Isabelle
%A Essler, Holger
%A Paparigopoulou, Asimina
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F pavlopoulos-etal-2023-dating
%X Dating Greek papyri accurately is crucial not only to edit their texts but also to understand numerous other aspects of ancient writing, document and book production and circulation, as well as various other aspects of administration, everyday life and intellectual history of antiquity. Although a substantial number of Greek papyri documents bear a date or other conclusive data as to their chronological placement, an even larger number can only be dated tentatively or in approximation, due to the lack of decisive evidence. By creating a dataset of 389 transcriptions of documentary Greek papyri, we train 389 regression models and we predict a date for the papyri with an average MAE of 54 years and an MSE of 1.17, outperforming image classifiers and other baselines. Last, we release date estimations for 159 manuscripts, for which only the upper limit is known.
%R 10.18653/v1/2023.acl-long.556
%U https://aclanthology.org/2023.acl-long.556
%U https://doi.org/10.18653/v1/2023.acl-long.556
%P 10001-10013
Markdown (Informal)
[Dating Greek Papyri with Text Regression](https://aclanthology.org/2023.acl-long.556) (Pavlopoulos et al., ACL 2023)
ACL
- John Pavlopoulos, Maria Konstantinidou, Isabelle Marthot-Santaniello, Holger Essler, and Asimina Paparigopoulou. 2023. Dating Greek Papyri with Text Regression. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 10001–10013, Toronto, Canada. Association for Computational Linguistics.