Explainable Publication Year Prediction of Eighteenth Century Texts with the BERT Model




Rastas Iiro, Ryan Yann, Tiihonen Iiro, Qaraei Mohammedreza, Repo Liina, Babbar Rohit, Mäkelä Eetu, Tolonen Mikko, Ginter Filip

Tahmasebi Nina, Montariol Syrielle, Kutuzov Andrey, Hengchen Simon, Dubossarsky Haim, Borin Lars

Workshop on Computational Approaches to Historical Language Change

2022

Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change

PROCEEDINGS OF THE 3RD INTERNATIONAL WORKSHOP ON COMPUTATIONAL APPROACHES TO HISTORICAL LANGUAGE CHANGE 2022 (LCHANGE 2022)

68

77

10

978-1-955917-42-1

https://aclanthology.org/2022.lchange-1.7.pdf

https://research.utu.fi/converis/portal/detail/Publication/176709131



In this paper, we describe a BERT model trained on the Eighteenth Century Collections Online (ECCO) dataset of digitized documents. The ECCO dataset poses unique modelling challenges due to the presence of Optical Character Recognition (OCR) artifacts. We establish the performance of the BERT model on a publication year prediction task against linear baseline models and human judgement, finding the BERT model to be superior to both and able to date the works, on average, with less than 7 years absolute error. We also explore how language change over time affects the model by analyzing the features the model uses for publication year predictions as given by the Integrated Gradients model explanation method.

Last updated on 2024-26-11 at 19:12