@inproceedings{chen-etal-2024-leveraging,
title = "Leveraging Part-of-Speech Tagging for Enhanced Stylometry of {L}atin Literature",
author = "Chen, Sarah and
Burns, Patrick and
Bolt, Thomas and
Chaudhuri, Pramit and
Dexter, Joseph",
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-1.24",
pages = "251--259",
abstract = "In literary critical applications, stylometry can benefit from hand-curated feature sets capturing various syntactic and rhetorical functions. For premodern languages, calculation of such features is hampered by a lack of adequate computational resources for accurate part-of-speech tagging and semantic disambiguation. This paper reports an evaluation of POS-taggers for Latin and their use in augmenting a hand-curated stylometric feature set. Our experiments show that POS-augmented features not only provide more accurate counts than POS-blind features but also perform better on tasks such as genre classification. In the course of this work we introduce POS n-grams as a feature for Latin stylometry.",
}
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%0 Conference Proceedings
%T Leveraging Part-of-Speech Tagging for Enhanced Stylometry of Latin Literature
%A Chen, Sarah
%A Burns, Patrick
%A Bolt, Thomas
%A Chaudhuri, Pramit
%A Dexter, Joseph
%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 chen-etal-2024-leveraging
%X In literary critical applications, stylometry can benefit from hand-curated feature sets capturing various syntactic and rhetorical functions. For premodern languages, calculation of such features is hampered by a lack of adequate computational resources for accurate part-of-speech tagging and semantic disambiguation. This paper reports an evaluation of POS-taggers for Latin and their use in augmenting a hand-curated stylometric feature set. Our experiments show that POS-augmented features not only provide more accurate counts than POS-blind features but also perform better on tasks such as genre classification. In the course of this work we introduce POS n-grams as a feature for Latin stylometry.
%U https://aclanthology.org/2024.ml4al-1.24
%P 251-259
Markdown (Informal)
[Leveraging Part-of-Speech Tagging for Enhanced Stylometry of Latin Literature](https://aclanthology.org/2024.ml4al-1.24) (Chen et al., ML4AL-WS 2024)
ACL