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HoLM: Analyzing the Linguistic Unexpectedness in Homeric Poetry

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

DOI:10.63317/297itczqip3w

Abstract

The authorship of the Homeric poems has been a matter of debate for centuries. Computational approaches such as language modeling exist that can aid experts in making crucial headway. We observe, however, that such work has, thus far, only been carried out at the level of lengthier excerpts, but not individual verses, the level at which most suspected interpolations occur. We address this weakness by presenting a corpus of Homeric verses, each complemented with a score quantifying linguistic unexpectedness based on Perplexity. We assess the nature of these scores by exploring their correlation with named entities, the frequency of character n-grams, and (inverse) word frequency, revealing robust correlations with the latter two. This apparent bias can be partly overcome by simply dividing scores for unexpectedness by the maximum term frequency per verse.

Details

Paper ID
lrec2024-main-0715
Pages
pp. 8166-8172
BibKey
pavlopoulos-etal-2024-holm
Editor
N/A
Publisher
European Language Resources Association (ELRA) and ICCL
ISSN
2522-2686
ISBN
979-10-95546-34-4
Conference
Joint International Conference on Computational Linguistics, Language Resources and Evaluation
Location
Turin, Italy
Date
20 May 2024 25 May 2024

Authors

  • JP

    John Pavlopoulos

  • RS

    Ryan Sandell

  • MK

    Maria Konstantinidou

  • CB

    Chiara Bozzone

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