Graecia capta ferum victorem cepit. Detecting Latin Allusions to Ancient Greek Literature

Graecia capta ferum victorem cepit. Detecting Latin Allusions to Ancient Greek Literature. Riemenschneider, F. & Frank, A. August, 2023. arXiv:2308.12008 [cs]

Paper doi abstract bibtex

Intertextual allusions hold a pivotal role in Classical Philology, with Latin authors frequently referencing Ancient Greek texts. Until now, the automatic identification of these intertextual references has been constrained to monolingual approaches, seeking parallels solely within Latin or Greek texts. In this study, we introduce SPhilBERTa, a trilingual Sentence-RoBERTa model tailored for Classical Philology, which excels at cross-lingual semantic comprehension and identification of identical sentences across Ancient Greek, Latin, and English. We generate new training data by automatically translating English texts into Ancient Greek. Further, we present a case study, demonstrating SPhilBERTa's capability to facilitate automated detection of intertextual parallels. Our models and resources are available at https://github.com/Heidelberg-NLP/ancient-language-models.

@misc{riemenschneider_graecia_2023,
	title = {Graecia capta ferum victorem cepit. {Detecting} {Latin} {Allusions} to {Ancient} {Greek} {Literature}},
	url = {http://arxiv.org/abs/2308.12008},
	doi = {10.48550/arXiv.2308.12008},
	abstract = {Intertextual allusions hold a pivotal role in Classical Philology, with Latin authors frequently referencing Ancient Greek texts. Until now, the automatic identification of these intertextual references has been constrained to monolingual approaches, seeking parallels solely within Latin or Greek texts. In this study, we introduce SPhilBERTa, a trilingual Sentence-RoBERTa model tailored for Classical Philology, which excels at cross-lingual semantic comprehension and identification of identical sentences across Ancient Greek, Latin, and English. We generate new training data by automatically translating English texts into Ancient Greek. Further, we present a case study, demonstrating SPhilBERTa's capability to facilitate automated detection of intertextual parallels. Our models and resources are available at https://github.com/Heidelberg-NLP/ancient-language-models.},
	urldate = {2023-09-29},
	publisher = {arXiv},
	author = {Riemenschneider, Frederick and Frank, Anette},
	month = aug,
	year = {2023},
	note = {arXiv:2308.12008 [cs]},
	keywords = {Computer Science - Computation and Language, I.2.7},
}

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