Graecia capta ferum victorem cepit. Detecting Latin Allusions to Ancient Greek Literature
This addresses a bottleneck in Classical Philology by enabling cross-lingual analysis, though it is incremental as it builds on existing multilingual models with new data.
The study tackled the problem of automatically detecting Latin allusions to Ancient Greek literature by introducing SPhilBERTa, a trilingual Sentence-RoBERTa model for cross-lingual semantic comprehension across Ancient Greek, Latin, and English, which facilitates automated detection of intertextual parallels.
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.