PhiloBERTA: A Transformer-Based Cross-Lingual Analysis of Greek and Latin Lexicons
This provides a quantitative framework for classical philological research, though it is incremental in applying existing methods to a new domain.
The paper tackled the problem of measuring semantic relationships between ancient Greek and Latin lexicons, showing that etymologically related pairs have significantly higher similarity scores, with statistical significance (p = 0.012).
We present PhiloBERTA, a cross-lingual transformer model that measures semantic relationships between ancient Greek and Latin lexicons. Through analysis of selected term pairs from classical texts, we use contextual embeddings and angular similarity metrics to identify precise semantic alignments. Our results show that etymologically related pairs demonstrate significantly higher similarity scores, particularly for abstract philosophical concepts such as epistēmē (scientia) and dikaiosynē (iustitia). Statistical analysis reveals consistent patterns in these relationships (p = 0.012), with etymologically related pairs showing remarkably stable semantic preservation compared to control pairs. These findings establish a quantitative framework for examining how philosophical concepts moved between Greek and Latin traditions, offering new methods for classical philological research.