MiqraBERT, a finetuned Sentence-BERT model, achieves 2.7-fold better distributional separation of parallel versus non-parallel Biblical Hebrew verses and reduces ambiguous overlap from 24% to 6%, with strong performance on narrative but weak on poetic parallels.
T’OMIM: Tanakh Observable Matches of Intertextual Mimesis
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MiqraBERT: Regression-Based Sentence-BERT Finetuning for Biblical Hebrew Parallel Detection
MiqraBERT, a finetuned Sentence-BERT model, achieves 2.7-fold better distributional separation of parallel versus non-parallel Biblical Hebrew verses and reduces ambiguous overlap from 24% to 6%, with strong performance on narrative but weak on poetic parallels.