Papers by Sophie Robert-Hayek

1 papers
A Classifier of Word-Level Variants in Witnesses of Biblical Hebrew Manuscripts (2025.findings-acl)

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Challenge: a strong classifier (F1 value of 0.80) is trained to predict the category of difference between word pairs as present in collated (aligned) pairs of witnesses.
Approach: The project is based on the relationship between available witnesses of biblical Hebrew and a strong classifier (F1 value of 0.80) is trained to predict the category of difference between word pairs as present in collated pairs of witnesses.
Outcome: The proposed model is non-neural and uses part-of-speech tags, hand-crafted rules per category and synthetically derived data.

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