A Fine-Tuned BERT Classifier for Personal-Letter Titles in Late-Ming and Early-Qing Collected Works
Researchers have developed Lepton, a BERT-based classifier designed to distinguish personal letter titles from prefaces in Classical Chinese collected works. The model was fine-tuned on over 5,000 hand-labeled titles from the late Ming and early Qing dynasties. This tool has been implemented at the China Biographical Database to identify an estimated 55,000 letters, contributing to the Ming Letter Platform. AI
IMPACT This model demonstrates a novel application of NLP for historical text analysis, potentially enabling new avenues for digital humanities research.