Thunder-DeID+: Boundary-Aware Korean De-identification from Court Judgments to Broader Sensitive Documents
Read the original on arXiv Computation and Language →Thunder‑DeID+ is a Korean de‑identification system that improves boundary precision, label granularity, and recall when applied to court judgments and other sensitive documents. It introduces a refined three‑tier PII taxonomy and a boundary‑aware tokenizer that augments a pretrained BPE vocabulary with N‑gram and boundary‑scoring components, enabling better alignment of token and PII span boundaries. Evaluations show the tokenizer raises the W. Strict Typed F1‑score from 0.76‑0.77 to 0.87‑0.88 across models, and fine‑tuning on 1,000 broader documents yields a 0.93 score, demonstrating effective transfer beyond court judgments.
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