Thunder-DeID+: Boundary-Aware Korean De-identification from Court Judgments to Broader Sensitive Documents
This study examines the transferability of a de-identification model developed for Korean court judgments to a broader range of sensitive documents, focusing on boundary precision, label granularity, and recall.
ProofPaper ↗
Key points
- The agglutinative structure of Korean causes Byte Pair Encoding (BPE) tokenizers to frequently merge Personally Identifiable Information (PII) with adjacent particles, which complicates accurate span recovery.
- To address these issues, this study introduces Thunder-DeID+, which integrates a refined three-tier PII taxonomy with a boundary-aware tokenizer.
- The proposed approach is evaluated using a tokenizer-independent word-segment-level protocol.
- Strict Typed F1-score, indicating effective transfer beyond court judgments.
Sources (1)
- [1]Thunder-DeID+: Boundary-Aware Korean De-identification from Court Judgments to Broader Sensitive DocumentsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 15, 11:11 PM
This study examines the transferability of a de-identification model developed for Korean court judgments to a broader range of sensitive documents, focusing on boundary precision, label granularity, and recall.
The agglutinative structure of Korean causes Byte Pair Encoding (BPE) tokenizers to frequently merge Personally Identifiable Information (PII) with adjacent particles, which complicates accurate span recovery.
Extractive summary: sentences quoted from the sources.
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