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Meddies-PII: A Multilingual Framework for Personally Identifiable Information Extraction in Clinical De-identification

arXiv · AI, language, vision and robotics · article · Sep 11, 2026 · UTC

Clinical de-identification relies on accurately identifying personally identifiable information (PII). However, manually annotated datasets are costly to construct, while existing synthetic alternatives often provide limited details about their generation process or rely on relatively simple synthesis strategies. We introduce Meddies-PII-Dataset, a corpus of one million synthetic clinical documents spanning seventeen languages and nine PII labels. The documents are generated using attribute-conditioned prompts and validated through thirteen deterministic gates that enforce structural and annot

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