building-gold-corpus
从项目初期提供可复现的评估夹具与注释配置，降低数据合规风险。
切勿提交真实受限临床数据到仓库，需严格合规与合成化。
搭建临床 NER/去标识化的合成金标语料、标注规范与分割用于评估。
搭建一套可直接用于 OpenMed 评估的金标注工程：定好标签集、写标注规范、生成 BRAT 或 Label Studio 的配置，并切分出训练/验证/测试集。强调能提交到仓库的金标必须是合成数据，受限真实语料（如 i2b2、MIMIC）只能本地用于评估。适合要组织标注、产出可复现 eval fixtures 或搭建评测基线时使用。
▸ 展开 SKILL.md 英文原文
Scaffold a synthetic gold-standard annotation project for evaluating OpenMed NER and de-identification models — label schema, annotation guidelines, BRAT or Label Studio config, and disjoint train/dev/test splits. Use when the user wants to create eval fixtures, set up annotation, define a label set, write guidelines, configure an annotation tool, or build a held-out gold set for the OpenMed eval harness. Trigger on "gold corpus", "annotation project", "label schema", "annotation guidelines", "BRAT", "Label Studio", "train dev test split", or "build eval fixtures" for OpenMed. Committed gold must be synthetic; licensed (i2b2/n2c2/MIMIC) data is eval-only and never committed.
帮我安装这个 skill：https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/building-gold-corpus/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/building-gold-corpus/SKILL.md"# Building a Gold Corpus You can't evaluate what you can't measure against. This skill scaffolds a gold-standard annotation project whose output drops straight into the OpenMed eval harness as fixtures. The hard rule: **anything committed to the repo is synthetic**. Licensed clinical corpora (i2b2, n2c2, MIMIC) are DUA-gated — use them at eval time from the user's own copy, never check them in. ## When to use this skill - You need eval fixtures for `benchmarking-clinical-ner` or `evaluating-with-leakage-gates` and have none. - You're standing up an annotation effort: schema, guidelines, tool config. - You need disciplined train/dev/test splits with no leakage between them. - You want a