datasets · release
The first open datasets in the EuroPriv-Bench suite
The first open EuroPriv-Bench datasets are now on Hugging Face — general-domain bring-up sets in Romanian, English, and Polish, 50,000 documents each:
- klusai/ds-kp-general-ro-50k — Romanian
- klusai/ds-kp-general-en-50k — English
- klusai/ds-kp-general-pl-50k — Polish
These aren’t the first synthetic-PII datasets — the field has plenty. They’re the first datasets in the EuroPriv-Bench suite, and they’re built to a quality bar most synthetic-PII sets miss.
The bar: valid IDs, correct spans, honest provenance
Synthetic PII is easy to generate and easy to get subtly wrong. We held these sets to four properties, each one checkable:
- Checksum-valid locale identifiers. Where an identifier carries a check digit, the emitted value passes it: Romanian CNP, Polish PESEL and NIP, IBAN (mod-97), payment cards (Luhn). Invalid or fake-checksum IDs are not emitted. A benchmark that quietly ships malformed national IDs can’t tell you whether a model handles real ones.
- Offset-correct gold spans, by construction. Because the PII is injected into the text, we know exactly where every entity sits — no post-hoc span alignment to drift. We verify it anyway: 100% byte-equality between each gold span and the substring it points at, and 100% BIOES validity on the tag sequence.
- Zero train/gold overlap. Training material and gold are kept strictly apart, so a model can’t score on rows it has effectively seen.
- Uniform provenance, per dataset. Each card records source and license, the generator seed, and the taxonomy version — the same fields, the same shape, every time.
Cleanly-licensed, openly redistributable
The whole set is CC-BY. We sourced cleanly-licensed material only, so the datasets are openly redistributable end to end — no “results you can see but data you can’t.” That’s a precondition for the kind of reproducibility EuroPriv-Bench is built around: a number you can’t trace to data you can load isn’t one you can check.
How it fits the program
These sets feed the EuroPriv-Bench models and benchmark — the general-domain foundation the detection and re-identification-risk evaluations run on. Romanian matters here in particular: it isn’t in the common training corpora, so a Romanian gold set tests models on genuinely unseen ground.
Re-identification risk, not detection-F1, is the metric we lead with — a missed national ID isn’t one missed token, it’s a leaked birthday, sex, and county at once. Clean, checksum-valid IDs are what make that measurement honest: you can only count what a miss exposes if the ID you’re decoding is structurally real.
This is the general-domain bring-up. Legal and clinical synthesis come next.
→ See where these feed in on the leaderboard, or read the roadmap.