Datasets:
metadata
license: cc-by-4.0
language:
- de
- en
- es
- fr
- it
tags:
- pii
- token-classification
- privacy
- multilingual
task_categories:
- token-classification
PiiScan training corpus — recipe and provenance
This repository publishes the recipe, not the rows.
The PiiScan corpus is derived from sources whose redistribution terms differ, and several forbid republication outright. Rather than ship a subset that is easy to misuse, this repo contains everything needed to rebuild the corpus byte-for-byte from the pinned upstream revisions.
What is here
| File | Purpose |
|---|---|
sources.json |
Every source with its pinned revision, licence, access status, and training decision |
training-data-mappings.json |
Explicit decision for every upstream label; no default branch |
canonical-training-row.schema.json |
The row schema all data is normalised to |
entity-tiers.json |
Which of the 39 types are trained, rule-only, experimental, or blocked |
build-manifest.json |
Counts by split, source, type, and language; fingerprints |
sample-training-data/ |
Hand-authored rows and hard negatives, one file per type (ours, freely reusable) |
Corpus shape
| Split | Rows |
|---|---|
| train | 1,299,487 |
| validation | 323,767 |
| test | 8,328 |
Benchmark tiers in the test split: external_human_annotated (127), held_out_same_generator (8,201).
Redistribution status by source
| Source | Licence | Access | Rows published |
|---|---|---|---|
openpii-1.5m |
CC-BY-4.0 | open | recipe only |
tab |
MIT | open | recipe only |
physionet-deid-resources |
ODC-By-1.0 and GPL-2.0-or-later components | open | recipe only |
wikiann |
unknown | open | no — licence forbids |
multinerd |
CC-BY-NC-SA-4.0 | open | no — licence forbids |
ai4privacy-health-phi-400k |
ai4privacy-commercial | gated | no — licence forbids |
ai4privacy-financial-pfi-400k |
ai4privacy-commercial | gated | no — licence forbids |
ai4privacy-location-pli-400k |
ai4privacy-commercial | gated | no — licence forbids |
ai4privacy-work-pwi-400k |
ai4privacy-commercial | gated | no — licence forbids |
ai4privacy-digital-pdi-350k |
ai4privacy-commercial | gated | no — licence forbids |
physionet-gold-medical-text |
PhysioNet credentialed health data terms | credentialed | no — licence forbids |
n2c2-i2b2-deidentification |
controlled research terms | currently_unavailable | no — licence forbids |
meddocan |
confirm with corpus owner | registration_required | no — licence forbids |
kaggle-pii-educational |
Kaggle competition rules | competition_terms_required | no — licence forbids |
ontonotes-5 |
LDC User Agreement | paid_or_membership | no — licence forbids |
Rebuild it
git clone https://github.com/palarnab/piiscan && cd piiscan
python downloaded-training-data/download.py # pinned revisions only
python scripts/build_training_data.py
python scripts/validate_training_data.py
The build fails rather than silently dropping data if an unknown upstream label appears, and validation enforces span integrity, unique IDs, and cross-split leakage checks.
Attribution
Training data derived from Ai4Privacy OpenPII 1.5M (CC-BY-4.0),
© Ai Suisse SA — https://huggingface.co/datasets/ai4privacy/pii-masking-openpii-1.5m
Evaluation uses the Text Anonymization Benchmark (MIT).