---
license: cc-by-4.0
language:
  - ar
  - de
  - el
  - en
  - es
  - fr
  - it
  - nl
  - pt
  - sl
  - tr
task_categories:
  - token-classification
task_ids:
  - named-entity-recognition
tags:
  - pii
  - privacy
  - anonymization
  - italian
  - multilingual
  - ner
size_categories:
  - 100K<n<1M
pretty_name: aliasit-pii-dataset-v3
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.parquet
      - split: validation
        path: data/validation.parquet
      - split: test
        path: data/test.parquet
      - split: benchmark
        path: data/benchmark.parquet
---

# aliasit-pii-dataset-v3

Multilingual PII span-annotation dataset, 79 entity types, 30 pinned sources, Italian-first. Text plus character spans, single-label BIO.

| | |
|---|---|
| Documents | 182,862 |
| Entities | 3,172,535 |
| Entity types | 79 (46 marked critical) |
| Languages | ar, de, el, en, es, fr, it, nl, pt, sl, tr |
| Taxonomy | v3.0.0 — `taxonomy.yaml` ships in this repo |
| Revision | 6.0.0 |
| Representation | text + character spans, `end` exclusive, non-overlapping |
| Distinct sources | 27, each pinned to a commit SHA or a file checksum |

## Splits

| Split | Documents | Entities | Languages | Training |
|---|---:|---:|---|---|
| `train` | 139,606 | 2,107,037 | 11 | allowed |
| `validation` | 16,261 | 368,663 | 10 | allowed |
| `test` | 16,066 | 362,725 | 9 | **FORBIDDEN** |
| `benchmark` | 10,929 | 334,110 | 6 | **FORBIDDEN** |

**`benchmark`, `test` must not be used for training**, nor for threshold calibration, model selection, distillation or hyper-parameter tuning. Anything that needs data for those uses `validation`. This is not a formality: these splits are how the project measures whether a model works, and an evaluation that cannot fail is not an evaluation.

## Sources and licences

Every source is pinned: a 40-character commit SHA for Hugging Face repositories, a SHA-256 of the downloaded file for public web files. A branch is not a pin.

| Source | Generation | Licence | Attribution | Docs |
|---|---|---|---|---:|
| `nvidia/Nemotron-PII` | delta1 | CC-BY-4.0 | **required** | 1,690 |
| `E3-JSI/synthetic-multi-pii-ner-v1` | delta1 + delta3 | MIT | — | 433 |
| `abhinavdread/msme-document-presence-dataset` | delta2 | MIT | — | 300 |
| `AIFA — farmaci di classe A per principio attivo` | delta2 | CC-BY-4.0 | **required** | 128 |
| `albertobarnabo/synthetic-receipts-ocr (IT locale)` | delta2 | APACHE-2.0 | — | 511 |
| `ANPR — archivio dei comuni (Ministero dell'Interno)` | delta2 | CC-BY-4.0 | **required** | 290 |
| `ANPR — tabella stati esteri (Ministero dell'Interno)` | delta2 | CC-BY-4.0 | **required** | 195 |
| `arnaudstiegler/synthetic_us_passports_easy` | delta2 | APACHE-2.0 | — | 294 |
| `computed in-repo (statutory codice fiscale algorithm)` | delta2 | APACHE-2.0 | — | 247 |
| `DataDock/geonames` | delta2 | CC-BY-4.0 | **required** | 1 |
| `dossier-legal/italian-legal-corpus` | delta2 | CC-BY-4.0 | **required** | 500 |
| `Ethosoft/TR-DocVQA-Synth` | delta2 | CC-BY-4.0 | **required** | 902 |
| `huseyinatahaninan/ContextualIntegritySyntheticDataset` | delta2 | APACHE-2.0 | — | 14 |
| `istat-ai/court-rulings-coi` | delta2 | APACHE-2.0 | — | 243 |
| `kurkowski/synthetic-contextual-anonymizer-dataset` | delta2 | MIT | — | 373 |
| `mik3ml/personas-italian` | delta2 | APACHE-2.0 | — | 255 |
| `Ministero della Salute — ICD-9-CM, versione italiana 2007` | delta2 | IODL-2.0 | **required** | 520 |
| `Toridion/lindisfarne-m1` | delta2 | CC-BY-4.0 | **required** | 586 |
| `albertobarnabo/synthetic-receipts-ocr (UK + DE locales)` | delta3 | APACHE-2.0 | — | 344 |
| `IVASS — Lista imprese assicurative vigilate` | delta3 | CC-BY-4.0 | **required** | 190 |
| `lucianfialho/privacy-filter-br-dataset` | delta3 | APACHE-2.0 | — | 698 |
| `PICO2/tau2-bench-data` | delta3 | MIT | — | 167 |
| `subhash-holla/pii-anon` | delta3 | CC0-1.0 | — | 176 |
| `ai4privacy/pii-masking-openpii-1m` | v2 | CC-BY-4.0 | **required** | 59,949 |
| `gretelai/synthetic_pii_finance_multilingual` | v2 | APACHE-2.0 | — | 19,258 |
| `rizzoaiacademy/anonimizzazione-testi-italiano-clean` | v2 | MIT | — | 72,313 |
| `urchade/synthetic-pii-ner-mistral-v1` | v2 | APACHE-2.0 | — | 21,905 |

Audited and mapped but contributing no documents, because a higher-priority source had already covered the need: `richardyoung/synthea-575k-patients`, `itamarcohen/insurance_car_Qfiles`, `strova-ai/financial_credit_dataset`.

### Attribution notices

These sources are redistributed under licences that require attribution. **If you redistribute this dataset, these notices must travel with it.**

- NVIDIA, Nemotron-PII (CC-BY-4.0)
- Agenzia Italiana del Farmaco (AIFA), liste dei farmaci di classe A (CC-BY-4.0)
- Ministero dell'Interno - ANPR, archivio dei comuni (CC-BY-4.0)
- Ministero dell'Interno - ANPR, tabella 2 stati esteri (CC-BY-4.0)
- GeoNames (CC-BY-4.0), mirror DataDock/geonames
- dossier-legal, italian-legal-corpus (CC-BY-4.0)
- Ethosoft, TR-DocVQA-Synth (CC-BY-4.0)
- Ministero della Salute, Manuale ICD-9-CM versione italiana 2007 (IODL 2.0)
- Toridion, Lindisfarne M1 (CC-BY-4.0)
- IVASS - Istituto per la Vigilanza sulle Assicurazioni, Lista imprese assicurative vigilate (CC-BY-4.0)
- Ai4Privacy / Ai Suisse SA (CC-BY-4.0)

Licence mix: APACHE-2.0 (10), CC-BY-4.0 (10), CC0-1.0 (1), IODL-2.0 (1), MIT (5). The strictest terms are CC-BY-4.0 and IODL-2.0 — both allow commercial use and derivative works and require attribution — so the dataset as a whole travels as **CC-BY-4.0 with attribution**.

## Record schema

```
id                  stable document id
text                the document
language            ISO 639-1, or `und`
split               train | validation | test | benchmark
ent_start[]         character offsets, `end` = start + len, exclusive
ent_len[]  ent_label[]  ent_source_label[]  ent_source_dataset[]  ent_mapping[]
unm_*[]             source annotations with no canonical counterpart, kept on the record
prov_*              dataset, repo_id, revision, original_id, licence, register, ...
fp_*                exact, normalized, entity_set, template, template_shape
cont_extra_json     origin (v2 / v3_delta…), source_family, annotation_origin, group_id
```

Invariants checked at build time and by the gate:

1. `text[start:end] == entity text` for every entity and every unmapped span;
2. `0 <= start < end <= len(text)`;
3. entities never overlap (the model is single-label BIO);
4. every label exists in the shipped taxonomy;
5. spans survive the round trip through the tokenizer, BIO encoding and decoding.

## Known data gaps

2 categories sit below a hard support threshold, 1 of them critical. They are listed rather than hidden, and each says which source was examined and why it was not usable.

| Category | Critical | Train | Val | Test | Reason |
|---|:-:|---:|---:|---:|---|
| `prescription_number` | yes | 238 | 23 | 21 | `INSUFFICIENT_EXACT_RECORDS` |
| `train_ticket_number` | — | 84 | 30 | 34 | `ONLY_EXISTING_SOURCE_AVAILABLE` |

Three entity types were **removed** from the taxonomy rather than filled with the wrong data: `serial_number` and `vehicle_registration_number` (no public source annotates them as the taxonomy defines them), and `digital_signature` (39% of its existing gold was the *phrase* "digital signature" instead of a value). Their spans were migrated or kept as unmapped spans, never silently dropped.

## Limitations

1. **Synthetic.** Effectively all of it. No real person's data is in here, which is the point, but synthetic-to-real transfer is not measured by anything in this repository.
2. **Derived frames.** Part of the support comes from documents written around structured records rather than natural text. Every record declares which it is in `cont_extra_json.annotation_origin`.
3. **Partial annotation from one source.** `E3-JSI/synthetic-multi-pii-ner-v1` has an open type vocabulary and only a verified allow-list is mapped, so its documents carry annotations for some of their entities and not all. For that reason every such document sits in `train` only.
4. **Reference-model contamination.** `urchade/synthetic-pii-ner-mistral-v1` is the training set of `urchade/gliner_multi_pii-v1`, and `rizzoaiacademy/anonimizzazione-testi-italiano-clean` is declared as the training corpus of `rizzo-pii-0.3B`. Source validation and benchmark are different questions and must not be reported as one.
5. **Two known id collisions.** `nvidia/Nemotron-PII` reuses the same `uid` across rows with different text, so two document ids sit on more than one document, and one value of `medical_record_number` crosses the train/validation boundary. It is measured, named, and cannot be fixed without rewriting a frozen document.

## Verifying what you downloaded

`manifest.json` ships with the files and carries the SHA-256 of each parquet. A dataset without a committed checksum is not a version, it is a copy — if a hash differs, this card does not describe what you have.

```python
import hashlib, json, pathlib
m = json.load(open('manifest.json'))
for f in m['files']:
    h = hashlib.sha256(pathlib.Path('data', f['path'].split('.')[-2] + '.parquet').read_bytes()).hexdigest()
    print(f['path'], h == f['sha256'])
```

## Citation

```bibtex
@dataset{aliasit_pii_aliasit_pii_dataset_v3,
  title   = {aliasit-pii-dataset-v3},
  version = {6.0.0},
  note    = {79 PII entity types, multilingual, Italian-first},
}
```

Derived from the sources listed above, under their respective licences. The attribution notices must travel with it.