Entity Types Classification
Personal Information
- Date of birth
- Age
- Gender
- Last name
- Occupation
- Education level
- Phone number
- Street address
- City
- Country
- Postcode
- User name
- Password
- Tax ID
- License plate
- CVV
- Bank routing number
- Account number
- SWIFT BIC
- Biometric identifier
- Device identifier
- Location
Financial Information
- Account number
- Bank routing number
- SWIFT BIC
- CVV
- Tax ID
- API key
Health and Medical Information
- Blood type
- Biometric identifier
- Organ
- Diseases symptom
- Diagnostics
- Preventive medicine
- Treatment
- Surgery
- Drug chemical
- Medical device technique
- Personal care
Online and Web-related Information
- URL
- IP address
- User name
- API key
Professional Information
- Occupation
- Skill
- Organization
- Company name
Location Information
- City
- Country
- Postcode
- Street address
- Location
Time-Related Information
- Date
- Date time
Miscellaneous
- Event
- Miscellaneous
Product and Goods Information
- Product
- Quantity
- Food drink
- Transportation
Identifiers
- Device identifier
- Biometric identifier
- User name
- Phone number
- URL
- License plate
Model Card for GLiNER PII
GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.
This model has been trained by fine-tuning urchade/gliner_multi-v2.1 on the urchade/synthetic-pii-ner-mistral-v1 dataset.
Links
- Paper: https://arxiv.org/abs/2311.08526
- Repository: https://github.com/urchade/GLiNER
from gliner import GLiNER
model = GLiNER.from_pretrained("urchade/gliner_multi_pii-v1")
text = """
Harilala Rasoanaivo, un homme d'affaires local d'Antananarivo, a enregistré une nouvelle société nommée "Rasoanaivo Enterprises" au Lot II M 92 Antohomadinika. Son numéro est le +261 32 22 345 67, et son adresse électronique est [email protected]. Il a fourni son numéro de sécu 501-02-1234 pour l'enregistrement.
"""
labels = ["work", "booking number", "personally identifiable information", "driver licence", "person", "book", "full address", "company", "actor", "character", "email", "passport number", "Social Security Number", "phone number"]
entities = model.predict_entities(text, labels)
for entity in entities:
print(entity["text"], "=>", entity["label"])
Harilala Rasoanaivo => person
Rasoanaivo Enterprises => company
Lot II M 92 Antohomadinika => full address
+261 32 22 345 67 => phone number
[email protected] => email
501-02-1234 => Social Security Number
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