Example use:
from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("PaDaS-Lab/gdpr-privacy-policy-ner", use_auth_token="AUTH_TOKEN")
model = AutoModelForTokenClassification.from_pretrained("PaDaS-Lab/gdpr-privacy-policy-ner", use_auth_token="AUTH_TOKEN")
ner = pipeline("ner", model=model, tokenizer=tokenizer)
example = "We do not knowingly collect personal information from anyone under 16. We may limit how we collect, use and store some of the information of EU or EEA users between ages 13 and 16."
results = ner(example)
print(results)
Classes:
Following are the 33 NER annotations in accordance with GDPR:
Abbreviation | Class |
---|---|
DC | Data Controller |
DP | Data Processor |
DPO | Data Protection Officer |
R | Recipient |
TP | Third Party |
A | Authority |
DS | Data Subject |
DSO | Data Source |
RP | Required Purpose |
NRP | Not-Required Purpose |
P | Processing |
NPD | Non-Personal Data |
PD | Personal Data |
OM | Organisational Measure |
TM | Technical Measure |
LB | Legal Basis |
CONS | Consent |
CONT | Contract |
LI | Legitimate Interest |
ADM | Automated Decision Making |
RET | Retention |
SEU | Scale EU |
SNEU | Scale Non-EU |
RI | Right |
DSR15 | Art. 15 Right of access by the data subject |
DSR16 | Art. 16 Right to rectification |
DSR17 | Art. 17 Right to erasure ("right to be forgotten") |
DSR18 | Art. 18 Right to restriction of processing |
DSR19 | Art. 19 Notification obligation regarding rectification or erasure of personal data or restriction of processing |
DSR20 | Art. 20 Right to data portability |
DSR21 | Art. 21 Right to object |
DSR22 | Art. 22 Automated individual decision-making, including profiling |
LC | Lodge Complaint |
Performance:
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