A newer version of the Streamlit SDK is available:
1.40.1
title: CAROLL NER Demos
emoji: 🐠
colorFrom: purple
colorTo: pink
sdk: streamlit
sdk_version: 1.36.0
app_file: app.py
pinned: false
license: mit
German Legal NER:
This language model is trained on the Legal Entity Recognition dataset. We conducted a stratified 10-fold cross-validation to prevent overfitting. The results showed that their fine-tuned German BERT model outperformed the existing BiLSTM-CRF+ model, which was previously used on the same LER dataset. It is capable of annotating German legal data with the following 19 distinct labels:
| Abbreviation | Class |
|---|---|
| PER | Person |
| RR | Judge |
| AN | Lawyer |
| LD | Country |
| ST | City |
| STR | Street |
| LDS | Landscape |
| ORG | Organization |
| UN | Company |
| INN | Institution |
| GRT | Court |
| MRK | Brand |
| GS | Law |
| VO | Ordinance |
| EUN | European legal norm |
| VS | Regulation |
| VT | Contract |
| RS | Court decision |
| LIT | Legal literature |
This model is publicly available at PaDaS-Lab/gbert-legal-ner. We have also published a corresponding paper in this regard. Please cite this paper while using this model:
@conference{icaart23,
author={Harshil Darji. and Jelena Mitrović. and Michael Granitzer.},
title={German BERT Model for Legal Named Entity Recognition},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={723-728},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011749400003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}
GDPR Privacy Policy NER:
This language model is trained on a privacy policy dataset. This dataset is annotated using 33 labels that are in accordance with GDPR. This model aims to facilitate information extraction related to GDPR from a given privacy policy. It can also be further improved to verify whether a given privacy policy follows the GDPR regulations. As stated above, this model is capable of annotating given privacy policy-related text with the following 33 labels:
| 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 |
This model is publicly available at PaDaS-Lab/gdpr-privacy-policy-ner.