Summary of Giusberto: a Legal Language Model For Personal Data De-identification in Italian Court Of Auditors Decisions, by Giulio Salierno et al.
GiusBERTo: A Legal Language Model for Personal Data De-identification in Italian Court of Auditors Decisions
by Giulio Salierno, Rosamaria Bertè, Luca Attias, Carla Morrone, Dario Pettazzoni, Daniela Battisti
First submitted to arxiv on: 21 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces GiusBERTo, a BERT-based model designed to anonymize personal data in Italian legal documents. The model is trained on a large dataset of Court of Auditors decisions to recognize entities such as names, dates, and locations while retaining contextual relevance. GiusBERTo achieves 97% token-level accuracy on a held-out test set, providing an accurate and tailored solution for the Italian legal community to balance privacy and data protection. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary GiusBERTo is a new tool that helps keep personal information private in Italian court documents. It uses a special kind of artificial intelligence called BERT, which has been successful in many different tasks. GiusBERTo can identify names, dates, and places in documents, while still understanding the rest of what’s being said. This means it can help protect people’s privacy by hiding their information without losing the important context. |
Keywords
» Artificial intelligence » Bert » Token
