Text – Anonymize node allows you to anonymize sensitive information from input text using pre-trained named entity recognition (NER) models. It replaces detected entities (like names or organizations) with a specified masking character.
| Input | Output |
|---|---|
| Text – Raw input for anonymization | Text – Anonymized version |
| Classifications – Optional filters |
How It Works
- Scans text for sensitive entities (names, organizations, etc.)
- Model Selection (Choose NER model based on language and domain)
- Replaces detected entities with your chosen masking character (Character used to replace entities, e.g., █ or *))
- Preserves overall text structure while protecting privacy
Configuration:
Example:
Input: John Smith is a patient at St. Mary’s Hospital.
Output: ████ █████ is a patient at ██████████████████.
Tutorial
Best Practices:
- Select an appropriate model for your content language and domain
- Use with preprocessor modules for optimal text handling
- Can be integrated into classification pipelines for comprehensive processing
