Version
AIAnonymizer
| This component is currently in the incubation phase. Although it is available for use, it is under active development and may be subject to changes. We welcome feedback and encourage users to explore its capabilities. |
Short description
The AIAnonymizer lets you run a token classification model (preferably a PII detection model such as Piiranha - see CloverDX Marketplace) and mask identified tokens in the output.
This component behaves just like AITokenClassifier but with the added functionality of masking (anonymizing) tokens identified by the model above configured thresholds.
| Same input metadata | Sorted inputs | Inputs | Outputs | Each to all outputs | Java | CTL | Auto-propagated metadata |
|---|---|---|---|---|---|---|---|
- |
⨯ |
1 |
1 |
⨯ |
⨯ |
⨯ |
✓ |
Ports
| Port type | Number | Required | Description | Metadata |
|---|---|---|---|---|
Input |
1 |
✓ |
The text(s) to classify |
At least one |
Output |
1 |
✓ |
Copy of the input data with anonymized texts + token classification result |
Any |
Metadata
AIAnonymizer propagates input metadata to output.
AIAnonymizer attributes
| Attribute | Req | Description | Possible values |
|---|---|---|---|
Model |
|||
Server model |
Recommended: Use a model installed as a library on the CloverDX Server. Check CloverDX Marketplace for available ready-to-use models. This is a more convenient alternative to Classification model directory. |
||
Classification model directory |
Path to the machine learning model directory. It is required unless Server model is defined. |
||
Model name |
no |
A read-only field displaying name defined in model configuration files (if available). |
|
Device |
yes |
The device to run the model – either processor (CPU) or graphics card (GPU). You must set the device the model is designed for. GPU models are much faster but you need a specialized hardware to use them. |
CPU (default) | GPU |
Model arguments |
no |
Configuration arguments for the model. See documentation of your particular model. |
|
Tokenizer arguments |
no |
Configuration arguments for the tokenizer. See documentation of your particular model. |
|
Translator arguments |
no |
Configuration arguments for the translator. See documentation of your particular model. |
|
Input / output parameters |
|||
Fields to anonymize |
yes |
List of |
|
Anonymize classes and thresholds |
List of token classes who shall be anonymized. The classes are model-dependent; you can use only some of them, but you cannot add classes unknown to the model. The thresholds define the minimum score at which the particular token is anonymized – it is masked if at least one class reaches its threshold. |
||
Mask character |
no |
The character used for masking characters of the anonymized tokens. |
|
Anonymization information |
no |
An output field which will store the analysis results. It must be of variant type. If the field already contains some analysis, the analyses are merged, so that you can concatenate several AI components and use their combined output. |
|
Batch size |
no |
Number of records processed by model together. |
an integer number |
Error handling |
|||
Token overflow policy |
no |
Specifies behavior when some input text cannot be encoded because it exceeds the model-specific maximum length. The strict policy causes the component to fail while lenient just logs a warning and truncates the input. |
strict (default) | lenient |
Compatibility
| Version | Compatibility notice |
|---|---|
7.1.0 |
AIAnonymizer is available since CloverDX version 7.1. |