langchain_experimental.data_anonymizer.deanonymizer_mapping.create_anonymizer_mapping¶
- langchain_experimental.data_anonymizer.deanonymizer_mapping.create_anonymizer_mapping(original_text: str, analyzer_results: List[RecognizerResult], anonymizer_results: EngineResult, is_reversed: bool = False) Dict[str, Dict[str, str]][source]¶
Creates or updates the mapping used to anonymize and/or deanonymize text.
This method exploits the results returned by the analysis and anonymization processes.
If is_reversed is True, it constructs a mapping from each original entity to its anonymized value.
If is_reversed is False, it constructs a mapping from each anonymized entity back to its original text value.
If there are multiple entities of the same type, the mapping will include a count to differentiate them. For example, if there are two names in the input text, the mapping will include NAME_1 and NAME_2.
Example of mapping: {
- “PERSON”: {
“<original>”: “<anonymized>”, “John Doe”: “Slim Shady”
}, “PHONE_NUMBER”: {
“111-111-1111”: “555-555-5555”
}