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Adjusts the reliability score of extracted data based on surrounding textual context and metadata.
Distinct from Confidence Scoring: Adds context-awareness to general extraction confidence scoring
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Awesome Contextual GitHub Repositories
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- microsoft/presidio
microsoft/presidio
6,995Ver en GitHubPresidio is a PII detection and anonymization framework designed to identify and mask personally identifiable information in text. It functions as a PII recognition pipeline and a data masking engine, using a combination of machine learning, regular expressions, and rule-based logic to locate sensitive entities. The system acts as an NER model orchestrator, allowing for the integration of external named entity recognition models and PII detectors to support multi-language privacy scrubbing. It employs a plugin-based recognizer architecture that can be extended with custom recognizers, deny-li
Uses surrounding keywords and metadata to refine the probability of PII detection and reduce false positives.
Pythonanonymizationdata-anonymizationdata-masking
