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  • Pozycja
    Anonymizer for Polish Language
    (Wydawnictwo Politechniki Łódzkiej, 2023) Walkowiak, Tomasz; Gniewkowski, Mateusz; Pogoda, Michał; Ropiak, Norbert
    Researchers and enterprises require anonymization of unstructured text. This is not only due to the GDPR regulation, but also due to the increasing use of large language models (LLMs) such as GPT-3, where there is growing concern about the privacy and security risks associated with these models. The texts to be processed by such models need to be anonymized beforehand, and very often they need to be anonymized at the data providers’ premises rather than at the machine learning teams. In this paper, we present an effective anonymization pipeline for Polish. It provides a modular and configurable solution that employs different modes, including the challenging pseudo-anonymization mode in languages with complex inflectional systems. The system can be easily integrated with existing systems and deployed in different environments using a microservices architecture solution with a REST interface.