Entity Extraction using GAN

Entity extraction using Generative Adversarial Networks (GAN) is an advanced natural language processing technique designed to automatically identify and extract specific types of entity information from unstructured text. This method improves the accuracy and robustness of entity recognition through adversarial training between a generator and a discriminator, and it is widely applied in areas such as information retrieval, knowledge graph construction, and intelligent question-answering systems, effectively enhancing the usability and intelligence of data.