Entity Recognition
Entity recognition is a natural language processing task that involves identifying and classifying named entities in unstructured text into predefined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, and more. The goal of entity recognition is to extract structured information from unstructured text data, which can be used for various downstream applications such as information retrieval, question answering, sentiment analysis, and machine translation. Entity recognition is typically performed using machine learning algorithms such as rule-based systems, statistical models, and deep learning models, which are trained on annotated datasets. The performance of entity recognition systems is evaluated based on precision, recall, and F1-score metrics.
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