Hottest Named Entity Recognition (NER) models (Subcategory)

Top Hottest 14 Models for Named Entity Recognition (NER) · 3/20/2025

Named Entity Recognition (NER) is a subcategory of Natural Language Processing (NLP) that identifies and categorizes named entities in unstructured text into predefined categories such as names, locations, organizations, and dates. Key features include tokenization, part-of-speech tagging, and machine learning algorithms. Common applications include information extraction, sentiment analysis, and question answering. Notable advancements include the development of deep learning-based models such as recurrent neural networks (RNNs) and transformers, which have significantly improved NER performance, achieving state-of-the-art results in various benchmarks and enabling applications in areas like text summarization and entity disambiguation.