Po Tagging

Part-of-speech (POS) tagging, the process of assigning grammatical tags to words in text, is crucial for various natural language processing tasks. Current research focuses on improving POS tagging accuracy, particularly for challenging domains like clinical speech and non-standardized languages, often employing transformer-based models like BERT and GPT, along with techniques like data augmentation and retrieval-augmented tagging. These advancements are significant for applications ranging from automated phenotype recognition in healthcare to enhancing multilingual speech recognition and improving keyword extraction, ultimately leading to more robust and accurate NLP systems across diverse contexts.