Po Tagger

Part-of-speech (POS) tagging automatically assigns grammatical tags (e.g., noun, verb, adjective) to words in text, a fundamental task in natural language processing. Current research focuses on improving tagging accuracy and efficiency, particularly in low-resource languages and specialized domains like finance, using models ranging from traditional machine learning algorithms to transformer-based architectures and leveraging techniques like instruction tuning and multimodal retrieval. These advancements enhance various NLP applications, including improved data findability in open government data portals, more effective news headline and tag generation, and more accurate automatic speech recognition.