Part of Speech

Part-of-speech (POS) tagging, the task of assigning grammatical labels (e.g., noun, verb) to words in text, is a fundamental step in many natural language processing (NLP) applications. Current research focuses on improving POS tagging accuracy across diverse languages, including low-resource and dialectal varieties, using advanced models like transformers, recurrent neural networks (RNNs), and conditional random fields (CRFs), often incorporating external knowledge sources such as named entities or morphological information. These advancements are crucial for enhancing the performance of downstream NLP tasks and enabling broader language technology access, particularly for under-resourced languages.