A Survey of Part-of-Speech Tagging

Abstract

Part-of-Speech(POS) tagging, a fundamental task in natural language processing (NLP) that involves categorizing each word in a text into specific grammatical categories, is not only crucial for linguistic research but also serves as a prerequisite for more complex NLP applications such as syntactic analysis, entity recognition, and machine translation. This paper reveals the transition from the laborious process of manual annotation to the development of automated techniques, showcasing how the application of advanced deep learning (DL) and machine learning (ML) methods can enhance the efficiency and accuracy of POS tagging. Finally, the paper discusses the current challenges faced in POS tagging, along with corresponding solutions and potential future directions.