POS Tagging: A Review of Recent Techniques

Abstract

Part-of-Speech (POS) tagging is a fundamental task in Natural Language Pro-cessing (NLP) that involves assigning grammatical categories such as noun, verb, adjective, and adverb to words in a text. Accurate POS tagging serves as a critical preprocessing step for higher-level NLP applications, including syntactic parsing, machine translation, information retrieval, and sentiment analysis. Over the past decades, a wide range of POS tagging techniques has been proposed, by different research scholars from rule-based systems to da-ta-driven and neural approaches. This review provides a systematic examination of recent techniques, highlighting their core methodologies, strengths, limitations, and applicability to different languages.