Part-of-Speech Tagging

Part-of-speech tagging is the natural-language-processing task of labelling each word in a text with its grammatical category — noun, verb, adjective, and so on — using context from surrounding words. Classical approaches use hidden Markov models with the Viterbi algorithm; modern approaches use neural sequence models. In accessibility research, POS tagging underpins predictive text systems that rank candidate words by how grammatically plausible they are in context, word-prediction engines in AAC devices, text-simplification pipelines aimed at cognitive-access users, and the grammatical scaffolding of automatic captioning and translation systems.