What is linguistic data annotation?

Linguistic data annotation is the process of labeling or tagging language data, such as text or speech, with relevant linguistic information. This can include marking parts of speech, named entities, syntactic structures, or semantic roles to help train and evaluate natural language processing (NLP) models. Annotators follow specific guidelines to ensure consistency and accuracy, making the data usable for machine learning tasks. Linguistic data annotation is essential for developing AI applications like chatbots, translation systems, and speech recognition software.