Скачать или смотреть Rule based tagging

Rule-based POS tagging assigns grammatical tags to words using a set of handcrafted linguistic rules. Instead of relying on probabilities or machine learning, it uses patterns such as word endings, prefixes, suffixes, capitalization, and the surrounding context to determine the correct tag. For example, a word ending in “-ly” is likely an adverb, or a word following a determiner is often a noun. Rule-based tagging is transparent and interpretable, but it requires extensive manual rule creation and may struggle with exceptions or ambiguous words. Despite its limitations, it remains an important foundational approach in NLP.