Unsupervised Part-Of-Speech Tagging

Unsupervised part-of-speech (POS) tagging is an important task in natural language processing, aiming to train models through unannotated corpora to automatically derive a set of POS tags and accurately label the words in the text by utilizing the definitions and contextual information of the words. This method does not require manually annotated data, effectively reducing annotation costs and improving annotation efficiency, and is widely applied in syntactic analysis, text mining, machine translation, and other fields under scenarios with scarce language resources.