An Introduction To Part-Of-Speech Tagging: What It Is And How You Can Use It In Natural Language Processing
Natural language processing (NLP) is the practice of analysing written and spoken language to extract meaningful insights from text. Part-of-speech (POS) tagging is a crucial part of NLP that helps identify the function of each word in a sentence or phrase. In this article, we will explore what POS tagging is, how it works, and how you can use it in your own projects.
What is Part-Of-Speech (POS) Tagging?
Part-of-speech tagging is the process of assigning a part of speech to each word in a sentence. The most common parts of speech are noun, verb, adjective, adverb, pronoun, preposition, and conjunction. There are also a few less common ones, such as interjection and article.
There are several different algorithms that can be used for POS tagging, but the most common one is the hidden Markov model. This algorithm looks at a sequence of words and uses statistical information to decide which part of speech each word is likely to be.
POS tagging can be used for a variety of tasks in natural language processing, including text classification and information extraction. It can also be used to improve the accuracy of other NLP tasks, such as parsing and machine…
