In previous chapters, we talked about all the preprocessing steps we need, in order to work with any text corpus. You should now be comfortable about parsing any kind of text and should be able to clean it. You should be able to perform all text preprocessing, such as Tokenization, Stemming, and Stop Word removal on any text. You can perform and customize all the preprocessing tools to fit your needs. So far, we have mainly discussed generic preprocessing to be done with text documents. Now let's move on to more intense NLP preprocessing steps.
In this chapter, we will discuss what part of speech tagging is, and what the significance of POS is in the context of NLP applications. We will also learn how to use NLTK to extract meaningful information using tagging and various taggers used for NLP intense applications. Lastly, we will learn how NLTK can be used to tag a named entity. We will discuss in detail the various NLP taggers and also give a small snippet...