Named entity recognition project
In this set of small projects, we will try our NER techniques on a variety of different types of text that we have seen already in prior chapters, as well as some new text. For variety, will look for named entities in e-mail texts, board meeting minutes, IRC chat dialogue, and human-created summaries of IRC chat dialogue. With these different types of data sources, we will be able to see how writing style and content both affect the accuracy of the NER system.
A simple NER tool
Our first step is to write a simple named entity recognition program that will allow us to find and extract named entities from a text sample. We will take this program and point it at several different text samples in turn. The code and text files for this project are all available on the GitHub site for this book, at https://github.com/megansquire/masteringDM/tree/master/ch6.
The code we will write is a short Python program that uses the same NLTK library we introduced in Chapter 3...
