Part 10: Step by Step Guide to Master NLP – Named Entity Recognition

This article was published as a part of the Data Science Blogathon

Introduction

This article is part of an ongoing blog series on Natural Language Processing (NLP). In the previous article, we discussed semantic analysis, which is a level of NLP tasks. In that article, we discussed the techniques of Semantic analysis in which we discussed one technique named entity extraction, which is very important to understand in NLP.

So, In this article, we will deep dive into the entity extraction technique named Named Entity Recognition, which is a very useful component in the pipeline of NLP.

This is part-10 of the blog series on the Step by Step Guide to Natural Language Processing.

 

Table of Contents

1. What is Named Entity Recognition (NER)?

2. Different blocks present in a Typical NER model

3. Deep understanding of Named Entity Recognition with an example

4. How does Named Entity Recognition work?

5. Use-cases of Named Entity Recognition

6. How can I use NER?

 

 

 

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