Book Image

Python Natural Language Processing

Book Image

Python Natural Language Processing

Overview of this book

This book starts off by laying the foundation for Natural Language Processing and why Python is one of the best options to build an NLP-based expert system with advantages such as Community support, availability of frameworks and so on. Later it gives you a better understanding of available free forms of corpus and different types of dataset. After this, you will know how to choose a dataset for natural language processing applications and find the right NLP techniques to process sentences in datasets and understand their structure. You will also learn how to tokenize different parts of sentences and ways to analyze them. During the course of the book, you will explore the semantic as well as syntactic analysis of text. You will understand how to solve various ambiguities in processing human language and will come across various scenarios while performing text analysis. You will learn the very basics of getting the environment ready for natural language processing, move on to the initial setup, and then quickly understand sentences and language parts. You will learn the power of Machine Learning and Deep Learning to extract information from text data. By the end of the book, you will have a clear understanding of natural language processing and will have worked on multiple examples that implement NLP in the real world.
Table of Contents (13 chapters)

Handling ambiguity

When we jump into semantic analysis, we may find there are many cases that are too ambiguous for an NLP system to handle. In these cases, we need to know what kinds of ambiguity exist and how we can handle them.

Ambiguity is one of the areas of NLP and cognitive sciences that doesn't have a well-defined solution. Sometimes, sentences are so complex and ambiguous that only the speaker can define the original or definite meaning of the sentence.

A word, phrase, or sentence is ambiguous if it has more than one meaning. If we consider word light,than it can mean not very heavy or not very dark. This is word level ambiguity. The phrase porcelain egg container is structure level ambiguity. So, here we will see different types of ambiguities in NLP .

First, let's see the types of ambiguity, and then see how to handle them by using the means that are available...