Book Image

Natural Language Processing: Python and NLTK

By : Jacob Perkins, Nitin Hardeniya, Deepti Chopra, Iti Mathur, Nisheeth Joshi
Book Image

Natural Language Processing: Python and NLTK

By: Jacob Perkins, Nitin Hardeniya, Deepti Chopra, Iti Mathur, Nisheeth Joshi

Overview of this book

Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it’s becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy. The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python. This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products: ? NTLK essentials by Nitin Hardeniya ? Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins ? Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur
Table of Contents (6 chapters)

Chapter 6. Semantic Analysis – Meaning Matters

Semantic analysis, or meaning generation is one of the tasks in NLP. It is defined as the process of determining the meaning of character sequences or word sequences. It may be used for performing the task of disambiguation.

This chapter will include the following topics:

  • NER
  • NER system using the HMM
  • Training NER using machine learning toolkits
  • NER using POS tagging
  • Generation of the synset id from Wordnet
  • Disambiguating senses using Wordnet

Introducing semantic analysis

NLP means performing computations on natural language. One of the steps performed while processing a natural language is semantic analysis. While analyzing an input sentence, if the syntactic structure of a sentence is built, then the semantic analysis of a sentence will be done. Semantic interpretation means mapping a meaning to a sentence. Contextual interpretation is mapping the logical form to the knowledge representation. The primitive or the basic unit of semantic...