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Natural Language Processing with Java

Natural Language Processing with Java

By : Richard M. Reese
2 (3)
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Natural Language Processing with Java

Natural Language Processing with Java

2 (3)
By: Richard M. Reese

Overview of this book

Natural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes. You’ll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you’ll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You’ll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more. By the end of this book, you’ll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications.
Table of Contents (14 chapters)
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Building a new dataset with the NER annotation tool

There are many annotation tools available in different forms. Some are standalone and can be configured or installed on a local machine, some are cloud-based, some are free, and some are paid. In this section, we will focus on free annotation tools, get an idea of how to use them, and see what we can achieve with annotation.

To see how we can use annotations to create a dataset, we will look at these tools:

  • brat
  • Stanford Annotator

brat stands for brat rapid annotation tool and can be found at http://brat.nlplab.org/index.html. It can be used online or offline. Installing it on your local machine is simple: follow the steps listed at http://brat.nlplab.org/installation.html. Once installed and running, open the browser. You need to create a text1.txt file in the data/test directory with the following...

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