Chapter 10: Putting Everything Together: Designing Your Chatbot with spaCy

In this chapter, you will use everything you have learned so far to design a chatbot. You will perform entity extraction, intent recognition, and context handling. You will use different ways of syntactic and semantic parsing, entity extraction, and text classification.

First, you'll explore the dataset we'll use to collect linguistic information about the utterances within it. Then, you'll perform entity extraction by combining the spaCy named entity recognition (NER) model and the spaCy Matcher class. After that, you'll perform intent recognition with two different techniques: a pattern-based method and statistical text classification with TensorFlow and Keras. You'll train a character-level LSTM to classify the utterance intents.

The final section is a section dedicated to sentence- and dialog-level semantics. You'll take a deep dive into semantic subjects such as anaphora...