Chapter 6: Putting Everything Together: Semantic Parsing with spaCy
This is a purely hands-on section. In this chapter, we will apply what we have learned hitherto to Airline Travel Information System (ATIS), a well-known airplane ticket reservation system dataset. First of all, we will get to know our dataset and make the basic statistics. As the first natural language understanding (NLU) task, we will extract the named entities with two different methods, with spaCy Matcher, and by walking on the dependency tree.
The next task is to determine the intent of the user utterance. We will explore intent recognition in different ways, too: by extracting the verbs and their direct objects, by using wordlists, and by walking on the dependency tree ...
Get Mastering spaCy now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
