Summary
This chapter gave you details of spaCy’s linguistic features and how to use them. You learned about POS tagging and applications and learned about an important yet not-so-well-known and well-used feature of spaCy—dependency labels. Then, we discovered a famous NLU tool and concept: NER. We saw how to do named entity extraction, again via examples. We finalized this chapter with a handy tool for merging and splitting spans.
What’s next? In the next chapter, we will discover how to use these linguistic features to extract information using the Matcher, PhraseMatcher, and SpanRuler classes.
