Summary
This chapter introduced you to a very handy and powerful feature of spaCy, spaCy's matcher classes. You learned how to do rule-based matching with linguistic and token-level features. You learned about the Matcher class, spaCy's rule-based matcher. We explored the Matcher class by using it with different token features, such as shape, lemma, text, and entity type.
Then, you learned about EntityRuler, another lifesaving class that you can achieve a lot with. You learned how to extract named entities with the EntityRuler class.
Finally, we put together what you've learned in this chapter and your previous knowledge and combined linguistic features with rule-based matching with several examples. You learned how to extract patterns, entities of specific formats, and entities specific to your domain.
With this chapter, you completed the linguistic features. In the next chapter, we'll dive into the world of statistical semantics via a very important concept...
