Doc container in spaCy
The first step of a spaCy text processing pipeline is to convert a given text string into a Doc container, which stores the processed text. In this exercise, you'll practice loading a spaCy model, creating an nlp() object, creating a Doc container and processing a text string that is available for you.
en_core_web_sm model is already downloaded.
This exercise is part of the course
Natural Language Processing with spaCy
Exercise instructions
- Load
en_core_web_smand create annlpobject. - Create a
doccontainer of thetextstring. - Create a list containing the text of each tokens in the
doccontainer.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load en_core_web_sm and create an nlp object
nlp = spacy.____(____)
# Create a Doc container for the text object
doc = ____(____)
# Create a list containing the text of each token in the Doc container
print([____ for ____ in ____])