Using SpaCy
SpaCy is a Python library for Natural Language Processing (NLP) such as tokenization, named entity recognition with pre-trained models for several languages.
Documentation for SpaCy is available at https://spacy.io/
Installing SpaCy
In a
code environment
, you need to install the
spacy
package.
To add a specific pre-trained model, you can add the URL of the pip package for that model, as specified in the Installation via pip page of the SpaCy documentation.
For example for the English model, your code env’s Requested Packages could be:
spacy
https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.0/en_core_web_sm-2.2.0.tar.gz
See SpaCy’s Models page for a list of languages.
Using SpaCy models
In a python notebook or recipe (using the aforementioned code environment), you can then
import
spacy
and use
spacy.load
with the model package name:
import spacy
nlp = spacy.load("en_core_web_sm")
doc = nlp(u"This is an example sentence.")