Components with extensions
Extension attributes are especially powerful if they're combined with custom pipeline components. In this exercise, you'll write a pipeline component that finds country names and a custom extension attribute that returns a country's capital, if available.
The nlp object has already been created and the Span class is already imported. A phrase matcher with all countries is available as the variable matcher. A dictionary of countries mapped to their capital cities is available as the variable capitals.
Cet exercice fait partie du cours
Advanced NLP with spaCy
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
def countries_component(doc):
# Create an entity Span with the label 'GPE' for all matches
doc.ents = [____(____, ____, ____, label=____)
for match_id, start, end in matcher(doc)]
return doc
# Add the component to the pipeline
____.____(____)
print(nlp.pipe_names)