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.
Questo esercizio fa parte del corso
Advanced NLP with spaCy
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
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)