explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2025-02-03 13:14:11 +03:00
Code Issues Packages Projects Releases Wiki Activity

Fix docs example [ci skip]

Browse Source
This commit is contained in:
Ines Montani 2020-10-09 16:03:57 +02:00
parent 9fb3244672
commit 97ff090e49
1 changed files with 23 additions and 31 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

54
website/docs/usage/processing-pipelines.md
View File

@ -1403,9 +1403,9 @@ especially useful it you want to pass in a string instead of calling
This example shows the implementation of a pipeline component that fetches
country meta data via the [REST Countries API](https://restcountries.eu), sets
entity annotations for countries, merges entities into one token and sets custom
attributes on the `Doc`, `Span` and `Token` – for example, the capital,
latitude/longitude coordinates and even the country flag.
entity annotations for countries and sets custom attributes on the `Doc` and
`Span` – for example, the capital, latitude/longitude coordinates and even the
country flag.
```python
### {executable="true"}
@ -1427,54 +1427,46 @@ class RESTCountriesComponent:
# Set up the PhraseMatcher with Doc patterns for each country name
self.matcher = PhraseMatcher(nlp.vocab)
self.matcher.add("COUNTRIES", [nlp.make_doc(c) for c in self.countries.keys()])
# Register attribute on the Token. We'll be overwriting this based on
# Register attributes on the Span. We'll be overwriting this based on
# the matches, so we're only setting a default value, not a getter.
Token.set_extension("is_country", default=False)
Token.set_extension("country_capital", default=False)
Token.set_extension("country_latlng", default=False)
Token.set_extension("country_flag", default=False)
# Register attributes on Doc and Span via a getter that checks if one of
# the contained tokens is set to is_country == True.
Span.set_extension("is_country", default=None)
Span.set_extension("country_capital", default=None)
Span.set_extension("country_latlng", default=None)
Span.set_extension("country_flag", default=None)
# Register attribute on Doc via a getter that checks if the Doc
# contains a country entity
Doc.set_extension("has_country", getter=self.has_country)
Span.set_extension("has_country", getter=self.has_country)
def __call__(self, doc):
spans = [] # keep the spans for later so we can merge them afterwards
for _, start, end in self.matcher(doc):
# Generate Span representing the entity & set label
entity = Span(doc, start, end, label=self.label)
# Set custom attributes on entity. Can be extended with other data
# returned by the API, like currencies, country code, calling code etc.
entity._.set("is_country", True)
entity._.set("country_capital", self.countries[entity.text]["capital"])
entity._.set("country_latlng", self.countries[entity.text]["latlng"])
entity._.set("country_flag", self.countries[entity.text]["flag"])
spans.append(entity)
# Set custom attribute on each token of the entity
# Can be extended with other data returned by the API, like
# currencies, country code, flag, calling code etc.
for token in entity:
token._.set("is_country", True)
token._.set("country_capital", self.countries[entity.text]["capital"])
token._.set("country_latlng", self.countries[entity.text]["latlng"])
token._.set("country_flag", self.countries[entity.text]["flag"])
# Iterate over all spans and merge them into one token
with doc.retokenize() as retokenizer:
for span in spans:
retokenizer.merge(span)
# Overwrite doc.ents and add entity – be careful not to replace!
doc.ents = list(doc.ents) + spans
return doc # don't forget to return the Doc!
def has_country(self, tokens):
"""Getter for Doc and Span attributes. Since the getter is only called
when we access the attribute, we can refer to the Token's 'is_country'
def has_country(self, doc):
"""Getter for Doc attributes. Since the getter is only called
when we access the attribute, we can refer to the Span's 'is_country'
attribute here, which is already set in the processing step."""
return any([t._.get("is_country") for t in tokens])
return any([entity._.get("is_country") for entity in doc.ents])
nlp = English()
nlp.add_pipe("rest_countries", config={"label": "GPE"})
doc = nlp("Some text about Colombia and the Czech Republic")
print("Pipeline", nlp.pipe_names) # pipeline contains component name
print("Doc has countries", doc._.has_country) # Doc contains countries
for token in doc:
if token._.is_country:
print(token.text, token._.country_capital, token._.country_latlng, token._.country_flag)
print("Entities", [(e.text, e.label_) for e in doc.ents])
for ent in doc.ents:
if ent._.is_country:
print(ent.text, ent.label_, ent._.country_capital, ent._.country_latlng, ent._.country_flag)
```
In this case, all data can be fetched on initialization in one request. However,