explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2024-12-26 18:06:29 +03:00
Code Issues Packages Projects Releases Wiki Activity

Update pipelines section in v2 overview

Browse Source
This commit is contained in:
ines 2017-10-10 06:33:50 +02:00
parent e0a9b02b67
commit 9c96a6e131
1 changed files with 21 additions and 15 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

36
website/usage/v2.jade
View File

@ -102,30 +102,36 @@ p
+h(3, "features-pipelines") Improved processing pipelines +h(3, "features-pipelines") Improved processing pipelines
+aside-code("Example"). +aside-code("Example").
# Modify an existing pipeline # Set custom attributes
nlp = spacy.load('en') Doc.set_extension('my_attr', default=False)
nlp.pipeline.append(my_component) Token.set_extension('my_attr', getter=my_token_getter)
assert doc._.my_attr, token._.my_attr
# Register a factory to create a component # Add components to the pipeline
spacy.set_factory('my_factory', my_factory) my_component = lambda doc: doc
nlp = Language(pipeline=['my_factory', mycomponent]) nlp.add_pipe(my_component)
p p
| It's now much easier to #[strong customise the pipeline] with your own | It's now much easier to #[strong customise the pipeline] with your own
| components, functions that receive a #[code Doc] object, modify and | components: functions that receive a #[code Doc] object, modify and
| return it. If your component is stateful, you can define and register a | return it. Extensions let you write any
| factory which receives the shared #[code Vocab] object and returns a | #[strong attributes, properties and methods] to the #[code Doc],
|  component. spaCy's default components can be added to your pipeline by | #[code Token] and #[code Span]. You can add data, implement new
| using their string IDs. This way, you won't have to worry about finding | features, integrate other libraries with spaCy or plug in your own
| and implementing them – simply add #[code "tagger"] to the pipeline, | machine learning models.
| and spaCy will know what to do.
+image +image
include ../assets/img/pipeline.svg include ../assets/img/pipeline.svg
+infobox +infobox
| #[+label-inline API:] #[+api("language") #[code Language]] | #[+label-inline API:] #[+api("language") #[code Language]],
| #[+label-inline Usage:] #[+a("/usage/language-processing-pipeline") Processing text] | #[+api("doc#set_extension") #[code Doc.set_extension]],
| #[+api("span#set_extension") #[code Span.set_extension]],
| #[+api("token#set_extension") #[code Token.set_extension]]
| #[+label-inline Usage:]
| #[+a("/usage/processing-pipelines") Processing pipelines]
| #[+label-inline Code:]
| #[+src("/usage/examples#section-pipeline") Pipeline examples]
+h(3, "features-text-classification") Text classification +h(3, "features-text-classification") Text classification