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Update processing pipelines guide

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ines 2017-05-29 14:21:00 +02:00
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website/docs/usage/language-processing-pipeline.jade
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@ -187,13 +187,13 @@ p
| #[+a("/docs/usage/saving-loading#models-generating") model package] with
| a custom pipeline.
+h(2, "example1") Example: Custom sentence segmentation logic
+aside("Real-world examples")
| To see real-world examples of pipeline factories and components in action,
| you can have a look at the source of spaCy's built-in components, e.g.
| the #[+src(gh("spacy")) tagger], #[+src(gh("spacy")) parser] or
| #[+src(gh("spacy")) entity recognizer].
| the #[+api("tagger") #[code Tagger]], #[+api("parser") #[code Parser]] or
| #[+api("entityrecognizer") #[code EntityRecongnizer]].
+h(2, "example1") Example: Custom sentence segmentation logic
p
| Let's say you want to implement custom logic to improve spaCy's sentence
@ -318,8 +318,8 @@ p
| If you don't need a particular component of the pipeline – for
| example, the tagger or the parser, you can disable loading it. This can
| sometimes make a big difference and improve loading speed. Disabled
| component names can be provided to #[+api("spacy#load") #[code spacy.load]],
| #[+api("language#from_disk") #[code Language.from_disk]] or the
| component names can be provided to #[+api("spacy#load") #[code spacy.load()]],
| #[+api("language#from_disk") #[code Language.from_disk()]] or the
| #[code nlp] object itself as a list:
+code.