From aa5230546142810884321f2c15a59dace8454dba Mon Sep 17 00:00:00 2001 From: Ines Montani Date: Sun, 24 Feb 2019 18:45:39 +0100 Subject: [PATCH] Improve pipeline model and meta example [ci skip] --- website/docs/usage/processing-pipelines.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/website/docs/usage/processing-pipelines.md b/website/docs/usage/processing-pipelines.md index a39482c21..ab780485f 100644 --- a/website/docs/usage/processing-pipelines.md +++ b/website/docs/usage/processing-pipelines.md @@ -29,10 +29,10 @@ components. spaCy then does the following: > > ```json > { -> "name": "example_model", > "lang": "en", +> "name": "core_web_sm", > "description": "Example model for spaCy", -> "pipeline": ["tagger", "parser"] +> "pipeline": ["tagger", "parser", "ner"] > } > ``` @@ -51,11 +51,11 @@ components. spaCy then does the following: So when you call this... ```python -nlp = spacy.load("en") +nlp = spacy.load("en_core_web_sm") ``` -... the model tells spaCy to use the language `"en"` and the pipeline -`["tagger", "parser", "ner"]`. spaCy will then initialize +... the model's `meta.json` tells spaCy to use the language `"en"` and the +pipeline `["tagger", "parser", "ner"]`. spaCy will then initialize `spacy.lang.en.English`, and create each pipeline component and add it to the processing pipeline. It'll then load in the model's data from its data directory and return the modified `Language` class for you to use as the `nlp` object.