anchor.diff:  +h(2, "disabling") Disabling the parser
   
   p
  -    |  The parser is loaded and enabled by default. If you don't need any of
  -    |  the syntactic information, you should disable the parser. Disabling the
  -    |  parser will make spaCy load and run much faster. Here's how to prevent
  -    |  the parser from being loaded:
  -
  -+code.
  -    nlp = spacy.load('en', parser=False)
  -
  -p
  -    |  If you need to load the parser, but need to disable it for specific
  -    |  documents, you can control its use with the #[code parse] keyword
  -    |  argument:
  -
  -+code.
  -    nlp = spacy.load('en')
  -    doc1 = nlp(u'Text I do want parsed.')
  -    doc2 = nlp(u"Text I don't want parsed", parse=False)
  +    |  In the #[+a("/docs/usage/models/available") default models], the parser
  +    |  is loaded and enabled as part of the
  +    |  #[+a("docs/usage/language-processing-pipelines") standard processing pipeline].
  +    |  If you don't need any of the syntactic information, you should disable
  +    |  the parser. Disabling the parser will make spaCy load and run much faster.
  +    |  If you want to load the parser, but need to disable it for specific
  +    |  documents, you can also control its use on the #[code nlp] object.
  +
  ++code.
  +    nlp = spacy.load('en', disable=['parser'])
  +    nlp = English().from_disk('/model', disable=['parser'])
  +    doc = nlp(u"I don't want parsed", disable=['parser'])
  +
  ++infobox("Important note: disabling pipeline components")
  +    .o-block
  +        |  Since spaCy v2.0 comes with better support for customising the
  +        |  processing pipeline components, the #[code parser] keyword argument
  +        |  has been replaced with #[code disable], which takes a list of
  +        |  #[+a("/docs/usage/language-processing-pipeline") pipeline component names].
  +        |  This lets you disable both default and custom components when loading
  +        |  a model, or initialising a Language class via
  +        |  #[+api("language-from_disk") #[code from_disk]].
  +    +code-new.
  +        nlp = spacy.load('en', disable=['parser'])
  +        doc = nlp(u"I don't want parsed", disable=['parser'])
  +    +code-old.
  +        nlp = spacy.load('en', parser=False)
  +        doc = nlp(u"I don't want parsed", parse=False)
  
positive.code:     |  #[strong Dep]: The syntactic relation connecting child to head.#[br]
      |  #[strong Head text]: The original text of the token head.#[br]
      |  #[strong Head POS]: The part-of-speech tag of the token head.#[br]
      |  #[strong Children]: ...
  
  +table(["Text", "Dep", "Head text", "Head POS", "Children"])
      - var style = [0, 1, 0, 1, 0]
  
negative.code:     |  spaCy features a fast and accurate syntactic dependency parser, and has
      |  a rich API for navigating the tree. The parser also powers the sentence
      |  boundary detection, and lets you iterate over base noun phrases, or
      |  "chunks". You can check whether a #[+api("doc") #[code Doc]] object has
      |  been parsed with the #[code doc.is_parsed] attribute, which returns a
      |  boolean value. If this attribute is #[code False], the default sentence
      |  iterator will raise an exception.
  
  +h(2, "noun-chunks") Noun chunks
      +tag-model("dependency parse")
  
  p
      |  Noun chunks are "base noun phrases" – flat phrases that have a noun as
      |  their head. You can think of noun chunks as a noun plus the words describing
      |  the noun – for example, "the lavish green grass" or "the world’s largest
      |  tech fund". To get the noun chunks in a document, simply iterate over
      |  #[+api("doc#noun_chunks") #[code Doc.noun_chunks]].
  
  +code("Example").
      nlp = spacy.load('en')
  