anchor.diff:  +infobox
       |  #[strong API:] #[+api("displacy") #[code displacy]]
       |  #[strong Usage:] #[+a("/docs/usage/visualizers") Visualizing spaCy]
  -
  -+h(3, "features-loading") Loading
  -
  -+aside-code("Example").
  -    nlp = spacy.load('en') # shortcut link
  -    nlp = spacy.load('en_core_web_sm') # package
  -    nlp = spacy.load('/path/to/en') # unicode path
  -    nlp = spacy.load(Path('/path/to/en')) # pathlib Path
  -
  -p
  -    |  The improved #[code spacy.load] makes loading models easier and more
  -    |  transparent. You can load a model by supplying its
  -    |  #[+a("/docs/usage/models#usage") shortcut link], the name of an installed
  -    |  #[+a("/docs/usage/saving-loading#generating") model package], a unicode
  -    |  path or a #[code Path]-like object. spaCy will try resolving the load
  -    |  argument in this order. The #[code path] keyword argument is now deprecated.
  -
  -p
  -    |  The #[code Language] class to initialise will be determined based on the
  -    |  model's settings. If no model is found, spaCy will let you know and won't
  -    |  just return an empty #[code Language] object anymore. If you want a blank
  -    |  language, you can always import the class directly, e.g.
  -    |  #[code from spacy.lang.en import English].
  -
  -+infobox
  -    |  #[strong API:] #[+api("spacy#load") #[code spacy.load]]
  -    |  #[strong Usage:] #[+a("/docs/usage/saving-loading") Saving and loading]
   
   +h(3, "features-language") Improved language data and lazy loading
   
  
positive.code:     |  and added more examples.
  
  +h(2, "features") New features
  
  +h(3, "features-displacy") displaCy visualizer with Jupyter support
  
  
negative.code:     |  complex regular expressions. The language data has also been tidied up
      |  and simplified. It's now also possible to overwrite the functions that
      |  compute lexical attributes like #[code like_num], and supply
      |  language-specific syntax iterators, e.g. to determine noun chunks. spaCy
      |  now also supports simple lookup-based lemmatization. The data is stored
      |  in a dictionary mapping a string to its lemma.
  
  +infobox
      |  #[strong API:] #[+api("language") #[code Language]]
      |  #[strong Code:] #[+src(gh("spaCy", "spacy/lang")) spacy/lang]
      |  #[strong Usage:] #[+a("/docs/usage/adding-languages") Adding languages]
  
  +h(3, "features-matcher") Revised matcher API
  