//- 💫 DOCS > USAGE > SPACY 101 > LANGUAGE DATA

p
    |  Every language is different – and usually full of
    |  #[strong exceptions and special cases], especially amongst the most
    |  common words. Some of these exceptions are shared across languages, while
    |  others are #[strong entirely specific] – usually so specific that they need
    |  to be hard-coded. The #[+src(gh("spaCy", "spacy/lang")) lang] module
    |  contains all language-specific data, organised in simple Python files.
    |  This makes the data easy to update and extend.

p
    |  The #[strong shared language data] in the directory root includes rules
    |  that can be generalised across languages – for example, rules for basic
    |  punctuation, emoji, emoticons, single-letter abbreviations and norms for
    |  equivalent tokens with different spellings, like #[code "] and
    |  #[code ”]. This helps the models make more accurate predictions.
    |  The #[strong individual language data] in a submodule contains
    |  rules that are only relevant to a particular language. It also takes
    |  care of putting together all components and creating the #[code Language]
    |  subclass – for example, #[code English] or #[code German].

+aside-code.
    from spacy.lang.en import English
    from spacy.lang.de import German

    nlp_en = English() # includes English data
    nlp_de = German() # includes German data

+image
    include ../../../assets/img/docs/language_data.svg
    .u-text-right
        +button("/assets/img/docs/language_data.svg", false, "secondary").u-text-tag View large graphic

+table(["Name", "Description"])
    +row
        +cell #[strong Stop words]#[br]
            |  #[+src(gh("spacy-dev-resources", "templates/new_language/stop_words.py")) stop_words.py]
        +cell
            |  List of most common words of a language that are often useful to
            |  filter out, for example "and" or "I". Matching tokens will
            |  return #[code True] for #[code is_stop].

    +row
        +cell #[strong Tokenizer exceptions]#[br]
            |  #[+src(gh("spacy-dev-resources", "templates/new_language/tokenizer_exceptions.py")) tokenizer_exceptions.py]
        +cell
            |  Special-case rules for the tokenizer, for example, contractions
            |  like "can't" and abbreviations with punctuation, like "U.K.".

    +row
        +cell #[strong Norm exceptions]
            |  #[+src(gh("spaCy", "spacy/lang/norm_exceptions.py")) norm_exceptions.py]
        +cell
            |  Special-case rules for normalising tokens to improve the model's
            |  predictions, for example on American vs. British spelling.

    +row
        +cell #[strong Punctuation rules]
            |  #[+src(gh("spaCy", "spacy/lang/punctuation.py")) punctuation.py]
        +cell
            |  Regular expressions for splitting tokens, e.g. on punctuation or
            |  special characters like emoji. Includes rules for prefixes,
            |  suffixes and infixes.

    +row
        +cell #[strong Character classes]
            |  #[+src(gh("spaCy", "spacy/lang/char_classes.py")) char_classes.py]
        +cell
            |  Character classes to be used in regular expressions, for example,
            |  latin characters, quotes, hyphens or icons.

    +row
        +cell #[strong Lexical attributes]
            |  #[+src(gh("spacy-dev-resources", "templates/new_language/lex_attrs.py")) lex_attrs.py]
        +cell
            |  Custom functions for setting lexical attributes on tokens, e.g.
            |  #[code like_num], which includes language-specific words like "ten"
            |  or "hundred".

    +row
        +cell #[strong Syntax iterators]
            |  #[+src(gh("spaCy", "spacy/lang/en/syntax_iterators.py")) syntax_iterators.py]
        +cell
            |  Functions that compute views of a #[code Doc] object based on its
            |  syntax. At the moment, only used for
            |  #[+a("/docs/usage/dependency-parse#noun-chunks") noun chunks].

    +row
        +cell #[strong Lemmatizer]
            |  #[+src(gh("spacy-dev-resources", "templates/new_language/lemmatizer.py")) lemmatizer.py]
        +cell
            |  Lemmatization rules or a lookup-based lemmatization table to
            |  assign base forms, for example "be" for "was".

    +row
        +cell #[strong Tag map]#[br]
            |  #[+src(gh("spacy-dev-resources", "templates/new_language/tag_map.py")) tag_map.py]
        +cell
            |  Dictionary mapping strings in your tag set to
            |  #[+a("http://universaldependencies.org/u/pos/all.html") Universal Dependencies]
            |  tags.

    +row
        +cell #[strong Morph rules]
            |  #[+src(gh("spaCy", "spacy/lang/en/morph_rules.py")) morph_rules.py]
        +cell
            |  Exception rules for morphological analysis of irregular words like
            |  personal pronouns.