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55 lines
4.1 KiB
Markdown
55 lines
4.1 KiB
Markdown
Every language is different – and usually full of **exceptions and special
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cases**, especially amongst the most common words. Some of these exceptions are
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shared across languages, while others are **entirely specific** – usually so
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specific that they need to be hard-coded. The
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[`lang`](https://github.com/explosion/spaCy/tree/master/spacy/lang) module
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contains all language-specific data, organized in simple Python files. This
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makes the data easy to update and extend.
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The **shared language data** in the directory root includes rules that can be
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generalized across languages – for example, rules for basic punctuation, emoji,
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emoticons and single-letter abbreviations. The **individual language data** in a
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submodule contains rules that are only relevant to a particular language. It
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also takes care of putting together all components and creating the `Language`
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subclass – for example, `English` or `German`.
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> ```python
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> from spacy.lang.en import English
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> from spacy.lang.de import German
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>
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> nlp_en = English() # Includes English data
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> nlp_de = German() # Includes German data
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> ```
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<!-- TODO: upgrade graphic
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-->
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<!-- TODO: remove this table in favor of more specific Language.Defaults docs in linguistic features? -->
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| Name | Description |
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| ---------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| **Stop words**<br />[`stop_words.py`][stop_words.py] | List of most common words of a language that are often useful to filter out, for example "and" or "I". Matching tokens will return `True` for `is_stop`. |
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| **Tokenizer exceptions**<br />[`tokenizer_exceptions.py`][tokenizer_exceptions.py] | Special-case rules for the tokenizer, for example, contractions like "can't" and abbreviations with punctuation, like "U.K.". |
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| **Punctuation rules**<br />[`punctuation.py`][punctuation.py] | Regular expressions for splitting tokens, e.g. on punctuation or special characters like emoji. Includes rules for prefixes, suffixes and infixes. |
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| **Character classes**<br />[`char_classes.py`][char_classes.py] | Character classes to be used in regular expressions, for example, latin characters, quotes, hyphens or icons. |
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| **Lexical attributes**<br />[`lex_attrs.py`][lex_attrs.py] | Custom functions for setting lexical attributes on tokens, e.g. `like_num`, which includes language-specific words like "ten" or "hundred". |
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| **Syntax iterators**<br />[`syntax_iterators.py`][syntax_iterators.py] | Functions that compute views of a `Doc` object based on its syntax. At the moment, only used for [noun chunks](/usage/linguistic-features#noun-chunks). |
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| **Lemmatizer**<br />[`spacy-lookups-data`][spacy-lookups-data] | Lemmatization rules or a lookup-based lemmatization table to assign base forms, for example "be" for "was". |
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[stop_words.py]:
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https://github.com/explosion/spaCy/tree/master/spacy/lang/en/stop_words.py
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[tokenizer_exceptions.py]:
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https://github.com/explosion/spaCy/tree/master/spacy/lang/de/tokenizer_exceptions.py
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[punctuation.py]:
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https://github.com/explosion/spaCy/tree/master/spacy/lang/punctuation.py
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[char_classes.py]:
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https://github.com/explosion/spaCy/tree/master/spacy/lang/char_classes.py
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[lex_attrs.py]:
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https://github.com/explosion/spaCy/tree/master/spacy/lang/en/lex_attrs.py
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[syntax_iterators.py]:
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https://github.com/explosion/spaCy/tree/master/spacy/lang/en/syntax_iterators.py
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[spacy-lookups-data]: https://github.com/explosion/spacy-lookups-data
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