mirror of https://github.com/explosion/spaCy.git
45 lines
4.1 KiB
ReStructuredText
45 lines
4.1 KiB
ReStructuredText
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=========
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Reference
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=========
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spaCy is a suite of natural language processing tools, arranged into
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a pipeline. It is substantially more opinionated than most similar libraries,
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which often give users the choice of multiple models that compute the same annotation.
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spaCy's philosophy is to just have one --- the best one. Our perspective is that
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the redundant options are really only useful to researchers, who need to replicate
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some prior work exactly.
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Being opinionated allows us to keep the library small, fast, and up-to-date.
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Below is a summary table showing every class in spaCy, where it is implemented,
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the basic usage, and a link to its documentation.
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Class name | Implemented in | Getting | Using | Documentation |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| English | spacy/en/__init__.py | nlp = English() | tokens = nlp(u'Some text') | processing.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Doc | spacy/doc.pyx | doc = nlp(text) | token = doc[10] | accessing/doc.rst|
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Token | spacy/token.pyx | token = doc[10] | token.head.repvec | accessing.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Span | spacy/span.pyx | sent = list(doc.sents)[0] | token = sent[0] | accessing.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Vocab | spacy/vocab.pyx | nlp.vocab | nlp.vocab[u'word'] | lookup/vocab.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| StringStore | spacy/strings.pyx | nlp.vocab.strings | nlp.vocab.strings[u'word'] | lookup/token.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Tokenizer | spacy/tokenizer.pyx | nlp.tokenizer | tokens = nlp.tokenizer(text) | processing.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| EnPosTagger | spacy/en/pos.pyx | nlp.tagger | nlp.tagger(tokens) | processing.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Parser | spacy/syntax/parser.pyx | nlp.parser | nlp.parser(tokens) | processing.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Lexeme | spacy/lexeme.pyx | lex = nlp.vocab[u'word'] | lex.repvec | lookup.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Lemmatizer | spacy/en/lemmatizer.py | | | misc.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| GoldParse | spacy/gold.pyx | | | misc.rst |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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| Scorer | spacy/scorer.py | | | |
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+-------------+--------------------------+---------------------------+------------------------------+------------------+
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