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fixed pizza example

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Kyle McDonald 2015-06-30 21:39:04 -04:00
parent 90e2059200
commit fc0780600e
1 changed files with 4 additions and 4 deletions
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docs/source/quickstart.rst
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@ -62,13 +62,13 @@ a convenient API:
>>> from spacy.en import English >>> from spacy.en import English
>>> nlp = English() >>> nlp = English()
>>> tokens = nlp(u'I ate the pizza with anchovies.') >>> tokens = nlp(u'I ate the pizza with anchovies.')
>>> pizza = tokens[3] >>> ate = tokens[1]
>>> (pizza.orth, pizza.orth_, pizza.head.lemma, pizza.head.lemma_) >>> (ate.orth, ate.orth_, ate.head.lemma, ate.head.lemma_)
... (14702, u'pizza', 14702, u'eat') ... (216, u'ate', 669, u'eat')
spaCy maps all strings to sequential integer IDs --- a common trick in NLP. spaCy maps all strings to sequential integer IDs --- a common trick in NLP.
If an attribute `Token.foo` is an integer ID, then `Token.foo_` is the string, If an attribute `Token.foo` is an integer ID, then `Token.foo_` is the string,
e.g. `pizza.orth` and `pizza.orth_` provide the integer ID and the string of e.g. `ate.orth` and `ate.orth_` provide the integer ID and the string of
the original orthographic form of the word. the original orthographic form of the word.
.. note:: en.English.__call__ is stateful --- it has an important **side-effect**. .. note:: en.English.__call__ is stateful --- it has an important **side-effect**.