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Fixing typos and errors!!
Fixed some typos and errors on the page.
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@ -43,7 +43,7 @@ p
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| #[code token.dep_].
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| #[code token.dep_].
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+aside-code("Example").
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+aside-code("Example").
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from spacy.symbols import DET
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from spacy.symbols import det
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the, dog = nlp(u'the dog')
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the, dog = nlp(u'the dog')
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assert the.dep == det
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assert the.dep == det
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assert the.dep_ == 'det'
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assert the.dep_ == 'det'
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@ -96,14 +96,14 @@ p
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print([w.text for w in apples.rights])
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print([w.text for w in apples.rights])
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# ['on']
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# ['on']
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assert apples.n_lefts == 2
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assert apples.n_lefts == 2
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assert apples.n_rights == 3
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assert apples.n_rights == 1
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from spacy.symbols import nsubj
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from spacy.symbols import nsubj
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doc = nlp(u'Credit and mortgage account holders must submit their requests within 30 days.')
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doc = nlp(u'Credit and mortgage account holders must submit their requests within 30 days.')
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root = [w for w in doc if w.head is w][0]
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root = [w for w in doc if w.head is w][0]
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subject = list(root.lefts)[0]
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subject = list(root.lefts)[0]
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for descendant in subject.subtree:
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for descendant in subject.subtree:
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assert subject.is_ancestor(descendant)
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assert subject.is_ancestor_of(descendant)
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from spacy.symbols import nsubj
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from spacy.symbols import nsubj
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doc = nlp(u'Credit and mortgage account holders must submit their requests.')
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doc = nlp(u'Credit and mortgage account holders must submit their requests.')
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@ -131,7 +131,7 @@ p
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p
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p
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| Finally, I often find the #[code .left_edge] and #[code right_edge]
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| Finally, I often find the #[code .left_edge] and #[code right_edge]
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| attributes especially useful. They give you the first and right tokens
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| attributes especially useful. They give you the first and last token
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| of the subtree. This is the easiest way to create a #[code Span] object
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| of the subtree. This is the easiest way to create a #[code Span] object
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| for a syntactic phrase — a useful operation.
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| for a syntactic phrase — a useful operation.
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@ -160,4 +160,4 @@ p
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+code.
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+code.
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nlp = spacy.load('en')
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nlp = spacy.load('en')
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doc1 = nlp(u'Text I do want parsed.')
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doc1 = nlp(u'Text I do want parsed.')
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doc2 = nlp(u'Text I don't want parsed', parser=False)
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doc2 = nlp(u"Text I don't want parsed", parse=False)
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