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Fix noun chunks test
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parent
69cdfc843e
commit
cc9c5dc7a3
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@ -1,15 +1,15 @@
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# coding: utf-8
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# coding: utf-8
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from __future__ import unicode_literals
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from __future__ import unicode_literals
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from ...attrs import HEAD, DEP
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from ....attrs import HEAD, DEP
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from ...symbols import nsubj, dobj, amod, nmod, conj, cc, root
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from ....symbols import nsubj, dobj, amod, nmod, conj, cc, root
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from ...syntax.iterators import english_noun_chunks
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from ....lang.en.syntax_iterators import SYNTAX_ITERATORS
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from ..util import get_doc
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from ...util import get_doc
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import numpy
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import numpy
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def test_doc_noun_chunks_not_nested(en_tokenizer):
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def test_en_noun_chunks_not_nested(en_tokenizer):
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text = "Peter has chronic command and control issues"
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text = "Peter has chronic command and control issues"
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heads = [1, 0, 4, 3, -1, -2, -5]
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heads = [1, 0, 4, 3, -1, -2, -5]
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deps = ['nsubj', 'ROOT', 'amod', 'nmod', 'cc', 'conj', 'dobj']
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deps = ['nsubj', 'ROOT', 'amod', 'nmod', 'cc', 'conj', 'dobj']
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@ -21,7 +21,7 @@ def test_doc_noun_chunks_not_nested(en_tokenizer):
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[HEAD, DEP],
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[HEAD, DEP],
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numpy.asarray([[1, nsubj], [0, root], [4, amod], [3, nmod], [-1, cc],
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numpy.asarray([[1, nsubj], [0, root], [4, amod], [3, nmod], [-1, cc],
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[-2, conj], [-5, dobj]], dtype='uint64'))
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[-2, conj], [-5, dobj]], dtype='uint64'))
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tokens.noun_chunks_iterator = english_noun_chunks
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tokens.noun_chunks_iterator = SYNTAX_ITERATORS['noun_chunks']
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word_occurred = {}
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word_occurred = {}
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for chunk in tokens.noun_chunks:
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for chunk in tokens.noun_chunks:
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for word in chunk:
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for word in chunk:
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