mirror of https://github.com/explosion/spaCy.git
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
from __future__ import unicode_literals
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import pytest
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@pytest.mark.models
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def test_nsubj(EN):
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sent = EN(u'A base phrase should be recognized.')
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base_nps = list(sent.noun_chunks)
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assert len(base_nps) == 1
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assert base_nps[0].string == 'A base phrase '
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@pytest.mark.models
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def test_coord(EN):
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sent = EN(u'A base phrase and a good phrase are often the same.')
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base_nps = list(sent.noun_chunks)
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assert len(base_nps) == 2
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assert base_nps[0].string == 'A base phrase '
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assert base_nps[1].string == 'a good phrase '
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@pytest.mark.models
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def test_pp(EN):
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sent = EN(u'A phrase with another phrase occurs')
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base_nps = list(sent.noun_chunks)
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assert len(base_nps) == 2
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assert base_nps[0].string == 'A phrase '
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assert base_nps[1].string == 'another phrase '
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@pytest.mark.models
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def test_merge_pp(EN):
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sent = EN(u'A phrase with another phrase occurs')
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nps = [(np[0].idx, np[-1].idx + len(np[-1]), np.lemma_, np[0].ent_type_) for np in sent.noun_chunks]
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for start, end, lemma, ent_type in nps:
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sent.merge(start, end, u'NP', lemma, ent_type)
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assert sent[0].string == 'A phrase '
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assert sent[1].string == 'with '
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assert sent[2].string == 'another phrase '
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assert sent[3].string == 'occurs'
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