mirror of https://github.com/explosion/spaCy.git
Update tests
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# -*- coding: utf-8 -*-
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# -*- coding: utf-8 -*-
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import pytest
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import pytest
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import numpy
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import numpy
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@pytest.mark.models
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@pytest.mark.models
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class TestModelSanity:
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class TestModelSanity:
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"""
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"""
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This is to make sure the model works as expected. The tests make sure that values are properly set.
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This is to make sure the model works as expected. The tests make sure that
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Tests are not meant to evaluate the content of the output, only make sure the output is formally okay.
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values are properly set.
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"""
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Tests are not meant to evaluate the content of the output, only make sure
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the output is formally okay.
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"""
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@pytest.fixture(scope='class', params=['en','de'])
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def example(self, request, EN, DE):
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assert EN.entity != None
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assert DE.entity != None
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if request.param == 'en':
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doc = EN(u'There was a stranger standing at the big ' +
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u'street talking to herself.')
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elif request.param == 'de':
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doc = DE(u'An der großen Straße stand eine merkwürdige ' +
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u'Gestalt und führte Selbstgespräche.')
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return doc
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@pytest.fixture(scope='class', params=['en','de'])
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def test_tokenization(self, example):
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def example(self, request, EN, DE):
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# tokenization should split the document into tokens
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if request.param == 'en':
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assert len(example) > 1
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return EN(u'There was a stranger standing at the big street talking to herself.')
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elif request.param == 'de':
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return DE(u'An der großen Straße stand eine merkwürdige Gestalt und führte Selbstgespräche.')
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def test_tokenization(self, example):
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def test_tagging(self, example):
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# tokenization should split the document into tokens
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# if tagging was done properly, pos tags shouldn't be empty
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assert len(example) > 1
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assert example.is_tagged
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assert all( t.pos != 0 for t in example )
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assert all( t.tag != 0 for t in example )
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def test_tagging(self, example):
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def test_parsing(self, example):
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# if tagging was done properly, pos tags shouldn't be empty
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# if parsing was done properly
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assert example.is_tagged
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# - dependency labels shouldn't be empty
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assert all( t.pos != 0 for t in example )
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# - the head of some tokens should not be root
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assert all( t.tag != 0 for t in example )
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assert example.is_parsed
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assert all( t.dep != 0 for t in example )
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assert any( t.dep != i for i,t in enumerate(example) )
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def test_parsing(self, example):
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def test_ner(self, example):
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# if parsing was done properly
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# if ner was done properly, ent_iob shouldn't be empty
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# - dependency labels shouldn't be empty
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assert all([t.ent_iob != 0 for t in example])
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# - the head of some tokens should not be root
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assert example.is_parsed
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assert all( t.dep != 0 for t in example )
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assert any( t.dep != i for i,t in enumerate(example) )
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def test_ner(self, example):
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def test_vectors(self, example):
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# if ner was done properly, ent_iob shouldn't be empty
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# if vectors are available, they should differ on different words
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assert all( t.ent_iob != 0 for t in example )
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# this isn't a perfect test since this could in principle fail
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# in a sane model as well,
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# but that's very unlikely and a good indicator if something is wrong
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vector0 = example[0].vector
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vector1 = example[1].vector
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vector2 = example[2].vector
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assert not numpy.array_equal(vector0,vector1)
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assert not numpy.array_equal(vector0,vector2)
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assert not numpy.array_equal(vector1,vector2)
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def test_vectors(self, example):
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def test_probs(self, example):
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# if vectors are available, they should differ on different words
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# if frequencies/probabilities are okay, they should differ for
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# this isn't a perfect test since this could in principle fail in a sane model as well,
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# different words
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# but that's very unlikely and a good indicator if something is wrong
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# this isn't a perfect test since this could in principle fail
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vector0 = example[0].vector
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# in a sane model as well,
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vector1 = example[1].vector
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# but that's very unlikely and a good indicator if something is wrong
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vector2 = example[2].vector
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prob0 = example[0].prob
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assert not numpy.array_equal(vector0,vector1)
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prob1 = example[1].prob
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assert not numpy.array_equal(vector0,vector2)
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prob2 = example[2].prob
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assert not numpy.array_equal(vector1,vector2)
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assert not prob0 == prob1
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assert not prob0 == prob2
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def test_probs(self, example):
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assert not prob1 == prob2
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# if frequencies/probabilities are okay, they should differ for different words
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# this isn't a perfect test since this could in principle fail in a sane model as well,
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# but that's very unlikely and a good indicator if something is wrong
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prob0 = example[0].prob
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prob1 = example[1].prob
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prob2 = example[2].prob
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assert not prob0 == prob1
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assert not prob0 == prob2
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assert not prob1 == prob2
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@ -27,6 +27,7 @@ def test_overlap_issue118(EN):
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assert len(list(doc.ents)) == 0
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assert len(list(doc.ents)) == 0
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
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assert matches == [(ORG, 9, 11), (ORG, 10, 11)]
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assert matches == [(ORG, 9, 11), (ORG, 10, 11)]
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doc.ents = matches[:1]
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ents = list(doc.ents)
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ents = list(doc.ents)
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assert len(ents) == 1
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assert len(ents) == 1
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assert ents[0].label == ORG
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assert ents[0].label == ORG
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@ -54,6 +55,7 @@ def test_overlap_issue242():
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doc = nlp.tokenizer(u'There are different food safety standards in different countries.')
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doc = nlp.tokenizer(u'There are different food safety standards in different countries.')
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in nlp.matcher(doc)]
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in nlp.matcher(doc)]
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doc.ents += tuple(matches)
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food_safety, safety_standards = matches
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food_safety, safety_standards = matches
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assert food_safety[1] == 3
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assert food_safety[1] == 3
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assert food_safety[2] == 5
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assert food_safety[2] == 5
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@ -79,6 +81,7 @@ def test_overlap_reorder(EN):
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assert len(list(doc.ents)) == 0
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assert len(list(doc.ents)) == 0
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
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assert matches == [(ORG, 9, 11), (ORG, 10, 11)]
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assert matches == [(ORG, 9, 11), (ORG, 10, 11)]
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doc.ents = matches[:1]
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ents = list(doc.ents)
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ents = list(doc.ents)
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assert len(ents) == 1
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assert len(ents) == 1
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assert ents[0].label == ORG
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assert ents[0].label == ORG
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@ -103,6 +106,7 @@ def test_overlap_prefix(EN):
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assert len(list(doc.ents)) == 0
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assert len(list(doc.ents)) == 0
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
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doc.ents = matches[1:]
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assert matches == [(ORG, 9, 10), (ORG, 9, 11)]
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assert matches == [(ORG, 9, 10), (ORG, 9, 11)]
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ents = list(doc.ents)
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ents = list(doc.ents)
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assert len(ents) == 1
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assert len(ents) == 1
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@ -128,8 +132,9 @@ def test_overlap_prefix_reorder(EN):
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assert len(list(doc.ents)) == 0
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assert len(list(doc.ents)) == 0
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
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matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
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doc.ents += tuple(matches)[1:]
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assert matches == [(ORG, 9, 10), (ORG, 9, 11)]
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assert matches == [(ORG, 9, 10), (ORG, 9, 11)]
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ents = list(doc.ents)
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ents = doc.ents
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assert len(ents) == 1
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assert len(ents) == 1
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assert ents[0].label == ORG
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assert ents[0].label == ORG
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assert ents[0].start == 9
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assert ents[0].start == 9
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tokens = EN(u'Where rap essentially went mainstream, illustrated by seminal Public Enemy, Beastie Boys and L.L. Cool J. tracks.')
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tokens = EN(u'Where rap essentially went mainstream, illustrated by seminal Public Enemy, Beastie Boys and L.L. Cool J. tracks.')
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tokens = EN(u'''Charity and other short-term aid have buoyed them so far, and a tax-relief bill working its way through Congress would help. But the September 11 Victim Compensation Fund, enacted by Congress to discourage people from filing lawsuits, will determine the shape of their lives for years to come.\n\n''', entity=False)
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tokens = EN(u'''Charity and other short-term aid have buoyed them so far, and a tax-relief bill working its way through Congress would help. But the September 11 Victim Compensation Fund, enacted by Congress to discourage people from filing lawsuits, will determine the shape of their lives for years to come.\n\n''', entity=False)
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ents = EN.matcher(tokens)
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tokens.ents += tuple(EN.matcher(tokens))
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EN.entity(tokens)
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EN.entity(tokens)
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@ -45,6 +45,7 @@ def test_unit_end_gazetteer(EN):
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if len(list(doc.ents)) == 0:
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if len(list(doc.ents)) == 0:
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ents = matcher(doc)
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ents = matcher(doc)
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assert len(ents) == 1
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assert len(ents) == 1
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doc.ents += tuple(ents)
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EN.entity(doc)
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EN.entity(doc)
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assert list(doc.ents)[0].text == 'cal'
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assert list(doc.ents)[0].text == 'cal'
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EN.tagger(doc)
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EN.tagger(doc)
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assert len(doc.ents) == 0
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assert len(doc.ents) == 0
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doc = EN.tokenizer('I like java')
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doc = EN.tokenizer('I like java')
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matcher(doc)
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doc.ents += tuple(matcher(doc))
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assert len(doc.ents) == 1
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assert len(doc.ents) == 1
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EN.tagger(doc)
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EN.tagger(doc)
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EN.entity(doc)
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EN.entity(doc)
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