mirror of
https://github.com/explosion/spaCy.git
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215 lines
7.1 KiB
Python
215 lines
7.1 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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import re
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from spacy.matcher import Matcher, DependencyTreeMatcher
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from spacy.tokens import Doc
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from ..util import get_doc
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@pytest.fixture
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def matcher(en_vocab):
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rules = {'JS': [[{'ORTH': 'JavaScript'}]],
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'GoogleNow': [[{'ORTH': 'Google'}, {'ORTH': 'Now'}]],
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'Java': [[{'LOWER': 'java'}]]}
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matcher = Matcher(en_vocab)
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for key, patterns in rules.items():
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matcher.add(key, None, *patterns)
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return matcher
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def test_matcher_from_api_docs(en_vocab):
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matcher = Matcher(en_vocab)
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pattern = [{'ORTH': 'test'}]
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assert len(matcher) == 0
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matcher.add('Rule', None, pattern)
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assert len(matcher) == 1
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matcher.remove('Rule')
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assert 'Rule' not in matcher
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matcher.add('Rule', None, pattern)
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assert 'Rule' in matcher
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on_match, patterns = matcher.get('Rule')
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assert len(patterns[0])
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def test_matcher_from_usage_docs(en_vocab):
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text = "Wow 😀 This is really cool! 😂 😂"
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doc = Doc(en_vocab, words=text.split(' '))
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pos_emoji = ['😀', '😃', '😂', '🤣', '😊', '😍']
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pos_patterns = [[{'ORTH': emoji}] for emoji in pos_emoji]
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def label_sentiment(matcher, doc, i, matches):
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match_id, start, end = matches[i]
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if doc.vocab.strings[match_id] == 'HAPPY':
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doc.sentiment += 0.1
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span = doc[start : end]
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token = span.merge()
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token.vocab[token.text].norm_ = 'happy emoji'
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matcher = Matcher(en_vocab)
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matcher.add('HAPPY', label_sentiment, *pos_patterns)
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matches = matcher(doc)
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assert doc.sentiment != 0
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assert doc[1].norm_ == 'happy emoji'
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def test_matcher_len_contains(matcher):
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assert len(matcher) == 3
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matcher.add('TEST', None, [{'ORTH': 'test'}])
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assert 'TEST' in matcher
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assert 'TEST2' not in matcher
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def test_matcher_no_match(matcher):
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doc = Doc(matcher.vocab, words=["I", "like", "cheese", "."])
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assert matcher(doc) == []
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def test_matcher_match_start(matcher):
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doc = Doc(matcher.vocab, words=["JavaScript", "is", "good"])
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assert matcher(doc) == [(matcher.vocab.strings['JS'], 0, 1)]
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def test_matcher_match_end(matcher):
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words = ["I", "like", "java"]
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doc = Doc(matcher.vocab, words=words)
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assert matcher(doc) == [(doc.vocab.strings['Java'], 2, 3)]
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def test_matcher_match_middle(matcher):
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words = ["I", "like", "Google", "Now", "best"]
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doc = Doc(matcher.vocab, words=words)
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assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], 2, 4)]
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def test_matcher_match_multi(matcher):
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words = ["I", "like", "Google", "Now", "and", "java", "best"]
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doc = Doc(matcher.vocab, words=words)
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assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], 2, 4),
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(doc.vocab.strings['Java'], 5, 6)]
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def test_matcher_empty_dict(en_vocab):
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"""Test matcher allows empty token specs, meaning match on any token."""
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matcher = Matcher(en_vocab)
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doc = Doc(matcher.vocab, words=["a", "b", "c"])
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matcher.add('A.C', None, [{'ORTH': 'a'}, {}, {'ORTH': 'c'}])
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matches = matcher(doc)
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assert len(matches) == 1
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assert matches[0][1:] == (0, 3)
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matcher = Matcher(en_vocab)
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matcher.add('A.', None, [{'ORTH': 'a'}, {}])
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matches = matcher(doc)
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assert matches[0][1:] == (0, 2)
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def test_matcher_operator_shadow(en_vocab):
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matcher = Matcher(en_vocab)
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doc = Doc(matcher.vocab, words=["a", "b", "c"])
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pattern = [{'ORTH': 'a'}, {"IS_ALPHA": True, "OP": "+"}, {'ORTH': 'c'}]
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matcher.add('A.C', None, pattern)
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matches = matcher(doc)
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assert len(matches) == 1
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assert matches[0][1:] == (0, 3)
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def test_matcher_match_zero(matcher):
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words1 = 'He said , " some words " ...'.split()
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words2 = 'He said , " some three words " ...'.split()
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pattern1 = [{'ORTH': '"'},
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{'OP': '!', 'IS_PUNCT': True},
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{'OP': '!', 'IS_PUNCT': True},
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{'ORTH': '"'}]
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pattern2 = [{'ORTH': '"'},
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{'IS_PUNCT': True},
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{'IS_PUNCT': True},
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{'IS_PUNCT': True},
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{'ORTH': '"'}]
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matcher.add('Quote', None, pattern1)
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doc = Doc(matcher.vocab, words=words1)
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assert len(matcher(doc)) == 1
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doc = Doc(matcher.vocab, words=words2)
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assert len(matcher(doc)) == 0
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matcher.add('Quote', None, pattern2)
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assert len(matcher(doc)) == 0
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def test_matcher_match_zero_plus(matcher):
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words = 'He said , " some words " ...'.split()
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pattern = [{'ORTH': '"'},
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{'OP': '*', 'IS_PUNCT': False},
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{'ORTH': '"'}]
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matcher = Matcher(matcher.vocab)
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matcher.add('Quote', None, pattern)
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doc = Doc(matcher.vocab, words=words)
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assert len(matcher(doc)) == 1
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def test_matcher_match_one_plus(matcher):
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control = Matcher(matcher.vocab)
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control.add('BasicPhilippe', None, [{'ORTH': 'Philippe'}])
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doc = Doc(control.vocab, words=['Philippe', 'Philippe'])
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m = control(doc)
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assert len(m) == 2
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matcher.add('KleenePhilippe', None, [{'ORTH': 'Philippe', 'OP': '1'},
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{'ORTH': 'Philippe', 'OP': '+'}])
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m = matcher(doc)
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assert len(m) == 1
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def test_matcher_any_token_operator(en_vocab):
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"""Test that patterns with "any token" {} work with operators."""
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matcher = Matcher(en_vocab)
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matcher.add('TEST', None, [{'ORTH': 'test'}, {'OP': '*'}])
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doc = Doc(en_vocab, words=['test', 'hello', 'world'])
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matches = [doc[start:end].text for _, start, end in matcher(doc)]
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assert len(matches) == 3
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assert matches[0] == 'test'
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assert matches[1] == 'test hello'
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assert matches[2] == 'test hello world'
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@pytest.fixture
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def text():
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return u"The quick brown fox jumped over the lazy fox"
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@pytest.fixture
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def heads():
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return [3,2,1,1,0,-1,2,1,-3]
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@pytest.fixture
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def deps():
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return ['det', 'amod', 'amod', 'nsubj', 'prep', 'pobj', 'det', 'amod']
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@pytest.fixture
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def dependency_tree_matcher(en_vocab):
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is_brown_yellow = lambda text: bool(re.compile(r'brown|yellow|over').match(text))
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IS_BROWN_YELLOW = en_vocab.add_flag(is_brown_yellow)
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pattern1 = [
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{'SPEC': {'NODE_NAME': 'fox'}, 'PATTERN': {'ORTH': 'fox'}},
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{'SPEC': {'NODE_NAME': 'q', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'},'PATTERN': {'LOWER': u'quick'}},
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{'SPEC': {'NODE_NAME': 'r', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'}, 'PATTERN': {IS_BROWN_YELLOW: True}}
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]
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pattern2 = [
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{'SPEC': {'NODE_NAME': 'jumped'}, 'PATTERN': {'ORTH': 'jumped'}},
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{'SPEC': {'NODE_NAME': 'fox', 'NBOR_RELOP': '>', 'NBOR_NAME': 'jumped'},'PATTERN': {'LOWER': u'fox'}},
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{'SPEC': {'NODE_NAME': 'over', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'}, 'PATTERN': {IS_BROWN_YELLOW: True}}
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]
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matcher = DependencyTreeMatcher(en_vocab)
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matcher.add('pattern1', None, pattern1)
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matcher.add('pattern2', None, pattern2)
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return matcher
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def test_dependency_tree_matcher_compile(dependency_tree_matcher):
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assert len(dependency_tree_matcher) == 2
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def test_dependency_tree_matcher(dependency_tree_matcher,text,heads,deps):
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doc = get_doc(dependency_tree_matcher.vocab,text.split(),heads=heads,deps=deps)
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matches = dependency_tree_matcher(doc)
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assert len(matches) == 2
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