mirror of https://github.com/explosion/spaCy.git
510 lines
18 KiB
Python
510 lines
18 KiB
Python
import pytest
|
|
import warnings
|
|
import srsly
|
|
from mock import Mock
|
|
|
|
from spacy.lang.en import English
|
|
from spacy.matcher import PhraseMatcher, Matcher
|
|
from spacy.tokens import Doc, Span
|
|
from spacy.vocab import Vocab
|
|
|
|
|
|
from ..util import make_tempdir
|
|
|
|
|
|
@pytest.mark.issue(3248)
|
|
def test_issue3248_1():
|
|
"""Test that the PhraseMatcher correctly reports its number of rules, not
|
|
total number of patterns."""
|
|
nlp = English()
|
|
matcher = PhraseMatcher(nlp.vocab)
|
|
matcher.add("TEST1", [nlp("a"), nlp("b"), nlp("c")])
|
|
matcher.add("TEST2", [nlp("d")])
|
|
assert len(matcher) == 2
|
|
|
|
|
|
@pytest.mark.issue(3331)
|
|
def test_issue3331(en_vocab):
|
|
"""Test that duplicate patterns for different rules result in multiple
|
|
matches, one per rule.
|
|
"""
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("A", [Doc(en_vocab, words=["Barack", "Obama"])])
|
|
matcher.add("B", [Doc(en_vocab, words=["Barack", "Obama"])])
|
|
doc = Doc(en_vocab, words=["Barack", "Obama", "lifts", "America"])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 2
|
|
match_ids = [en_vocab.strings[matches[0][0]], en_vocab.strings[matches[1][0]]]
|
|
assert sorted(match_ids) == ["A", "B"]
|
|
|
|
|
|
@pytest.mark.issue(3972)
|
|
def test_issue3972(en_vocab):
|
|
"""Test that the PhraseMatcher returns duplicates for duplicate match IDs."""
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("A", [Doc(en_vocab, words=["New", "York"])])
|
|
matcher.add("B", [Doc(en_vocab, words=["New", "York"])])
|
|
doc = Doc(en_vocab, words=["I", "live", "in", "New", "York"])
|
|
matches = matcher(doc)
|
|
|
|
assert len(matches) == 2
|
|
|
|
# We should have a match for each of the two rules
|
|
found_ids = [en_vocab.strings[ent_id] for (ent_id, _, _) in matches]
|
|
assert "A" in found_ids
|
|
assert "B" in found_ids
|
|
|
|
|
|
@pytest.mark.issue(4002)
|
|
def test_issue4002(en_vocab):
|
|
"""Test that the PhraseMatcher can match on overwritten NORM attributes."""
|
|
matcher = PhraseMatcher(en_vocab, attr="NORM")
|
|
pattern1 = Doc(en_vocab, words=["c", "d"])
|
|
assert [t.norm_ for t in pattern1] == ["c", "d"]
|
|
matcher.add("TEST", [pattern1])
|
|
doc = Doc(en_vocab, words=["a", "b", "c", "d"])
|
|
assert [t.norm_ for t in doc] == ["a", "b", "c", "d"]
|
|
matches = matcher(doc)
|
|
assert len(matches) == 1
|
|
matcher = PhraseMatcher(en_vocab, attr="NORM")
|
|
pattern2 = Doc(en_vocab, words=["1", "2"])
|
|
pattern2[0].norm_ = "c"
|
|
pattern2[1].norm_ = "d"
|
|
assert [t.norm_ for t in pattern2] == ["c", "d"]
|
|
matcher.add("TEST", [pattern2])
|
|
matches = matcher(doc)
|
|
assert len(matches) == 1
|
|
|
|
|
|
@pytest.mark.issue(4373)
|
|
def test_issue4373():
|
|
"""Test that PhraseMatcher.vocab can be accessed (like Matcher.vocab)."""
|
|
matcher = Matcher(Vocab())
|
|
assert isinstance(matcher.vocab, Vocab)
|
|
matcher = PhraseMatcher(Vocab())
|
|
assert isinstance(matcher.vocab, Vocab)
|
|
|
|
|
|
@pytest.mark.issue(4651)
|
|
def test_issue4651_with_phrase_matcher_attr():
|
|
"""Test that the EntityRuler PhraseMatcher is deserialized correctly using
|
|
the method from_disk when the EntityRuler argument phrase_matcher_attr is
|
|
specified.
|
|
"""
|
|
text = "Spacy is a python library for nlp"
|
|
nlp = English()
|
|
patterns = [{"label": "PYTHON_LIB", "pattern": "spacy", "id": "spaCy"}]
|
|
ruler = nlp.add_pipe("entity_ruler", config={"phrase_matcher_attr": "LOWER"})
|
|
ruler.add_patterns(patterns)
|
|
doc = nlp(text)
|
|
res = [(ent.text, ent.label_, ent.ent_id_) for ent in doc.ents]
|
|
nlp_reloaded = English()
|
|
with make_tempdir() as d:
|
|
file_path = d / "entityruler"
|
|
ruler.to_disk(file_path)
|
|
nlp_reloaded.add_pipe("entity_ruler").from_disk(file_path)
|
|
doc_reloaded = nlp_reloaded(text)
|
|
res_reloaded = [(ent.text, ent.label_, ent.ent_id_) for ent in doc_reloaded.ents]
|
|
assert res == res_reloaded
|
|
|
|
|
|
@pytest.mark.issue(6839)
|
|
def test_issue6839(en_vocab):
|
|
"""Ensure that PhraseMatcher accepts Span as input"""
|
|
# fmt: off
|
|
words = ["I", "like", "Spans", "and", "Docs", "in", "my", "input", ",", "and", "nothing", "else", "."]
|
|
# fmt: on
|
|
doc = Doc(en_vocab, words=words)
|
|
span = doc[:8]
|
|
pattern = Doc(en_vocab, words=["Spans", "and", "Docs"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("SPACY", [pattern])
|
|
matches = matcher(span)
|
|
assert matches
|
|
|
|
|
|
@pytest.mark.issue(10643)
|
|
def test_issue10643(en_vocab):
|
|
"""Ensure overlapping terms can be removed from PhraseMatcher"""
|
|
|
|
# fmt: off
|
|
words = ["Only", "save", "out", "the", "binary", "data", "for", "the", "individual", "components", "."]
|
|
# fmt: on
|
|
doc = Doc(en_vocab, words=words)
|
|
terms = {
|
|
"0": Doc(en_vocab, words=["binary"]),
|
|
"1": Doc(en_vocab, words=["binary", "data"]),
|
|
}
|
|
matcher = PhraseMatcher(en_vocab)
|
|
for match_id, term in terms.items():
|
|
matcher.add(match_id, [term])
|
|
|
|
matches = matcher(doc)
|
|
assert matches == [(en_vocab.strings["0"], 4, 5), (en_vocab.strings["1"], 4, 6)]
|
|
|
|
matcher.remove("0")
|
|
assert len(matcher) == 1
|
|
new_matches = matcher(doc)
|
|
assert new_matches == [(en_vocab.strings["1"], 4, 6)]
|
|
|
|
matcher.remove("1")
|
|
assert len(matcher) == 0
|
|
no_matches = matcher(doc)
|
|
assert not no_matches
|
|
|
|
|
|
def test_matcher_phrase_matcher(en_vocab):
|
|
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
|
|
# intermediate phrase
|
|
pattern = Doc(en_vocab, words=["Google", "Now"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("COMPANY", [pattern])
|
|
assert len(matcher(doc)) == 1
|
|
# initial token
|
|
pattern = Doc(en_vocab, words=["I"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("I", [pattern])
|
|
assert len(matcher(doc)) == 1
|
|
# initial phrase
|
|
pattern = Doc(en_vocab, words=["I", "like"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("ILIKE", [pattern])
|
|
assert len(matcher(doc)) == 1
|
|
# final token
|
|
pattern = Doc(en_vocab, words=["best"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("BEST", [pattern])
|
|
assert len(matcher(doc)) == 1
|
|
# final phrase
|
|
pattern = Doc(en_vocab, words=["Now", "best"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("NOWBEST", [pattern])
|
|
assert len(matcher(doc)) == 1
|
|
|
|
|
|
def test_phrase_matcher_length(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
assert len(matcher) == 0
|
|
matcher.add("TEST", [Doc(en_vocab, words=["test"])])
|
|
assert len(matcher) == 1
|
|
matcher.add("TEST2", [Doc(en_vocab, words=["test2"])])
|
|
assert len(matcher) == 2
|
|
|
|
|
|
def test_phrase_matcher_contains(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("TEST", [Doc(en_vocab, words=["test"])])
|
|
assert "TEST" in matcher
|
|
assert "TEST2" not in matcher
|
|
|
|
|
|
def test_phrase_matcher_add_new_api(en_vocab):
|
|
doc = Doc(en_vocab, words=["a", "b"])
|
|
patterns = [Doc(en_vocab, words=["a"]), Doc(en_vocab, words=["a", "b"])]
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("OLD_API", None, *patterns)
|
|
assert len(matcher(doc)) == 2
|
|
matcher = PhraseMatcher(en_vocab)
|
|
on_match = Mock()
|
|
matcher.add("OLD_API_CALLBACK", on_match, *patterns)
|
|
assert len(matcher(doc)) == 2
|
|
assert on_match.call_count == 2
|
|
# New API: add(key: str, patterns: List[List[dict]], on_match: Callable)
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("NEW_API", patterns)
|
|
assert len(matcher(doc)) == 2
|
|
matcher = PhraseMatcher(en_vocab)
|
|
on_match = Mock()
|
|
matcher.add("NEW_API_CALLBACK", patterns, on_match=on_match)
|
|
assert len(matcher(doc)) == 2
|
|
assert on_match.call_count == 2
|
|
|
|
|
|
def test_phrase_matcher_repeated_add(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
# match ID only gets added once
|
|
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
|
|
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
|
|
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
|
|
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
|
|
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
|
|
assert "TEST" in matcher
|
|
assert "TEST2" not in matcher
|
|
assert len(matcher(doc)) == 1
|
|
|
|
|
|
def test_phrase_matcher_remove(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("TEST1", [Doc(en_vocab, words=["like"])])
|
|
matcher.add("TEST2", [Doc(en_vocab, words=["best"])])
|
|
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
|
|
assert "TEST1" in matcher
|
|
assert "TEST2" in matcher
|
|
assert "TEST3" not in matcher
|
|
assert len(matcher(doc)) == 2
|
|
matcher.remove("TEST1")
|
|
assert "TEST1" not in matcher
|
|
assert "TEST2" in matcher
|
|
assert "TEST3" not in matcher
|
|
assert len(matcher(doc)) == 1
|
|
matcher.remove("TEST2")
|
|
assert "TEST1" not in matcher
|
|
assert "TEST2" not in matcher
|
|
assert "TEST3" not in matcher
|
|
assert len(matcher(doc)) == 0
|
|
with pytest.raises(KeyError):
|
|
matcher.remove("TEST3")
|
|
assert "TEST1" not in matcher
|
|
assert "TEST2" not in matcher
|
|
assert "TEST3" not in matcher
|
|
assert len(matcher(doc)) == 0
|
|
|
|
|
|
def test_phrase_matcher_overlapping_with_remove(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("TEST", [Doc(en_vocab, words=["like"])])
|
|
# TEST2 is added alongside TEST
|
|
matcher.add("TEST2", [Doc(en_vocab, words=["like"])])
|
|
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
|
|
assert "TEST" in matcher
|
|
assert len(matcher) == 2
|
|
assert len(matcher(doc)) == 2
|
|
# removing TEST does not remove the entry for TEST2
|
|
matcher.remove("TEST")
|
|
assert "TEST" not in matcher
|
|
assert len(matcher) == 1
|
|
assert len(matcher(doc)) == 1
|
|
assert matcher(doc)[0][0] == en_vocab.strings["TEST2"]
|
|
# removing TEST2 removes all
|
|
matcher.remove("TEST2")
|
|
assert "TEST2" not in matcher
|
|
assert len(matcher) == 0
|
|
assert len(matcher(doc)) == 0
|
|
|
|
|
|
def test_phrase_matcher_string_attrs(en_vocab):
|
|
words1 = ["I", "like", "cats"]
|
|
pos1 = ["PRON", "VERB", "NOUN"]
|
|
words2 = ["Yes", ",", "you", "hate", "dogs", "very", "much"]
|
|
pos2 = ["INTJ", "PUNCT", "PRON", "VERB", "NOUN", "ADV", "ADV"]
|
|
pattern = Doc(en_vocab, words=words1, pos=pos1)
|
|
matcher = PhraseMatcher(en_vocab, attr="POS")
|
|
matcher.add("TEST", [pattern])
|
|
doc = Doc(en_vocab, words=words2, pos=pos2)
|
|
matches = matcher(doc)
|
|
assert len(matches) == 1
|
|
match_id, start, end = matches[0]
|
|
assert match_id == en_vocab.strings["TEST"]
|
|
assert start == 2
|
|
assert end == 5
|
|
|
|
|
|
def test_phrase_matcher_string_attrs_negative(en_vocab):
|
|
"""Test that token with the control codes as ORTH are *not* matched."""
|
|
words1 = ["I", "like", "cats"]
|
|
pos1 = ["PRON", "VERB", "NOUN"]
|
|
words2 = ["matcher:POS-PRON", "matcher:POS-VERB", "matcher:POS-NOUN"]
|
|
pos2 = ["X", "X", "X"]
|
|
pattern = Doc(en_vocab, words=words1, pos=pos1)
|
|
matcher = PhraseMatcher(en_vocab, attr="POS")
|
|
matcher.add("TEST", [pattern])
|
|
doc = Doc(en_vocab, words=words2, pos=pos2)
|
|
matches = matcher(doc)
|
|
assert len(matches) == 0
|
|
|
|
|
|
def test_phrase_matcher_bool_attrs(en_vocab):
|
|
words1 = ["Hello", "world", "!"]
|
|
words2 = ["No", "problem", ",", "he", "said", "."]
|
|
pattern = Doc(en_vocab, words=words1)
|
|
matcher = PhraseMatcher(en_vocab, attr="IS_PUNCT")
|
|
matcher.add("TEST", [pattern])
|
|
doc = Doc(en_vocab, words=words2)
|
|
matches = matcher(doc)
|
|
assert len(matches) == 2
|
|
match_id1, start1, end1 = matches[0]
|
|
match_id2, start2, end2 = matches[1]
|
|
assert match_id1 == en_vocab.strings["TEST"]
|
|
assert match_id2 == en_vocab.strings["TEST"]
|
|
assert start1 == 0
|
|
assert end1 == 3
|
|
assert start2 == 3
|
|
assert end2 == 6
|
|
|
|
|
|
def test_phrase_matcher_validation(en_vocab):
|
|
doc1 = Doc(en_vocab, words=["Test"])
|
|
doc1[0].dep_ = "ROOT"
|
|
doc2 = Doc(en_vocab, words=["Test"])
|
|
doc2[0].tag_ = "TAG"
|
|
doc2[0].pos_ = "X"
|
|
doc2[0].set_morph("Feat=Val")
|
|
doc3 = Doc(en_vocab, words=["Test"])
|
|
matcher = PhraseMatcher(en_vocab, validate=True)
|
|
with pytest.warns(UserWarning):
|
|
matcher.add("TEST1", [doc1])
|
|
with pytest.warns(UserWarning):
|
|
matcher.add("TEST2", [doc2])
|
|
with warnings.catch_warnings():
|
|
warnings.simplefilter("error")
|
|
matcher.add("TEST3", [doc3])
|
|
matcher = PhraseMatcher(en_vocab, attr="POS", validate=True)
|
|
with warnings.catch_warnings():
|
|
warnings.simplefilter("error")
|
|
matcher.add("TEST4", [doc2])
|
|
|
|
|
|
def test_attr_validation(en_vocab):
|
|
with pytest.raises(ValueError):
|
|
PhraseMatcher(en_vocab, attr="UNSUPPORTED")
|
|
|
|
|
|
def test_attr_pipeline_checks(en_vocab):
|
|
doc1 = Doc(en_vocab, words=["Test"])
|
|
doc1[0].dep_ = "ROOT"
|
|
doc2 = Doc(en_vocab, words=["Test"])
|
|
doc2[0].tag_ = "TAG"
|
|
doc2[0].pos_ = "X"
|
|
doc2[0].set_morph("Feat=Val")
|
|
doc2[0].lemma_ = "LEMMA"
|
|
doc3 = Doc(en_vocab, words=["Test"])
|
|
# DEP requires DEP
|
|
matcher = PhraseMatcher(en_vocab, attr="DEP")
|
|
matcher.add("TEST1", [doc1])
|
|
with pytest.raises(ValueError):
|
|
matcher.add("TEST2", [doc2])
|
|
with pytest.raises(ValueError):
|
|
matcher.add("TEST3", [doc3])
|
|
# TAG, POS, LEMMA require those values
|
|
for attr in ("TAG", "POS", "LEMMA"):
|
|
matcher = PhraseMatcher(en_vocab, attr=attr)
|
|
matcher.add("TEST2", [doc2])
|
|
with pytest.raises(ValueError):
|
|
matcher.add("TEST1", [doc1])
|
|
with pytest.raises(ValueError):
|
|
matcher.add("TEST3", [doc3])
|
|
# TEXT/ORTH only require tokens
|
|
matcher = PhraseMatcher(en_vocab, attr="ORTH")
|
|
matcher.add("TEST3", [doc3])
|
|
matcher = PhraseMatcher(en_vocab, attr="TEXT")
|
|
matcher.add("TEST3", [doc3])
|
|
|
|
|
|
def test_phrase_matcher_callback(en_vocab):
|
|
mock = Mock()
|
|
doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
|
|
pattern = Doc(en_vocab, words=["Google", "Now"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("COMPANY", [pattern], on_match=mock)
|
|
matches = matcher(doc)
|
|
mock.assert_called_once_with(matcher, doc, 0, matches)
|
|
|
|
|
|
def test_phrase_matcher_remove_overlapping_patterns(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
pattern1 = Doc(en_vocab, words=["this"])
|
|
pattern2 = Doc(en_vocab, words=["this", "is"])
|
|
pattern3 = Doc(en_vocab, words=["this", "is", "a"])
|
|
pattern4 = Doc(en_vocab, words=["this", "is", "a", "word"])
|
|
matcher.add("THIS", [pattern1, pattern2, pattern3, pattern4])
|
|
matcher.remove("THIS")
|
|
|
|
|
|
def test_phrase_matcher_basic_check(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
# Potential mistake: pass in pattern instead of list of patterns
|
|
pattern = Doc(en_vocab, words=["hello", "world"])
|
|
with pytest.raises(ValueError):
|
|
matcher.add("TEST", pattern)
|
|
|
|
|
|
def test_phrase_matcher_pickle(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
mock = Mock()
|
|
matcher.add("TEST", [Doc(en_vocab, words=["test"])])
|
|
matcher.add("TEST2", [Doc(en_vocab, words=["test2"])], on_match=mock)
|
|
doc = Doc(en_vocab, words=["these", "are", "tests", ":", "test", "test2"])
|
|
assert len(matcher) == 2
|
|
|
|
b = srsly.pickle_dumps(matcher)
|
|
matcher_unpickled = srsly.pickle_loads(b)
|
|
|
|
# call after pickling to avoid recursion error related to mock
|
|
matches = matcher(doc)
|
|
matches_unpickled = matcher_unpickled(doc)
|
|
|
|
assert len(matcher) == len(matcher_unpickled)
|
|
assert matches == matches_unpickled
|
|
|
|
# clunky way to vaguely check that callback is unpickled
|
|
(vocab, docs, callbacks, attr) = matcher_unpickled.__reduce__()[1]
|
|
assert isinstance(callbacks.get("TEST2"), Mock)
|
|
|
|
|
|
def test_phrase_matcher_as_spans(en_vocab):
|
|
"""Test the new as_spans=True API."""
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("A", [Doc(en_vocab, words=["hello", "world"])])
|
|
matcher.add("B", [Doc(en_vocab, words=["test"])])
|
|
doc = Doc(en_vocab, words=["...", "hello", "world", "this", "is", "a", "test"])
|
|
matches = matcher(doc, as_spans=True)
|
|
assert len(matches) == 2
|
|
assert isinstance(matches[0], Span)
|
|
assert matches[0].text == "hello world"
|
|
assert matches[0].label_ == "A"
|
|
assert isinstance(matches[1], Span)
|
|
assert matches[1].text == "test"
|
|
assert matches[1].label_ == "B"
|
|
|
|
|
|
def test_phrase_matcher_deprecated(en_vocab):
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("TEST", [Doc(en_vocab, words=["helllo"])])
|
|
doc = Doc(en_vocab, words=["hello", "world"])
|
|
with pytest.warns(DeprecationWarning) as record:
|
|
for _ in matcher.pipe([doc]):
|
|
pass
|
|
assert record.list
|
|
assert "spaCy v3.0" in str(record.list[0].message)
|
|
|
|
|
|
@pytest.mark.parametrize("attr", ["SENT_START", "IS_SENT_START"])
|
|
def test_phrase_matcher_sent_start(en_vocab, attr):
|
|
_ = PhraseMatcher(en_vocab, attr=attr) # noqa: F841
|
|
|
|
|
|
def test_span_in_phrasematcher(en_vocab):
|
|
"""Ensure that PhraseMatcher accepts Span and Doc as input"""
|
|
# fmt: off
|
|
words = ["I", "like", "Spans", "and", "Docs", "in", "my", "input", ",", "and", "nothing", "else", "."]
|
|
# fmt: on
|
|
doc = Doc(en_vocab, words=words)
|
|
span = doc[:8]
|
|
pattern = Doc(en_vocab, words=["Spans", "and", "Docs"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("SPACY", [pattern])
|
|
matches_doc = matcher(doc)
|
|
matches_span = matcher(span)
|
|
assert len(matches_doc) == 1
|
|
assert len(matches_span) == 1
|
|
|
|
|
|
def test_span_v_doc_in_phrasematcher(en_vocab):
|
|
"""Ensure that PhraseMatcher only returns matches in input Span and not in entire Doc"""
|
|
# fmt: off
|
|
words = [
|
|
"I", "like", "Spans", "and", "Docs", "in", "my", "input", ",", "Spans",
|
|
"and", "Docs", "in", "my", "matchers", "," "and", "Spans", "and", "Docs",
|
|
"everywhere", "."
|
|
]
|
|
# fmt: on
|
|
doc = Doc(en_vocab, words=words)
|
|
span = doc[9:15] # second clause
|
|
pattern = Doc(en_vocab, words=["Spans", "and", "Docs"])
|
|
matcher = PhraseMatcher(en_vocab)
|
|
matcher.add("SPACY", [pattern])
|
|
matches_doc = matcher(doc)
|
|
matches_span = matcher(span)
|
|
assert len(matches_doc) == 3
|
|
assert len(matches_span) == 1
|