mirror of https://github.com/explosion/spaCy.git
216 lines
7.2 KiB
Python
216 lines
7.2 KiB
Python
import pytest
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from spacy import registry
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from spacy.tokens import Span
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from spacy.language import Language
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from spacy.pipeline import EntityRuler
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from spacy.errors import MatchPatternError
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from thinc.api import NumpyOps, get_current_ops
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@pytest.fixture
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def nlp():
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return Language()
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@pytest.fixture
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@registry.misc("entity_ruler_patterns")
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def patterns():
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return [
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{"label": "HELLO", "pattern": "hello world"},
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{"label": "BYE", "pattern": [{"LOWER": "bye"}, {"LOWER": "bye"}]},
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{"label": "HELLO", "pattern": [{"ORTH": "HELLO"}]},
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{"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]},
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{"label": "TECH_ORG", "pattern": "Apple", "id": "a1"},
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{"label": "TECH_ORG", "pattern": "Microsoft", "id": "a2"},
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]
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@Language.component("add_ent")
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def add_ent_component(doc):
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doc.ents = [Span(doc, 0, 3, label="ORG")]
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return doc
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def test_entity_ruler_init(nlp, patterns):
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ruler = EntityRuler(nlp, patterns=patterns)
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assert len(ruler) == len(patterns)
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assert len(ruler.labels) == 4
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assert "HELLO" in ruler
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assert "BYE" in ruler
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ruler = nlp.add_pipe("entity_ruler")
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ruler.add_patterns(patterns)
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doc = nlp("hello world bye bye")
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assert len(doc.ents) == 2
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assert doc.ents[0].label_ == "HELLO"
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assert doc.ents[1].label_ == "BYE"
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def test_entity_ruler_init_patterns(nlp, patterns):
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# initialize with patterns
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ruler = nlp.add_pipe("entity_ruler")
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assert len(ruler.labels) == 0
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ruler.initialize(lambda: [], patterns=patterns)
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assert len(ruler.labels) == 4
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doc = nlp("hello world bye bye")
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assert doc.ents[0].label_ == "HELLO"
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assert doc.ents[1].label_ == "BYE"
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nlp.remove_pipe("entity_ruler")
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# initialize with patterns from misc registry
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nlp.config["initialize"]["components"]["entity_ruler"] = {
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"patterns": {"@misc": "entity_ruler_patterns"}
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}
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ruler = nlp.add_pipe("entity_ruler")
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assert len(ruler.labels) == 0
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nlp.initialize()
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assert len(ruler.labels) == 4
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doc = nlp("hello world bye bye")
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assert doc.ents[0].label_ == "HELLO"
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assert doc.ents[1].label_ == "BYE"
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def test_entity_ruler_init_clear(nlp, patterns):
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"""Test that initialization clears patterns."""
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ruler = nlp.add_pipe("entity_ruler")
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ruler.add_patterns(patterns)
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assert len(ruler.labels) == 4
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ruler.initialize(lambda: [])
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assert len(ruler.labels) == 0
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def test_entity_ruler_existing(nlp, patterns):
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ruler = nlp.add_pipe("entity_ruler")
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ruler.add_patterns(patterns)
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nlp.add_pipe("add_ent", before="entity_ruler")
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doc = nlp("OH HELLO WORLD bye bye")
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assert len(doc.ents) == 2
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assert doc.ents[0].label_ == "ORG"
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assert doc.ents[1].label_ == "BYE"
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def test_entity_ruler_existing_overwrite(nlp, patterns):
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ruler = nlp.add_pipe("entity_ruler", config={"overwrite_ents": True})
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ruler.add_patterns(patterns)
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nlp.add_pipe("add_ent", before="entity_ruler")
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doc = nlp("OH HELLO WORLD bye bye")
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assert len(doc.ents) == 2
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assert doc.ents[0].label_ == "HELLO"
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assert doc.ents[0].text == "HELLO"
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assert doc.ents[1].label_ == "BYE"
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def test_entity_ruler_existing_complex(nlp, patterns):
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ruler = nlp.add_pipe("entity_ruler", config={"overwrite_ents": True})
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ruler.add_patterns(patterns)
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nlp.add_pipe("add_ent", before="entity_ruler")
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doc = nlp("foo foo bye bye")
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assert len(doc.ents) == 2
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assert doc.ents[0].label_ == "COMPLEX"
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assert doc.ents[1].label_ == "BYE"
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assert len(doc.ents[0]) == 2
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assert len(doc.ents[1]) == 2
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def test_entity_ruler_entity_id(nlp, patterns):
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ruler = nlp.add_pipe("entity_ruler", config={"overwrite_ents": True})
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ruler.add_patterns(patterns)
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doc = nlp("Apple is a technology company")
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assert len(doc.ents) == 1
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assert doc.ents[0].label_ == "TECH_ORG"
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assert doc.ents[0].ent_id_ == "a1"
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def test_entity_ruler_cfg_ent_id_sep(nlp, patterns):
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config = {"overwrite_ents": True, "ent_id_sep": "**"}
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ruler = nlp.add_pipe("entity_ruler", config=config)
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ruler.add_patterns(patterns)
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assert "TECH_ORG**a1" in ruler.phrase_patterns
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doc = nlp("Apple is a technology company")
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assert len(doc.ents) == 1
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assert doc.ents[0].label_ == "TECH_ORG"
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assert doc.ents[0].ent_id_ == "a1"
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def test_entity_ruler_serialize_bytes(nlp, patterns):
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ruler = EntityRuler(nlp, patterns=patterns)
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assert len(ruler) == len(patterns)
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assert len(ruler.labels) == 4
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ruler_bytes = ruler.to_bytes()
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new_ruler = EntityRuler(nlp)
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assert len(new_ruler) == 0
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assert len(new_ruler.labels) == 0
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new_ruler = new_ruler.from_bytes(ruler_bytes)
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assert len(new_ruler) == len(patterns)
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assert len(new_ruler.labels) == 4
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assert len(new_ruler.patterns) == len(ruler.patterns)
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for pattern in ruler.patterns:
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assert pattern in new_ruler.patterns
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assert sorted(new_ruler.labels) == sorted(ruler.labels)
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def test_entity_ruler_serialize_phrase_matcher_attr_bytes(nlp, patterns):
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ruler = EntityRuler(nlp, phrase_matcher_attr="LOWER", patterns=patterns)
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assert len(ruler) == len(patterns)
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assert len(ruler.labels) == 4
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ruler_bytes = ruler.to_bytes()
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new_ruler = EntityRuler(nlp)
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assert len(new_ruler) == 0
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assert len(new_ruler.labels) == 0
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assert new_ruler.phrase_matcher_attr is None
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new_ruler = new_ruler.from_bytes(ruler_bytes)
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assert len(new_ruler) == len(patterns)
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assert len(new_ruler.labels) == 4
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assert new_ruler.phrase_matcher_attr == "LOWER"
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def test_entity_ruler_validate(nlp):
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ruler = EntityRuler(nlp)
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validated_ruler = EntityRuler(nlp, validate=True)
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valid_pattern = {"label": "HELLO", "pattern": [{"LOWER": "HELLO"}]}
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invalid_pattern = {"label": "HELLO", "pattern": [{"ASDF": "HELLO"}]}
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# invalid pattern raises error without validate
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with pytest.raises(ValueError):
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ruler.add_patterns([invalid_pattern])
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# valid pattern is added without errors with validate
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validated_ruler.add_patterns([valid_pattern])
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# invalid pattern raises error with validate
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with pytest.raises(MatchPatternError):
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validated_ruler.add_patterns([invalid_pattern])
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def test_entity_ruler_properties(nlp, patterns):
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ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True)
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assert sorted(ruler.labels) == sorted(["HELLO", "BYE", "COMPLEX", "TECH_ORG"])
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assert sorted(ruler.ent_ids) == ["a1", "a2"]
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def test_entity_ruler_overlapping_spans(nlp):
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ruler = EntityRuler(nlp)
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patterns = [
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{"label": "FOOBAR", "pattern": "foo bar"},
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{"label": "BARBAZ", "pattern": "bar baz"},
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]
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ruler.add_patterns(patterns)
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doc = ruler(nlp.make_doc("foo bar baz"))
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assert len(doc.ents) == 1
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assert doc.ents[0].label_ == "FOOBAR"
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@pytest.mark.parametrize("n_process", [1, 2])
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def test_entity_ruler_multiprocessing(nlp, n_process):
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if isinstance(get_current_ops, NumpyOps) or n_process < 2:
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texts = ["I enjoy eating Pizza Hut pizza."]
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patterns = [{"label": "FASTFOOD", "pattern": "Pizza Hut", "id": "1234"}]
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ruler = nlp.add_pipe("entity_ruler")
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ruler.add_patterns(patterns)
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for doc in nlp.pipe(texts, n_process=2):
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for ent in doc.ents:
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assert ent.ent_id_ == "1234"
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