spaCy/spacy/tests/pipeline/test_entity_ruler.py
Kevin Humphreys 19650ebb52
Enable fuzzy text matching in Matcher (#11359)
* enable fuzzy matching

* add fuzzy param to EntityMatcher

* include rapidfuzz_capi

not yet used

* fix type

* add FUZZY predicate

* add fuzzy attribute list

* fix type properly

* tidying

* remove unnecessary dependency

* handle fuzzy sets

* simplify fuzzy sets

* case fix

* switch to FUZZYn predicates

use Levenshtein distance.
remove fuzzy param.
remove rapidfuzz_capi.

* revert changes added for fuzzy param

* switch to polyleven

(Python package)

* enable fuzzy matching

* add fuzzy param to EntityMatcher

* include rapidfuzz_capi

not yet used

* fix type

* add FUZZY predicate

* add fuzzy attribute list

* fix type properly

* tidying

* remove unnecessary dependency

* handle fuzzy sets

* simplify fuzzy sets

* case fix

* switch to FUZZYn predicates

use Levenshtein distance.
remove fuzzy param.
remove rapidfuzz_capi.

* revert changes added for fuzzy param

* switch to polyleven

(Python package)

* fuzzy match only on oov tokens

* remove polyleven

* exclude whitespace tokens

* don't allow more edits than characters

* fix min distance

* reinstate FUZZY operator

with length-based distance function

* handle sets inside regex operator

* remove is_oov check

* attempt build fix

no mypy failure locally

* re-attempt build fix

* don't overwrite fuzzy param value

* move fuzzy_match

to its own Python module to allow patching

* move fuzzy_match back inside Matcher

simplify logic and add tests

* Format tests

* Parametrize fuzzyn tests

* Parametrize and merge fuzzy+set tests

* Format

* Move fuzzy_match to a standalone method

* Change regex kwarg type to bool

* Add types for fuzzy_match

- Refactor variable names
- Add test for symmetrical behavior

* Parametrize fuzzyn+set tests

* Minor refactoring for fuzz/fuzzy

* Make fuzzy_match a Matcher kwarg

* Update type for _default_fuzzy_match

* don't overwrite function param

* Rename to fuzzy_compare

* Update fuzzy_compare default argument declarations

* allow fuzzy_compare override from EntityRuler

* define new Matcher keyword arg

* fix type definition

* Implement fuzzy_compare config option for EntityRuler and SpanRuler

* Rename _default_fuzzy_compare to fuzzy_compare, remove from reexported objects

* Use simpler fuzzy_compare algorithm

* Update types

* Increase minimum to 2 in fuzzy_compare to allow one transposition

* Fix predicate keys and matching for SetPredicate with FUZZY and REGEX

* Add FUZZY6..9

* Add initial docs

* Increase default fuzzy to rounded 30% of pattern length

* Update docs for fuzzy_compare in components

* Update EntityRuler and SpanRuler API docs

* Rename EntityRuler and SpanRuler setting to matcher_fuzzy_compare

To having naming similar to `phrase_matcher_attr`, rename
`fuzzy_compare` setting for `EntityRuler` and `SpanRuler` to
`matcher_fuzzy_compare. Organize next to `phrase_matcher_attr` in docs.

* Fix schema aliases

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fix typo

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Add FUZZY6-9 operators and update tests

* Parameterize test over greedy

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Fix type for fuzzy_compare to remove Optional

* Rename to spacy.levenshtein_compare.v1, move to spacy.matcher.levenshtein

* Update docs following levenshtein_compare renaming

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2023-01-10 10:36:17 +01:00

685 lines
25 KiB
Python

import pytest
from spacy import registry
from spacy.tokens import Doc, Span
from spacy.language import Language
from spacy.lang.en import English
from spacy.pipeline import EntityRuler, EntityRecognizer, merge_entities
from spacy.pipeline import SpanRuler
from spacy.pipeline.ner import DEFAULT_NER_MODEL
from spacy.errors import MatchPatternError
from spacy.tests.util import make_tempdir
from thinc.api import NumpyOps, get_current_ops
ENTITY_RULERS = ["entity_ruler", "future_entity_ruler"]
@pytest.fixture
def nlp():
return Language()
@pytest.fixture
@registry.misc("entity_ruler_patterns")
def patterns():
return [
{"label": "HELLO", "pattern": "hello world"},
{"label": "BYE", "pattern": [{"LOWER": "bye"}, {"LOWER": "bye"}]},
{"label": "HELLO", "pattern": [{"ORTH": "HELLO"}]},
{"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]},
{"label": "TECH_ORG", "pattern": "Apple", "id": "a1"},
{"label": "TECH_ORG", "pattern": "Microsoft", "id": "a2"},
]
@Language.component("add_ent")
def add_ent_component(doc):
doc.ents = [Span(doc, 0, 3, label="ORG")]
return doc
@pytest.mark.issue(3345)
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_issue3345(entity_ruler_factory):
"""Test case where preset entity crosses sentence boundary."""
nlp = English()
doc = Doc(nlp.vocab, words=["I", "live", "in", "New", "York"])
doc[4].is_sent_start = True
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns([{"label": "GPE", "pattern": "New York"}])
cfg = {"model": DEFAULT_NER_MODEL}
model = registry.resolve(cfg, validate=True)["model"]
ner = EntityRecognizer(doc.vocab, model)
# Add the OUT action. I wouldn't have thought this would be necessary...
ner.moves.add_action(5, "")
ner.add_label("GPE")
doc = ruler(doc)
# Get into the state just before "New"
state = ner.moves.init_batch([doc])[0]
ner.moves.apply_transition(state, "O")
ner.moves.apply_transition(state, "O")
ner.moves.apply_transition(state, "O")
# Check that B-GPE is valid.
assert ner.moves.is_valid(state, "B-GPE")
@pytest.mark.issue(4849)
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_issue4849(entity_ruler_factory):
nlp = English()
patterns = [
{"label": "PERSON", "pattern": "joe biden", "id": "joe-biden"},
{"label": "PERSON", "pattern": "bernie sanders", "id": "bernie-sanders"},
]
ruler = nlp.add_pipe(
entity_ruler_factory,
name="entity_ruler",
config={"phrase_matcher_attr": "LOWER"},
)
ruler.add_patterns(patterns)
text = """
The left is starting to take aim at Democratic front-runner Joe Biden.
Sen. Bernie Sanders joined in her criticism: "There is no 'middle ground' when it comes to climate policy."
"""
# USING 1 PROCESS
count_ents = 0
for doc in nlp.pipe([text], n_process=1):
count_ents += len([ent for ent in doc.ents if ent.ent_id > 0])
assert count_ents == 2
# USING 2 PROCESSES
if isinstance(get_current_ops, NumpyOps):
count_ents = 0
for doc in nlp.pipe([text], n_process=2):
count_ents += len([ent for ent in doc.ents if ent.ent_id > 0])
assert count_ents == 2
@pytest.mark.issue(5918)
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_issue5918(entity_ruler_factory):
# Test edge case when merging entities.
nlp = English()
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "ORG", "pattern": "Digicon Inc"},
{"label": "ORG", "pattern": "Rotan Mosle Inc's"},
{"label": "ORG", "pattern": "Rotan Mosle Technology Partners Ltd"},
]
ruler.add_patterns(patterns)
text = """
Digicon Inc said it has completed the previously-announced disposition
of its computer systems division to an investment group led by
Rotan Mosle Inc's Rotan Mosle Technology Partners Ltd affiliate.
"""
doc = nlp(text)
assert len(doc.ents) == 3
# make it so that the third span's head is within the entity (ent_iob=I)
# bug #5918 would wrongly transfer that I to the full entity, resulting in 2 instead of 3 final ents.
# TODO: test for logging here
# with pytest.warns(UserWarning):
# doc[29].head = doc[33]
doc = merge_entities(doc)
assert len(doc.ents) == 3
@pytest.mark.issue(8168)
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_issue8168(entity_ruler_factory):
nlp = English()
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "ORG", "pattern": "Apple"},
{
"label": "GPE",
"pattern": [{"LOWER": "san"}, {"LOWER": "francisco"}],
"id": "san-francisco",
},
{
"label": "GPE",
"pattern": [{"LOWER": "san"}, {"LOWER": "fran"}],
"id": "san-francisco",
},
]
ruler.add_patterns(patterns)
doc = nlp("San Francisco San Fran")
assert all(t.ent_id_ == "san-francisco" for t in doc)
@pytest.mark.issue(8216)
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_fix8216(nlp, patterns, entity_ruler_factory):
"""Test that patterns don't get added excessively."""
ruler = nlp.add_pipe(
entity_ruler_factory, name="entity_ruler", config={"validate": True}
)
ruler.add_patterns(patterns)
pattern_count = sum(len(mm) for mm in ruler.matcher._patterns.values())
assert pattern_count > 0
ruler.add_patterns([])
after_count = sum(len(mm) for mm in ruler.matcher._patterns.values())
assert after_count == pattern_count
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_init(nlp, patterns, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns(patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 4
assert "HELLO" in ruler
assert "BYE" in ruler
nlp.remove_pipe("entity_ruler")
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns(patterns)
doc = nlp("hello world bye bye")
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "HELLO"
assert doc.ents[1].label_ == "BYE"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_no_patterns_warns(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
assert len(ruler) == 0
assert len(ruler.labels) == 0
nlp.remove_pipe("entity_ruler")
nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
assert nlp.pipe_names == ["entity_ruler"]
with pytest.warns(UserWarning):
doc = nlp("hello world bye bye")
assert len(doc.ents) == 0
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_init_patterns(nlp, patterns, entity_ruler_factory):
# initialize with patterns
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
assert len(ruler.labels) == 0
ruler.initialize(lambda: [], patterns=patterns)
assert len(ruler.labels) == 4
doc = nlp("hello world bye bye")
assert doc.ents[0].label_ == "HELLO"
assert doc.ents[1].label_ == "BYE"
nlp.remove_pipe("entity_ruler")
# initialize with patterns from misc registry
nlp.config["initialize"]["components"]["entity_ruler"] = {
"patterns": {"@misc": "entity_ruler_patterns"}
}
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
assert len(ruler.labels) == 0
nlp.initialize()
assert len(ruler.labels) == 4
doc = nlp("hello world bye bye")
assert doc.ents[0].label_ == "HELLO"
assert doc.ents[1].label_ == "BYE"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_init_clear(nlp, patterns, entity_ruler_factory):
"""Test that initialization clears patterns."""
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns(patterns)
assert len(ruler.labels) == 4
ruler.initialize(lambda: [])
assert len(ruler.labels) == 0
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_clear(nlp, patterns, entity_ruler_factory):
"""Test that initialization clears patterns."""
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns(patterns)
assert len(ruler.labels) == 4
doc = nlp("hello world")
assert len(doc.ents) == 1
ruler.clear()
assert len(ruler.labels) == 0
with pytest.warns(UserWarning):
doc = nlp("hello world")
assert len(doc.ents) == 0
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_existing(nlp, patterns, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns(patterns)
nlp.add_pipe("add_ent", before="entity_ruler")
doc = nlp("OH HELLO WORLD bye bye")
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "ORG"
assert doc.ents[1].label_ == "BYE"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_existing_overwrite(nlp, patterns, entity_ruler_factory):
ruler = nlp.add_pipe(
entity_ruler_factory, name="entity_ruler", config={"overwrite_ents": True}
)
ruler.add_patterns(patterns)
nlp.add_pipe("add_ent", before="entity_ruler")
doc = nlp("OH HELLO WORLD bye bye")
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "HELLO"
assert doc.ents[0].text == "HELLO"
assert doc.ents[1].label_ == "BYE"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_existing_complex(nlp, patterns, entity_ruler_factory):
ruler = nlp.add_pipe(
entity_ruler_factory, name="entity_ruler", config={"overwrite_ents": True}
)
ruler.add_patterns(patterns)
nlp.add_pipe("add_ent", before="entity_ruler")
doc = nlp("foo foo bye bye")
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "COMPLEX"
assert doc.ents[1].label_ == "BYE"
assert len(doc.ents[0]) == 2
assert len(doc.ents[1]) == 2
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_entity_id(nlp, patterns, entity_ruler_factory):
ruler = nlp.add_pipe(
entity_ruler_factory, name="entity_ruler", config={"overwrite_ents": True}
)
ruler.add_patterns(patterns)
doc = nlp("Apple is a technology company")
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "TECH_ORG"
assert doc.ents[0].ent_id_ == "a1"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_cfg_ent_id_sep(nlp, patterns, entity_ruler_factory):
config = {"overwrite_ents": True, "ent_id_sep": "**"}
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler", config=config)
ruler.add_patterns(patterns)
doc = nlp("Apple is a technology company")
if isinstance(ruler, EntityRuler):
assert "TECH_ORG**a1" in ruler.phrase_patterns
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "TECH_ORG"
assert doc.ents[0].ent_id_ == "a1"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_serialize_bytes(nlp, patterns, entity_ruler_factory):
ruler = EntityRuler(nlp, patterns=patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 4
ruler_bytes = ruler.to_bytes()
new_ruler = EntityRuler(nlp)
assert len(new_ruler) == 0
assert len(new_ruler.labels) == 0
new_ruler = new_ruler.from_bytes(ruler_bytes)
assert len(new_ruler) == len(patterns)
assert len(new_ruler.labels) == 4
assert len(new_ruler.patterns) == len(ruler.patterns)
for pattern in ruler.patterns:
assert pattern in new_ruler.patterns
assert sorted(new_ruler.labels) == sorted(ruler.labels)
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_serialize_phrase_matcher_attr_bytes(
nlp, patterns, entity_ruler_factory
):
ruler = EntityRuler(nlp, phrase_matcher_attr="LOWER", patterns=patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 4
ruler_bytes = ruler.to_bytes()
new_ruler = EntityRuler(nlp)
assert len(new_ruler) == 0
assert len(new_ruler.labels) == 0
assert new_ruler.phrase_matcher_attr is None
new_ruler = new_ruler.from_bytes(ruler_bytes)
assert len(new_ruler) == len(patterns)
assert len(new_ruler.labels) == 4
assert new_ruler.phrase_matcher_attr == "LOWER"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_validate(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
validated_ruler = EntityRuler(nlp, validate=True)
valid_pattern = {"label": "HELLO", "pattern": [{"LOWER": "HELLO"}]}
invalid_pattern = {"label": "HELLO", "pattern": [{"ASDF": "HELLO"}]}
# invalid pattern raises error without validate
with pytest.raises(ValueError):
ruler.add_patterns([invalid_pattern])
# valid pattern is added without errors with validate
validated_ruler.add_patterns([valid_pattern])
# invalid pattern raises error with validate
with pytest.raises(MatchPatternError):
validated_ruler.add_patterns([invalid_pattern])
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_properties(nlp, patterns, entity_ruler_factory):
ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True)
assert sorted(ruler.labels) == sorted(["HELLO", "BYE", "COMPLEX", "TECH_ORG"])
assert sorted(ruler.ent_ids) == ["a1", "a2"]
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_overlapping_spans(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "FOOBAR", "pattern": "foo bar"},
{"label": "BARBAZ", "pattern": "bar baz"},
]
ruler.add_patterns(patterns)
doc = nlp("foo bar baz")
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "FOOBAR"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_fuzzy_pipe(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [{"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}]
ruler.add_patterns(patterns)
doc = nlp("helloo")
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "HELLO"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_fuzzy(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [{"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}]
ruler.add_patterns(patterns)
doc = nlp("helloo")
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "HELLO"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_fuzzy_disabled(nlp, entity_ruler_factory):
@registry.misc("test_fuzzy_compare_disabled")
def make_test_fuzzy_compare_disabled():
return lambda x, y, z: False
ruler = nlp.add_pipe(
entity_ruler_factory,
name="entity_ruler",
config={"matcher_fuzzy_compare": {"@misc": "test_fuzzy_compare_disabled"}},
)
patterns = [{"label": "HELLO", "pattern": [{"LOWER": {"FUZZY": "hello"}}]}]
ruler.add_patterns(patterns)
doc = nlp("helloo")
assert len(doc.ents) == 0
@pytest.mark.parametrize("n_process", [1, 2])
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_multiprocessing(nlp, n_process, entity_ruler_factory):
if isinstance(get_current_ops, NumpyOps) or n_process < 2:
texts = ["I enjoy eating Pizza Hut pizza."]
patterns = [{"label": "FASTFOOD", "pattern": "Pizza Hut", "id": "1234"}]
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns(patterns)
for doc in nlp.pipe(texts, n_process=2):
for ent in doc.ents:
assert ent.ent_id_ == "1234"
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_serialize_jsonl(nlp, patterns, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns(patterns)
with make_tempdir() as d:
ruler.to_disk(d / "test_ruler.jsonl")
ruler.from_disk(d / "test_ruler.jsonl") # read from an existing jsonl file
with pytest.raises(ValueError):
ruler.from_disk(d / "non_existing.jsonl") # read from a bad jsonl file
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_serialize_dir(nlp, patterns, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
ruler.add_patterns(patterns)
with make_tempdir() as d:
ruler.to_disk(d / "test_ruler")
ruler.from_disk(d / "test_ruler") # read from an existing directory
with pytest.raises(ValueError):
ruler.from_disk(d / "non_existing_dir") # read from a bad directory
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_remove_basic(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "PERSON", "pattern": "Dina", "id": "dina"},
{"label": "ORG", "pattern": "ACME", "id": "acme"},
{"label": "ORG", "pattern": "ACM"},
]
ruler.add_patterns(patterns)
doc = nlp("Dina went to school")
assert len(ruler.patterns) == 3
assert len(doc.ents) == 1
if isinstance(ruler, EntityRuler):
assert "PERSON||dina" in ruler.phrase_matcher
assert doc.ents[0].label_ == "PERSON"
assert doc.ents[0].text == "Dina"
if isinstance(ruler, EntityRuler):
ruler.remove("dina")
else:
ruler.remove_by_id("dina")
doc = nlp("Dina went to school")
assert len(doc.ents) == 0
if isinstance(ruler, EntityRuler):
assert "PERSON||dina" not in ruler.phrase_matcher
assert len(ruler.patterns) == 2
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_remove_same_id_multiple_patterns(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "PERSON", "pattern": "Dina", "id": "dina"},
{"label": "ORG", "pattern": "DinaCorp", "id": "dina"},
{"label": "ORG", "pattern": "ACME", "id": "acme"},
]
ruler.add_patterns(patterns)
doc = nlp("Dina founded DinaCorp and ACME.")
assert len(ruler.patterns) == 3
if isinstance(ruler, EntityRuler):
assert "PERSON||dina" in ruler.phrase_matcher
assert "ORG||dina" in ruler.phrase_matcher
assert len(doc.ents) == 3
if isinstance(ruler, EntityRuler):
ruler.remove("dina")
else:
ruler.remove_by_id("dina")
doc = nlp("Dina founded DinaCorp and ACME.")
assert len(ruler.patterns) == 1
if isinstance(ruler, EntityRuler):
assert "PERSON||dina" not in ruler.phrase_matcher
assert "ORG||dina" not in ruler.phrase_matcher
assert len(doc.ents) == 1
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_remove_nonexisting_pattern(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "PERSON", "pattern": "Dina", "id": "dina"},
{"label": "ORG", "pattern": "ACME", "id": "acme"},
{"label": "ORG", "pattern": "ACM"},
]
ruler.add_patterns(patterns)
assert len(ruler.patterns) == 3
with pytest.raises(ValueError):
ruler.remove("nepattern")
if isinstance(ruler, SpanRuler):
with pytest.raises(ValueError):
ruler.remove_by_id("nepattern")
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_remove_several_patterns(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "PERSON", "pattern": "Dina", "id": "dina"},
{"label": "ORG", "pattern": "ACME", "id": "acme"},
{"label": "ORG", "pattern": "ACM"},
]
ruler.add_patterns(patterns)
doc = nlp("Dina founded her company ACME.")
assert len(ruler.patterns) == 3
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "PERSON"
assert doc.ents[0].text == "Dina"
assert doc.ents[1].label_ == "ORG"
assert doc.ents[1].text == "ACME"
if isinstance(ruler, EntityRuler):
ruler.remove("dina")
else:
ruler.remove_by_id("dina")
doc = nlp("Dina founded her company ACME")
assert len(ruler.patterns) == 2
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "ORG"
assert doc.ents[0].text == "ACME"
if isinstance(ruler, EntityRuler):
ruler.remove("acme")
else:
ruler.remove_by_id("acme")
doc = nlp("Dina founded her company ACME")
assert len(ruler.patterns) == 1
assert len(doc.ents) == 0
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_remove_patterns_in_a_row(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "PERSON", "pattern": "Dina", "id": "dina"},
{"label": "ORG", "pattern": "ACME", "id": "acme"},
{"label": "DATE", "pattern": "her birthday", "id": "bday"},
{"label": "ORG", "pattern": "ACM"},
]
ruler.add_patterns(patterns)
doc = nlp("Dina founded her company ACME on her birthday")
assert len(doc.ents) == 3
assert doc.ents[0].label_ == "PERSON"
assert doc.ents[0].text == "Dina"
assert doc.ents[1].label_ == "ORG"
assert doc.ents[1].text == "ACME"
assert doc.ents[2].label_ == "DATE"
assert doc.ents[2].text == "her birthday"
if isinstance(ruler, EntityRuler):
ruler.remove("dina")
ruler.remove("acme")
ruler.remove("bday")
else:
ruler.remove_by_id("dina")
ruler.remove_by_id("acme")
ruler.remove_by_id("bday")
doc = nlp("Dina went to school")
assert len(doc.ents) == 0
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_remove_all_patterns(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [
{"label": "PERSON", "pattern": "Dina", "id": "dina"},
{"label": "ORG", "pattern": "ACME", "id": "acme"},
{"label": "DATE", "pattern": "her birthday", "id": "bday"},
]
ruler.add_patterns(patterns)
assert len(ruler.patterns) == 3
if isinstance(ruler, EntityRuler):
ruler.remove("dina")
else:
ruler.remove_by_id("dina")
assert len(ruler.patterns) == 2
if isinstance(ruler, EntityRuler):
ruler.remove("acme")
else:
ruler.remove_by_id("acme")
assert len(ruler.patterns) == 1
if isinstance(ruler, EntityRuler):
ruler.remove("bday")
else:
ruler.remove_by_id("bday")
assert len(ruler.patterns) == 0
with pytest.warns(UserWarning):
doc = nlp("Dina founded her company ACME on her birthday")
assert len(doc.ents) == 0
@pytest.mark.parametrize("entity_ruler_factory", ENTITY_RULERS)
def test_entity_ruler_remove_and_add(nlp, entity_ruler_factory):
ruler = nlp.add_pipe(entity_ruler_factory, name="entity_ruler")
patterns = [{"label": "DATE", "pattern": "last time"}]
ruler.add_patterns(patterns)
doc = ruler(
nlp.make_doc("I saw him last time we met, this time he brought some flowers")
)
assert len(ruler.patterns) == 1
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "DATE"
assert doc.ents[0].text == "last time"
patterns1 = [{"label": "DATE", "pattern": "this time", "id": "ttime"}]
ruler.add_patterns(patterns1)
doc = ruler(
nlp.make_doc("I saw him last time we met, this time he brought some flowers")
)
assert len(ruler.patterns) == 2
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "DATE"
assert doc.ents[0].text == "last time"
assert doc.ents[1].label_ == "DATE"
assert doc.ents[1].text == "this time"
if isinstance(ruler, EntityRuler):
ruler.remove("ttime")
else:
ruler.remove_by_id("ttime")
doc = ruler(
nlp.make_doc("I saw him last time we met, this time he brought some flowers")
)
assert len(ruler.patterns) == 1
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "DATE"
assert doc.ents[0].text == "last time"
ruler.add_patterns(patterns1)
doc = ruler(
nlp.make_doc("I saw him last time we met, this time he brought some flowers")
)
assert len(ruler.patterns) == 2
assert len(doc.ents) == 2
patterns2 = [{"label": "DATE", "pattern": "another time", "id": "ttime"}]
ruler.add_patterns(patterns2)
doc = ruler(
nlp.make_doc(
"I saw him last time we met, this time he brought some flowers, another time some chocolate."
)
)
assert len(ruler.patterns) == 3
assert len(doc.ents) == 3
if isinstance(ruler, EntityRuler):
ruler.remove("ttime")
else:
ruler.remove_by_id("ttime")
doc = ruler(
nlp.make_doc(
"I saw him last time we met, this time he brought some flowers, another time some chocolate."
)
)
assert len(ruler.patterns) == 1
assert len(doc.ents) == 1