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spaCy/spacy/tests/pipeline/test_span_ruler.py
Adriane Boyd a322d6d5f2
Add SpanRuler component (#9880) 
* Add SpanRuler component

Add a `SpanRuler` component similar to `EntityRuler` that saves a list
of matched spans to `Doc.spans[spans_key]`. The matches from the token
and phrase matchers are deduplicated and sorted before assignment but
are not otherwise filtered.

* Update spacy/pipeline/span_ruler.py

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

* Fix cast

* Add self.key property

* Use number of patterns as length

* Remove patterns kwarg from init

* Update spacy/tests/pipeline/test_span_ruler.py

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

* Add options for spans filter and setting to ents

* Add `spans_filter` option as a registered function'
* Make `spans_key` optional and if `None`, set to `doc.ents` instead of
`doc.spans[spans_key]`.

* Update and generalize tests

* Add test for setting doc.ents, fix key property type

* Fix typing

* Allow independent doc.spans and doc.ents

* If `spans_key` is set, set `doc.spans` with `spans_filter`.
* If `annotate_ents` is set, set `doc.ents` with `ents_fitler`.
  * Use `util.filter_spans` by default as `ents_filter`.
  * Use a custom warning if the filter does not work for `doc.ents`.

* Enable use of SpanC.id in Span

* Support id in SpanRuler as Span.id

* Update types

* `id` can only be provided as string (already by `PatternType`
definition)

* Update all uses of Span.id/ent_id in Doc

* Rename Span id kwarg to span_id

* Update types and docs

* Add ents filter to mimic EntityRuler overwrite_ents

* Refactor `ents_filter` to take `entities, spans` args for more
  filtering options
* Give registered filters more descriptive names
* Allow registered `filter_spans` filter
  (`spacy.first_longest_spans_filter.v1`) to take any number of
  `Iterable[Span]` objects as args so it can be used for spans filter
  or ents filter

* Implement future entity ruler as span ruler

Implement a compatible `entity_ruler` as `future_entity_ruler` using
`SpanRuler` as the underlying component:
* Add `sort_key` and `sort_reverse` to allow the sorting behavior to be
  customized. (Necessary for the same sorting/filtering as in
  `EntityRuler`.)
* Implement `overwrite_overlapping_ents_filter` and
  `preserve_existing_ents_filter` to support
  `EntityRuler.overwrite_ents` settings.
* Add `remove_by_id` to support `EntityRuler.remove` functionality.
* Refactor `entity_ruler` tests to parametrize all tests to test both
  `entity_ruler` and `future_entity_ruler`
* Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns`
  properties.

Additional changes:

* Move all config settings to top-level attributes to avoid duplicating
  settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of
  casting.)

* Format

* Fix filter make method name

* Refactor to use same error for removing by label or ID

* Also provide existing spans to spans filter

* Support ids property

* Remove token_patterns and phrase_patterns

* Update docstrings

* Add span ruler docs

* Fix types

* Apply suggestions from code review

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

* Move sorting into filters

* Check for all tokens in seen tokens in entity ruler filters

* Remove registered sort key

* Set Token.ent_id in a backwards-compatible way in Doc.set_ents

* Remove sort options from API docs

* Update docstrings

* Rename entity ruler filters

* Fix and parameterize scoring

* Add id to Span API docs

* Fix typo in API docs

* Include explicit labeled=True for scorer

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2022-06-02 13:12:53 +02:00

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import pytest
import spacy
from spacy import registry
from spacy.errors import MatchPatternError
from spacy.tokens import Span
from spacy.training import Example
from spacy.tests.util import make_tempdir
from thinc.api import NumpyOps, get_current_ops
@pytest.fixture
@registry.misc("span_ruler_patterns")
def patterns():
return [
{"label": "HELLO", "pattern": "hello world", "id": "hello1"},
{"label": "BYE", "pattern": [{"LOWER": "bye"}, {"LOWER": "bye"}]},
{"label": "HELLO", "pattern": [{"ORTH": "HELLO"}], "id": "hello2"},
{"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]},
{"label": "TECH_ORG", "pattern": "Apple"},
{"label": "TECH_ORG", "pattern": "Microsoft"},
]
@pytest.fixture
def overlapping_patterns():
return [
{"label": "FOOBAR", "pattern": "foo bar"},
{"label": "BARBAZ", "pattern": "bar baz"},
]
@pytest.fixture
def person_org_patterns():
return [
{"label": "PERSON", "pattern": "Dina"},
{"label": "ORG", "pattern": "ACME"},
{"label": "ORG", "pattern": "ACM"},
]
@pytest.fixture
def person_org_date_patterns(person_org_patterns):
return person_org_patterns + [{"label": "DATE", "pattern": "June 14th"}]
def test_span_ruler_add_empty(patterns):
"""Test that patterns don't get added excessively."""
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_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
def test_span_ruler_init(patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 4
assert "HELLO" in ruler
assert "BYE" in ruler
doc = nlp("hello world bye bye")
assert len(doc.spans["ruler"]) == 2
assert doc.spans["ruler"][0].label_ == "HELLO"
assert doc.spans["ruler"][0].id_ == "hello1"
assert doc.spans["ruler"][1].label_ == "BYE"
assert doc.spans["ruler"][1].id_ == ""
def test_span_ruler_no_patterns_warns():
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
assert len(ruler) == 0
assert len(ruler.labels) == 0
assert nlp.pipe_names == ["span_ruler"]
with pytest.warns(UserWarning):
doc = nlp("hello world bye bye")
assert len(doc.spans["ruler"]) == 0
def test_span_ruler_init_patterns(patterns):
# initialize with patterns
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
assert len(ruler.labels) == 0
ruler.initialize(lambda: [], patterns=patterns)
assert len(ruler.labels) == 4
doc = nlp("hello world bye bye")
assert doc.spans["ruler"][0].label_ == "HELLO"
assert doc.spans["ruler"][1].label_ == "BYE"
nlp.remove_pipe("span_ruler")
# initialize with patterns from misc registry
nlp.config["initialize"]["components"]["span_ruler"] = {
"patterns": {"@misc": "span_ruler_patterns"}
}
ruler = nlp.add_pipe("span_ruler")
assert len(ruler.labels) == 0
nlp.initialize()
assert len(ruler.labels) == 4
doc = nlp("hello world bye bye")
assert doc.spans["ruler"][0].label_ == "HELLO"
assert doc.spans["ruler"][1].label_ == "BYE"
def test_span_ruler_init_clear(patterns):
"""Test that initialization clears patterns."""
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(patterns)
assert len(ruler.labels) == 4
ruler.initialize(lambda: [])
assert len(ruler.labels) == 0
def test_span_ruler_clear(patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(patterns)
assert len(ruler.labels) == 4
doc = nlp("hello world")
assert len(doc.spans["ruler"]) == 1
ruler.clear()
assert len(ruler.labels) == 0
with pytest.warns(UserWarning):
doc = nlp("hello world")
assert len(doc.spans["ruler"]) == 0
def test_span_ruler_existing(patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler", config={"overwrite": False})
ruler.add_patterns(patterns)
doc = nlp.make_doc("OH HELLO WORLD bye bye")
doc.spans["ruler"] = [doc[0:2]]
doc = nlp(doc)
assert len(doc.spans["ruler"]) == 3
assert doc.spans["ruler"][0] == doc[0:2]
assert doc.spans["ruler"][1].label_ == "HELLO"
assert doc.spans["ruler"][1].id_ == "hello2"
assert doc.spans["ruler"][2].label_ == "BYE"
assert doc.spans["ruler"][2].id_ == ""
def test_span_ruler_existing_overwrite(patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler", config={"overwrite": True})
ruler.add_patterns(patterns)
doc = nlp.make_doc("OH HELLO WORLD bye bye")
doc.spans["ruler"] = [doc[0:2]]
doc = nlp(doc)
assert len(doc.spans["ruler"]) == 2
assert doc.spans["ruler"][0].label_ == "HELLO"
assert doc.spans["ruler"][0].text == "HELLO"
assert doc.spans["ruler"][1].label_ == "BYE"
def test_span_ruler_serialize_bytes(patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 4
ruler_bytes = ruler.to_bytes()
new_nlp = spacy.blank("xx")
new_ruler = new_nlp.add_pipe("span_ruler")
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)
def test_span_ruler_validate():
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
validated_ruler = nlp.add_pipe(
"span_ruler", name="validated_span_ruler", config={"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])
def test_span_ruler_properties(patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler", config={"overwrite": True})
ruler.add_patterns(patterns)
assert sorted(ruler.labels) == sorted(set([p["label"] for p in patterns]))
def test_span_ruler_overlapping_spans(overlapping_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(overlapping_patterns)
doc = ruler(nlp.make_doc("foo bar baz"))
assert len(doc.spans["ruler"]) == 2
assert doc.spans["ruler"][0].label_ == "FOOBAR"
assert doc.spans["ruler"][1].label_ == "BARBAZ"
def test_span_ruler_scorer(overlapping_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(overlapping_patterns)
text = "foo bar baz"
pred_doc = ruler(nlp.make_doc(text))
assert len(pred_doc.spans["ruler"]) == 2
assert pred_doc.spans["ruler"][0].label_ == "FOOBAR"
assert pred_doc.spans["ruler"][1].label_ == "BARBAZ"
ref_doc = nlp.make_doc(text)
ref_doc.spans["ruler"] = [Span(ref_doc, 0, 2, label="FOOBAR")]
scores = nlp.evaluate([Example(pred_doc, ref_doc)])
assert scores["spans_ruler_p"] == 0.5
assert scores["spans_ruler_r"] == 1.0
@pytest.mark.parametrize("n_process", [1, 2])
def test_span_ruler_multiprocessing(n_process):
if isinstance(get_current_ops, NumpyOps) or n_process < 2:
texts = ["I enjoy eating Pizza Hut pizza."]
patterns = [{"label": "FASTFOOD", "pattern": "Pizza Hut"}]
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(patterns)
for doc in nlp.pipe(texts, n_process=2):
for ent in doc.spans["ruler"]:
assert ent.label_ == "FASTFOOD"
def test_span_ruler_serialize_dir(patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_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
def test_span_ruler_remove_basic(person_org_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(person_org_patterns)
doc = ruler(nlp.make_doc("Dina went to school"))
assert len(ruler.patterns) == 3
assert len(doc.spans["ruler"]) == 1
assert doc.spans["ruler"][0].label_ == "PERSON"
assert doc.spans["ruler"][0].text == "Dina"
ruler.remove("PERSON")
doc = ruler(nlp.make_doc("Dina went to school"))
assert len(doc.spans["ruler"]) == 0
assert len(ruler.patterns) == 2
def test_span_ruler_remove_nonexisting_pattern(person_org_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(person_org_patterns)
assert len(ruler.patterns) == 3
with pytest.raises(ValueError):
ruler.remove("NE")
with pytest.raises(ValueError):
ruler.remove_by_id("NE")
def test_span_ruler_remove_several_patterns(person_org_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(person_org_patterns)
doc = ruler(nlp.make_doc("Dina founded the company ACME."))
assert len(ruler.patterns) == 3
assert len(doc.spans["ruler"]) == 2
assert doc.spans["ruler"][0].label_ == "PERSON"
assert doc.spans["ruler"][0].text == "Dina"
assert doc.spans["ruler"][1].label_ == "ORG"
assert doc.spans["ruler"][1].text == "ACME"
ruler.remove("PERSON")
doc = ruler(nlp.make_doc("Dina founded the company ACME"))
assert len(ruler.patterns) == 2
assert len(doc.spans["ruler"]) == 1
assert doc.spans["ruler"][0].label_ == "ORG"
assert doc.spans["ruler"][0].text == "ACME"
ruler.remove("ORG")
with pytest.warns(UserWarning):
doc = ruler(nlp.make_doc("Dina founded the company ACME"))
assert len(ruler.patterns) == 0
assert len(doc.spans["ruler"]) == 0
def test_span_ruler_remove_patterns_in_a_row(person_org_date_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(person_org_date_patterns)
doc = ruler(nlp.make_doc("Dina founded the company ACME on June 14th"))
assert len(doc.spans["ruler"]) == 3
assert doc.spans["ruler"][0].label_ == "PERSON"
assert doc.spans["ruler"][0].text == "Dina"
assert doc.spans["ruler"][1].label_ == "ORG"
assert doc.spans["ruler"][1].text == "ACME"
assert doc.spans["ruler"][2].label_ == "DATE"
assert doc.spans["ruler"][2].text == "June 14th"
ruler.remove("ORG")
ruler.remove("DATE")
doc = ruler(nlp.make_doc("Dina went to school"))
assert len(doc.spans["ruler"]) == 1
def test_span_ruler_remove_all_patterns(person_org_date_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
ruler.add_patterns(person_org_date_patterns)
assert len(ruler.patterns) == 4
ruler.remove("PERSON")
assert len(ruler.patterns) == 3
ruler.remove("ORG")
assert len(ruler.patterns) == 1
ruler.remove("DATE")
assert len(ruler.patterns) == 0
with pytest.warns(UserWarning):
doc = ruler(nlp.make_doc("Dina founded the company ACME on June 14th"))
assert len(doc.spans["ruler"]) == 0
def test_span_ruler_remove_and_add():
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler")
patterns1 = [{"label": "DATE1", "pattern": "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) == 1
assert len(doc.spans["ruler"]) == 1
assert doc.spans["ruler"][0].label_ == "DATE1"
assert doc.spans["ruler"][0].text == "last time"
patterns2 = [{"label": "DATE2", "pattern": "this time"}]
ruler.add_patterns(patterns2)
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.spans["ruler"]) == 2
assert doc.spans["ruler"][0].label_ == "DATE1"
assert doc.spans["ruler"][0].text == "last time"
assert doc.spans["ruler"][1].label_ == "DATE2"
assert doc.spans["ruler"][1].text == "this time"
ruler.remove("DATE1")
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.spans["ruler"]) == 1
assert doc.spans["ruler"][0].label_ == "DATE2"
assert doc.spans["ruler"][0].text == "this 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.spans["ruler"]) == 2
patterns3 = [{"label": "DATE3", "pattern": "another time"}]
ruler.add_patterns(patterns3)
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.spans["ruler"]) == 3
ruler.remove("DATE3")
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) == 2
assert len(doc.spans["ruler"]) == 2
def test_span_ruler_spans_filter(overlapping_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe(
"span_ruler",
config={"spans_filter": {"@misc": "spacy.first_longest_spans_filter.v1"}},
)
ruler.add_patterns(overlapping_patterns)
doc = ruler(nlp.make_doc("foo bar baz"))
assert len(doc.spans["ruler"]) == 1
assert doc.spans["ruler"][0].label_ == "FOOBAR"
def test_span_ruler_ents_default_filter(overlapping_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe("span_ruler", config={"annotate_ents": True})
ruler.add_patterns(overlapping_patterns)
doc = ruler(nlp.make_doc("foo bar baz"))
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "FOOBAR"
def test_span_ruler_ents_overwrite_filter(overlapping_patterns):
nlp = spacy.blank("xx")
ruler = nlp.add_pipe(
"span_ruler",
config={
"annotate_ents": True,
"overwrite": False,
"ents_filter": {"@misc": "spacy.prioritize_new_ents_filter.v1"},
},
)
ruler.add_patterns(overlapping_patterns)
# overlapping ents are clobbered, non-overlapping ents are preserved
doc = nlp.make_doc("foo bar baz a b c")
doc.ents = [Span(doc, 1, 3, label="BARBAZ"), Span(doc, 3, 6, label="ABC")]
doc = ruler(doc)
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "FOOBAR"
assert doc.ents[1].label_ == "ABC"
def test_span_ruler_ents_bad_filter(overlapping_patterns):
@registry.misc("test_pass_through_filter")
def make_pass_through_filter():
def pass_through_filter(spans1, spans2):
return spans1 + spans2
return pass_through_filter
nlp = spacy.blank("xx")
ruler = nlp.add_pipe(
"span_ruler",
config={
"annotate_ents": True,
"ents_filter": {"@misc": "test_pass_through_filter"},
},
)
ruler.add_patterns(overlapping_patterns)
with pytest.raises(ValueError):
ruler(nlp.make_doc("foo bar baz"))
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