Add ENT_IOB key to Matcher (#9649)

* added new field

* added exception for IOb strings

* minor refinement to schema

* removed field

* fixed typo

* imported numeriacla val

* changed the code bit

* cosmetics

* added test for matcher

* set ents of moc docs

* added invalid pattern

* minor update to documentation

* blacked matcher

* added pattern validation

* add IOB vals to schema

* changed into test

* mypy compat

* cleaned left over

* added compat import

* changed type

* added compat import

* changed literal a bit

* went back to old

* made explicit type

* Update spacy/schemas.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update spacy/schemas.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* Update spacy/schemas.py

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
This commit is contained in:
Duygu Altinok 2022-01-20 13:18:39 +01:00 committed by GitHub
parent 32bd3856b3
commit 268ddf8a06
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5 changed files with 37 additions and 2 deletions

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@ -18,7 +18,7 @@ from ..tokens.doc cimport Doc, get_token_attr_for_matcher
from ..tokens.span cimport Span
from ..tokens.token cimport Token
from ..tokens.morphanalysis cimport MorphAnalysis
from ..attrs cimport ID, attr_id_t, NULL_ATTR, ORTH, POS, TAG, DEP, LEMMA, MORPH
from ..attrs cimport ID, attr_id_t, NULL_ATTR, ORTH, POS, TAG, DEP, LEMMA, MORPH, ENT_IOB
from ..schemas import validate_token_pattern
from ..errors import Errors, MatchPatternError, Warnings
@ -798,7 +798,10 @@ def _get_attr_values(spec, string_store):
attr = "SENT_START"
attr = IDS.get(attr)
if isinstance(value, str):
value = string_store.add(value)
if attr == ENT_IOB and value in Token.iob_strings():
value = Token.iob_strings().index(value)
else:
value = string_store.add(value)
elif isinstance(value, bool):
value = int(value)
elif isinstance(value, int):

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@ -1,5 +1,6 @@
from typing import Dict, List, Union, Optional, Any, Callable, Type, Tuple
from typing import Iterable, TypeVar, TYPE_CHECKING
from .compat import Literal
from enum import Enum
from pydantic import BaseModel, Field, ValidationError, validator, create_model
from pydantic import StrictStr, StrictInt, StrictFloat, StrictBool
@ -209,6 +210,7 @@ NumberValue = Union[TokenPatternNumber, StrictInt, StrictFloat]
UnderscoreValue = Union[
TokenPatternString, TokenPatternNumber, str, int, float, list, bool
]
IobValue = Literal["", "I", "O", "B", 0, 1, 2, 3]
class TokenPattern(BaseModel):
@ -222,6 +224,7 @@ class TokenPattern(BaseModel):
lemma: Optional[StringValue] = None
shape: Optional[StringValue] = None
ent_type: Optional[StringValue] = None
ent_iob: Optional[IobValue] = None
ent_id: Optional[StringValue] = None
ent_kb_id: Optional[StringValue] = None
norm: Optional[StringValue] = None

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@ -642,3 +642,30 @@ def test_matcher_no_zero_length(en_vocab):
matcher = Matcher(en_vocab)
matcher.add("TEST", [[{"TAG": "C", "OP": "?"}]])
assert len(matcher(doc)) == 0
def test_matcher_ent_iob_key(en_vocab):
"""Test that patterns with ent_iob works correctly."""
matcher = Matcher(en_vocab)
matcher.add("Rule", [[{"ENT_IOB": "I"}]])
doc1 = Doc(en_vocab, words=["I", "visited", "New", "York", "and", "California"])
doc1.ents = [Span(doc1, 2, 4, label="GPE"), Span(doc1, 5, 6, label="GPE")]
doc2 = Doc(en_vocab, words=["I", "visited", "my", "friend", "Alicia"])
doc2.ents = [Span(doc2, 4, 5, label="PERSON")]
matches1 = [doc1[start:end].text for _, start, end in matcher(doc1)]
matches2 = [doc2[start:end].text for _, start, end in matcher(doc2)]
assert len(matches1) == 1
assert matches1[0] == "York"
assert len(matches2) == 0
matcher = Matcher(en_vocab) # Test iob pattern with operators
matcher.add("Rule", [[{"ENT_IOB": "I", "OP": "+"}]])
doc = Doc(
en_vocab, words=["I", "visited", "my", "friend", "Anna", "Maria", "Esperanza"]
)
doc.ents = [Span(doc, 4, 7, label="PERSON")]
matches = [doc[start:end].text for _, start, end in matcher(doc)]
assert len(matches) == 3
assert matches[0] == "Maria"
assert matches[1] == "Maria Esperanza"
assert matches[2] == "Esperanza"

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@ -12,6 +12,7 @@ TEST_PATTERNS = [
([{"IS_PUNCT": True, "OP": "$"}], 1, 1),
([{"_": "foo"}], 1, 1),
('[{"TEXT": "foo"}, {"LOWER": "bar"}]', 1, 1),
([{"ENT_IOB": "foo"}], 1, 1),
([1, 2, 3], 3, 1),
# Bad patterns flagged outside of Matcher
([{"_": {"foo": "bar", "baz": {"IN": "foo"}}}], 2, 0), # prev: (1, 0)

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@ -44,6 +44,7 @@ rule-based matching are:
| `SPACY` | Token has a trailing space. ~~bool~~ |
|  `POS`, `TAG`, `MORPH`, `DEP`, `LEMMA`, `SHAPE` | The token's simple and extended part-of-speech tag, morphological analysis, dependency label, lemma, shape. ~~str~~ |
| `ENT_TYPE` | The token's entity label. ~~str~~ |
| `ENT_IOB` | The IOB part of the token's entity tag. ~~str~~ |
| `ENT_ID` | The token's entity ID (`ent_id`). ~~str~~ |
| `ENT_KB_ID` | The token's entity knowledge base ID (`ent_kb_id`). ~~str~~ |
| `_` <Tag variant="new">2.1</Tag> | Properties in [custom extension attributes](/usage/processing-pipelines#custom-components-attributes). ~~Dict[str, Any]~~ |