add fuzzy param to EntityMatcher

This commit is contained in:
Kevin Humphreys 2022-08-24 13:13:27 +02:00
parent dacfb57b03
commit 66e9fdd246

View File

@ -28,6 +28,7 @@ PatternType = Dict[str, Union[str, List[Dict[str, Any]]]]
"overwrite_ents": False,
"ent_id_sep": DEFAULT_ENT_ID_SEP,
"scorer": {"@scorers": "spacy.entity_ruler_scorer.v1"},
"fuzzy": None,
},
default_score_weights={
"ents_f": 1.0,
@ -44,6 +45,7 @@ def make_entity_ruler(
overwrite_ents: bool,
ent_id_sep: str,
scorer: Optional[Callable],
fuzzy: Optional[float],
):
return EntityRuler(
nlp,
@ -53,6 +55,7 @@ def make_entity_ruler(
overwrite_ents=overwrite_ents,
ent_id_sep=ent_id_sep,
scorer=scorer,
fuzzy=fuzzy,
)
@ -87,6 +90,7 @@ class EntityRuler(Pipe):
ent_id_sep: str = DEFAULT_ENT_ID_SEP,
patterns: Optional[List[PatternType]] = None,
scorer: Optional[Callable] = entity_ruler_score,
fuzzy: Optional[float] = None,
) -> None:
"""Initialize the entity ruler. If patterns are supplied here, they
need to be a list of dictionaries with a `"label"` and `"pattern"`
@ -118,7 +122,7 @@ class EntityRuler(Pipe):
self.token_patterns = defaultdict(list) # type: ignore
self.phrase_patterns = defaultdict(list) # type: ignore
self._validate = validate
self.matcher = Matcher(nlp.vocab, validate=validate)
self.matcher = Matcher(nlp.vocab, validate=validate, fuzzy=fuzzy)
self.phrase_matcher_attr = phrase_matcher_attr
self.phrase_matcher = PhraseMatcher(
nlp.vocab, attr=self.phrase_matcher_attr, validate=validate
@ -128,6 +132,7 @@ class EntityRuler(Pipe):
if patterns is not None:
self.add_patterns(patterns)
self.scorer = scorer
self.fuzzy = fuzzy
def __len__(self) -> int:
"""The number of all patterns added to the entity ruler."""
@ -338,7 +343,7 @@ class EntityRuler(Pipe):
self.token_patterns = defaultdict(list)
self.phrase_patterns = defaultdict(list)
self._ent_ids = defaultdict(tuple)
self.matcher = Matcher(self.nlp.vocab, validate=self._validate)
self.matcher = Matcher(self.nlp.vocab, validate=self._validate, fuzzy=self.fuzzy)
self.phrase_matcher = PhraseMatcher(
self.nlp.vocab, attr=self.phrase_matcher_attr, validate=self._validate
)