spaCy/spacy/lang/pl/__init__.py
Adriane Boyd abd3f2b65a
Rename Polish lemmatizer method (#5960)
Rename Polish lemmatizer method to `pos_lookup` to distinguish it from
pure token-based lookup methods.
2020-08-25 00:22:27 +02:00

53 lines
1.3 KiB
Python

from typing import Optional
from thinc.api import Model
from .punctuation import TOKENIZER_PREFIXES, TOKENIZER_INFIXES
from .punctuation import TOKENIZER_SUFFIXES
from .stop_words import STOP_WORDS
from .lex_attrs import LEX_ATTRS
from .lemmatizer import PolishLemmatizer
from ..tokenizer_exceptions import BASE_EXCEPTIONS
from ...lookups import Lookups
from ...language import Language
TOKENIZER_EXCEPTIONS = {
exc: val for exc, val in BASE_EXCEPTIONS.items() if not exc.endswith(".")
}
class PolishDefaults(Language.Defaults):
tokenizer_exceptions = TOKENIZER_EXCEPTIONS
prefixes = TOKENIZER_PREFIXES
infixes = TOKENIZER_INFIXES
suffixes = TOKENIZER_SUFFIXES
lex_attr_getters = LEX_ATTRS
stop_words = STOP_WORDS
class Polish(Language):
lang = "pl"
Defaults = PolishDefaults
@Polish.factory(
"lemmatizer",
assigns=["token.lemma"],
default_config={"model": None, "mode": "pos_lookup", "lookups": None},
scores=["lemma_acc"],
default_score_weights={"lemma_acc": 1.0},
)
def make_lemmatizer(
nlp: Language,
model: Optional[Model],
name: str,
mode: str,
lookups: Optional[Lookups],
):
lookups = PolishLemmatizer.load_lookups(nlp.lang, mode, lookups)
return PolishLemmatizer(nlp.vocab, model, name, mode=mode, lookups=lookups)
__all__ = ["Polish"]