spaCy/spacy/lang/en/__init__.py

from typing import Optional

from thinc.api import Model

from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
from .stop_words import STOP_WORDS
from .lex_attrs import LEX_ATTRS
from .syntax_iterators import SYNTAX_ITERATORS
from .punctuation import TOKENIZER_INFIXES
from .lemmatizer import EnglishLemmatizer
from ...language import Language
from ...lookups import Lookups


class EnglishDefaults(Language.Defaults):
    tokenizer_exceptions = TOKENIZER_EXCEPTIONS
    infixes = TOKENIZER_INFIXES
    lex_attr_getters = LEX_ATTRS
    syntax_iterators = SYNTAX_ITERATORS
    stop_words = STOP_WORDS


class English(Language):
    lang = "en"
    Defaults = EnglishDefaults


@English.factory(
    "lemmatizer",
    assigns=["token.lemma"],
    default_config={"model": None, "mode": "rule", "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 = EnglishLemmatizer.load_lookups(nlp.lang, mode, lookups)
    return EnglishLemmatizer(nlp.vocab, model, name, mode=mode, lookups=lookups)


__all__ = ["English"]