spaCy/spacy/lang/it/__init__.py
Duygu Altinok 25bd9f9d48
Noun chunks for Italian (#9662)
* added it vocab

* copied portuguese

* added possessive determiner

* added conjed Nps

* added nmoded Nps

* test misc

* more examples

* fixed typo

* fixed parenth

* fixed comma

* comma fix

* added syntax iters

* fix some index problems

* fixed index

* corrected heads for test case

* fixed tets case

* fixed determiner gender

* cleaned left over

* added example with apostophe
2021-11-23 16:29:25 +01:00

50 lines
1.2 KiB
Python

from typing import Optional, Callable
from thinc.api import Model
from .stop_words import STOP_WORDS
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
from .punctuation import TOKENIZER_PREFIXES, TOKENIZER_INFIXES
from ...language import Language, BaseDefaults
from .lemmatizer import ItalianLemmatizer
from .syntax_iterators import SYNTAX_ITERATORS
class ItalianDefaults(BaseDefaults):
tokenizer_exceptions = TOKENIZER_EXCEPTIONS
prefixes = TOKENIZER_PREFIXES
infixes = TOKENIZER_INFIXES
stop_words = STOP_WORDS
syntax_iterators = SYNTAX_ITERATORS
class Italian(Language):
lang = "it"
Defaults = ItalianDefaults
@Italian.factory(
"lemmatizer",
assigns=["token.lemma"],
default_config={
"model": None,
"mode": "pos_lookup",
"overwrite": False,
"scorer": {"@scorers": "spacy.lemmatizer_scorer.v1"},
},
default_score_weights={"lemma_acc": 1.0},
)
def make_lemmatizer(
nlp: Language,
model: Optional[Model],
name: str,
mode: str,
overwrite: bool,
scorer: Optional[Callable],
):
return ItalianLemmatizer(
nlp.vocab, model, name, mode=mode, overwrite=overwrite, scorer=scorer
)
__all__ = ["Italian"]