mirror of
https://github.com/explosion/spaCy.git
synced 2025-01-29 18:54:07 +03:00
d17afb4826
* Initial Spanish lemmatizer * Handle merged verb+pron(s) multi-word tokens * Use VERB for AUX rule lookup * Add morph to lemma cache key * Fix aux lookups, minor refactoring * Improve verb+pron handling * Move verb+pron handling into its own method * Check for exceptions (primarily for se) * Collect pronouns in the same (not reversed) order * Only add modified possible lemmas
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
from typing import Optional
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from thinc.api import Model
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from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
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from .stop_words import STOP_WORDS
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from .lex_attrs import LEX_ATTRS
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from .lemmatizer import SpanishLemmatizer
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from .syntax_iterators import SYNTAX_ITERATORS
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from .punctuation import TOKENIZER_INFIXES, TOKENIZER_SUFFIXES
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from ...language import Language
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class SpanishDefaults(Language.Defaults):
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tokenizer_exceptions = TOKENIZER_EXCEPTIONS
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infixes = TOKENIZER_INFIXES
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suffixes = TOKENIZER_SUFFIXES
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lex_attr_getters = LEX_ATTRS
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syntax_iterators = SYNTAX_ITERATORS
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stop_words = STOP_WORDS
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class Spanish(Language):
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lang = "es"
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Defaults = SpanishDefaults
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@Spanish.factory(
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"lemmatizer",
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assigns=["token.lemma"],
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default_config={"model": None, "mode": "rule", "overwrite": False},
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default_score_weights={"lemma_acc": 1.0},
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)
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def make_lemmatizer(nlp: Language, model: Optional[Model], name: str, mode: str, overwrite: bool):
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return SpanishLemmatizer(nlp.vocab, model, name, mode=mode, overwrite=overwrite)
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__all__ = ["Spanish"]
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