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			58 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			58 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| from typing import Optional, Callable
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| 
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| from thinc.api import Model
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| 
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| from .punctuation import TOKENIZER_PREFIXES, TOKENIZER_INFIXES
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| from .punctuation import TOKENIZER_SUFFIXES
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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 PolishLemmatizer
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| from ..tokenizer_exceptions import BASE_EXCEPTIONS
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| from ...language import Language, BaseDefaults
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| 
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| 
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| TOKENIZER_EXCEPTIONS = {
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|     exc: val for exc, val in BASE_EXCEPTIONS.items() if not exc.endswith(".")
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| }
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| 
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| 
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| class PolishDefaults(BaseDefaults):
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|     tokenizer_exceptions = TOKENIZER_EXCEPTIONS
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|     prefixes = TOKENIZER_PREFIXES
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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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|     stop_words = STOP_WORDS
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| 
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| 
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| class Polish(Language):
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|     lang = "pl"
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|     Defaults = PolishDefaults
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| 
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| 
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| @Polish.factory(
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|     "lemmatizer",
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|     assigns=["token.lemma"],
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|     default_config={
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|         "model": None,
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|         "mode": "pos_lookup",
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|         "overwrite": False,
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|         "scorer": {"@scorers": "spacy.lemmatizer_scorer.v1"},
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|     },
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|     default_score_weights={"lemma_acc": 1.0},
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| )
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| def make_lemmatizer(
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|     nlp: Language,
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|     model: Optional[Model],
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|     name: str,
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|     mode: str,
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|     overwrite: bool,
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|     scorer: Optional[Callable],
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| ):
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|     return PolishLemmatizer(
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|         nlp.vocab, model, name, mode=mode, overwrite=overwrite, scorer=scorer
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|     )
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| 
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| 
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| __all__ = ["Polish"]
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