mirror of
				https://github.com/explosion/spaCy.git
				synced 2025-10-30 23:47:31 +03:00 
			
		
		
		
	
		
			
				
	
	
		
			39 lines
		
	
	
		
			1.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			39 lines
		
	
	
		
			1.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| 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
 | |
| 
 | |
| 
 | |
| 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", "overwrite": False},
 | |
|     default_score_weights={"lemma_acc": 1.0},
 | |
| )
 | |
| def make_lemmatizer(
 | |
|     nlp: Language, model: Optional[Model], name: str, mode: str, overwrite: bool
 | |
| ):
 | |
|     return EnglishLemmatizer(nlp.vocab, model, name, mode=mode, overwrite=overwrite)
 | |
| 
 | |
| 
 | |
| __all__ = ["English"]
 |