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	* Add Lemmatizer and simplify related components * Add `Lemmatizer` pipe with `lookup` and `rule` modes using the `Lookups` tables. * Reduce `Tagger` to a simple tagger that sets `Token.tag` (no pos or lemma) * Reduce `Morphology` to only keep track of morph tags (no tag map, lemmatizer, or morph rules) * Remove lemmatizer from `Vocab` * Adjust many many tests Differences: * No default lookup lemmas * No special treatment of TAG in `from_array` and similar required * Easier to modify labels in a `Tagger` * No extra strings added from morphology / tag map * Fix test * Initial fix for Lemmatizer config/serialization * Adjust init test to be more generic * Adjust init test to force empty Lookups * Add simple cache to rule-based lemmatizer * Convert language-specific lemmatizers Convert language-specific lemmatizers to component lemmatizers. Remove previous lemmatizer class. * Fix French and Polish lemmatizers * Remove outdated UPOS conversions * Update Russian lemmatizer init in tests * Add minimal init/run tests for custom lemmatizers * Add option to overwrite existing lemmas * Update mode setting, lookup loading, and caching * Make `mode` an immutable property * Only enforce strict `load_lookups` for known supported modes * Move caching into individual `_lemmatize` methods * Implement strict when lang is not found in lookups * Fix tables/lookups in make_lemmatizer * Reallow provided lookups and allow for stricter checks * Add lookups asset to all Lemmatizer pipe tests * Rename lookups in lemmatizer init test * Clean up merge * Refactor lookup table loading * Add helper from `load_lemmatizer_lookups` that loads required and optional lookups tables based on settings provided by a config. Additional slight refactor of lookups: * Add `Lookups.set_table` to set a table from a provided `Table` * Reorder class definitions to be able to specify type as `Table` * Move registry assets into test methods * Refactor lookups tables config Use class methods within `Lemmatizer` to provide the config for particular modes and to load the lookups from a config. * Add pipe and score to lemmatizer * Simplify Tagger.score * Add missing import * Clean up imports and auto-format * Remove unused kwarg * Tidy up and auto-format * Update docstrings for Lemmatizer Update docstrings for Lemmatizer. Additionally modify `is_base_form` API to take `Token` instead of individual features. * Update docstrings * Remove tag map values from Tagger.add_label * Update API docs * Fix relative link in Lemmatizer API docs
		
			
				
	
	
		
			111 lines
		
	
	
		
			3.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			111 lines
		
	
	
		
			3.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| from typing import Optional, Any, Dict
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| from thinc.api import Config
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| 
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| from .stop_words import STOP_WORDS
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| from .tag_map import TAG_MAP
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| from .lex_attrs import LEX_ATTRS
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| from ...language import Language
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| from ...tokens import Doc
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| from ...compat import copy_reg
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| from ...symbols import POS
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| from ...util import DummyTokenizer, registry
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| 
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| 
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| DEFAULT_CONFIG = """
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| [nlp]
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| 
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| [nlp.tokenizer]
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| @tokenizers = "spacy.ko.KoreanTokenizer"
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| """
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| 
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| 
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| @registry.tokenizers("spacy.ko.KoreanTokenizer")
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| def create_tokenizer():
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|     def korean_tokenizer_factory(nlp):
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|         return KoreanTokenizer(nlp)
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| 
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|     return korean_tokenizer_factory
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| 
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| 
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| class KoreanTokenizer(DummyTokenizer):
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|     def __init__(self, nlp: Optional[Language] = None):
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|         self.vocab = nlp.vocab
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|         MeCab = try_mecab_import()
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|         self.mecab_tokenizer = MeCab("-F%f[0],%f[7]")
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| 
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|     def __del__(self):
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|         self.mecab_tokenizer.__del__()
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| 
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|     def __call__(self, text: str) -> Doc:
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|         dtokens = list(self.detailed_tokens(text))
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|         surfaces = [dt["surface"] for dt in dtokens]
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|         doc = Doc(self.vocab, words=surfaces, spaces=list(check_spaces(text, surfaces)))
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|         for token, dtoken in zip(doc, dtokens):
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|             first_tag, sep, eomi_tags = dtoken["tag"].partition("+")
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|             token.tag_ = first_tag  # stem(어간) or pre-final(선어말 어미)
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|             token.pos = TAG_MAP[token.tag_][POS]
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|             token.lemma_ = dtoken["lemma"]
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|         doc.user_data["full_tags"] = [dt["tag"] for dt in dtokens]
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|         return doc
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| 
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|     def detailed_tokens(self, text: str) -> Dict[str, Any]:
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|         # 품사 태그(POS)[0], 의미 부류(semantic class)[1],	종성 유무(jongseong)[2], 읽기(reading)[3],
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|         # 타입(type)[4], 첫번째 품사(start pos)[5],	마지막 품사(end pos)[6], 표현(expression)[7], *
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|         for node in self.mecab_tokenizer.parse(text, as_nodes=True):
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|             if node.is_eos():
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|                 break
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|             surface = node.surface
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|             feature = node.feature
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|             tag, _, expr = feature.partition(",")
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|             lemma, _, remainder = expr.partition("/")
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|             if lemma == "*":
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|                 lemma = surface
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|             yield {"surface": surface, "lemma": lemma, "tag": tag}
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| 
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| 
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| class KoreanDefaults(Language.Defaults):
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|     config = Config().from_str(DEFAULT_CONFIG)
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|     lex_attr_getters = LEX_ATTRS
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|     stop_words = STOP_WORDS
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|     writing_system = {"direction": "ltr", "has_case": False, "has_letters": False}
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| 
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| 
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| class Korean(Language):
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|     lang = "ko"
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|     Defaults = KoreanDefaults
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| 
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| 
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| def try_mecab_import() -> None:
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|     try:
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|         from natto import MeCab
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| 
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|         return MeCab
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|     except ImportError:
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|         raise ImportError(
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|             "Korean support requires [mecab-ko](https://bitbucket.org/eunjeon/mecab-ko/src/master/README.md), "
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|             "[mecab-ko-dic](https://bitbucket.org/eunjeon/mecab-ko-dic), "
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|             "and [natto-py](https://github.com/buruzaemon/natto-py)"
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|         ) from None
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| 
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| 
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| def check_spaces(text, tokens):
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|     prev_end = -1
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|     start = 0
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|     for token in tokens:
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|         idx = text.find(token, start)
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|         if prev_end > 0:
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|             yield prev_end != idx
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|         prev_end = idx + len(token)
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|         start = prev_end
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|     if start > 0:
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|         yield False
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| 
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| 
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| def pickle_korean(instance):
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|     return Korean, tuple()
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| 
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| 
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| copy_reg.pickle(Korean, pickle_korean)
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| 
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| __all__ = ["Korean"]
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