mirror of https://github.com/explosion/spaCy.git
59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
from collections import OrderedDict
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from typing import List
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from ...pipeline import Lemmatizer
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from ...tokens import Token
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class MacedonianLemmatizer(Lemmatizer):
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def rule_lemmatize(self, token: Token) -> List[str]:
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string = token.text
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univ_pos = token.pos_.lower()
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if univ_pos in ("", "eol", "space"):
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return [string.lower()]
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if string[-3:] == "јќи":
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string = string[:-3]
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univ_pos = "verb"
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index_table = self.lookups.get_table("lemma_index", {})
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exc_table = self.lookups.get_table("lemma_exc", {})
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rules_table = self.lookups.get_table("lemma_rules", {})
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if not any(
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(
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index_table.get(univ_pos),
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exc_table.get(univ_pos),
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rules_table.get(univ_pos),
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)
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):
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if univ_pos == "propn":
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return [string]
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else:
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return [string.lower()]
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index = index_table.get(univ_pos, {})
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exceptions = exc_table.get(univ_pos, {})
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rules = rules_table.get(univ_pos, [])
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orig = string
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string = string.lower()
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forms = []
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for old, new in rules:
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if string.endswith(old):
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form = string[: len(string) - len(old)] + new
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if not form:
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continue
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if form in index or not form.isalpha():
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forms.append(form)
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forms = list(OrderedDict.fromkeys(forms))
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for form in exceptions.get(string, []):
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if form not in forms:
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forms.insert(0, form)
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if not forms:
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forms.append(orig)
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return forms
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