code: def _pymorphy_lookup_lemmatize(self, token: Token) -> List[str]:
      string = token.text
      analyses = self._morph.parse(string)
      # often multiple forms would derive from the same normal form
      # thus check _unique_ normal forms
      normal_forms = set([an.normal_form for an in analyses])
      if len(normal_forms) == 1:
          return [next(iter(normal_forms))]
      return [string]
  
file_path: spacy/spacy/lang/ru/lemmatizer.py
imports: from typing import Callable, Dict, List, Optional, Tuple
  from thinc.api import Model
  from ...pipeline import Lemmatizer
  from ...pipeline.lemmatizer import lemmatizer_score
  from ...symbols import POS
  from ...tokens import Token
  from ...vocab import Vocab
label_desc: Use image node_id 3 for calling the RussianLemmatizer obj's underlying member method code with example usage: obj._pymorphy_lookup_lemmatize(token) and returns: list, list