class_docstr: Abstract base class for lemmatizers created as a subclass of
  NLTK's SequentialBackoffTagger. Lemmatizers in this class "[tag]
  words sequentially, left to right. Tagging of individual words is
  performed by the ``choose_tag()`` method, which should be defined
  by subclasses.  If a tagger is unable to determine a tag for the
  specified token, then its backoff tagger is consulted."
  
  See: https://www.nltk.org/_modules/nltk/tag/sequential.html#SequentialBackoffTagger
  
  :type _taggers: list
  :ivar _taggers: A list of all the taggers in the backoff chain,
      inc. self.
  :type _repr: Repr object
  :ivar _repr: An instance of Repr() from reprlib to handle list
      and dict length in subclass __repr__'s
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docstr: Transform tag method into custom method for lemmatizing
  tasks. Cf. ``tag`` method above.
docstr_tok: ["Transform","tag","method","into","custom","method","for","lemmatizing","tasks",".","Cf",".","``","tag","``","method","above","."]
code: def lemmatize(self, tokens: List[str]) -> List:
      """
      Transform tag method into custom method for lemmatizing
      tasks. Cf. ``tag`` method above.
      """
      return self.tag(tokens)
  
imports: import re
  import reprlib
  from typing import Dict, List, Optional, Tuple
  from nltk.tag.sequential import RegexpTagger, SequentialBackoffTagger, TaggerI, UnigramTagger
label_desc: Use image node_id 4 for calling the SequentialBackoffLemmatizer obj's underlying member method code with example usage: obj.lemmatize(tokens) and returns: self