class_docstr: For each type of NLP process there needs to be a definition.
  It includes the type of data it expects (``str``, ``List[str]``,
  ``Word``, etc.) and what field within ``Word`` it will populate.
  This base class is intended to be inherited by NLP process
  types (e.g., ``TokenizationProcess`` or ``DependencyProcess``).
class_docstr_tok: ["For","each","type","of","NLP","process","there","needs","to","be","a","definition",".","It","includes","the","type","of","data","it","expects","(","``","str","``",",","``","List","[","str","]","``",",","``","Word","``",",","etc",".",")","and","what","field","within","``","Word","``","it","will","populate",".","This","base","class","is","intended","to","be","inherited","by","NLP","process","types","(","e.g.",",","``","TokenizationProcess","``","or","``","DependencyProcess","``",")","."]
code: def run(self, input_doc: Doc) -> Doc:
      pass
  
imports: import importlib
  from abc import ABC, abstractmethod
  from collections import defaultdict
  from dataclasses import dataclass, field
  from typing import Dict, List, Optional, Type, Union
  import numpy
  import stringcase
  from cltk.morphology.morphosyntax import MorphosyntacticFeatureBundle
  from cltk.morphology.universal_dependencies_features import MorphosyntacticFeature
label_desc: Use image node_id 1 for calling the Process obj's underlying member method code with example usage: obj.run(input_doc) without return types