class_docstr: Class which prettifies morphological tagger output to 4-column
  or 10-column (Universal Dependencies) format.
  Args:
      format_mode: output format,
          in `basic` mode output data contains 4 columns (id, word, pos, features),
          in `conllu` or `ud` mode it contains 10 columns:
          id, word, lemma, pos, xpos, feats, head, deprel, deps, misc
          (see http://universaldependencies.org/format.html for details)
          Only id, word, lemma, tag and pos columns are predicted in current version,
          other columns are filled by `_` value.
      begin: a string to append in the beginning
      end: a string to append in the end
      sep: separator between word analyses
class_docstr_tok: ["Class","which","prettifies","morphological","tagger","output","to","4-column","or","10-column","(","Universal","Dependencies",")","format",".","Args",":","format_mode",":","output","format",",","in","`","basic","`","mode","output","data","contains","4","columns","(","id",",","word",",","pos",",","features",")",",","in","`","conllu","`","or","`","ud","`","mode","it","contains","10","columns",":","id",",","word",",","lemma",",","pos",",","xpos",",","feats",",","head",",","deprel",",","deps",",","misc","(","see","http",":","\/\/universaldependencies.org\/format.html","for","details",")","Only","id",",","word",",","lemma",",","tag","and","pos","columns","are","predicted","in","current","version",",","other","columns","are","filled","by","`","_","`","value",".","begin",":","a","string","to","append","in","the","beginning","end",":","a","string","to","append","in","the","end","sep",":","separator","between","word","analyses"]
code: def __init__(
      self,
      return_string: bool = True,
      begin: str = "",
      end: str = "\n",
      sep: str = "\n",
      **kwargs,
  ) -> None:
      super().__init__(return_string, begin, end, sep, **kwargs)
      self.format_string = "{}\t{}\t{}\t{}\t_\t{}\t_\t_\t_\t_"
  
file_path: DeepPavlov/deeppavlov/models/morpho_syntax_parser/syntax_parsing.py
imports: from typing import List, Optional, Tuple, Union
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.models.component import Component
label_desc: Use image node_id 1 to create a new LemmatizedOutputPrettifier object from inherited base classes: OutputPrettifier with example: obj = LemmatizedOutputPrettifier(return_string, begin, end, sep)