class_docstr: Converts a ``CHUNK`` type column back into ``DOCUMENT``.
  
  Useful when trying to re-tokenize or do further analysis on a ``CHUNK`` result.
  
  ====================== ======================
  Input Annotation types Output Annotation type
  ====================== ======================
  ``CHUNK``              ``DOCUMENT``
  ====================== ======================
  
  Parameters
  ----------
  None
  
  Examples
  --------
  >>> import sparknlp
  >>> from sparknlp.base import *
  >>> from sparknlp.pretrained import PretrainedPipeline
  
  Location entities are extracted and converted back into ``DOCUMENT`` type for
  further processing.
  
  >>> data = spark.createDataFrame([[1, "New York and New Jersey aren't that far apart actually."]]).toDF("id", "text")
  
  Define pretrained pipeline that extracts Named Entities amongst other things
  and apply `Chunk2Doc` on it.
  
  >>> pipeline = PretrainedPipeline("explain_document_dl")
  >>> chunkToDoc = Chunk2Doc().setInputCols("entities").setOutputCol("chunkConverted")
  >>> explainResult = pipeline.transform(data)
  
  Show results.
  
  >>> result = chunkToDoc.transform(explainResult)
  >>> result.selectExpr("explode(chunkConverted)").show(truncate=False)
  +------------------------------------------------------------------------------+
  |col                                                                           |
  +------------------------------------------------------------------------------+
  |[document, 0, 7, New York, [entity -> LOC, sentence -> 0, chunk -> 0], []]    |
  |[document, 13, 22, New Jersey, [entity -> LOC, sentence -> 0, chunk -> 1], []]|
  +------------------------------------------------------------------------------+
  
  See Also
  --------
  Doc2Chunk : for converting `DOCUMENT` annotations to `CHUNK`
code: def setParams(self):
      kwargs = self._input_kwargs
      return self._set(**kwargs)
  
file_path: spark-nlp/python/sparknlp/annotator/chunk2_doc.py
imports: from pyspark import keyword_only
  from sparknlp.common import AnnotatorProperties
  from sparknlp.common.annotator_type import AnnotatorType
  from sparknlp.internal import AnnotatorTransformer
label_desc: Use image node_id 2 for calling the Chunk2Doc obj's underlying member method code with example usage: obj.setParams() and returns: self