class_docstr: Represents the output of Spark NLP Annotators and their details.
  
  Parameters
  ----------
  annotator_type : str
      The type of the output of the annotator. Possible values are ``DOCUMENT,
      TOKEN, WORDPIECE, WORD_EMBEDDINGS, SENTENCE_EMBEDDINGS, CATEGORY, DATE,
      ENTITY, SENTIMENT, POS, CHUNK, NAMED_ENTITY, NEGEX, DEPENDENCY,
      LABELED_DEPENDENCY, LANGUAGE, KEYWORD, DUMMY``.
  begin : int
      The index of the first character under this annotation.
  end : int
      The index of the last character under this annotation.
  result : str
      The resulting string of the annotation.
  metadata : dict
      Associated metadata for this annotation
  embeddings : list
      Embeddings vector where applicable
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docstr: Returns a Spark `StructType`, that represents the schema of the
  Annotation.
  
  The Schema looks like::
  
      struct (containsNull = True)
      |-- annotatorType: string (nullable = False)
      |-- begin: integer (nullable = False)
      |-- end: integer (nullable = False)
      |-- result: string (nullable = False)
      |-- metadata: map (nullable = False)
      |    |-- key: string
      |    |-- value: string (valueContainsNull = True)
      |-- embeddings: array (nullable = False)
      |    |-- element: float (containsNull = False)
  
  Returns
  -------
  :class:`pyspark.sql.types.StructType`
      Spark Schema of the Annotation
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code: def dataType():
      """Returns a Spark `StructType`, that represents the schema of the
      Annotation.
  
      The Schema looks like::
  
          struct (containsNull = True)
          |-- annotatorType: string (nullable = False)
          |-- begin: integer (nullable = False)
          |-- end: integer (nullable = False)
          |-- result: string (nullable = False)
          |-- metadata: map (nullable = False)
          |    |-- key: string
          |    |-- value: string (valueContainsNull = True)
          |-- embeddings: array (nullable = False)
          |    |-- element: float (containsNull = False)
  
      Returns
      -------
      :class:`pyspark.sql.types.StructType`
          Spark Schema of the Annotation
      """
      return StructType(
          [
              StructField("annotatorType", StringType(), False),
              StructField("begin", IntegerType(), False),
              StructField("end", IntegerType(), False),
              StructField("result", StringType(), False),
              StructField(
                  "metadata", MapType(StringType(), StringType()), False
              ),
              StructField("embeddings", ArrayType(FloatType()), False),
          ]
      )
  
file_path: spark-nlp/python/sparknlp/annotation.py
imports: from pyspark.sql.types import *
label_desc: Use image node_id 6 for calling the Annotation obj's underlying member method code with example usage: obj.dataType() and returns: StructType