class_docstr: Instantiated model of the TextMatcher.
  
  This is the instantiated model of the :class:`.TextMatcher`. For training
  your own model, please see the documentation of that class.
  
  ====================== ======================
  Input Annotation types Output Annotation type
  ====================== ======================
  ``DOCUMENT, TOKEN``    ``CHUNK``
  ====================== ======================
  
  Parameters
  ----------
  mergeOverlapping
      Whether to merge overlapping matched chunks, by default False
  entityValue
      Value for the entity metadata field
  buildFromTokens
      Whether the TextMatcher should take the CHUNK from TOKEN or not
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docstr: Sets whether the TextMatcher should take the CHUNK from TOKEN or not.
  
  Parameters
  ----------
  b : bool
      Whether the TextMatcher should take the CHUNK from TOKEN or not
docstr_tok: ["Sets","whether","the","TextMatcher","should","take","the","CHUNK","from","TOKEN","or","not",".","Parameters","--","--","--","--","--","b",":","bool","Whether","the","TextMatcher","should","take","the","CHUNK","from","TOKEN","or","not"]
code: def setBuildFromTokens(self, b):
      """Sets whether the TextMatcher should take the CHUNK from TOKEN or not.
  
      Parameters
      ----------
      b : bool
          Whether the TextMatcher should take the CHUNK from TOKEN or not
      """
      return self._set(buildFromTokens=b)
  
file_path: spark-nlp/python/sparknlp/annotator/matcher/text_matcher.py
imports: from sparknlp.common import *
label_desc: Use image node_id 4 for calling the TextMatcherModel obj's underlying member method code with example usage: obj.setBuildFromTokens(b) and returns: self