docs: def get_text_path(self):
          """
          Returns the path of the directory containing text if they exist in this dataset.
          """
          for res in self.dsDoc['dataResources']:
              resPath = res['resPath']
              resType = res['resType']
              isCollection = res['isCollection']
              if resType == 'text' and isCollection:
                  return os.path.join(self.dsHome, resPath)
  
          # if the for loop is over and no image directory is found, then return None
          raise RuntimeError('could not find learningData file the dataset')