code: def predict(self, texts, merge_tokens=True, batch_size=32):
      """
      ```
      Extract named entities from supplied text
  
      Args:
        texts (list of str or str): list of texts to annotate
        merge_tokens(bool):  If True, tokens will be merged together by the entity
                             to which they are associated:
                             ('Paul', 'B-PER'), ('Newman', 'I-PER') becomes ('Paul Newman', 'PER')
        batch_size(int):    Batch size to use for predictions (default:32)
      ```
      """
      if isinstance(texts, str):
          texts = [texts]
      self.predictor.batch_size = batch_size
      texts = [t.strip() for t in texts]
      results = self.predictor.predict(texts, merge_tokens=merge_tokens)
      if len(results) == 1:
          results = results[0]
      return results
  
label_desc: Use image node_id 2 for calling the NER obj's underlying member method code with example usage: obj.predict(texts, merge_tokens, batch_size) and returns: results