docstr: The prediction interface for nptag.
  
  Args:
      texts(str or list[str]): the input texts to be predict.
  
  Returns:
      results(list[dict]): inference results. The element is a dictionary consists of:
          {
              'text': str, the input texts.
              'head': list[dict], tagging results, the element is a dictionary consists of:
                  {
                      'item': str, segmented word.
                      'offset': int, the offset compared with the first character.
                      'nptag_label':str, Part-Of-Speech label.
                      'length': int, word length.
                      'termid': str, link result with encyclopedia knowledge tree.
                  }
          }
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code: def predict(self, texts):
      """
      The prediction interface for nptag.
  
      Args:
          texts(str or list[str]): the input texts to be predict.
  
      Returns:
          results(list[dict]): inference results. The element is a dictionary consists of:
              {
                  'text': str, the input texts.
                  'head': list[dict], tagging results, the element is a dictionary consists of:
                      {
                          'item': str, segmented word.
                          'offset': int, the offset compared with the first character.
                          'nptag_label':str, Part-Of-Speech label.
                          'length': int, word length.
                          'termid': str, link result with encyclopedia knowledge tree.
                      }
              }
      """
      return self.nptag(texts)
  
file_path: PaddleHub/modules/text/text_to_knowledge/nptag/module.py
imports: import os
  import argparse
  import paddle
  import paddlehub
  from paddlehub.module.module import serving, moduleinfo, runnable
  from paddlenlp import Taskflow
label_desc: Use image node_id 2 for calling the NPTag obj's underlying member method code with example usage: obj.predict(texts) and returns: self