code: def predict(self, sentence, format=None):
      tokens = [(tokens[0], tokens[1], "X") for tokens in sentence]
      x = self.transformer.transform([tokens])[0][0]
      tags = self.model.tag(x)
      output = [
          (tokens[0], tokens[1], tag)
          for tokens, tag in zip(sentence, tags)
      ]
      return output
  
file_path: underthesea/underthesea/pipeline/chunking/model_crf.py
imports: from os.path import join, dirname
  from underthesea.util.singleton import Singleton
  import pycrfsuite
  import sys
label_desc: Use image node_id 2 for calling the CRFChunkingPredictor obj's underlying member method code with example usage: obj.predict(sentence, format) and returns: output