code: def predict(self, sentence, format=None):
      tokens = [(token, "X") for token in sentence]
      x = self.transformer.transform([tokens])[0][0]
      tags = self.model.tag(x)
      return list(zip(sentence, tags))
  
file_path: underthesea/underthesea/pipeline/pos_tag/model_crf.py
imports: from os.path import join, dirname
  from underthesea.util.singleton import Singleton
  import pycrfsuite
  from .tagged_feature import word2features
label_desc: Use image node_id 2 for calling the CRFPOSTagPredictor obj's underlying member method code with example usage: obj.predict(sentence, format) and returns: list