class_docstr: Tagger base class that defines the interface. 
class_docstr_tok: ["Tagger","base","class","that","defines","the","interface","."]
docstr: Annotate a squence of words with entity tags.
  
  Args:
    sent: sequence of strings/words.
docstr_tok: ["Annotate","a","squence","of","words","with","entity","tags",".","Args",":","sent",":","sequence","of","strings\/words","."]
code: def annotate(self, sent):
      """Annotate a squence of words with entity tags.
  
      Args:
        sent: sequence of strings/words.
      """
      preds = []
      words = []
      for word, fv in self.sent2examples(sent):
          probs = self.predictor(fv)
          tags = probs.argsort()
          tag = self.ID_TAG[tags[-1]]
  
          words.append(word)
          preds.append(tag)
  
      # fix_chunks(preds)
      annotations = zip(words, preds)
      return annotations
  
imports: import numpy
  from six.moves import range
  from ..decorators import memoize
  from ..load import load_embeddings, load_ner_model, load_pos_model, load_unified_pos_model
label_desc: Use image node_id 4 for calling the TaggerBase obj's underlying member method code with example usage: obj.annotate(sent) and returns: annotations