class_docstr: A class for pos tagging with Stanford Tagger. The input is the paths to:
   - a model trained on training data
   - (optionally) the path to the stanford tagger jar file. If not specified here,
     then this jar file must be specified in the CLASSPATH environment variable.
   - (optionally) the encoding of the training data (default: UTF-8)
  
  Example:
  
      >>> from nltk.tag import StanfordPOSTagger
      >>> st = StanfordPOSTagger('english-bidirectional-distsim.tagger') # doctest: +SKIP
      >>> st.tag('What is the airspeed of an unladen swallow ?'.split()) # doctest: +SKIP
      [('What', 'WP'), ('is', 'VBZ'), ('the', 'DT'), ('airspeed', 'NN'), ('of', 'IN'), ('an', 'DT'), ('unladen', 'JJ'), ('swallow', 'VB'), ('?', '.')]
code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
  
imports: import os
  import tempfile
  import warnings
  from abc import abstractmethod
  from subprocess import PIPE
  from nltk.internals import _java_options, config_java, find_file, find_jar, java
  from nltk.tag.api import TaggerI
label_desc: Use image node_id 1 to create a new StanfordPOSTagger object from inherited base classes: StanfordTagger with example: obj = StanfordPOSTagger()