class_docstr: An abstract base class for Features. A Feature is a combination of
  a specific property-computing method and a list of relative positions
  to apply that method to.
  
  The property-computing method, M{extract_property(tokens, index)},
  must be implemented by every subclass. It extracts or computes a specific
  property for the token at the current index. Typical extract_property()
  methods return features such as the token text or tag; but more involved
  methods may consider the entire sequence M{tokens} and
  for instance compute the length of the sentence the token belongs to.
  
  In addition, the subclass may have a PROPERTY_NAME, which is how
  it will be printed (in Rules and Templates, etc). If not given, defaults
  to the classname.
docstr: Return True if this Feature always returns True when other does
  
  More precisely, return True if this feature refers to the same property as other;
  and this Feature looks at all positions that other does (and possibly
  other positions in addition).
  
  #For instance, importing a concrete subclass (Feature is abstract)
  >>> from nltk.tag.brill import Word, Pos
  
  >>> Word([-3,-2,-1]).issuperset(Word([-3,-2]))
  True
  
  >>> Word([-3,-2,-1]).issuperset(Word([-3,-2, 0]))
  False
  
  #Feature subclasses must agree
  >>> Word([-3,-2,-1]).issuperset(Pos([-3,-2]))
  False
  
  :param other: feature with which to compare
  :type other: (subclass of) Feature
  :return: True if this feature is superset, otherwise False
  :rtype: bool
docstr_tok: ["Return","True","if","this","Feature","always","returns","True","when","other","does","More","precisely",",","return","True","if","this","feature","refers","to","the","same","property","as","other",";","and","this","Feature","looks","at","all","positions","that","other","does","(","and","possibly","other","positions","in","addition",")",".","#","For","instance",",","importing","a","concrete","subclass","(","Feature","is","abstract",")",">",">",">","from","nltk.tag.brill","import","Word",",","Pos",">",">",">","Word","(","[","-3",",","-2",",","-1","]",")",".issuperset","(","Word","(","[","-3",",","-2","]",")",")","True",">",">",">","Word","(","[","-3",",","-2",",","-1","]",")",".issuperset","(","Word","(","[","-3",",","-2",",","0","]",")",")","False","#","Feature","subclasses","must","agree",">",">",">","Word","(","[","-3",",","-2",",","-1","]",")",".issuperset","(","Pos","(","[","-3",",","-2","]",")",")","False",":","param","other",":","feature","with","which","to","compare",":","type","other",":","(","subclass","of",")","Feature",":","return",":","True","if","this","feature","is","superset",",","otherwise","False",":","rtype",":","bool"]
code: def issuperset(self, other):
      """
      Return True if this Feature always returns True when other does
  
      More precisely, return True if this feature refers to the same property as other;
      and this Feature looks at all positions that other does (and possibly
      other positions in addition).
  
      #For instance, importing a concrete subclass (Feature is abstract)
      >>> from nltk.tag.brill import Word, Pos
  
      >>> Word([-3,-2,-1]).issuperset(Word([-3,-2]))
      True
  
      >>> Word([-3,-2,-1]).issuperset(Word([-3,-2, 0]))
      False
  
      #Feature subclasses must agree
      >>> Word([-3,-2,-1]).issuperset(Pos([-3,-2]))
      False
  
      :param other: feature with which to compare
      :type other: (subclass of) Feature
      :return: True if this feature is superset, otherwise False
      :rtype: bool
  
  
      """
      return self.__class__ is other.__class__ and set(
          self.positions
      ) >= set(other.positions)
  
file_path: nltk/nltk/tbl/feature.py
imports: from abc import ABCMeta, abstractmethod
label_desc: Use image node_id 6 for calling the Feature obj's underlying member method code with example usage: obj.issuperset(other) and returns: unknown