class_docstr: A contiguous span over some part of the input string representing
  dependency (head -> modifier) relationships amongst words.  An atomic
  span corresponds to only one word so it isn't a 'span' in the conventional
  sense, as its _start_index = _end_index = _head_index for concatenation
  purposes.  All other spans are assumed to have arcs between all nodes
  within the start and end indexes of the span, and one head index corresponding
  to the head word for the entire span.  This is the same as the root node if
  the dependency structure were depicted as a graph.
class_docstr_tok: ["A","contiguous","span","over","some","part","of","the","input","string","representing","dependency","(","head","-",">","modifier",")","relationships","amongst","words",".","An","atomic","span","corresponds","to","only","one","word","so","it","is","n't","a","'span","'","in","the","conventional","sense",",","as","its","_start_index","=","_end_index","=","_head_index","for","concatenation","purposes",".","All","other","spans","are","assumed","to","have","arcs","between","all","nodes","within","the","start","and","end","indexes","of","the","span",",","and","one","head","index","corresponding","to","the","head","word","for","the","entire","span",".","This","is","the","same","as","the","root","node","if","the","dependency","structure","were","depicted","as","a","graph","."]
code: def __ne__(self, other):
      return not self == other
  
imports: from collections import defaultdict
  from functools import total_ordering
  from itertools import chain
  from nltk.grammar import DependencyGrammar, DependencyProduction, ProbabilisticDependencyGrammar
  from nltk.internals import raise_unorderable_types
  from nltk.parse.dependencygraph import DependencyGraph
label_desc: Use image node_id 6 for calling the DependencySpan obj's underlying member method code with example usage: obj.__ne__(other) and returns: unknown