Dependency tree using Stanford Parser from NLTK results not matching with Stanford Parser

Question

I am trying to compare results of Stanford Parser from NLTK, but I do not know why I am getting different results when I compare with stanford parser I have checked related questions but this does not help me much.

stan_dep_parser = StanfordDependencyParser() # stanford parser from NLTK 
dependency_parser =stan_dep_parser.raw_parse("Four men died in an accident")
dep = dependency_parser.next()
for triple in dep.triples():
   print triple[1],"(",triple[0][0],", ",triple[2][0],")"

Current Output:

nsubj ( died ,  men )
nummod ( men ,  Four )
nmod ( died ,  accident )
case ( accident ,  in )
det ( accident ,  an )

Expected Output according to stanford parser :

nummod(men-2, Four-1)
nsubj(died-3, men-2)
root(ROOT-0, died-3)
case(accident-6, in-4)
det(accident-6, an-5)
nmod(died-3, accident-6)

NLTK version: 3.2.4 Stanford Parser: stanford-parser-3.8.0-models

Answer 1

I have solved problem myself:

I found 'root' or 'head' of the sentence:

final_dependency = []
sentence = "Four men died in an accident"
dependency_tree = StanfordDependencyParser()
dependency_parser = dependency_tree.raw_parse(sentence)
parsetree = list(dependency_parser)[0]
for k in parsetree.nodes.values():
       if k["head"] == 0:
            final_dependency.append(str(k["rel"])  + "(" + "Root" + "-" 
                + str(k["head"]) + "," + str(k["word"]) + "-" + str(k["address"]) + ")" )

Then I added numbers with words as in expected output with simple string operations as numbers are indexes of each word in sentence.