Stanford Core NLP - understanding coreference resolution

I've been working with the coreference dependency graph and I started by using the other answer to this question. After a while though I realized that this algorithm above is not exactly correct. The output it produced is not even close to the modified version I have.

For anyone else who uses this article, here is the algorithm I ended up with which also filters out self references because every representativeMention also mentions itself and a lot of mentions only reference themselves.

Map<Integer, CorefChain> coref = document.get(CorefChainAnnotation.class);

for(Map.Entry<Integer, CorefChain> entry : coref.entrySet()) {
    CorefChain c = entry.getValue();

    //this is because it prints out a lot of self references which aren't that useful
    if(c.getCorefMentions().size() <= 1)
        continue;

    CorefMention cm = c.getRepresentativeMention();
    String clust = "";
    List<CoreLabel> tks = document.get(SentencesAnnotation.class).get(cm.sentNum-1).get(TokensAnnotation.class);
    for(int i = cm.startIndex-1; i < cm.endIndex-1; i++)
        clust += tks.get(i).get(TextAnnotation.class) + " ";
    clust = clust.trim();
    System.out.println("representative mention: \"" + clust + "\" is mentioned by:");

    for(CorefMention m : c.getCorefMentions()){
        String clust2 = "";
        tks = document.get(SentencesAnnotation.class).get(m.sentNum-1).get(TokensAnnotation.class);
        for(int i = m.startIndex-1; i < m.endIndex-1; i++)
            clust2 += tks.get(i).get(TextAnnotation.class) + " ";
        clust2 = clust2.trim();
        //don't need the self mention
        if(clust.equals(clust2))
            continue;

        System.out.println("\t" + clust2);
    }
}

And the final output for your example sentence is the following:

representative mention: "a basic unit of matter" is mentioned by:
The atom
it

Usually "the atom" ends up being the rep