hub and spoke vs chained architecture (or adding more Antlr tree walkers)

After writing a Graphviz Dot language parser and one tree walker, I made the decision to go for a hub and spoke architecture vs a chained architecture.  Where the hub was a Dot file and the spokes are multiple tree walkers.  

I had already parsed the Dot language to populate an internal domain object.  Next I needed to render this in a Java graphing library that allowed me to specify positional information for each node (I chose the prefuse library (http://prefuse.org)).  I also knew I wanted to parse everything from one dot file that looked like so:

graph g {
a [x=3,y=100]
b [x=4,y=150]

a--b;
}

I saw two basic options:  

1. Update my current tree walker to read node and node attribute information, update my domain model to contain that information.  Then write a converter from my domain model -> the prefuse graph object.
2. Write a new tree walker that knows about node and node attribute information, and directly populates a prefuse graph object.

Option #1 seemed like a chained approach where #2 was more like a hub and a spoke.  Clearly context is king, but in my context, going for a hub and spoke approach really seems like the best way to go, and looked like soooooo much less work (Option #1 has like a million pieces where #2 had like 0, really which would you do?).

I implemented option #2 and after working out the fiddly bits with prefuse it only cost 2 hours to build and test.  

I think that's pretty fast.

It seems that Antlr really encourages going towards a hub and spoke architecture and in this case I think that turned out to be a really good thing.  Now I have two spokes... how to build more??!?!?!  If two is good more must be better right?

One mistake I made, I didn't do any unit testing of the dot language parser.  The tree walkers are well tested so the parser is at least tested via integration.  I haven't spent enough time figuring out how to test the parser, so I guess that's the next step that should have been the first step, oh well.