Which Iterator To Be Use To Create Instances From Feature Value Pairs (Mallet API)

I am tring to run LDA to generate some topics from txt files as the following one:

Document1 label1 forest=3.4 tree=5 wood=2.85 hammer=1 colour=1 leaf=1.5
Document2 label2 forest=10 tree=5 wood=2.75 hammer=1 colour=4 leaf=1
Document3 label3 forest=19 tree=0.90 wood=2 hammer=2 colour=9 leaf=4.3
Document4 label4 forest=4 tree=5 wood=10 hammer=1 colour=6 leaf=3

Each numeric value in the file is an indication of the number of occurrences of each feature (e.g., forest, tree) multiplied by a given penalty. To generate instances from such a file, I use the following Java code:

String lineRegex = "^(S*)[s,]*(S*)[s,]*(.*)$";
String dataRegex = "[p{L}([0-9]*.[0-9]+|[0-9]+)_=]+";
InstanceList generateInstances(String dataPath) throws UnsupportedEncodingException, FileNotFoundException {
ArrayList<Pipe> pipeList = new ArrayList<Pipe>();
pipeList.add(new Target2Label());

[Code] .....

I then add the so-generated instances to my model using the instruction model.addInstances(generatedInstances). The resulting output is described below.

It contains errors caused by the instruction model.addInstances(generatedInstances). Debugging my code showed me that the alphabet associated to the model is null. Am I using the wrong iterator?

name: document1
target: label1
input: TokenSequence [forest=3.4 feature(forest)=3.4 span[0..10], tree=5 feature(tree)=5.0 span[11..17], wood=2.85 feature(wood)=2.85 span[18..27], hammer=1 feature(hammer)=1.0 span[28..36], colour=1 feature(colour)=1.0 span[37..45], leaf=1.5 feature(leaf)=1.5 span[46..54]]
Token#0:forest=3.4 feature(forest)=3.4 span[0..10]

[Code] ....