[SOLVED] creating very many models using a single data set?

Hi,

I'm a new user of RapidMiner and was wondering if someone in the community knows a good way to create what I am trying. 

I am working with a very large dataset (millions of examples) that has 1 id attribute, 1 text attribute, 52 numerical attributes per example (row) and 1 label attribute.  There are about 500 unique text attributes in the whole data set.  What I would like to do is create a decision tree model (and store it) for data corresponding to each unique text attribute.  That is, for each unique text attribute, I want all the examples corresponding to that text attribute and then train a decision tree model using the 52 numerical and 1 label attributes.  I could do it using filter examples, decision tree model, and repository store operators manually for each unique text attribute, but I would have to do this about 500 times.  Is there an efficient way to implement this?  I could try to do this using scripting, but I was just wondering if I could use the built in operators.  Is the Loop operator the answer?

Thanks in advance.