PCFG and Adaptive FSM

I'm having some success with a first approach to machine reading. The algorithm is to convert a PCFG parse into a sequence and map this to a sequence of predicate assembly instructions using an adaptive FSM. The adaptive FSM algorithm basically maps sequences from one domain to another and utilizes patterns in the mappings of subsequences to optimize memory usage. This optimization relates to generalization in which patterns can be induced from training examples. I'll post further results as they occur; basically, the algorithm is an online parser (word-by-word) to convert sentences to predicates though the training data is structural (sentence-by-sentence).