Can CEP be used to analyze transaction flow?

While Complex Event Processing (CEP) is a general purpose technology for processing events in real-time, I am wondering how it can be used to analyze transaction/message flow. The basic premise of transaction tracking within SOA and message driven architecture is to identify the flow of messages by observing message exchanges between systems and applications. In such environment messages have to be related, correlated and analyzed to determine beginning and the end of the flow, timings of each exchange as well as discover hidden relationships. Transaction boundaries are determined by observing units of work and relating them based on message exchanges. Sometime ago I published a method of correlating transactions, which describes the basic mechanics.

So far I don't see how it can be done using CEP based approach (using rule based (EPL) CEP principles). One can create a rule that observes messages (aka events), however I don't see a way to derive relationships that can later on be used to classify incoming message or events.

It seems to me that CEP would require a relationship engine of some sort that can be used to derive, store and query relationships that can be used by the CEP engine when processing events. 

For example: say we observe events A, B and C. There maybe a relationship between these events. We can say events A->B a related (-> related) if A and Bs pay load contains a certain key (example order number of customer id).  Lets call E(x) event E with payload x. If we observe A(x), B(x) and C(x): we can derive that A->B and B->C. If relation is transitive we can derive that A->C as well.

So it would be helpful to have a relationship service within CEP engines where once can declare a relationship and then at runtime determine whether events A and B are related and how, an if they are what types of relations qualify.