I am using a SPIN reasoner to apply SPIN rules to data contained within a 
JENA model.

For each run of SPINInferences, the code does:

- Gets the SPINModuleRegistry and inits it.
- Adds my JENA model and the model containing the SPIN rules to the 
registry.
- Runs SPINInferences on the models and generates a set of SPINStatistics.
- Resets the SPINModuleRegistry so that the next pass is completely fresh.

In the first instance, I apply a set of four SPIN rules to 350 models, and 
(on average) these take around 10 milliseconds to complete (calculated 
using the SPINStatistics results). During this run, the rules produce 
annotations in the ntriples model which are added back into the original 
model for the second pass.

In the second pass, I apply the same set of SPIN rules to these 350 models 
including their annotations. The rules do not consider these new 
annotations and so, at the very least, the average reasoning time (calc. 
using SPINStatistics) should be roughly the same. However, due to the 
larger model size it could be expected that the time will increase. 
Unfortunately, the reasoning time is reduced during the second pass (on 
average, roughly 7ms.

I assume that this is possibly caused by some kind of optimisation within 
SPIN. Do you agree? If so, is there any way to switch this off? Is it 
caused by me resetting SPIN the wrong way? What is the correct way to do 
this?

Thanks
Chris

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