OPA 12 – It’s all in the Natural Language Text
I suppose this article could have just as easily been about Oracle Policy Modelling 10 as well. But since I was teaching version 12 I decided to use it for the screenshots. I also was teaching a group of French students so the examples are in French and English. Ultimately the same challenges occur no matter what language you are using, provided that language uses definite articles in the same way. Natural Language is not always natural.
Consider the following :
An Entity called “the contact” or “l’interlocuteur”.
As you can see, the Relationship Text has been changed to “tous les interlocuteurs” or “all the contacts” instead of the standard “all instances of the contact” or “toutes les instances de l’interlocuteur”. I see a lot of students working in this way. However there are some side effects of using this kind of wording…
Let’s imagine that every contact has a telephone number, and we want to check that the telephone number has been entered. The first part is fine, we can write the following rule to assign a Boolean value depending on whether we have a telephone number or not, and let’s build a rule that uses Entity Quantifiers to look at the different contacts.
When is Natural Language really Natural?
In English we would have something like
We are using the longest version of the “natural language” Function “ForAll“. And it looks a bit, well, long-winded. So we might try one of the other versions:
That’s even worse. In French too it’s almost comical …
That’s even worse. So let us try a different approach. We decide to modify the Relationship Text and remove the “all” to leave only “the contacts” or “les interlocuteurs”. So now our rules look a bit more “natural language” when we use the ForAll function in it’s long form.
Of course I can hear people saying, why don’t you just use ForAll or PourTous – that is, the terse or short version of the function? It does of course depend on your environment, but a non-technical user is going to be far more comfortable using a natural language-based solution.
Have fun improving your text, until next time