Oh, I see. It does state that this is 'SHACL property value rules, a
proposed extension to the SHACL-AF specification.', so not yet in the
standard, and therefore not yet in pySHACL. Looks interesting, though I
prefer the clarity of Datalog-based rules such as
https://docs.stardog.com/inference-eng
Hi Boris,
Thank you for fixing the errors and showing how pyshacl can do it.
The shapes do come from the TopQuadrant site:
https://www.topquadrant.com/graphql/values.html , expecting that these
would run for sure.
This explains the spif class .
Kind regards,
Richard
On Friday, May 21, 2021 a
Took a look at your code and shapes, had to make a couple of little fixes.
In your prologue, you had:
data_graph_orig = data_graph
That made them both reference the same graph, so there was never a
difference. I replaced that with:
data_graph_orig = Graph()
for t in data_graph:
data_graph_
Thank you Boris for the hint.
Inferences going into the datagraph makes sense indeed. However attached
example does not give the wanted result.
I will check this in the weekend again.
btw I am running on Windows10 using RDFlib 5.0.0
Kind regards,
Richard
On Thursday, May 20, 2021 at 7:50:17 P
Richard,
As per the code, it appears that triples created by inference from sh:rule
are added into the data_graph, which makes sense, since you can evaluate
the other rules against the inferred content. In SPARQLRule:
data_graph = clone_graph(g, target_graph=data_graph)
and in TripleRule:
Using shacl-af withpyshacl -a I want to materialize the inferred
triples using shacl-rules.
It is however not clear to me in what result the triples are collected.
Any hint is appreciated.
kind regards, Richard
--
http://github.com/RDFLib
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