sansa-stack / sansa-inference Goto Github PK
View Code? Open in Web Editor NEWA general Inference API based on two of the most popular Big Data processing engines: Apache Spark and Apache Flink
License: Apache License 2.0
A general Inference API based on two of the most popular Big Data processing engines: Apache Spark and Apache Flink
License: Apache License 2.0
I ran the RDFS forward chaining (on GO) through the example set up in SANSA-Examples/sansa-examples-spark and got triples looking like this
<"Reactome:REACT_90070"^^<http://www.w3.org/2001/XMLSchema#string>> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://www.w3.org/2000/01/rdf-schema#Resource> .
in the output.
I think a literal check is needed here: https://github.com/SANSA-Stack/SANSA-Inference/blob/develop/sansa-inference-spark/src/main/scala/net/sansa_stack/inference/spark/forwardchaining/ForwardRuleReasonerRDFS.scala#L186
When calling mvn clean test
e.g. in sansa-inference-spark/
I get
net.sansa_stack.inference.spark.conformance.RDFSConformanceTest *** ABORTED ***
java.lang.RuntimeException: Unable to load a Suite class that was discovered in the runpath: net.sansa_stack.inference.spark.conformance.RDFSConformanceTest
at org.scalatest.tools.DiscoverySuite$.getSuiteInstance(DiscoverySuite.scala:81)
at org.scalatest.tools.DiscoverySuite$$anonfun$1.apply(DiscoverySuite.scala:38)
at org.scalatest.tools.DiscoverySuite$$anonfun$1.apply(DiscoverySuite.scala:37)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
...
Cause: java.lang.NullPointerException:
at scala.collection.mutable.ArrayOps$ofRef$.newBuilder$extension(ArrayOps.scala:190)
at scala.collection.mutable.ArrayOps$ofRef.newBuilder(ArrayOps.scala:186)
at scala.collection.TraversableLike$class.filterImpl(TraversableLike.scala:246)
at scala.collection.TraversableLike$class.filter(TraversableLike.scala:259)
at scala.collection.mutable.ArrayOps$ofRef.filter(ArrayOps.scala:186)
at net.sansa_stack.test.conformance.TestCases$.loadTestCases(TestCases.scala:29)
at net.sansa_stack.test.conformance.ConformanceTestBase.<init>(ConformanceTestBase.scala:38)
at net.sansa_stack.test.conformance.RDFSConformanceTestBase.<init>(RDFSConformanceTestBase.scala:17)
at net.sansa_stack.inference.spark.conformance.RDFSConformanceTest.<init>(RDFSConformanceTest.scala:21)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
for RDFSConformanceTest
and OWLHorstConformanceTest
. Seems, the problem is, that in net.sansa_stack.test.conformance.TestCases
(part of sansa-inference-tests) the directory: File
variable passed in, holds e.g. the path file:/home/me/.m2/repository/net/sansa-stack/sansa-inference-tests_2.11/0.3.0-SNAPSHOT/sansa-inference-tests_2.11-0.3.0-SNAPSHOT-tests.jar!/data/conformance/owl2rl
and directory.listFiles()
returns null
.
While creating the axioms inference example I noticed that the result set is different from the one implemented on triples inference example.
Instead of returning inferred graph, it just returns the inferred axioms. Is there a reason behind it? Shall we consider being consistent in both cases?
Best regards,
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.