First, we investigate OPIEC triples and DBpedia facts having the same arguments by comparing the information on the OIE surface relation with the KB rela- tion.
SAFRAN yields new state-of-the-art results for fully interpretable link prediction on the established general-purpose benchmarks FB15K-237, WN18RR and YAGO3-10.
Ranked #2 on Link Prediction on FB15k-237
We compare a rule-based approach for knowledge graph completion against current state-of-the-art, which is based on embbedings.
SAFRAN yields new state-of-the-art results for fully interpretable link prediction on the established general-purpose benchmark FB15K-237 and the large-scale biomedical benchmark OpenBioLink.
In this paper, we are concerned with two extensions of AnyBURL.
In this paper, we explore whether recent models work well for knowledge base completion and argue that the current evaluation protocols are more suited for question answering rather than knowledge base completion.
We propose a new approach for calculating the root cause for an observed failure in an IT infrastructure.