  A new challenge for knowledge graph reasoning started in 2018. Deep learning
has promoted the application of artificial intelligence (AI) techniques to a
wide variety of social problems. Accordingly, being able to explain the reason
for an AI decision is becoming important to ensure the secure and safe use of
AI techniques. Thus, we, the Special Interest Group on Semantic Web and
Ontology of the Japanese Society for AI, organized a challenge calling for
techniques that reason and/or estimate which characters are criminals while
providing a reasonable explanation based on an open knowledge graph of a
well-known Sherlock Holmes mystery story. This paper presents a summary report
of the first challenge held in 2018, including the knowledge graph
construction, the techniques proposed for reasoning and/or estimation, the
evaluation metrics, and the results. The first prize went to an approach that
formalized the problem as a constraint satisfaction problem and solved it using
a lightweight formal method; the second prize went to an approach that used
SPARQL and rules; the best resource prize went to a submission that constructed
word embedding of characters from all sentences of Sherlock Holmes novels; and
the best idea prize went to a discussion multi-agents model. We conclude this
paper with the plans and issues for the next challenge in 2019.
