  Question answering (QA) over knowledge graphs has gained significant momentum
over the past five years due to the increasing availability of large knowledge
graphs and the rising importance of question answering for user interaction.
DBpedia has been the most prominently used knowledge graph in this setting and
most approaches currently use a pipeline of processing steps connecting a
sequence of components. In this article, we analyse and micro evaluate the
behaviour of 29 available QA components for DBpedia knowledge graph that were
released by the research community since 2010. As a result, we provide a
perspective on collective failure cases, suggest characteristics of QA
components that prevent them from performing better and provide future
challenges and research directions for the field.
