Question answering (QA) systems, which source answers to natural language questions from Semantic Web data, have recently shifted from the research realm to become commercially viable products. Increasing investments have refined an interaction paradigm that allows end users to profit from the expressive power of Semantic Web standards, while at the same time hiding their complexity behind intuitive and easy-to-use interfaces. Not surprisingly, after the first excitement we did not witness a cooling-down phenomenon: regular interactions with question answering systems have become more and more natural. As consumers expectations around the capabilities of systems able to answer questions formulated in natural language keep growing, so is the availability of such systems in various settings, devices and languages. Increasing usage in real (non-experimental) settings have boosted the demand for resilient systems, which can cope with high volume demand.