Abstract. The Semantic Web contains an enormous amount of information in the form of knowledge bases. To make this information available to end-users many question answering (QA) systems over knowledge bases were created in the last years. Their goal is to enable users to access large amounts of structured data in the Semantic Web by bridging the gap between natural language and formal query languages like SPARQL. But automatically generating a SPARQL query from a user's question is not sufficient to bridge the gap between Semantic Web data and the end-users. The result of a SPARQL query consists of a list of URIs and/or literals, which is not a user-friendly presentation of the answer. Such a presentation includes the representation of the URI in the right language and additional information like images, maps, entity summaries and more. We present Trill, the first reusable user-interface (UI) for QA systems over knowledge bases supporting text and audio input, able to present answers from DBpedia and Wikidata in 4 languages (English, French, German, and Italian). It is designed to be used together with Qanary, an infrastructure for composing QA pipelines. This front-end enables the QA community to show their results to end-users and enables the research community to explore new research directions like studying and designing user-interactions with QA systems.

Abstract. Providing a general and efficient Question Answering system over Knowledge Bases (KB) has been studied for years. Most of the works concentrated on the automatic translation of a natural language question into a formal query. However, few works address the problem on how users can interact with Question Answering systems during this translation process. We present a general mechanism that allows users to interact with Question Answering systems. It is built on top of Qanary, a framework for integrating Question Answering components. We show how the mechanism can be applied in a generalized way. In particular, we show how it can be used when the user asks ambiguous questions.