Abstract
Question answering (QA) is one of the biggest challenges for making sense out of data. The Web of Data has attracted the attention of the QA community and recently, a number of schema-aware QA systems have been introduced. While research achievements are individually significant, yet, integrating different approaches is not possible due to lack of a systematic approach for conceptually describing QA systems. In this paper, we present a message-driven vocabulary built upon an abstract level. This vocabulary is concluded from conceptual views of different QA systems. In this way, we are enabling researchers and industry to implement message-driven QA systems and to reuse and extend different approaches without interoperability and extension concerns.