Question answering (QA) has been the subject of a resurgence over the past years. The said resurgence has led to a multitude of question answering (QA) systems being developed both by companies and research facilities. While a few components of QA systems get reused across implementations, most systems do not leverage the full potential of component reuse. Hence, the development of QA systems is currently still a tedious and time-consuming process. We address the challenge of accelerating the creation of novel or tailored QA systems by presenting a concept for a self-wiring approach to composing QA systems. Our approach will allow the reuse of existing, web-based QA systems or modules while developing new QA platforms. To this end, it will rely on QA modules being described using the Web Ontology Language. Based on these descriptions, our approach will be able to automatically compose QA systems using a data-driven approach automatically.
QANARY @cite_11 is the first real implementation of a semantic approach towards generating QA systems from components. Using the provided QA ontology from QANARY, modules can be exchanged, e.g. various versions of NER tools, to benchmark various pipelines and choose the best performing one.
@cite_11
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Question answering (QA) systems focus on making sense out of data via an easy-to-use interface. However, these systems are very complex and integrate a lot of technology tightly. Previously presented QA systems are mostly singular and monolithic implementations. Hence, their reusability is limited. In contrast, we follow the research agenda of establishing an ecosystem for components of QA systems, which will enable the QA community to elevate the reusability of such components and to intensify their research activities.