Automatic question answering for multiple stakeholders, the epidemic question answering dataset

One of the effects of COVID-19 pandemic is a rapidly growing and changing stream of publications to inform clinicians, researchers, policy makers, and patients about the health, socio-economic, and cultural consequences of the pandemic. Managing this information stream manually is not feasible. Automatic Question Answering can quickly bring the most salient points to the user's attention. Leveraging a collection of scientific articles, government websites, relevant news articles, curated social media posts, and questions asked by researchers, clinicians, and the general public, we developed a dataset to explore automatic Question Answering for multiple stakeholders. Analysis of questions asked by various stakeholders shows that while information needs of experts and the public may overlap, satisfactory answers to these questions often originate from different information sources or benefit from different approaches to answer generation. We believe that this dataset has the potential to support the development of question answering systems not only for epidemic questions, but for other domains with varying expertise such as legal or finance.

Automated summary

The COVID-19 pandemic has led to a rapid increase in the publication of information regarding its health, socio-economic, and cultural consequences. Manual management of this information is not feasible, thus the use of automatic question answering systems can efficiently highlight the key points. By utilizing various information sources and questions from different stakeholders, a dataset was developed to explore automatic question answering for multiple domains. Analysis of these questions revealed that while the information needs of experts and the public may overlap, satisfying answers often require different information sources or approaches. This dataset has the potential to support the development of question answering systems in various domains, including epidemics as well as legal or financial domains.