The recent outbreak of the novel coronavirus is wreaking havoc on the world and researchers are struggling to effectively combat it. One reason why the fight is difficult is due to the lack of information and knowledge. In this work, we outline our effort to contribute to shrinking this knowledge vacuum by creating covidAsk, a question answering (QA) system that combines biomedical text mining and QA techniques to provide answers to questions in real-time. Our system leverages both supervised and unsupervised approaches to provide informative answers using DenSPI (Seo et al. , 2019) and BEST (Lee et al., 2016). Evaluation of covidAsk is carried out by using a manually created dataset called COVID-19 Questions which is based on facts about COVID-19 . We hope our system will be able to aid researchers in their search for knowledge and information not only for COVID-19  but for future pandemics as well.
The recent outbreak of the novel coronavirus is wreaking havoc on the world and researchers are struggling to effectively combat it. One reason why the fight is difficult is due to the lack of information and knowledge. In this work, we outline our effort to contribute to shrinking this knowledge vacuum by creating covidAsk, a question answering (QA) system that combines biomedical text mining and QA techniques to provide answers to questions in real-time. Our system also leverages information retrieval (IR) approaches to provide entity-level answers that are complementary to QA models. Evaluation of covidAsk is carried out by using a manually created dataset called COVID-19 Questions which is based on information from various sources, including the CDC and the WHO . We hope our system will be able to aid researchers in their search for knowledge and information not only for COVID-19 , but for future pandemics as well.
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leverages both supervised and unsupervised
also leverages information retrieval (IR)
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informative answers using DenSPI (Seo et al. , 2019) and BEST (Lee et al., 2016).
entity-level answers that are complementary to QA models.
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facts about COVID-19
information from various sources, including the CDC and the WHO
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