Concept Wikification for COVID-19
Panagiotis Lymperopoulos, Haoling Qiu, Bonan Min · 2020
Understanding scientific articles related to COVID-19 requires broad knowledge about concepts such as symptoms, diseases and medicine.Given the very large and evergrowing scientific articles related to COVID-19, it is a daunting task even for experts to recognize the large set of concepts mentioned in these articles.In this paper, we address the problem of concept wikification for COVID-19, which is to automatically recognize mentions of concepts related to COVID-19 in text and resolve them into Wikipedia titles.We develop an approach to curate a COVID-19 concept wikification dataset by mining Wikipedia text and the associated intra-Wikipedia links.We also develop an end-to-end system for concept wikification for COVID-19.Preliminary experiments show very encouraging results.Our dataset, code and pre-trained model are available at github.com/panlybero/ Covid19_wikification.