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Rapidly Bootstrapping a Question Answering Dataset for COVID-19. (arXiv:2004.11339v1 [cs.CL])

Date:

Node: 120715

[Submitted on 23 Apr 2020]

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Abstract: We present CovidQA, the beginnings of a question answering dataset
specifically designed for COVID-19, built by hand from knowledge gathered from
Kaggle’s COVID-19 Open Research Dataset Challenge. To our knowledge, this is
the first publicly available resource of its type, and intended as a stopgap
measure for guiding research until more substantial evaluation resources become
available. While this dataset, comprising 124 question-article pairs as of the
present version 0.1 release, does not have sufficient examples for supervised
machine learning, we believe that it can be helpful for evaluating the
zero-shot or transfer capabilities of existing models on topics specifically
related to COVID-19. This paper describes our methodology for constructing the
dataset and presents the effectiveness of a number of baselines, including
term-based techniques and various transformer-based models. The dataset is
available at this http URL

Submission history

From: Jimmy Lin [view email]
[v1]
Thu, 23 Apr 2020 17:35:11 UTC (33 KB)

Source: http://arxiv.org/abs/2004.11339