COUGH: A Challenge Dataset and Models for COVID-19 FAQ Retrieval

10/24/2020
by   Xinliang Frederick Zhang, et al.
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We present a large challenging dataset, COUGH, for COVID-19 FAQ retrieval. Specifically, similar to a standard FAQ dataset, COUGH consists of three parts: FAQ Bank, User Query Bank and Annotated Relevance Set. FAQ Bank contains  16K FAQ items scraped from 55 credible websites (e.g., CDC and WHO). For evaluation, we introduce User Query Bank and Annotated Relevance Set, where the former contains 1201 human-paraphrased queries while the latter contains  32 human-annotated FAQ items for each query. We analyze COUGH by testing different FAQ retrieval models built on top of BM25 and BERT, among which the best model achieves 0.29 under P@5, indicating that the dataset presents a great challenge for future research. Our dataset is freely available at https://github.com/sunlab-osu/covid-faq.

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