covid19sum

  • Description:

CORD-19 is a resource of over 45,000 scholarly articles, including over 33,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses.

To help organizing information in scientific literatures of COVID-19 through abstractive summarization. This dataset parse those articles to pairs of document and summaries of full_text-abstract or introduction-abstract.

Features includes strings of: abstract, full_text, sha (hash of pdf), source_x (source of publication), title, doi (digital object identifier), license, authors, publish_time, journal, url.

Split Examples
  • Feature structure:
FeaturesDict({
    'abstract': string,
    'authors': string,
    'body_text': Sequence({
        'section': string,
        'text': string,
    }),
    'doi': string,
    'journal': string,
    'license': string,
    'publish_time': string,
    'sha': string,
    'source_x': string,
    'title': string,
    'url': string,
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
abstract Tensor string
authors Tensor string
body_text Sequence
body_text/section Tensor string
body_text/text Tensor string
doi Tensor string
journal Tensor string
license Tensor string
publish_time Tensor string
sha Tensor string
source_x Tensor string
title Tensor string
url Tensor string
@ONLINE {CORD-19-research-challenge,
    author = "An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House",
    title  = "COVID-19 Open Research Dataset Challenge (CORD-19)",
    month  = "april",
    year   = "2020",
    url    = "https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge"
}