{
  "citation": "@inproceedings{Dua2019DROP,\n  author={Dheeru Dua and Yizhong Wang and Pradeep Dasigi and Gabriel Stanovsky and Sameer Singh and Matt Gardner},\n  title={  {DROP}: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs},\n  booktitle={Proc. of NAACL},\n  year={2019}\n}",
  "description": "With system performance on existing reading comprehension benchmarks nearing or\nsurpassing human performance, we need a new, hard dataset that improves systems'\ncapabilities to actually read paragraphs of text. DROP is a crowdsourced,\nadversarially-created, 96k-question benchmark, in which a system must resolve\nreferences in a question, perhaps to multiple input positions, and perform\ndiscrete operations over them (such as addition, counting, or sorting). These\noperations require a much more comprehensive understanding of the content of\nparagraphs than what was necessary for prior datasets.",
  "downloadSize": "8308692",
  "location": {
    "urls": [
      "https://allennlp.org/drop"
    ]
  },
  "name": "drop",
  "splits": [
    {
      "name": "dev",
      "numBytes": "12161069",
      "shardLengths": [
        "9536"
      ]
    },
    {
      "name": "train",
      "numBytes": "109727409",
      "shardLengths": [
        "77409"
      ]
    }
  ],
  "version": "2.0.0"
}