{
  "@type": "dcat:Dataset",
  "accessLevel": "public",
  "bureauCode": [
    "006:55"
  ],
  "contactPoint": {
    "fn": "Ian Soboroff",
    "hasEmail": "mailto:ian.soboroff@nist.gov"
  },
  "description": "The Deep Learning track focuses on IR tasks where a large training set is available, allowing us to compare a variety of retrieval approaches including deep neural networks and strong non-neural approaches, to see what works best in a large-data regime.",
  "distribution": [
    {
      "accessURL": "https://microsoft.github.io/msmarco/TREC-Deep-Learning#document-ranking-dataset",
      "title": "Document Ranking Corpus"
    },
    {
      "accessURL": "https://microsoft.github.io/msmarco/TREC-Deep-Learning#passage-ranking-dataset",
      "title": "Passage Ranking Corpus"
    },
    {
      "accessURL": "https://microsoft.github.io/msmarco/TREC-Deep-Learning#passage-ranking-dataset",
      "title": "Passage Ranking Topics"
    },
    {
      "accessURL": "https://trec.nist.gov/data/deep/2023.qrels.docs.wihDupes.no1.txt",
      "title": "Document Ranking (NIST, 1 judgments mapped to 0)"
    },
    {
      "accessURL": "https://trec.nist.gov/data/deep/2023.qrels.docs.wihDupes.txt",
      "title": "Document Ranking NIST QRels"
    },
    {
      "accessURL": "https://trec.nist.gov/data/deep/2023.qrels.pass.withDupes.no1.txt",
      "title": "Passage Ranking (NIST, 1 judgments mapped to 0)"
    },
    {
      "accessURL": "https://trec.nist.gov/data/deep/2023.qrels.pass.withDupes.txt",
      "title": "Passage Ranking NIST QRels"
    },
    {
      "accessURL": "https://trec.nist.gov/data/deep2023.html",
      "title": "2023 Deep Learning Data Page"
    }
  ],
  "identifier": "ark:/88434/mds2-3259",
  "issued": "2024-05-10",
  "keyword": [
    "TREC text retrieval conference"
  ],
  "landingPage": "https://data.nist.gov/od/id/mds2-3259",
  "language": [
    "en"
  ],
  "license": "https://www.nist.gov/open/license",
  "modified": "2024-05-08 00:00:00",
  "programCode": [
    "006:045"
  ],
  "publisher": {
    "@type": "org:Organization",
    "name": "National Institute of Standards and Technology"
  },
  "references": [
    "https://trec.nist.gov/pubs/trec32/papers/Overview_deep.pdf"
  ],
  "theme": [
    "Information Technology:Data and informatics"
  ],
  "title": "2023 TREC Deep Learning Track Dataset"
}