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MuLD: The Multitask Long Document Benchmark [dataset]

NarrativeQA - validation [dataset] Open Access

MuLD (Multitask Long Document Benchmark) is a set of 6 NLP tasks where the inputs consist of at least 10,000 words. The benchmark covers a wide variety of task types including translation, summarization, question answering, and classification. Additionally there is a range of output lengths from a single word classification label all the way up to an output longer than the input text.

Descriptions

Resource type
Dataset
Contributors
Data collector: Hudson, G Thomas 1
1 Durham Univesity
Funder
Research methods
Other description
Keyword
nlp
multitask
long document
Subject
Location
Language
Cited in
Identifier
ark:/32150/r2cf95jb47p
Rights
MIT Licence (MIT)

Publisher
Durham University
Date Created

File Details

Depositor
G.T. Hudson
Date Uploaded
Date Modified
3 May 2022, 13:05:45
Audit Status
Audits have not yet been run on this file.
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Characterization
File format: x-bzip2 (bzip2 compressed data, block size = 900k, BZ2, Bzip2)
Mime type: application/x-bzip2
File size: 219089409
Last modified: 2022:04:26 16:12:05+01:00
Filename: narrativeqa_validation.json.bz2
Original checksum: a04b447014cd30fbf5f022acc7903e37
Activity of users you follow
User Activity Date
User N. Syrotiuk has updated NarrativeQA - validation [dataset] over 2 years ago
User G.T. Hudson has updated NarrativeQA - validation [dataset] over 2 years ago
User G.T. Hudson has updated narrativeqa_validation.json.bz2 [dataset] over 2 years ago
User G.T. Hudson has deposited narrativeqa_validation.json.bz2 over 2 years ago