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Text · dataset · 2022

stanfordnlp/concurrentqa

Listed in Hugging Face Datasets

ConcurrentQA is a textual multi-hop QA benchmark to require concurrent retrieval over multiple data-distributions (i.e. Wikipedia and email data).

Description

This dataset was constructed by researchers at Stanford and FAIR, following the data collection process and schema of HotpotQA. This benchmark can be used to study generalization in retrieval as well as privacy when reasoning across multiple privacy scopes --- i.e. public Wikipedia documents and private emails.

This dataset is for the… See the full description on the dataset page: huggingface.co/datasets/stanfordnlp/concurrentqa.

Links

Where it is published

Catalogue records · 1

Topics

Stated by source
question answering · text
Inferred from text
Theory of computation 69%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetsstanfordnlp/concurrentqa12 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].anzsrc:group:4613enrichment · Hugging Facetaxonomy-embedding@1.1.0title+keywords+description (69%)
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:textsource · Hugging Faceconnector:huggingface@1.0.0
concepts[task].hf_task:question-answeringsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
licensesource · Hugging Faceconnector:huggingface@1.0.0/tags[license:*]
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0