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Table · dataset · 2022

DISFL-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Listed in Hugging Face Datasets

Dataset Card for DISFL-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering Dataset

Description

Summary

Disfl-QA is a targeted dataset for contextual disfluencies in an information seeking setting, namely question answering over Wikipedia passages. Disfl-QA builds upon the SQuAD-v2 (Rajpurkar et al., 2018) dataset, where each question in the dev set is annotated to add a contextual disfluency using the paragraph as a source of distractors. The final dataset… See the full description on the dataset page: huggingface.co/datasets/google-research-datasets/disfl_qa.

Links

Documentation and papers

Catalogue records · 1

Topics

Stated by source
question answering · text
Inferred from text
Artificial intelligence 72%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetsgoogle-research-datasets/disfl_qa13 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].anzsrc:group:4602enrichment · Hugging Facetaxonomy-embedding@1.1.0title+keywords+description (72%)
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
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