Datasets › QA-SRL

QA-SRL

Introduced by Luheng He et al. in Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language1 Jan 2015 archive 2025-07-28

QA-SRL was proposed as an open schema for semantic roles, in which the relation between an argument and a predicate is expressed as a natural-language question containing the predicate (“Where was someone educated?”) whose answer is the argument (“Princeton”). The authors collected about 19,000 question-answer pairs from 3,200 sentences.

Source: Zero-Shot Relation Extraction via Reading Comprehension Image Source: http://browse.qasrl.org/

Homepage JSON

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 43 papers for it but never published that list.

Dataset loaders archive 2025-07-28

huggingface.co/datasets/luheng/qa_srl huggingface/datasetstfpytorchjax

huggingface.co/datasets/qa_srl huggingface/datasetstfpytorchjax

parl.ai/docs/tasks.html#qa-srl-semantic-role-labeling facebookresearch/ParlAIpytorch

3 loaders as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

Relation Extraction Open Information Extraction Semantic Role Labeling

License archive 2025-07-28

Unknown

Modalities archive 2025-07-28

Texts

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

QA-SRL

1 variant name, as the archive lists them.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections