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QA-SRL 2020 (Gold Standard)

The dataset contains question-answer pairs to model verbal predicate-argument structure. The questions start with wh-words (Who, What, Where, What, etc.) and contain a verb predicate in the sentence; the answers are phrases in the sentence. This dataset, a.k.a "QASRL-GS" (Gold Standard) or "QASRL-2020", which was constructed via controlled crowdsourcing, includes high-quality QA-SRL annotations to serve as an evaluation set (dev and test) for models trained on the large-scale QA-SRL dataset (you can find it in this hub as biu-nlp/qa_srl2018).

See the paper for details: Controlled Crowdsourcing for High-Quality QA-SRL Annotation, Roit et. al., 2020.

Check out our GitHub repository to find code for evaluation.

The dataset was annotated by selected workers from Amazon Mechanical Turk.

Models trained or fine-tuned on biu-nlp/qa_srl2020

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