SQuAD

doi:doi:10.57702/r783klx9

SQuAD

The dataset used in the paper is a multiple-choice reading comprehension dataset, which includes a passage, question, and answer. The passage is a script, and the question is a multiple-choice question. The answer is one of the options in the multiple-choice question.

BibTex:

@dataset{Pranav_Rajpurkar_and_Jian_Zhang_and_Konstantin_Lopyrev_and_Percy_Liang_2024,
    abstract = {The dataset used in the paper is a multiple-choice reading comprehension dataset, which includes a passage, question, and answer. The passage is a script, and the question is a multiple-choice question. The answer is one of the options in the multiple-choice question.},
    author = {Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
    doi = {10.57702/r783klx9},
    institution = {No Organization},
    keyword = {'Multiple Choice', 'Natural Language Processing', 'Question Answering', 'SQuAD', 'SQuAD dataset', 'Text Classification', 'Wikipedia passages', 'contextual understanding', 'entailment', 'entities', 'multiple-choice', 'natural language inference', 'natural language processing', 'natural language question answering', 'natural language understanding', 'passage understanding', 'question answering', 'question generation', 'reading comprehension', 'relations', 'script knowledge', 'single entity', 'single relation', 'span-based', 'transformer model'},
    month = {nov},
    publisher = {TIB},
    title = {SQuAD},
    url = {https://service.tib.eu/ldmservice/dataset/squad},
    year = {2024}
}