matinf

MATINF is the first jointly labeled large-scale dataset for classification, question answering and summarization.
MATINF contains 1.07 million question-answer pairs with human-labeled categories and user-generated question
descriptions. Based on such rich information, MATINF is applicable for three major NLP tasks, including classification,
question answering, and summarization. We benchmark existing methods and a novel multi-task baseline over MATINF to
inspire further research. Our comprehensive comparison and experiments over MATINF and other datasets demonstrate the
merits held by MATINF.

MATINF乃首个联合标注的大型规模数据集，旨在用于分类、问答和摘要等自然语言处理任务。该数据集包含约107万条由人类标注的问答对以及用户生成的问答描述。基于如此丰富的信息资源，MATINF适用于包括分类、问答和摘要在内的三大主要自然语言处理任务。我们对现有方法以及基于MATINF的全新多任务基线进行了基准测试，以激发进一步的研究。在MATINF及其他数据集上的全面比较与实验，展现了MATINF所具有的显著优势。