SimpleQuestions v2
收藏帕依提提2024-03-04 收录
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资源简介：
TheSimpleQuestions, a dataset collected for research in automatic question answering with human generated questions. Details and baseline results on this dataset can be found in the paper: Antoine Bordes, Nicolas Usunier, Sumit Chopra and Jason Weston. Large-Scale Simple Question answering with Memory Networks, arXiv:1506.02075. The dataset consists of a total of 108,442 questions written in natural language by human English-speaking annotators each paired with a corresponding fact, formatted as (subject, relationship, object), that provides the answer but also a complete explanation. Facts have been extracted from the Knowledge Base Freebase. We randomly shuffle these questions and use 70% of them (75910) as training set, 10% as validation set (10845), and the remaining 20% as test set. Here are some examples of questions and facts:
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