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We examine the problem of question answering over knowledge graphs, focusingon simple questions that can be answered by the lookup of a single fact.Adopting a straightforward decomposition of the problem into entity detection,entity linking, relation prediction, and evidence combination, we exploresimple yet strong baselines. On the popular SimpleQuestions dataset, we findthat basic LSTMs and GRUs plus a few heuristics yield accuracies that approachthe state of the art, and techniques that do not use neural networks alsoperform reasonably well. These results show that gains from sophisticated deeplearning techniques proposed in the literature are quite modest and that someprevious models exhibit unnecessary complexity.

Strong Baselines for Simple Question Answering over Knowledge Graphs with and without Neural Networks