论文标题
从互动小说中得出常识性推理任务
Deriving Commonsense Inference Tasks from Interactive Fictions
论文作者
论文摘要
常识性推理模拟了人类对我们物理世界做出推定的能力，这是建立通用AI系统的必不可少的基石。我们根据人类的互动小说游戏玩法提出了一个新的常识性推理数据集，因为人类玩家表现出丰富而多样的常识性推理。新的数据集减轻了先前艺术的几个局限性。实验表明，我们的任务可以解决给具有足够常识知识的人类专家，但对现有机器阅读模型构成了挑战，其性能差距很大30％以上。
Commonsense reasoning simulates the human ability to make presumptions about our physical world, and it is an indispensable cornerstone in building general AI systems. We propose a new commonsense reasoning dataset based on human's interactive fiction game playings as human players demonstrate plentiful and diverse commonsense reasoning. The new dataset mitigates several limitations of the prior art. Experiments show that our task is solvable to human experts with sufficient commonsense knowledge but poses challenges to existing machine reading models, with a big performance gap of more than 30%.
