Compiling commonsense knowledge is traditionally an AI topic approached by manual labor. Recent advances in web data processing have enabled automated approaches. In this demonstration we will showcase three systems for automated commonsense knowledge base construction, highlighting each time one aspect of specific interest to the data management community. (i) We use Quasimodo to illustrate knowledge extraction systems engineering, (ii) Dice to illustrate the role that schema constraints play in cleaning fuzzy commonsense knowledge, and (iii) Ascent to illustrate the relevance of conceptual modelling. The demos are available online at https://quasimodo.r2.enst.fr, https://dice.mpi-inf.mpg.de and ascent.mpi-inf.mpg.de.

中文翻译：

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大数据时代的常识知识库建设

传统上，编译常识知识是人工劳动解决的AI主题。Web数据处理的最新进展使自动化方法成为可能。在这个演示中，我们将展示三种用于自动常识知识库构建的系统，每次都突出显示数据管理社区特定关注的一个方面。（i）我们使用Quasimodo来说明知识提取系统工程，（ii）使用Dice来说明架构约束在清除模糊常识知识中的作用，并且（iii）使用Ascent来说明概念建模的相关性。该演示可在https：//quasimodo.r2.enst.fr、https：//dice.mpi-inf.mpg.de和ascent.mpi-inf.mpg.de在线获得。