Knowledge Graph Programming with a Human-in-the-Loop: Preliminary Results

Yuze Lou, Mahfus Uddin, Noam Brown, Michael J. Cafarella
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引用次数: 2

Abstract

In this paper we introduce knowledge graph programming, a new method for writing extremely succinct programs. This method allows programmers to save work by writing programs that are brief but also underspecified and underconstrained; a human-in-the-loop "data compiler" then automatically fills in missing values without the programmer's explicit help. It uses modern data quality mechanisms such as information extraction, data integration, and crowdsourcing. The language encourages users to mention knowledge graph entities in their programs, thus enabling the data compiler to exploit the extensive factual and type structure present in modern KGs. We describe the knowledge graph programming user experience, explain its conceptual steps and data model, describe our prototype KGP system, and present some preliminary experimental results.
知识图编程与人在循环:初步结果
本文介绍了知识图编程,这是一种编写极其简洁程序的新方法。这种方法允许程序员通过编写简短但不明确和不受约束的程序来节省工作;然后,人在循环中的“数据编译器”会自动填充缺失的值,而无需程序员的明确帮助。它使用现代数据质量机制,如信息提取、数据集成和众包。该语言鼓励用户在程序中提到知识图实体,从而使数据编译器能够利用现代KGP中存在的广泛的事实和类型结构。我们描述了知识图编程的用户体验,解释了其概念步骤和数据模型,描述了我们的原型KGP系统,并给出了一些初步的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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