Business Knowledge Graphs (KGs) are important to many enterprises today,
providing factual knowledge and structured data that steer many products and
make them more intelligent. Despite their promising benefits, building business
KG necessitates solving prohibitive issues of deficient structure and multiple
modalities. In this paper, we advance the understanding of the practical
challenges related to building KG in non-trivial real-world systems. We
introduce the process of building an open business knowledge graph (OpenBG)
derived from a well-known enterprise, Alibaba Group. Specifically, we define a
core ontology to cover various abstract products and consumption demands, with
fine-grained taxonomy and multimodal facts in deployed applications. OpenBG is
an open business KG of unprecedented scale: 2.6 billion triples with more than
88 million entities covering over 1 million core classes/concepts and 2,681
types of relations. We release all the open resources (OpenBG benchmarks)
derived from it for the community and report experimental results of KG-centric
tasks. We also run up an online competition based on OpenBG benchmarks, and has
attracted thousands of teams. We further pre-train OpenBG and apply it to many
KG- enhanced downstream tasks in business scenarios, demonstrating the
effectiveness of billion-scale multimodal knowledge for e-commerce. All the
resources with codes have been released at
https://github.com/OpenBGBenchmark/OpenBG.

本文介绍了基于企业阿里巴巴集团的知识图谱的构建过程及其应用，形成了一个前所未有规模的公开业务知识图谱 OpenBG，其中覆盖了各种抽象产品和消费需求，包括精细的分类和多模态事实，并分享了 OpenBG 基准资源以及基于 OpenBG 基准的在线竞赛结果。