I. Introduction
Knowledge Graphs (KGs) are one of the most effective ways to organize world facts in the form of a directed graph, where nodes denote entities and edges denote their relations. Recently, a series of KGs have been curated in various domains, including medicine [1], health care [2], and finance [3]. They are playing an increasingly important role in a variety of applications, such as drug discovery [4], user modeling [5], [6], dialog system [7], and question answering [8], [9]. However, existing KGs suffer from serious incompleteness issues. Due to the high cost of manual labeling, KG Completion (KGC) becomes an essential task for predicting missing facts based on an incomplete KG.