2023
DOI: 10.48550/arxiv.2302.02601
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Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction

Abstract: Knowledge graphs represent known facts using triplets. While existing knowledge graph embedding methods only consider the connections between entities, we propose considering the relationships between triplets. For example, let us consider two triplets T1 and T2 where T1 is (Academy Awards, Nominates, Avatar) and T2 is (Avatar, Wins, Academy Awards). Given these two base-level triplets, we see that T1 is a prerequisite for T2. In this paper, we define a higher-level triplet to represent a relationship between … Show more

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