Exploring and Evaluating Attributes, Values, and Structures for Entity Alignment

empirical methods in natural language processing, pp. 6355-6364, 2020.

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We propose a novel Entity Alignment model and contribute a hard experimental setting for practical evaluation

Abstract:

Entity alignment (EA) aims at building a unified Knowledge Graph (KG) of rich content by linking the equivalent entities from various KGs. GNN-based EA methods present promising performance by modeling the KG structure defined by relation triples. However, attribute triples can also provide crucial alignment signal but have not been well ...More

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