Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignment. (arXiv:2401.16960v1 [cs.CL])

Entity alignment, which is a prerequisite for creating a more comprehensive
Knowledge Graph (KG), involves pinpointing equivalent entities across disparate
KGs. Contemporary methods for entity alignment have predominantly utilized
knowledge embedding models to procure entity embeddings that encapsulate
various similarities-structural, relational, and attributive. These embeddings
are then integrated through attention-based information fusion mechanisms.
Despite this progress, effectively harnessing multifaceted information remains
challenging due to inherent heterogeneity. Moreover, while Large Language
Models (LLMs) have exhibited exceptional performance across diverse downstream
tasks …

alignment arxiv cs.cl embedding embedding models embeddings graph graphs knowledge knowledge graph knowledge graphs language language models large language large language models