Predicate Importance Estimation and Decoupled Rationale-Score Distillation for Entity Alignment
Knowledge graphs (KGs) are increasingly used as structured context for Large Language Models (LLMs), but industrial KG-RAG systems often need to integrate public and domain-specific KGs constructed from heterogeneous databases. This integration relies on Entity Alignment (EA), where lexical matching alone is insufficient under predicate-name variation and incomplete local neighborhoods. We address EA for KG integration by constructing a pairwise EA dataset and proposing two complementary modules: Predicate Importance Estimation (PIE) and Decoupled Rationale-Score Distillation (DRSD). PIE is a compact embedding-based approach that removes the subject information from each 1-hop triple, enc...
| Authors | Keunha Kim, Yoonjin Jang, Hyeon-gu Lee et al. |
|---|---|
| Primary category | cs.CL |
| Published | 22 June 2026 |
| Last updated at source | 22 June 2026 |
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