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Synthesizing event semantics for temporal knowledge graph reasoning
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AI
DOI：10.1016/j.ipm.2026.105232.png)
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Abstract
En 中文
• Fact-aligned event semantics are integrated at both the data and model levels to enhance reasoning in temporal knowledge graphs.
• Hierarchical event type semantics improve the discriminability of relation representations.
• Static background semantics enrich entity and contextual representations.
• Dynamic and static semantics are adaptively fused for future entity and relation prediction.
Keywords:
Knowledge graph
Event semantics
Temporal knowledge graph reasoning
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