SABET-QA: Temporal Knowledge Graph Question Answering
Question Answering over Temporal Knowledge Graphs (TKGQA) requires reasoning over time-sensitive facts, yet existing embedding-based methods struggle with multi-step queries due to single-pass reasoning pipelines. We propose SABET-QA, a framework that iteratively refines reasoning states across multiple hops via a bidirectional entity-temporal scoring mechanism and a slot-aware contextualization module that aligns question semantics with temporal KG embeddings. A differentiable working memory enables progressive hypothesis refinement, while auxiliary temporal boundaries serve as coarse supervision when available. Experiments on CronQuestions, Complex-CronQuestions, MultiTQ, and TimeQuesti...
| Authors | Brahim Touayouch, Mirette Moawad, Dmitry Akulov |
|---|---|
| Primary category | cs.CL |
| Published | 20 August 2026 |
| Last updated at source | 20 August 2026 |
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