arXiv cs.CL· Feng Liang, Weixin Zeng, Runhao Zhao, Mingjun Zhou, Shaoshi Yang, Xiang Zhao·· 13 小时前AI 评分22
ChronoSynth：面向时序知识图谱的约束感知问题生成框架
ChronoSynth: Constraint-Aware Question Synthesis over Temporal Knowledge Graphs
AI 导读
ChronoSynth 是一个记忆增强、约束感知的时序知识图谱问题生成框架，通过构建 Temporal Intent State 显式表达问题语义，并从索引模式记忆中检索兼容的类型化问题模式进行适配与校验。
正文 · 原文
Abstract:Knowledge graph question generation (KGQG) generates natural-language questions from structured graph evidence and a target answer. When the input graph is temporal, a valid question must also preserve the answer field, time condition, reference event, and temporal order that determine the answer set. Existing KGQG methods and prompting baselines can produce fluent questions that alter these conditions, causing temporal semantic drift. This paper studies temporal KGQG as a constraint-preserving graph-to-question problem and proposes ChronoSynth, a memory-augmented and constraint-aware generation framework. ChronoSynth first constructs a Temporal Intent State to make the intended question semantics explicit. It then retrieves compatible typed question patterns from an indexed pattern memory, adapts them to the input graph, and validates the generated question. Validation feedback guides revisions when a supported inconsistency is detected. Experiments on CRONQUESTIONS and MultiTQ demonstrate state-of-the-art generation performance, with ablations supporting the contributions of its components.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.29339 [cs.CL] |
| (or arXiv:2610.29339v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.29339 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Feng Liang [view email]
[v1]
Wed, 21 Oct 2026 07:35:17 UTC (388 KB)
来源：arXiv cs.CL · arxiv.org