mlsanityData to 7 Oct 2026

TimelineKGQA: A Comprehensive Question-Answer Pair Generator for Temporal Knowledge Graphs

arXiv 2501.04343 ↗First posted 8 Jan 2025cs.LO cs.AI cs.CLcited by 5

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Abstract (arXiv)

Question answering over temporal knowledge graphs (TKGs) is crucial for understanding evolving facts and relationships, yet its development is hindered by limited datasets and difficulties in generating custom QA pairs. We propose a novel categorization framework based on timeline-context relationships, along with TimelineKGQA, a universal temporal QA generator applicable to any TKGs. The code is available at: urlhttps://github.com/PascalSun/TimelineKGQA as an open source Python package.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 5 of its 8 references that are in the map. First posted on arXiv 8 Jan 2025.

Builds on

5 of 8 references.

References · 5

  1. 2021A Dataset for Answering Time-Sensitive Questionscited by 150
  2. 2021Question Answering Over Temporal Knowledge Graphscited by 99
  3. 2021Complex Temporal Question Answering on Knowledge Graphscited by 69
  4. 2024Question Calibration and Multi-Hop Modeling for Temporal Question Answeringcited by 25
  5. 2024Faithful Temporal Question Answering over Heterogeneous Sourcescited by 13

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025TRAVELER: A Benchmark for Evaluating Temporal Reasoning across Vague, Implicit and Explicit Referencescited by 3
  2. 2025Plan of Knowledge: Retrieval-Augmented Large Language Models for Temporal Knowledge Graph Question Answeringcited by 2
  3. 2026Let the Agent Search: Autonomous Exploration Beats Rigid Workflows in Temporal Question Answeringcited by 0
  4. 2026The Dynamic Gist-Based Memory Model (DGMM): A Memory-Centric Architecture for Artificial Intelligencecited by 0
  5. 2026ChronoQG: Towards a Temporally Expressive and Hop-Bounded Benchmark for Temporal Knowledge Graph Question Generationcited by 0