timelinekgqa
TimelineKGQA: A Comprehensive Question-Answer Pair Generator for Temporal Knowledge Graphs
Sun, Qiang, Li, Sirui, Huynh, Du, Reynolds, Mark, Liu, Wei
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 \textbf{TimelineKGQA}, a universal temporal QA generator applicable to any TKGs. The code is available at: \url{https://github.com/PascalSun/TimelineKGQA} as an open source Python package.
Country:
- Oceania > Australia > Western Australia > Perth (0.05)
- Oceania > Australia > New South Wales > Sydney (0.05)
- Asia > Indonesia (0.05)
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Industry:
- Education (0.47)
- Government > Regional Government > North America Government > United States Government (0.47)
Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning > Temporal Reasoning (0.72)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Semantic Networks (0.64)
- Information Technology > Artificial Intelligence > Natural Language > Question Answering (0.57)