Is Complex Query Answering Really Complex?
Cosimo Gregucci, Bo Xiong, Daniel Hernández, Lorenzo Loconte, Pasquale Minervini, Steffen Staab, Antonio Vergari
摘要
Complex query answering (CQA) on knowledge graphs (KGs) is gaining momentum as a challenging reasoning task. In this paper, we show that the current benchmarks for CQA might not be as complex as we think, as the way they are built distorts our perception of progress in this field. For example, we find that in these benchmarks, most queries (up to 98% for some query types) can be reduced to simpler problems, e.g. link prediction, where only one link needs to be predicted.The performance of state-of-the-art CQA models decreases significantly when such models are evaluated on queries that cannot be reduced to easier types. Thus, we propose a set of more challenging benchmarks composed of queries that require models to reason over multiple hops and better reflect the construction of real-world KGs. In a systematic empirical investigation, the new benchmarks show that current methods leave much to be desired from current CQA methods. 1 Not to be confused with the computational complexity of query answering (Dalvi & Suciu, 2012). 2 Also known as projection in related works (Ren et al., 2023) .
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- Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box EmbeddingsHongyu Ren, Weihua Hu, Jure LeskovecICLR 2020 · 被引用 355 次
- Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge GraphsHongyu Ren, Jure LeskovecNeurIPS 2020 · 被引用 267 次
- ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge GraphsZhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji 等NeurIPS 2021 · 被引用 161 次
- Faithful Embeddings for Knowledge Base QueriesHaitian Sun, Andrew O. Arnold, Tania Bedrax-Weiss, Fernando Pereira 等NeurIPS 2020 · 被引用 104 次
- Towards Foundation Models for Knowledge Graph ReasoningMikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang 等ICLR 2024 · 被引用 95 次
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- Maestro: Automatic Generation of Comprehensive Benchmarks for Question Answering Over Knowledge GraphsAbdelghny Orogat, Ahmed El-RobySIGMOD 2023 · 被引用 10 次
- Can LLMs Evaluate Complex Attribution in QA? Automatic Benchmarking using Knowledge GraphsNan Hu, Jiaoyan Chen, Yike Wu, Guilin Qi 等ACL 2025
