Abstract
Knowledge Graph Question Answering (KGQA) involves retrieving entities as answers from a Knowledge Graph (KG) using natural language queries. The challenge is to learn to reason over question-relevant KG facts that traverse KG entities and lead to the question answers. To facilitate reasoning, the question is decoded into instructions, which are dense question representations used to guide the KG traversals. However, if the derived instructions do not exactly match the underlying KG information, they may lead to reasoning under irrelevant context.Our method, termed ReaRev, introduces a new way to KGQA reasoning with respectto both instruction decoding and execution. To improve instruction decoding, we perform reasoning in an adaptive manner, where KG-aware information is used to iteratively update the initial instructions. To improve instruction execution, we emulate breadth-first search (BFS) with graph neural networks (GNNs). The BFS strategy treats the instructions as a set and allows our method to decide on their execution order on the fly. Experimental results on three KGQA benchmarks demonstrate the ReaRev’s effectiveness compared with previous state-of-the-art, especially when the KG is incomplete or when we tackle complex questions. Our code is publicly available at https://github.com/cmavro/ReaRev_KGQA.- Anthology ID:
- 2022.findings-emnlp.181
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2022
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates
- Editors:
- Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2447–2458
- Language:
- URL:
- https://aclanthology.org/2022.findings-emnlp.181
- DOI:
- 10.18653/v1/2022.findings-emnlp.181
- Cite (ACL):
- Costas Mavromatis and George Karypis. 2022. ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 2447–2458, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
- Cite (Informal):
- ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs (Mavromatis & Karypis, Findings 2022)
- PDF:
- https://preview.aclanthology.org/naacl-24-ws-corrections/2022.findings-emnlp.181.pdf