Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
80 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
7 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Relation-Aware Question Answering for Heterogeneous Knowledge Graphs (2312.11922v1)

Published 19 Dec 2023 in cs.CL and cs.AI

Abstract: Multi-hop Knowledge Base Question Answering(KBQA) aims to find the answer entity in a knowledge graph (KG), which requires multiple steps of reasoning. Existing retrieval-based approaches solve this task by concentrating on the specific relation at different hops and predicting the intermediate entity within the reasoning path. During the reasoning process of these methods, the representation of relations are fixed but the initial relation representation may not be optimal. We claim they fail to utilize information from head-tail entities and the semantic connection between relations to enhance the current relation representation, which undermines the ability to capture information of relations in KGs. To address this issue, we construct a \textbf{dual relation graph} where each node denotes a relation in the original KG (\textbf{primal entity graph}) and edges are constructed between relations sharing same head or tail entities. Then we iteratively do primal entity graph reasoning, dual relation graph information propagation, and interaction between these two graphs. In this way, the interaction between entity and relation is enhanced, and we derive better entity and relation representations. Experiments on two public datasets, WebQSP and CWQ, show that our approach achieves a significant performance gain over the prior state-of-the-art. Our code is available on \url{https://github.com/yanmenxue/RAH-KBQA}.

PDF HTML Abstract
Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Bookmark Chat Bubble Oval Streamline Icon: https://streamlinehq.com Chat (Pro)
Definition Search Book Streamline Icon: https://streamlinehq.com
References (34)
  1. Sqaler: Scaling question answering by decoupling multi-hop and logical reasoning. Advances in Neural Information Processing Systems, 34:12587–12599.
  2. Semantic parsing on freebase from question-answer pairs. In Proceedings of the 2013 conference on empirical methods in natural language processing, pages 1533–1544.
  3. Freebase: a collaboratively created graph database for structuring human knowledge. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data, pages 1247–1250.
  4. Translating embeddings for modeling multi-relational data. Advances in neural information processing systems, 26.
  5. Program transfer for answering complex questions over knowledge bases. arXiv preprint arXiv:2110.05743.
  6. Learning phrase representations using rnn encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078.
  7. Scalable neural methods for reasoning with a symbolic knowledge base. arXiv preprint arXiv:2002.06115.
  8. Question answering over freebase with multi-column convolutional neural networks. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 260–269.
  9. Building watson: An overview of the deepqa project. AI magazine, 31(3):59–79.
  10. Dialog-to-action: Conversational question answering over a large-scale knowledge base. In Advances in Neural Information Processing Systems, pages 2942–2951.
  11. Improving multi-hop knowledge base question answering by learning intermediate supervision signals. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining, pages 553–561.
  12. Unikgqa: Unified retrieval and reasoning for solving multi-hop question answering over knowledge graph. arXiv preprint arXiv:2212.00959.
  13. Neural symbolic machines: Learning semantic parsers on freebase with weak supervision. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 23–33.
  14. Focal loss for dense object detection. In Proceedings of the IEEE international conference on computer vision, pages 2980–2988.
  15. Costas Mavromatis and George Karypis. 2022. Rearev: Adaptive reasoning for question answering over knowledge graphs. arXiv preprint arXiv:2210.13650.
  16. Stepwise reasoning for multi-relation question answering over knowledge graph with weak supervision. In Proceedings of the 13th International Conference on Web Search and Data Mining, pages 474–482.
  17. Nils Reimers and Iryna Gurevych. 2019. Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084.
  18. Complex program induction for querying knowledge bases in the absence of gold programs. Transactions of the Association for Computational Linguistics, 7:185–200.
  19. Improving multi-hop question answering over knowledge graphs using knowledge base embeddings. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4498–4507.
  20. Expanding end-to-end question answering on differentiable knowledge graphs with intersection. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 8805–8812.
  21. Transfernet: An effective and transparent framework for multi-hop question answering over relation graph. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 4149–4158.
  22. Pullnet: Open domain question answering with iterative retrieval on knowledge bases and text. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 2380–2390.
  23. Open domain question answering using early fusion of knowledge bases and text. arXiv preprint arXiv:1809.00782.
  24. Alon Talmor and Jonathan Berant. 2018. The web as a knowledge-base for answering complex questions. arXiv preprint arXiv:1803.06643.
  25. Graph attention networks. arXiv preprint arXiv:1710.10903.
  26. Modelling long-distance node relations for kbqa with global dynamic graph. In Proceedings of the 28th International Conference on Computational Linguistics, pages 2572–2582.
  27. Relation-aware entity alignment for heterogeneous knowledge graphs. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence.
  28. Rng-kbqa: Generation augmented iterative ranking for knowledge base question answering. arXiv preprint arXiv:2109.08678.
  29. Semantic parsing via staged query graph generation: Question answering with knowledge base. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1321–1331.
  30. Decaf: Joint decoding of answers and logical forms for question answering over knowledge bases. arXiv preprint arXiv:2210.00063.
  31. Variational reasoning for question answering with knowledge graph. In Thirty-Second AAAI Conference on Artificial Intelligence.
  32. Simple question answering with subgraph ranking and joint-scoring. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 324–334.
  33. Graph neural networks: A review of methods and applications. AI Open, 1:57–81.
  34. An interpretable reasoning network for multi-relation question answering. In Proceedings of the 27th International Conference on Computational Linguistics, pages 2010–2022.
User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (6)
  1. Haowei Du (7 papers)
  2. Quzhe Huang (22 papers)
  3. Chen Li (386 papers)
  4. Chen Zhang (403 papers)
  5. Yang Li (1140 papers)
  6. Dongyan Zhao (144 papers)
Citations (2)
View on Semantic Scholar
Github Logo Streamline Icon: https://streamlinehq.com

GitHub

  1. GitHub - yanmenxue/RAH-KBQA (6 stars)