ONSEP: A Novel Online Neural-Symbolic Framework for Event Prediction Based on Large Language Model

Xuanqing Yu, Wangtao Sun, Jingwei Li, Kang Liu, Chengbao Liu, Jie Tan


Abstract
In the realm of event prediction, temporal knowledge graph forecasting (TKGF) stands as a pivotal technique. Previous approaches face the challenges of not utilizing experience during testing and relying on a single short-term history, which limits adaptation to evolving data. In this paper, we introduce the Online Neural-Symbolic Event Prediction (ONSEP) framework, which innovates by integrating dynamic causal rule mining (DCRM) and dual history augmented generation (DHAG). DCRM dynamically constructs causal rules from real-time data, allowing for swift adaptation to new causal relationships. In parallel, DHAG merges short-term and long-term historical contexts, leveraging a bi-branch approach to enrich event prediction. Our framework demonstrates notable performance enhancements across diverse datasets, with significant Hit@k (k=1,3,10) improvements, showcasing its ability to augment large language models (LLMs) for event prediction without necessitating extensive retraining. The ONSEP framework not only advances the field of TKGF but also underscores the potential of neural-symbolic approaches in adapting to dynamic data environments.
Anthology ID:
2024.findings-acl.378
Volume:
Findings of the Association for Computational Linguistics: ACL 2024
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6335–6350
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/2024.findings-acl.378/
DOI:
10.18653/v1/2024.findings-acl.378
Bibkey:
Cite (ACL):
Xuanqing Yu, Wangtao Sun, Jingwei Li, Kang Liu, Chengbao Liu, and Jie Tan. 2024. ONSEP: A Novel Online Neural-Symbolic Framework for Event Prediction Based on Large Language Model. In Findings of the Association for Computational Linguistics: ACL 2024, pages 6335–6350, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
ONSEP: A Novel Online Neural-Symbolic Framework for Event Prediction Based on Large Language Model (Yu et al., Findings 2024)
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PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/2024.findings-acl.378.pdf