Abstract
This paper presents the winning system participating in the ACL 2024 workshop SIGHAN-10 shared task: Chinese dimensional aspect-based sentiment analysis (dimABSA). This task aims to identify four sentiment elements in restaurant reviews: aspect, category, opinion, and sentiment intensity evaluated in valence-arousal dimensions, providing a concise yet fine-grained sentiment description for user opinions. To tackle this task, we introduce a system that integrates BERT and large language models (LLM) to leverage their strengths. First, we explore their performance in entity extraction, relation classification, and intensity prediction. Based on preliminary experiments, we develop an integrated approach to fully utilize their advantages in different scenarios. Our system achieves first place in all subtasks and obtains a 41.7% F1-score in quadruple extraction.- Anthology ID:
- 2024.sighan-1.20
- Volume:
- Proceedings of the 10th SIGHAN Workshop on Chinese Language Processing (SIGHAN-10)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Kam-Fai Wong, Min Zhang, Ruifeng Xu, Jing Li, Zhongyu Wei, Lin Gui, Bin Liang, Runcong Zhao
- Venues:
- SIGHAN | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 175–185
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.sighan-1.20/
- DOI:
- Cite (ACL):
- Hongling Xu, Delong Zhang, Yice Zhang, and Ruifeng Xu. 2024. HITSZ-HLT at SIGHAN-2024 dimABSA Task: Integrating BERT and LLM for Chinese Dimensional Aspect-Based Sentiment Analysis. In Proceedings of the 10th SIGHAN Workshop on Chinese Language Processing (SIGHAN-10), pages 175–185, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- HITSZ-HLT at SIGHAN-2024 dimABSA Task: Integrating BERT and LLM for Chinese Dimensional Aspect-Based Sentiment Analysis (Xu et al., SIGHAN 2024)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.sighan-1.20.pdf