Question-Driven Span Labeling Model for Aspect–Opinion Pair Extraction

Authors

  • Lei Gao State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications EBUPT Information Technology Co., Ltd.
  • Yulong Wang State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications EBUPT Information Technology Co., Ltd.
  • Tongcun Liu School of Information Engineering, Zhejiang A&F University EBUPT Information Technology Co., Ltd.
  • Jingyu Wang State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications EBUPT Information Technology Co., Ltd.
  • Lei Zhang State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications EBUPT Information Technology Co., Ltd.
  • Jianxin Liao State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications EBUPT Information Technology Co., Ltd.

Keywords:

Information Extraction

Abstract

Aspect term extraction and opinion word extraction are two fundamental subtasks of aspect-based sentiment analysis. The internal relationship between aspect terms and opinion words is typically ignored, and information for the decision-making of buyers and sellers is insufficient. In this paper, we explore an aspect–opinion pair extraction (AOPE) task and propose a Question-Driven Span Labeling (QDSL) model to extract all the aspect–opinion pairs from user-generated reviews. Specifically, we divide the AOPE task into aspect term extraction (ATE) and aspect-specified opinion extraction (ASOE) subtasks; we first extract all the candidate aspect terms and then the corresponding opinion words given the aspect term. Unlike existing approaches that use the BIO-based tagging scheme for extraction, the QDSL model adopts a span-based tagging scheme and builds a question–answer-based machine-reading comprehension task for an effective aspect–opinion pair extraction. Extensive experiments conducted on three tasks (ATE, ASOE, and AOPE) on four benchmark datasets demonstrate that the proposed method significantly outperforms state-of-the-art approaches.

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Published

2021-05-18

How to Cite

Gao, L., Wang, Y., Liu, T., Wang, J., Zhang, L., & Liao, J. (2021). Question-Driven Span Labeling Model for Aspect–Opinion Pair Extraction. Proceedings of the AAAI Conference on Artificial Intelligence, 35(14), 12875-12883. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17523

Issue

Section

AAAI Technical Track on Speech and Natural Language Processing I