Emotion-Cause Pair Extraction as Question Answering

Huu-Hiep Nguyen, Minh-Tien Nguyen

2023

Abstract

The task of Emotion-Cause Pair Extraction (ECPE) aims to extract all potential emotion-cause pairs of a document without any annotation of emotion or cause clauses. Previous approaches on ECPE have tried to improve conventional two-step processing schemes by using complex architectures for modeling emotion-cause interaction. In this paper, we cast the ECPE task to the question answering (QA) problem and propose simple yet effective BERT-based solutions to tackle it. Given a document, our Guided-QA model first predicts the best emotion clause using a fixed question. Then the predicted emotion is used as a question to predict the most potential cause for the emotion. We evaluate our model on a standard ECPE corpus. The experimental results show that despite its simplicity, our Guided-QA achieves promising results and is easy to reproduce. The code of Guided-QA is also provided.

Paper Citation

in Harvard Style

Nguyen H. and Nguyen M. (2023). Emotion-Cause Pair Extraction as Question Answering. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 988-995. DOI: 10.5220/0011883100003393

in Bibtex Style

@conference{icaart23,
author={Huu-Hiep Nguyen and Minh-Tien Nguyen},
title={Emotion-Cause Pair Extraction as Question Answering},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={988-995},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011883100003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Emotion-Cause Pair Extraction as Question Answering
SN - 978-989-758-623-1
AU - Nguyen H.
AU - Nguyen M.
PY - 2023
SP - 988
EP - 995
DO - 10.5220/0011883100003393