An End-to-End Network for Emotion-Cause Pair Extraction

Aaditya Singh, Shreeshail Hingane, Saim Wani, Ashutosh Modi


Abstract
The task of Emotion-Cause Pair Extraction (ECPE) aims to extract all potential clause-pairs of emotions and their corresponding causes in a document. Unlike the more well-studied task of Emotion Cause Extraction (ECE), ECPE does not require the emotion clauses to be provided as annotations. Previous works on ECPE have either followed a multi-stage approach where emotion extraction, cause extraction, and pairing are done independently or use complex architectures to resolve its limitations. In this paper, we propose an end-to-end model for the ECPE task. Due to the unavailability of an English language ECPE corpus, we adapt the NTCIR-13 ECE corpus and establish a baseline for the ECPE task on this dataset. On this dataset, the proposed method produces significant performance improvements (∼ 6.5% increase in F1 score) over the multi-stage approach and achieves comparable performance to the state-of-the-art methods.
Anthology ID:
2021.wassa-1.9
Volume:
Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
Month:
April
Year:
2021
Address:
Online
Venue:
WASSA
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
84–91
Language:
URL:
https://aclanthology.org/2021.wassa-1.9
DOI:
Bibkey:
Cite (ACL):
Aaditya Singh, Shreeshail Hingane, Saim Wani, and Ashutosh Modi. 2021. An End-to-End Network for Emotion-Cause Pair Extraction. In Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 84–91, Online. Association for Computational Linguistics.
Cite (Informal):
An End-to-End Network for Emotion-Cause Pair Extraction (Singh et al., WASSA 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/remove-xml-comments/2021.wassa-1.9.pdf
Code
 Aaditya-Singh/E2E-ECPE
Data
ECEXia and Ding, 2019