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:
- 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)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2021.wassa-1.9.pdf
- Code
- Aaditya-Singh/E2E-ECPE
- Data
- ECE, Xia and Ding, 2019