Abstract
In this paper, we present our approach and empirical observations for Cause-Effect Signal Span Detection—Subtask 2 of Shared task 3 at CASE 2022. The shared task aims to extract the cause, effect, and signal spans from a given causal sentence.We model the task as a reading comprehension (RC) problem and apply a token-level RC-based span prediction paradigm to the task as the baseline.We explore different training objectives to fine-tune the model, as well as data augmentation (DA) tricks based on the language model (LM) for performance improvement.Additionally, we propose an efficient beam-search post-processing strategy to due with the drawbacks of span detection to obtain a further performance gain.Our approach achieves an average $F_1$ score of 54.15 and ranks {textbf{$1ˆ{st}$} in the CASE competition. Our code is available at {url{https://github.com/Gzhang-umich/1CademyTeamOfCASE}.- Anthology ID:
- 2022.case-1.14
- Volume:
- Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Venue:
- CASE
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 100–105
- Language:
- URL:
- https://aclanthology.org/2022.case-1.14
- DOI:
- Cite (ACL):
- Xingran Chen, Ge Zhang, Adam Nik, Mingyu Li, and Jie Fu. 2022. 1Cademy @ Causal News Corpus 2022: Enhance Causal Span Detection via Beam-Search-based Position Selector. In Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE), pages 100–105, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- 1Cademy @ Causal News Corpus 2022: Enhance Causal Span Detection via Beam-Search-based Position Selector (Chen et al., CASE 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.case-1.14.pdf