Abstract
Computational detection of rhetorical figures focuses mostly on figures such as metaphor, irony, or analogy. However, there exist many more figures that are neither less important nor less prevalent. We wanted to pinpoint the reasons why researchers often avoid other figures and to shed light on the challenges they struggle with when investigating those figures. In this comprehensive survey, we analyzed over 40 papers dealing with the computational detection of rhetorical figures other than metaphor, simile, sarcasm, and irony. We encountered recurrent challenges from which we compiled a ten point list. Furthermore, we suggest solutions for each challenge to encourage researchers to investigate a greater variety of rhetorical figures.- Anthology ID:
- 2024.figlang-1.6
- Volume:
- Proceedings of the 4th Workshop on Figurative Language Processing (FigLang 2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico (Hybrid)
- Editors:
- Debanjan Ghosh, Smaranda Muresan, Anna Feldman, Tuhin Chakrabarty, Emmy Liu
- Venues:
- Fig-Lang | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 45–52
- Language:
- URL:
- https://aclanthology.org/2024.figlang-1.6
- DOI:
- Cite (ACL):
- Ramona Kühn and Jelena Mitrović. 2024. The Elephant in the Room: Ten Challenges of Computational Detection of Rhetorical Figures. In Proceedings of the 4th Workshop on Figurative Language Processing (FigLang 2024), pages 45–52, Mexico City, Mexico (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- The Elephant in the Room: Ten Challenges of Computational Detection of Rhetorical Figures (Kühn & Mitrović, Fig-Lang-WS 2024)
- PDF:
- https://preview.aclanthology.org/jeptaln-2024-ingestion/2024.figlang-1.6.pdf