Abstract
Given a specific discourse, which discourse properties trigger the use of metaphorical language, rather than using literal alternatives? For example, what drives people to say grasp the meaning rather than understand the meaning within a specific context? Many NLP approaches to metaphorical language rely on cognitive and (psycho-)linguistic insights and have successfully defined models of discourse coherence, abstractness and affect. In this work, we build five simple models relying on established cognitive and linguistic properties ? frequency, abstractness, affect, discourse coherence and contextualized word representations ? to predict the use of a metaphorical vs. synonymous literal expression in context. By comparing the models? outputs to human judgments, our study indicates that our selected properties are not sufficient to systematically explain metaphorical vs. literal language choices.- Anthology ID:
- 2022.starsem-1.26
- Volume:
- Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, Washington
- Venue:
- *SEM
- SIG:
- SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 299–310
- Language:
- URL:
- https://aclanthology.org/2022.starsem-1.26
- DOI:
- 10.18653/v1/2022.starsem-1.26
- Cite (ACL):
- Prisca Piccirilli and Sabine Schulte Im Walde. 2022. What Drives the Use of Metaphorical Language? Negative Insights from Abstractness, Affect, Discourse Coherence and Contextualized Word Representations. In Proceedings of the 11th Joint Conference on Lexical and Computational Semantics, pages 299–310, Seattle, Washington. Association for Computational Linguistics.
- Cite (Informal):
- What Drives the Use of Metaphorical Language? Negative Insights from Abstractness, Affect, Discourse Coherence and Contextualized Word Representations (Piccirilli & Schulte Im Walde, *SEM 2022)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2022.starsem-1.26.pdf