Literal and metaphorical meaning: in search of a lost distinction

Allott, Nicholas; Textor, Mark

doi:10.1080/0020174x.2022.2128867

Cited by 5 publications

(1 citation statement)

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“…The abundance in which metaphors occur in everyday language (Gibbs, 1992;Ortony, 1993), such as "winning someone's heart" or "tax evasion", presents a need for metaphor interpretation and, to that end, the computational decoding of metaphors. Much like in other forms of figurative language, such as sarcasm, a central challenge with metaphors is that the implicit intended meaning differs from the meaning of the explicit metaphorical expression (Goatly, 1997;Allott and Textor, 2022). The context provided by the neighboring words in the sentence is an indicator of this implicit meaning (Stern, 2000).…”

Section: Introductionmentioning

confidence: 99%

Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms

Sengupta,

Alshomary,

Scharlau

et al. 2023

Findings of the Association for Computational Linguistics: EMNLP 2023

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Metaphorical language, such as "spending time together", projects meaning from a source domain (here, money) to a target domain (time). Thereby, it highlights certain aspects of the target domain, such as the effort behind the time investment. Highlighting aspects with metaphors (while hiding others) bridges the two domains and is the core of metaphorical meaning construction. For metaphor interpretation, linguistic theories stress that identifying the highlighted aspects is important for a better understanding of metaphors. However, metaphor research in NLP has not yet dealt with the phenomenon of highlighting. In this paper, we introduce the task of identifying the main aspect highlighted in a metaphorical sentence. Given the inherent interaction of source domains and highlighted aspects, we propose two multitask approaches -a joint learning approach and a continual learning approach -based on a finetuned contrastive learning model to jointly predict highlighted aspects and source domains. We further investigate whether (predicted) information about a source domain leads to better performance in predicting the highlighted aspects, and vice versa. Our experiments on an existing corpus suggest that, with the corresponding information, the performance to predict the other improves in terms of model accuracy in predicting highlighted aspects and source domains notably compared to the single-task baselines.

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Section: Introductionmentioning

confidence: 99%

Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms

Sengupta,

Alshomary,

Scharlau

et al. 2023

Findings of the Association for Computational Linguistics: EMNLP 2023

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Metaphors, religious language and linguistic expressibility

Hesse

2023

Int J Philos Relig

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This paper examines different functions of metaphors in religious language. In order to do that it will be analyzed in which ways metaphorical language can be understood as irreducible. First, it will be argued that metaphors communicate more than just propositional contents. They also frame their targets with an imagistic perspective that cannot be reduced to a literal paraphrase. Furthermore, there are also cases where metaphors are used to fill gaps of what can be expressed with literal language. In order to clarify this function of catachresis the notion of de re metaphors will be introduced. With those metaphors we can convey contents that we cannot conceptualize independently from a certain context of utterance. Hence, with such metaphors we can reach beyond the limits of our conceptual repertoire which is a crucial function for religious language. Finally, the consistency and plausibility of the radical position that all assertions about God are irreducibly and necessarily metaphorical if they are supposed to be true will be discussed on the basis of the results of the former considerations about the irreducibility of metaphors.

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