Abstract
Adjectives such as tall or late which can enter comparative constructions or be modified by intensifiers such as very are called gradable. They have received considerable attention in formal semantics and, more recently, in Bayesian pragmatics. While comparative constructions are well understood, less is known about the contribution of intensifiers. In this paper, we compare several concrete models for the meaning of very tall with data from a previous study, in the hope of shedding light on the semantic contributions of intensifiers.
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Notes
- 1.
In practice we might use these expressions loosely, e.g. if Ronald arrives just a few seconds later, it may not really count as late. But here we should distinguish between imprecision and vagueness (see also Kennedy and McNally 2005). We can read an adjective as absolute as long as we are able to set a fixed standard of comparison if forced to, and even without reference to the context (e.g. ‘full’, ‘empty’).
However, this characterization of the absolute-relative distinction is based on the assumption that a predicate is vague as long as it has borderline cases. But it has been argued that this conception might not be sufficient (e.g. Smith 2008 Sect.3.2). An alternative characterization, as noted by Burnett (2014), Egré and Bonnay (2010), would be the asymmetric tolerance displayed by absolute adjectives (but not relative adjectives): If Ronald is only a few seconds late, it might still count as not late in certain contexts; in contrast, if he is a few seconds earlier, then he is definitely not late. Such asymmetry is also visible in the experimental data we refer to later Leffel et al. (2018). Since this paper targets mainly on relative adjectives, we will not further this discussion (with an exception in Sect. 2.5), but it would be ideal for any quantitative models of gradable adjectives to capture such pattern. Many thanks to the anonymous reviewer for bringing this point to my attention.
- 2.
Leffel et al. (2018) interpret their results as reflecting not just truth but also pragmatic felicity (i.e. truth of the sentence together with its implicatures). However the implicatures they discuss only surfaced for more complex sentences (involving negation), and should therefore do not affect our interpretation of the simpler sentences discussed here.
- 3.
Here we leave a more in-depth evaluation of the model for later. Ideally, we would like to fit not just the median but the data from each participant (as both SOM and RSA are originally individual-level models), and in a more systematic way.
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Acknowledgements
The author would like to thank Dr. Alexandre Cremers for supervising the project. I’m also grateful to the anonymous reviewers for their valuable feedback. Last but not least, many thanks to ESSLLI 2018 Grant Committee and EACL for the student grants, and Springer for sponsorship and prizes.
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Zhao, Z. (2019). Interpreting Intensifiers for Relative Adjectives: Comparing Models and Theories. In: Sikos, J., Pacuit, E. (eds) At the Intersection of Language, Logic, and Information. ESSLLI 2018. Lecture Notes in Computer Science(), vol 11667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59620-3_14
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