Quantifiers in Natural Language: Efficient Communication and Degrees of Semantic Universals

Abstract

While the languages of the world vary greatly, they exhibit systematic patterns, as well. Semantic universals are restrictions on the variation in meaning exhibit cross-linguistically (e.g., that, in all languages, expressions of a certain type can only denote meanings with a certain special property). This paper pursues an efficient communication analysis to explain the presence of semantic universals in a domain of function words: quantifiers. Two experiments measure how well languages do in optimally trading off between competing pressures of simplicity and informativeness. First, we show that artificial languages which more closely resemble natural languages are more optimal. Then, we introduce information-theoretic measures of degrees of semantic universals and show that these are not correlated with optimality in a random sample of artificial languages. These results suggest both that efficient communication shapes semantic typology in both content and function word domains, as well as that semantic universals may not stand in need of independent explanation.

Indefinite Pronouns Optimize the Simplicity/Informativeness Trade‐Off

“…First, it would strengthen the case that the simplicity/informativeness trade‐off shapes both content and function word categories in language. In doing so, our work aligns with several concurrent studies exploring the simplicity/informativeness trade‐off in functional vocabulary (Mollica et al., 2021 ; Steinert‐Threlkeld, 2019 , 2021 ; Uegaki, 2022 ; Zaslavsky et al., 2021 ).…”

“…We find that natural languages optimize the simplicity/informativeness trade-off in how they organize their indefinite pronoun systems. These results represent an extension of efficiency analyses to a system of function words, thus tying in with Steinert-Threlkeld, 2019, 2021Mollica et al, 2021;Zaslavsky et al, 2021;Uegaki, 2022 in concluding that similar communication pressures are shaping both content and function word categories across languages.…”

A Database for Modal Semantic Typology

“…For example, it can enable the verification of robust semantic universals (Nauze, 2008;Vander Klok, 2013b; and possibly trigger the formulation of new ones. Similarly, these data and their format can be used in comparison to artificial languages to attempt to explain what pressures have shaped semantic typology in the domain of modality, as has been done in several other domains (Kemp and Regier, 2012;Zaslavsky et al, 2018;Steinert-Threlkeld andSzymanik, 2019, 2020;Steinert-Threlkeld, 2021;Denić et al, 2022;Mollica et al, 2021;Uegaki, 2022, i.a. ).…”

Generalized Quantifiers as a Source of Error in Multilingual NLU Benchmarks

“…Most human languages contain ways of expressing generalized quantifiers, and their semantics exhibit striking similarities across languages (Matthewson, 2004;Fintel and Matthewson, 2008;Steinert-Threlkeld, 2019). At the same time, generalized quantifiers can be instantiated very differently across languages due to pragmatic considerations (Grice, 1989) or cognitive economy and costbenefit optimisation in the exchange of information (Levinson et al, 2000;Steinert-Threlkeld, 2021;Uegaki, 2022). Quantifier words also exhibit syntactic differences, e.g., with some languages having specialized words to express quantity, while others rely on metaphorical usage of common nouns (Katsos et al, 2012).…”