Languages have various ways of referring to collections like families, herds and forests. The grammatical properties of collective expressions critically determine how we understand them. The sentences “this forest is old” and “these trees are old” categorize an arboreal collection using a concept (“old”), while conveying different meanings. This semantic difference correlates with the difference in grammatical number between the sentences: singular vs. plural. Such effects of *collective categorization* in language are crucial for understanding the connections between grammar and the mind, as well as for artificial intelligence. This project aims to develop a novel linguistic theory of this ability, applied to a wide range of empirical phenomena and interdisciplinary challenges in computational semantics and comparative linguistics. The project benefited from the recent synergy between linguistics and the psychology of concepts. The main idea is that when classifying a collection, speakers rely on two inferential principles with mental concepts: (i) geometric inferences: a forest is considered “far away” if all of its trees are far; (ii) symmetric inferences: two trees are “similar” if each of them is similar to the other. The leading hypothesis is that uniform interactions between these inferential principles and the grammar of collective expressions account for collective categorization in language. This hypothesis was explored in three work packages. Each work package has developed the semantic theory and evaluated it on a different interdisciplinary domain: human interaction with geographic data, behavioral linguistic experiments, and comparative linguistics. Together, the three components of the project have led to substantial theoretical developments in semantic theory and enriched its interdisciplinary connections with neighboring disciplines.
