Mayfest 2025 - Constraints on Meaning
When and why are certain meanings missing?
Research at our top-ranked department spans syntax, semantics, phonology, language acquisition, computational linguistics, psycholinguistics and neurolinguistics.
Connections between our core competencies are strong, with theoretical, experimental and computational work typically pursued in tandem.
A network of collaboration at all levels sustains a research climate that is both vigorous and friendly. Here new ideas develop in conversation, stimulated by the steady activity of our labs and research groups, frequent student meetings with faculty, regular talks by local and invited scholars and collaborations with the broader University of Maryland language science community, the largest and most integrated language science research community in North America.
Nick Huang (*19)
Many proposals on restructuring suggest that restructuring phenomena are only observed when a control predicate takes as a complement a functional projection smaller than a clause. In this paper, I present novel Mandarin data against recent proposals that restructuring control predicates cannot take clausal complements and the related generalization that clausal complements always block restructuring phenomena. An alternative account of the Mandarin data is presented. The data also bear on the question of whether a finiteness distinction exists in Chinese. In particular, they provide clearer evidence that control predicates can take clausal complements that differ syntactically from those of non-control attitude predicates. This difference parallels the cross-linguistic correlation between control predicates and non-finite clausal complements and lends new support for the claim that Chinese makes a finiteness distinction.
Laurel Perkins (*19)
Language learners use the data in their environment in order to infer the grammatical system that produced that data. Yang (2018) makes the important point that this process requires integrating learners’ experiences with their current linguistic knowledge. A complete theory of language acquisition must explain how learners leverage their developing knowledge in order to draw further inferences on the basis of new data. As Yang and others have argued, the fact that input plays a role in learning is orthogonal to the question of whether language acquisition is primarily knowledge-driven or data-driven (J. A. Fodor, 1966; Lidz & Gagliardi, 2015; Lightfoot, 1991; Wexler & Culicover, 1980). Learning from data is not incompatible with approaches that attribute rich initial linguistic knowledge to the learner. On the contrary, such approaches must still account for how knowledge guides learners in using their data to infer a grammar.
Aaron Steven White (*15)
In English, the distinction between belief verbs, such as think, and desire verbs, such as want, is tracked by tense found in the subordinate clauses of those verbs. This suggests that subordinate clause tense might be a useful cue for learning the meanings of these verbs via syntactic bootstrapping. However, the correlation between tense and the belief v. desire distinction is not cross-linguistically robust; yet the acquisition profile of these verbs is similar cross-linguistically. Our proposal in this chapter is that, instead of using concrete cues like subordinate clause tense, learners may utilize more abstract syntactic cues that must be tuned to the syntactic distinctions present in a particular language. We present computational modeling evidence supporting the viability of this proposal.
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