Postdoctoral Fellowship: SPRF: Characterizing Compositionality in Natural Language

This award was provided as part of NSF's Social, Behavioral and Economic Sciences (SBE) Postdoctoral Research Fellowships (SPRF) and SBE's Perception, Action and Cognition (PAC) programs. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government.

SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal.

Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Roger Levy at the Massachusetts Institute of Technology, this postdoctoral fellowship award supports an early career scientist examining the role of non-systematic structures in natural language.

A fundamental property of language is that words can be combined into larger phrases in systematic and predictable ways. However, this property is not absolute. The meaning of an idiom like “kick the bucket” (meaning “die”) is not predictable based on the meanings of “kick” and “bucket” individually.

The proposed research examines how widespread non-systematicity is in language, the circumstances under which it emerges, and the implications for language learning. The proposed work makes new connections between the fields of theoretical linguistics and computational cognitive science while furthering our understanding of both.

This project develops a novel measure of systematicity in language using mathematical tools from information theory. The measure is then used to investigate the effect of non-systematicity on grammatical structure, using corpus data and behavioral experiments. The project further studies the distribution of non-systematicity across different languages in order to better understand the task facing a child learning language.

The proposed studies will elucidate the ways in which the relationship between meaning and linguistic form is represented in the mind, and what this tells us about the human capacity to learn and use language productively and creatively.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.