Is It JUST Semantics? A Case Study of Discourse Particle Understanding in LLMs
William Berkeley Sheffield, Kanishka Misra, Valentina Pyatkin, Ashwini Deo, Kyle Mahowald, Junyi Jessy Li
Abstract
Discourse particles are crucial elements that subtly shape the meaning of text. These words, often polyfunctional, give rise to nuanced and often quite disparate semantic/discourse effects,as exemplified by the diverse uses of the particle *just* (e.g., exclusive, temporal, emphatic). This work investigates the capacity of LLMs to distinguish the fine-grained senses of English *just*, a well-studied example in formal semantics, using data meticulously created and labeled by expert linguists. Our findings reveal that while LLMs exhibit some ability to differentiate between broader categories, they struggle to fully capture more subtle nuances, highlighting a gap in their understanding of discourse particles.
BibTeX
@inproceedings{sheffield-etal-2025-just,
title = "Is It {JUST} Semantics? A Case Study of Discourse Particle Understanding in {LLM}s",
author = "Sheffield, William Berkeley and
Misra, Kanishka and
Pyatkin, Valentina and
Deo, Ashwini and
Mahowald, Kyle and
Li, Junyi Jessy",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-acl.1117/",
doi = "10.18653/v1/2025.findings-acl.1117",
pages = "21704--21715",
ISBN = "979-8-89176-256-5"
}