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.
@article{arxiv.2506.04534,
title = {Is It JUST Semantics? A Case Study of Discourse Particle Understanding in LLMs},
author = {William Sheffield and Kanishka Misra and Valentina Pyatkin and Ashwini Deo and Kyle Mahowald and Junyi Jessy Li},
journal= {arXiv preprint arXiv:2506.04534},
year = {2025}
}
Comments
To be published in Findings of The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025). The main paper is 5 pages and contains 3 figures and 1 table. In total, the paper is 12 pages and contains 8 figures and 5 tables (References + Appendix)