Can LLMs Detect Ambiguous Plural Reference?: An Analysis of Split-Antecedent and Mereological Reference

Publication date

2025-11

Authors

Dang, Anh
Nouwen, R.W.F.ORCID 0000-0001-9571-4644ISNI 0000000398065728
Poesio, MassimoORCID 0000-0001-8469-2072ISNI 0000000124478066

Editors

Belinkov, Yonatan
Mueller, Aaron
Kim, Najoung
Mohebbi, Hosein
Chen, Hanjie
Arad, Dana
Sarti, Gabriele

Advisors

Supervisors

Document Type

Part of book
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License

cc_by

Abstract

Our goal is to study how LLMs represent and interpret plural reference in ambiguous and unambiguous contexts. We ask the following research questions: (1) Do LLMs exhibit human-like preferences in representing plural reference? and (2) Are LLMs able to detect ambiguity in plural anaphoric expressions and identify possible referents? To address these questions, we design a set of experiments, examining pronoun production using next-token prediction tasks, pronoun interpretation, and ambiguity detection using different prompting strategies. We then assess how comparable LLMs are to humans in formulating and interpreting plural reference. We find that LLMs are sometimes aware of possible referents of ambiguous pronouns. However, they do not always follow human reference when choosing between interpretations, especially when the possible interpretation is not explicitly mentioned. In addition, they struggle to identify ambiguity without direct instruction. Our findings also reveal inconsistencies in the results across different types of experiments.

Keywords

Citation

Dang, A, Nouwen, R & Poesio, M 2025, Can LLMs Detect Ambiguous Plural Reference? An Analysis of Split-Antecedent and Mereological Reference. in Y Belinkov, A Mueller, N Kim, H Mohebbi, H Chen, D Arad & G Sarti (eds), Proceedings of the 8th BlackboxNLP Workshop : Analyzing and Interpreting Neural Networks for NLP. Association for Computational Linguistics, Suzhou, China, pp. 263-275. https://doi.org/10.18653/v1/2025.blackboxnlp-1.16