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Title: Compositionality and event retrieval in complement coercion : a study of language models in a low-resource setting
Authors: Radaelli, M
Chersoni, E 
Lenci, A
Baggio, G
Issue Date: 2025
Source: In Proceedings of the 29th Conference on Computational Natural Language Learning, p. 469-480. Kerrville : Association for Computational Linguistics, 2025
Abstract: In sentences such as John began the book, the complement noun, lexically denoting an entity, is interpreted as an event. This phenomenon is known in linguistics as complement coercion: the event associated with the verb is not overtly expressed but can be recovered from the meanings of other constituents, context and world knowledge. We investigate whether language models (LMs) can exploit sentence structure and compositional meaning to recover plausible events in complement coercion. For the first time, we tested different LMs in Norwegian, a low-resource language with high syntactic variation in coercion constructions across aspectual verbs. Results reveal that LMs struggle with retrieving plausible events and with ranking them above less plausible ones. Moreover, we found that LMs do not exploit the compositional properties of coercion sentences in their predictions.
Publisher: Association for Computational Linguistics
ISBN: 979-8-89176-271-8
DOI: 10.18653/v1/2025.conll-1.31
Description: The 29th Conference on Computational Natural Language Learning (CoNLL 2025), Vienna, Austria, July 31- August 1, 2025
Rights: ©2025 Association for Computational Linguistics
Licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/)
The following publication Matteo Radaelli, Emmanuele Chersoni, Alessandro Lenci, and Giosuè Baggio. 2025. Compositionality and Event Retrieval in Complement Coercion: A Study of Language Models in a Low-resource Setting. In Proceedings of the 29th Conference on Computational Natural Language Learning, pages 469–480, Vienna, Austria. Association for Computational Linguistics is available at https://aclanthology.org/2025.conll-1.31/.
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