@inproceedings{cassotti-etal-2026-senserel,
title = "{S}ense{R}el: A Sense-Level Benchmark for Denotational and Connotational Meaning Relations",
author = "Cassotti, Pierluigi and
Baes, Naomi and
De Pascale, Stefano and
de S{\'a}, J{\'a}der Martins Camboim and
Periti, Francesco and
Haslam, Nick and
Geeraerts, Dirk and
Tahmasebi, Nina",
editor = "Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David",
booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = jul,
year = "2026",
address = "San Diego, California, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.acl-long.20/",
pages = "499--515",
ISBN = "979-8-89176-390-6",
abstract = "Polysemy enables a single word to convey multiple related meanings, reflecting the conceptual and emotional aspects of the evolution of the senses. We introduce the first sense-level benchmark, \textit{SenseRel}, for modeling semantic relations between word senses, uniting denotational and connotational aspects of meaning. SenseRel distinguishes denotational relations, such as generalization or metaphor, as well as two connotational dimensions: valence and arousal. We evaluate large language models (LLMs), GPT-4o, Llama 3.1, and DeepSeek, in zero-shot and fine-tuned settings. Results show that GPT-4o best aligns with human affective judgments, while a fine-tuned RoBERTa model excels at classifying denotational relations."
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<abstract>Polysemy enables a single word to convey multiple related meanings, reflecting the conceptual and emotional aspects of the evolution of the senses. We introduce the first sense-level benchmark, SenseRel, for modeling semantic relations between word senses, uniting denotational and connotational aspects of meaning. SenseRel distinguishes denotational relations, such as generalization or metaphor, as well as two connotational dimensions: valence and arousal. We evaluate large language models (LLMs), GPT-4o, Llama 3.1, and DeepSeek, in zero-shot and fine-tuned settings. Results show that GPT-4o best aligns with human affective judgments, while a fine-tuned RoBERTa model excels at classifying denotational relations.</abstract>
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%0 Conference Proceedings
%T SenseRel: A Sense-Level Benchmark for Denotational and Connotational Meaning Relations
%A Cassotti, Pierluigi
%A Baes, Naomi
%A De Pascale, Stefano
%A de Sá, Jáder Martins Camboim
%A Periti, Francesco
%A Haslam, Nick
%A Geeraerts, Dirk
%A Tahmasebi, Nina
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-390-6
%F cassotti-etal-2026-senserel
%X Polysemy enables a single word to convey multiple related meanings, reflecting the conceptual and emotional aspects of the evolution of the senses. We introduce the first sense-level benchmark, SenseRel, for modeling semantic relations between word senses, uniting denotational and connotational aspects of meaning. SenseRel distinguishes denotational relations, such as generalization or metaphor, as well as two connotational dimensions: valence and arousal. We evaluate large language models (LLMs), GPT-4o, Llama 3.1, and DeepSeek, in zero-shot and fine-tuned settings. Results show that GPT-4o best aligns with human affective judgments, while a fine-tuned RoBERTa model excels at classifying denotational relations.
%U https://aclanthology.org/2026.acl-long.20/
%P 499-515
Markdown (Informal)
[SenseRel: A Sense-Level Benchmark for Denotational and Connotational Meaning Relations](https://aclanthology.org/2026.acl-long.20/) (Cassotti et al., ACL 2026)
ACL
- Pierluigi Cassotti, Naomi Baes, Stefano De Pascale, Jáder Martins Camboim de Sá, Francesco Periti, Nick Haslam, Dirk Geeraerts, and Nina Tahmasebi. 2026. SenseRel: A Sense-Level Benchmark for Denotational and Connotational Meaning Relations. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 499–515, San Diego, California, United States. Association for Computational Linguistics.