Pragmatic Perspective on Assessing Implicit Meaning Interpretation in Sentiment Analysis Models

Rashid Mustafin


Abstract
Drawing on pragmatic theories of implicature by Grice (1975) and Levinson (1983), according to which speakers often convey more than it is explicitly said, the paper argues that interpreting texts with implicit meaning correctly is essential for precise natural language understanding. To illustrate the challenges in computational interpretation of implicatures, the study introduces a series of illustrative micro-experiments with the use of four transformer models fine-tuned for sentiment analysis. In these micro-experiments, the models classified sentences specifically designed to expose difficulties in handling implicit meaning. The study demonstrates that contrasting qualitative pragmatic analysis with the models’ tendency to focus on formal linguistic markers can reveal the limitations of supervised machine learning methods in detecting implicit sentiments.
Anthology ID:
2025.acl-srw.65
Volume:
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Jin Zhao, Mingyang Wang, Zhu Liu
Venues:
ACL | WS
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Publisher:
Association for Computational Linguistics
Note:
Pages:
898–907
Language:
URL:
https://preview.aclanthology.org/landing_page/2025.acl-srw.65/
DOI:
Bibkey:
Cite (ACL):
Rashid Mustafin. 2025. Pragmatic Perspective on Assessing Implicit Meaning Interpretation in Sentiment Analysis Models. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 898–907, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
Pragmatic Perspective on Assessing Implicit Meaning Interpretation in Sentiment Analysis Models (Mustafin, ACL 2025)
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PDF:
https://preview.aclanthology.org/landing_page/2025.acl-srw.65.pdf