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    <abstract>We present a hybrid system for SemEval-2026 Task 5 on graded word-sense plausibility in narrative contexts. Our approach combines prompt-based large language model (LLM) scoring with three complementary features: semantic embedding similarity, story-conditioned definition generation, and a synthetic gaze signal based on predicted fixation time. We combine these signals using an ordinary least squares regressor. On the official test set, our best system achieves 90.10 Acc\ensuremath\pmSD and 79.19 Spearman correlation. The system surpasses the reported human reference score on Acc\ensuremath\pmSD, highlighting the value of combining LLM-based judgments with targeted linguistic and cognitive-inspired features.</abstract>
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%0 Conference Proceedings
%T CiNet-Handai-Kyodai at SemEval-2026 Task 5: Combining LLM Prompting, Semantic Similarity, and Synthetic Gaze for Graded Sense Plausibility
%A Kanashiro Pereira, Lis
%A Cheng, Fei
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F kanashiro-pereira-cheng-2026-cinet
%X We present a hybrid system for SemEval-2026 Task 5 on graded word-sense plausibility in narrative contexts. Our approach combines prompt-based large language model (LLM) scoring with three complementary features: semantic embedding similarity, story-conditioned definition generation, and a synthetic gaze signal based on predicted fixation time. We combine these signals using an ordinary least squares regressor. On the official test set, our best system achieves 90.10 Acc\ensuremath\pmSD and 79.19 Spearman correlation. The system surpasses the reported human reference score on Acc\ensuremath\pmSD, highlighting the value of combining LLM-based judgments with targeted linguistic and cognitive-inspired features.
%U https://aclanthology.org/2026.semeval-1.245/
%P 1950-1956

Markdown (Informal)

[CiNet-Handai-Kyodai at SemEval-2026 Task 5: Combining LLM Prompting, Semantic Similarity, and Synthetic Gaze for Graded Sense Plausibility](https://aclanthology.org/2026.semeval-1.245/) (Kanashiro Pereira & Cheng, SemEval 2026)

• CiNet-Handai-Kyodai at SemEval-2026 Task 5: Combining LLM Prompting, Semantic Similarity, and Synthetic Gaze for Graded Sense Plausibility (Kanashiro Pereira & Cheng, SemEval 2026)

ACL

• Lis Kanashiro Pereira and Fei Cheng. 2026. CiNet-Handai-Kyodai at SemEval-2026 Task 5: Combining LLM Prompting, Semantic Similarity, and Synthetic Gaze for Graded Sense Plausibility. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 1950–1956, San Diego, California, USA. Association for Computational Linguistics.