@inproceedings{liu-etal-2026-evaluating-social,
title = "Evaluating Social Intelligence in {LLM}s via {J}apanese Honorifics in Email Generation: A Social Semiotic System Perspective",
author = "Liu, Muxuan and
Ishigaki, Tatsuya and
Miyao, Yusuke and
Takamura, Hiroya and
Kobayashi, Ichiro",
editor = "Piperidis, Stelios and
Bel, N{\'u}ria and
van den Heuvel, Henk and
Ide, Nancy and
Krek, Simon and
Toral, Antonio",
booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resource Association",
url = "https://aclanthology.org/2026.lrec-1.154/",
doi = "10.63317/54wnt2fwhk8j",
pages = "1957--1976",
abstract = "We propose JaSocial, a novel evaluation framework that leverages Japanese emails to comprehensively evaluate large language models' (LLMs) social intelligence across varied social-status relationships. The framework integrates three core components. First, we construct and publicly release a meticulously human-annotated Japanese email dataset covering six distinct social-status contexts, thereby capturing nuanced shifts in social hierarchy and politeness. Second, we adopt Systemic Functional Linguistics (SFL){---}a social-semiotic linguistic theory that explicitly models how linguistic choices realize interpersonal relations and hierarchical distinctions{---}to classify email content in terms of three perspectives: social relationships, speech functions, and honorific expressions. Based on these perspectives, we design an automated evaluation method that assigns each LLM-generated email a contextual appropriateness score, quantifying how well it reflects socially intelligent behavior. Third, we release the full evaluation code to ensure reproducibility and enable fair cross-model comparisons. JaSocial exposes current LLMs' limitations in capturing cultural nuance, while providing an open benchmark for future research."
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<abstract>We propose JaSocial, a novel evaluation framework that leverages Japanese emails to comprehensively evaluate large language models’ (LLMs) social intelligence across varied social-status relationships. The framework integrates three core components. First, we construct and publicly release a meticulously human-annotated Japanese email dataset covering six distinct social-status contexts, thereby capturing nuanced shifts in social hierarchy and politeness. Second, we adopt Systemic Functional Linguistics (SFL)—a social-semiotic linguistic theory that explicitly models how linguistic choices realize interpersonal relations and hierarchical distinctions—to classify email content in terms of three perspectives: social relationships, speech functions, and honorific expressions. Based on these perspectives, we design an automated evaluation method that assigns each LLM-generated email a contextual appropriateness score, quantifying how well it reflects socially intelligent behavior. Third, we release the full evaluation code to ensure reproducibility and enable fair cross-model comparisons. JaSocial exposes current LLMs’ limitations in capturing cultural nuance, while providing an open benchmark for future research.</abstract>
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%0 Conference Proceedings
%T Evaluating Social Intelligence in LLMs via Japanese Honorifics in Email Generation: A Social Semiotic System Perspective
%A Liu, Muxuan
%A Ishigaki, Tatsuya
%A Miyao, Yusuke
%A Takamura, Hiroya
%A Kobayashi, Ichiro
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F liu-etal-2026-evaluating-social
%X We propose JaSocial, a novel evaluation framework that leverages Japanese emails to comprehensively evaluate large language models’ (LLMs) social intelligence across varied social-status relationships. The framework integrates three core components. First, we construct and publicly release a meticulously human-annotated Japanese email dataset covering six distinct social-status contexts, thereby capturing nuanced shifts in social hierarchy and politeness. Second, we adopt Systemic Functional Linguistics (SFL)—a social-semiotic linguistic theory that explicitly models how linguistic choices realize interpersonal relations and hierarchical distinctions—to classify email content in terms of three perspectives: social relationships, speech functions, and honorific expressions. Based on these perspectives, we design an automated evaluation method that assigns each LLM-generated email a contextual appropriateness score, quantifying how well it reflects socially intelligent behavior. Third, we release the full evaluation code to ensure reproducibility and enable fair cross-model comparisons. JaSocial exposes current LLMs’ limitations in capturing cultural nuance, while providing an open benchmark for future research.
%R 10.63317/54wnt2fwhk8j
%U https://aclanthology.org/2026.lrec-1.154/
%U https://doi.org/10.63317/54wnt2fwhk8j
%P 1957-1976
Markdown (Informal)
[Evaluating Social Intelligence in LLMs via Japanese Honorifics in Email Generation: A Social Semiotic System Perspective](https://aclanthology.org/2026.lrec-1.154/) (Liu et al., LREC 2026)
ACL