Services that operate in Korean often write their evaluation rubrics in Korean and hand them to an LLM judge. We test whether a judge's verdict depends on the language of the rubric and on how a rubric item is phrased. We write 12 criteria for support dialogues in four clause structures (affirmative, negated, conditional, exception) such that two pairs of structures have the same meaning, and we give each item in Korean and in English. Six low-cost models from three providers, plus one reference model, judge 60 translated ESConv dialogues and 144 constructed boundary cases under every combination (51,744 requests across the seven models). The analysis plan was fixed and committed before data collection.
Cross-provider agreement is lower with Korean rubrics than with English rubrics
Cross-provider agreement is lower with Korean rubrics than with English rubrics (Cohen's kappa 0.687 vs. 0.745; difference -0.058, 95% CI [-0.072,-0.045]).
Disagreement concentrates in negated, conditional, and exception items
Disagreement concentrates in negated, conditional, and exception items (odds ratio 5.6 relative to affirmative items).
A single model changes its verdict between two items with the same meaning in 11-15% of cases
A single model changes its verdict between two items with the same meaning in 11-15% of cases.
Two hypotheses are not supported
Two hypotheses are not supported: models from the same provider do not agree more than models from different providers, and adding paired examples does not reduce the language gap.
We measure consistency only
We measure consistency only; no human labels are used, and all materials were drafted by an LLM.