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We present publicly available COPAL-ID, a novel Indonesian language commonsense reasoning dataset. Unlike the previous Indonesian COPA dataset(XCOPA-ID), COPAL-ID incorporates Indonesian local and cultural nuances, andtherefore, provides a more natural portrayal of day-to-day causal reasoningwithin the Indonesian cultural sphere. Professionally written by natives fromscratch, COPAL-ID is more fluent and free from awkward phrases, unlike thetranslated XCOPA-ID. In addition, we present COPAL-ID in both standardIndonesian and in Jakartan Indonesian--a dialect commonly used in dailyconversation. COPAL-ID poses a greater challenge for existing open-sourced andclosed state-of-the-art multilingual language models, yet is trivially easy forhumans. Our findings suggest that even the current best open-source,multilingual model struggles to perform well, achieving 65.47% accuracy onCOPAL-ID, significantly lower than on the culturally-devoid XCOPA-ID (79.40%).Despite GPT-4's impressive score, it suffers the same performance degradationcompared to its XCOPA-ID score, and it still falls short of human performance.This shows that these language models are still way behind in comprehending thelocal nuances of Indonesian.

COPAL-ID: Indonesian Language Reasoning with Local Culture and Nuances