---
license: cc-by-sa-4.0
task_categories:
- multiple-choice
language:
- id
size_categories:
- n<1K
configs:
- config_name: id
  data_files:
  - split: test
    path: test_copal.csv
  - split: test_colloquial
    path: test_copal_colloquial.csv
---


## Paper

URL Arxiv: https://arxiv.org/abs/2311.01012


We present publicly available COPAL-ID, a novel Indonesian language common sense reasoning dataset. Unlike the previous Indonesian COPA dataset (XCOPA-ID), COPAL-ID incorporates Indonesian local and cultural nuances, and therefore, provides a more natural portrayal of day-to-day causal reasoning within the Indonesian cultural sphere. Professionally written by natives from scratch, COPAL-ID is more fluent and free from awkward phrases, unlike the translated XCOPA-ID. In addition, we present COPAL-ID in both standard Indonesian and in Jakartan Indonesian--a dialect commonly used in daily conversation. COPAL-ID poses a greater challenge for existing open-sourced and closed state-of-the-art multilingual language models, yet is trivially easy for humans. Our findings suggest that even the current best open-source, multilingual model struggles to perform well, achieving 65.47% accuracy on COPAL-ID, significantly lower than on the culturally-devoid XCOPA-ID (79.40%). Despite GPT-4's impressive score, it suffers the same performance degradation compared 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 the local nuances of Indonesian.

## How to Use

```py
from datasets import load_dataset

copal_id_dataset = load_dataset('haryoaw/COPAL', 'id', subset='test')
copal_id_colloquial_dataset = load_dataset('haryoaw/COPAL', 'id', subset='test_colloquial')
```

## Cite Our Work

```
@article{wibowo2023copal,
  title={COPAL-ID: Indonesian Language Reasoning with Local Culture and Nuances},
  author={Wibowo, Haryo Akbarianto and Fuadi, Erland Hilman and Nityasya, Made Nindyatama and Prasojo, Radityo Eko and Aji, Alham Fikri},
  journal={arXiv preprint arXiv:2311.01012},
  year={2023}
}
```