aisingapore/NLU-Metaphor

SEA Metaphor

SEA Metaphor evaluates a model's ability to interpret paired figurative phrases with divergent meanings. It is sampled from Multilingual-Fig-QA for Indonesian, Javanese, and Sundanese.

Supported Tasks and Leaderboards

SEA Metaphor is designed for evaluating chat or instruction-tuned large language models (LLMs). It is part of the SEA-HELM leaderboard from AI Singapore.

Languages

• Indonesian (id)
• Javanese (jv)
• Sundanese (su)

Dataset Details

SEA Metaphor is split by language, with additional splits containing fewshot examples. Below are the statistics for this dataset. The number of tokens only refer to the strings of text found within the prompts column.

Split	# of examples	# of GPT-4o tokens	# of Gemma 2 tokens	# of Llama 3 tokens
id	295	10289	10120	13265
jv	282	10167	10923	13279
su	295	8973	10046	11858
id_fewshot	5	183	178	239
jv_fewshot	5	154	168	198
su_fewshot	5	153	165	193
total	887	29919	31600	39032

Data Sources

Data Source	License	Language/s	Split/s
Multilingual-Fig-QA	MIT	Indonesian, Javanese, Sundanese	id, id_fewshot, jv, jv_fewshot, su, su_fewshot

License

For the license/s of the dataset/s, please refer to the data sources table above.

We endeavor to ensure data used is permissible and have chosen datasets from creators who have processes to exclude copyrighted or disputed data.

Acknowledgement

This project is supported by the National Research Foundation Singapore and Infocomm Media Development Authority (IMDA), Singapore under its National Large Language Model Funding Initiative.

References

@inproceedings{kabra-etal-2023-multi,
    title = "Multi-lingual and Multi-cultural Figurative Language Understanding",
    author = "Kabra, Anubha  and
      Liu, Emmy  and
      Khanuja, Simran  and
      Aji, Alham Fikri  and
      Winata, Genta  and
      Cahyawijaya, Samuel  and
      Aremu, Anuoluwapo  and
      Ogayo, Perez  and
      Neubig, Graham",
    editor = "Rogers, Anna  and
      Boyd-Graber, Jordan  and
      Okazaki, Naoaki",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-acl.525",
    doi = "10.18653/v1/2023.findings-acl.525",
    pages = "8269--8284",
}