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metadata
pretty_name: SEA Metaphor
license:
  - mit
task_categories:
  - text-generation
  - question-answering
language:
  - id
  - jv
  - su
dataset_info:
  features:
    - name: id
      dtype: string
    - name: label
      dtype: string
    - name: prompts
      list:
        - name: phrase
          dtype: string
        - name: choice1
          dtype: string
        - name: choice2
          dtype: string
    - name: prompt_templates
      sequence: string
    - name: metadata
      struct:
        - name: language
          dtype: string
  splits:
    - name: id
      num_bytes: 163609
      num_examples: 295
    - name: id_fewshot
      num_bytes: 905
      num_examples: 5
    - name: jv
      num_bytes: 141631
      num_examples: 282
    - name: jv_fewshot
      num_bytes: 714
      num_examples: 5
    - name: su
      num_bytes: 139902
      num_examples: 295
    - name: su_fewshot
      num_bytes: 701
      num_examples: 5
  download_size: 85457
  dataset_size: 447462
configs:
  - config_name: default
    data_files:
      - split: id
        path: data/id-*
      - split: id_fewshot
        path: data/id_fewshot-*
      - split: jv
        path: data/jv-*
      - split: jv_fewshot
        path: data/jv_fewshot-*
      - split: su
        path: data/su-*
      - split: su_fewshot
        path: data/su_fewshot-*
size_categories:
  - 1K<n<10K

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.

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",
}