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metadata
dataset_info:
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    features:
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        dtype: string
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configs:
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    data_files:
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        path: 5768/train-*
      - split: test
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license: cc-by-nc-sa-4.0
task_categories:
  - text-classification
language:
  - en
tags:
  - finance
  - econ
pretty_name: swiss_national_bank
size_categories:
  - 1K<n<10K

Dataset Summary

For dataset summary, please refer to https://huggingface.co/datasets/gtfintechlab/swiss_national_bank

Additional Information

This dataset is annotated across three different tasks: Stance Detection, Temporal Classification, and Uncertainty Estimation. The tasks have four, two, and two unique labels, respectively. This dataset contains 1,000 sentences taken from the meeting minutes of the Swiss National Bank.

Label Interpretation

Stance Detection

  • Hawkish: The sentence supports contractionary monetary policy.
  • Dovish: The sentence supports expansionary monetary policy.
  • Neutral: The sentence contains neither hawkish or dovish sentiment, or both hawkish and dovish sentiment.
  • Irrelevant: The sentence is not related to monetary policy.

Temporal Classification

  • Forward-looking: The sentence discusses future economic events or decisions.
  • Not Forward-looking: The sentence discusses past or current economic events or decisions.

Uncertainty Estimation

  • Certain: Indicates that the sentence presents information definitively.
  • Uncertain: Indicates that the sentence presents information with speculation, possibility, or doubt.

Licensing Information

The swiss_national_bank dataset is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International. More information in the paper.

Citation Information

@article{WCBShahSukhaniPardawala,
  title={Words That Unite The World: A Unified Framework for Deciphering Global Central Bank Communications},
  author={Agam Shah, Siddhant Sukhani, Huzaifa Pardawala et al.},
  year={2025}
}

Contact

For any swiss_national_bank dataset related issues and questions, please contact:

  • Huzaifa Pardawala: huzaifahp7[at]gatech[dot]edu

  • Siddhant Sukhani: ssukhani3[at]gatech[dot]edu

  • Agam Shah: ashah482[at]gatech[dot]edu

GitHub Link

Link to our GitHub repository.