Datasets:

AiLab-IMCS-UL
/

copa-lv

license: cc-by-4.0
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
      - split: val
        path: data/val-*
dataset_info:
  features:
    - name: context
      dtype: string
    - name: question
      dtype: string
    - name: choices
      list: string
    - name: label
      dtype: int64
    - name: id
      dtype: int64
  splits:
    - name: train
      num_bytes: 55178
      num_examples: 400
    - name: test
      num_bytes: 67432
      num_examples: 500
    - name: val
      num_bytes: 14042
      num_examples: 100
  download_size: 88365
  dataset_size: 136652

copa-lv

Latvian version of the COPA (Choice of Plausible Alternatives) dataset for commonsense causal reasoning.

The dataset is based on the original English COPA dataset and its Latvian translation introduced by Skadiņa et al. (2025). The original data was machine translated using Tilde MT and partially manually post-edited.

This version completes manual post-editing for all samples and provides a consistent structured format.

Data Format

Each example contains:

context: premise sentence
question: "cēlonis" (cause) or "sekas" (effect)
choices: two answer options
label: correct answer index (0 or 1)
id: unique identifier

Splits

Train: 400
Validation: 100
Test: 500

Citation

@inproceedings{znotins-2026-pretraining,
    title = "Pretraining and Benchmarking Modern Encoders for {L}atvian",
    author = "Znotins, Arturs",
    booktitle = "Proceedings of the Second Workshop on Language Models for Low-Resource Languages ({L}o{R}es{LM} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.loreslm-1.40/",
    doi = "10.18653/v1/2026.loreslm-1.40",
    pages = "461--470",
    ISBN = "979-8-89176-377-7"
}

@inproceedings{skadina-etal-2025-first,
    title = "First Steps in Benchmarking {L}atvian in Large Language Models",
    author = "Skadina, Inguna  and
      Bakanovs, Bruno  and
      Dar{\c{g}}is, Roberts",
    booktitle = "Proceedings of the Third Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2025)",
    month = mar,
    year = "2025",
    address = "Tallinn, Estonia",
    publisher = "University of Tartu Library, Estonia",
    url = "https://aclanthology.org/2025.resourceful-1.22/",
    pages = "86--95",
    ISBN = "978-9908-53-121-2"
}

@inproceedings{roemmele2011choice,
  title={Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning.},
  author={Roemmele, Melissa and Bejan, Cosmin Adrian and Gordon, Andrew S},
  booktitle={AAAI spring symposium: logical formalizations of commonsense reasoning},
  pages={90--95},
  year={2011}
}