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tripathysagar/odia-truthfulqa

Odia TruthfulQA (generation) Odia translation of the TruthfulQA generation split. Open-ended truthfulness questions with English and Odia question/answer pairs. Part of OdiaBench — parallel English–Odia benchmark translations for evaluating Odia-capable language models. Splits Split Rows validation 817 Total rows: 817 Schema Column Type Description id int64 Pipeline row index (0-based, sorted) question string English… See the full description on the dataset page: https://huggingface.co/datasets/tripathysagar/odia-truthfulqa.

sourceHugging Faceapache-2.0updated 4mo agoView on Hugging Face
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Dataset Card

Odia TruthfulQA (generation)

Odia translation of the TruthfulQA generation split. Open-ended truthfulness questions with English and Odia question/answer pairs.

Part of **OdiaBench** — parallel English–Odia benchmark translations for evaluating Odia-capable language models.

Splits

SplitRows
validation817

Total rows: 817

Schema

ColumnTypeDescription
idint64Pipeline row index (0-based, sorted)
questionstringEnglish question / context
answerstringEnglish answer (gold ending, formatted choices, etc.)
odia_questionstringOdia translation of question
odia_answerstringOdia translation of answer
typestringTruthfulQA question type
categorystringTruthfulQA category

Translation methodology

OdiaBench translations were produced via Cursor subagents (Composer 2.5-fast) using the v3 translation prompt in `cursor_translate/odia_trans`:

  1. 1.Download upstream split and shard into 30-row JSONL batches
  2. 2.Translate question and answer into odia_question / odia_answer
  3. 3.Apply structural fixers, grammar audit (7 rules), and quality evaluation
  4. 4.Merge batches, dedupe by id, and export parquet splits

Translation rules preserve numbers as digits, keep benchmark-specific structural tokens (e.g. A:–D: for ARC, _ blank for Winogrande, <<calc>> / #### N for GSM8K), and transliterate proper nouns into Odia script.

Usage

python
from datasets import load_dataset

ds = load_dataset("tripathysagar/odia-truthfulqa")
print(ds)
print(ds["validation"][0]["odia_question"])

Source dataset

Citation

If you use this dataset, please cite OdiaBench and the upstream source:

bibtex
@misc{odiabench2026,
  title={OdiaBench: English-Odia Benchmark Translations},
  author={OdiaBench Contributors},
  year={2026},
  howpublished={\url{https://github.com/tripathysagar/OdiaBench}}
}

Upstream source:

bibtex
@article{lin2022truthfulqa,
  title={TruthfulQA: Measuring How Models Mimic Human Falsehoods},
  author={Stephanie Lin and Jacob Hilton and Owain Evans},
  journal={ACL},
  year={2022}
}