README.md

---
license: cc-by-4.0
language:
- en
task_categories:
- question-answering
pretty_name: ElephantBench
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: test
    path: data/elephantbench.jsonl
---

# ElephantBench

<p align="center">
  <a href="https://github.com/Tencent/ElephantBench">
    <img
      src="https://img.shields.io/badge/ElephantBench-GitHub-blue?logo=github"
      alt="GitHub Repo"
    />
  </a>
  <a href="https://tencent.github.io/ElephantBench/">
    <img
      src="https://img.shields.io/badge/ElephantBench-Leaderboard-ff725e?logo=githubpages&logoColor=white"
      alt="ElephantBench Leaderboard"
    />
  </a>
  <a href="https://arxiv.org/abs/2608.28478">
    <img
      src="https://img.shields.io/badge/ElephantBench-Paper-red?logo=arxiv&logoColor=red"
      alt="Paper"
    />
  </a>
</p>

ElephantBench is a closed-book knowledge probe for evaluating whether a language model
remembers long-tail facts and recalls the different verified accounts associated with them.
The release contains 1,094 English questions.

Evaluation code, prompts, construction utilities, and full documentation are available in
the [ElephantBench GitHub repository](https://github.com/Tencent/ElephantBench).

![ElephantBench overview](assets/benchmark_overview.png)

## Load the dataset

```python
from datasets import load_dataset

dataset = load_dataset("Tencent/ElephantBench", split="test")
```

## Record format

```json
{
  "benchmark_id": "4382fd6d-ec5d-5ec8-a3f2-8abc706fa010",
  "item_group_id": "c9ef1c87-3e50-5190-8e8e-37a82ec25634",
  "eval": {
    "question": "What birth date was reported for Mother Teresa?",
    "gold_answers": [
      {"value": "August 26, 1910"},
      {"value": "August 27, 1910"}
    ],
    "preferred_answer": "Reports cite August 26 and August 27, 1910."
  }
}
```

The target model receives only `eval.question`. Gold answers are supplied to the judge after
generation.

## Evaluation

- **C (complete):** all verified answers are covered without a material contradiction.
- **P (partial):** at least one, but not all, verified answers are covered.
- **F (failed):** no verified answer is covered, a material contradiction is present, or the
  generation/judging request failed.
- **K (conditional completeness):** `C / (C + P)`.

## License

[cc-by-4.0](https://huggingface.co/datasets/tencent/ElephantBench/blob/main/LICENSE).

## Citation

```
@article{pan2026elephantbench,
  title={Blind Men and the Elephant: Probing the Epistemic Myopia of LLMs under Long-Tail Divergent Knowledge},
  author={Pan, Zhuoshi and Lu, Junru and Qian, Yan and Zhao, H. Vicky and Yin, Di and Sun, Xing},
  journal={arXiv preprint arXiv:2608.28478},
  year={2026}
}
```