---
license: apache-2.0
language:
  - en
pretty_name: Tiny QA Benchmark (Original EN Core for TQB++)
size_categories:
  - n<1K
tags:
  - question-answering
  - evaluation
  - benchmark
  - toy-dataset
  - tqb++-core
task_categories:
  - question-answering
task_ids:
  - extractive-qa
  - closed-book-qa
arxiv: 2505.12058
datasets:
  - vincentkoc/tiny_qa_benchmark_pp
---

# Tiny QA Benchmark (Original English Core for TQB++)

**This dataset (`vincentkoc/tiny_qa_benchmark`) is the original 52-item English Question-Answering set. It now serves as the immutable "gold standard" core for the expanded [Tiny QA Benchmark++ (TQB++)](https://huggingface.co/datasets/vincentkoc/tiny_qa_benchmark_pp) project.**

The TQB++ project builds upon this core dataset by introducing a powerful synthetic generation toolkit, pre-built multilingual datasets, and a comprehensive framework for rapid LLM smoke testing.

**For the full TQB++ toolkit, the latest research paper, multilingual datasets, and the synthetic generator, please visit:**
*   **TQB++ Hugging Face Dataset Collection & Toolkit:** [vincentkoc/tiny_qa_benchmark_pp](https://huggingface.co/datasets/vincentkoc/tiny_qa_benchmark_pp)
*   **TQB++ GitHub Repository (Code, Paper & Toolkit):** [vincentkoc/tiny_qa_benchmark_pp](https://github.com/vincentkoc/tiny_qa_benchmark_pp)

This original dataset (`vincentkoc/tiny_qa_benchmark`) contains 52 hand-crafted general-knowledge QA pairs covering geography, history, math, science, literature, and more. It remains ideal for quick sanity checks, pipeline smoke-tests, and as a foundational component of TQB++. Each example includes:

- **text**: the question prompt  
- **label**: the “gold” answer  
- **metadata.context**: a one-sentence fact  
- **tags**: additional annotations (`category`, `difficulty`)

It’s intentionally tiny (<100 KB) so you can iterate on data loading, evaluation scripts, or CI steps in under a second using these specific 52 items.

## Supported Tasks and Formats (for this core dataset)

- **Tasks**:  
  - Extractive QA  
  - Generative QA  
- **Format**: JSON  
- **Splits**:  
  - `train` (all 52 examples)  

## Languages (for this core dataset)

- English (`en`)

## Dataset Structure

### Data Fields

Each example in `data/train.json` (as loaded by `datasets`) has:

| field               | type   | description                                  |
|---------------------|--------|----------------------------------------------|
| `text`              | string | The question prompt.                         |
| `label`             | string | The correct answer.                          |
| `metadata`          | object | Additional info.                             |
| `metadata.context`  | string | A one-sentence fact supporting the answer.   |
| `tags.category`     | string | Broad question category (e.g. `geography`).  |
| `tags.difficulty`   | string | Rough difficulty level (e.g. `easy`).        |

## Data Example

```json
[
  {
    "text": "What is the capital of France?",
    "label": "Paris",
    "metadata": {
      "context": "France is a country in Europe. Its capital is Paris."
    },
    "tags": {
      "category": "geography",
      "difficulty": "easy"
    }
  },
  {
    "text": "What is 2 + 2?",
    "label": "4",
    "metadata": {
      "context": "Basic arithmetic: 2 + 2 equals 4."
    },
    "tags": {
      "category": "math",
      "difficulty": "easy"
    }
  }
]
```
*(Note: The actual file on the Hub might be a `.jsonl` file where each line is a JSON object, but `load_dataset` handles this.)*

## Data Splits

Only one split for this core dataset:

- **train**: 52 examples, used for development, quick evaluation, and as the TQB++ core.

## Data Creation

### Curation Rationale

The "Tiny QA Benchmark" (this 52-item set) was originally created to:

1. Smoke-test QA pipelines (loading, preprocessing, evaluation).  
2. Demo Hugging Face Datasets integration in tutorials.  
3. Verify model–eval loops run without downloading large corpora.
4. **Serve as the immutable "gold standard" English core for the [Tiny QA Benchmark++ (TQB++)](https://huggingface.co/datasets/vincentkoc/tiny_qa_benchmark_pp) project.**

### Source Data

Hand-crafted by the dataset creator from well-known, public-domain facts.
It was initially developed as a dataset for sample projects to demonstrate [Opik](https://github.com/comet-ml/opik/) and now forms the foundational English core of TQB++.

### Annotations

Self-annotated. Each `metadata.context` and `tags` field is manually created for these 52 items.

## Usage

Load this specific 52-item core dataset with:

```python
from datasets import load_dataset

ds = load_dataset("vincentkoc/tiny_qa_benchmark")
print(ds["train"][0])
# Expected output:
# {
#   "text": "What is the capital of France?",
#   "label": "Paris",
#   "metadata": {
#     "context": "France is a country in Europe. Its capital is Paris."
#   },
#   "tags": {
#     "category": "geography",
#     "difficulty": "easy"
#   }
# }
```
For accessing the full TQB++ suite, including multilingual packs and the synthetic generator, refer to the [TQB++ Hugging Face Dataset Collection](https://huggingface.co/datasets/vincentkoc/tiny_qa_benchmark_pp).

## Considerations for Use

*   **Immutable Core for TQB++:** This dataset is the stable, hand-curated English core of the TQB++ project. Its 52 items are not intended to change.
*   **Not a Comprehensive Benchmark (on its own):** While excellent for quick checks, these 52 items are too few for statistically significant model ranking. For broader evaluation, use in conjunction with the TQB++ synthetic generator and its multilingual capabilities found at [vincentkoc/tiny_qa_benchmark_pp](https://huggingface.co/datasets/vincentkoc/tiny_qa_benchmark_pp).
*   **Do Not Train:** Primarily intended for evaluation, smoke-tests, or demos.
*   **No Sensitive Data:** All facts are public domain.

## Licensing

Apache-2.0. See the `LICENSE` file in the [TQB++ GitHub repository](https://github.com/vincentkoc/tiny_qa_benchmark_pp) for details (as this dataset is now part of that larger project).

## Citation

If you use this specific 52-item core English dataset, please cite it. You can use the following BibTeX entry, which has been updated to reflect its role:

```bibtex
@misc{koctinyqabenchmark_original_core,
	author       = { Vincent Koc },
	title        = { Tiny QA Benchmark (Original 52-item English Core for TQB++) },
	year         = 2025,
	url          = { https://huggingface.co/datasets/vincentkoc/tiny_qa_benchmark },
	doi          = { 10.57967/hf/5417 },
	publisher    = { Hugging Face }
}
```

For the complete **Tiny QA Benchmark++ (TQB++)** project (which includes this core set, the synthetic generator, multilingual packs, and the associated research paper), please refer to and cite the TQB++ project directly:

```bibtex
@misc{koctinyqabenchmark_pp_dataset,
  author       = {Vincent Koc},
  title        = {Tiny QA Benchmark++ (TQB++) Datasets and Toolkit},
  year         = {2025},
  publisher    = {Hugging Face & GitHub},
  doi          = {10.57967/hf/5531}, /* DOI for the TQB++ collection */
  howpublished = {\\url{https://huggingface.co/datasets/vincentkoc/tiny_qa_benchmark_pp}},
  note         = {See also: \\url{https://github.com/vincentkoc/tiny_qa_benchmark_pp}}
}
```