# boolq by Google: AI Training Dataset
Source: https://savrn.com/datasets/boolq
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Dataset Card

By Google, published under cc-by-sa-3.0, revision 35b264d03638.

### Dataset Card for Boolq

### Table of Contents

- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Personal and Sensitive Information
- Considerations for Using the Data
- Social Impact of Dataset
- Discussion of Biases
- Other Known Limitations
- Additional Information
- Dataset Curators
- Licensing Information
- Citation Information
- Contributions

### Dataset Description

- Homepage: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- Repository: https://github.com/google-research-datasets/boolean-questions
- Paper: https://arxiv.org/abs/1905.10044
- Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- Size of downloaded dataset files: 8.77 MB
- Size of the generated dataset: 7.83 MB
- Total amount of disk used: 16.59 MB

#### Dataset Summary

BoolQ is a question answering dataset for yes/no questions containing 15942 examples. These questions are naturally occurring ---they are generated in unprompted and unconstrained settings. Each example is a triplet of (question, passage, answer), with the title of the page as optional additional context. The text-pair classification setup is similar to existing natural language inference tasks.

#### Supported Tasks and Leaderboards

[Read the full dataset card (421 words)](https://savrn.com/datasets/boolq/card)

## Structure

### default 12,697 rows

| Split | Rows | Size |
| --- | --- | --- |
| train | 9,427 | 5.8 MB |
| validation | 3,270 | 2.0 MB |

questionstringanswerboolpassagestring

## Details

Repository

google/boolq

Publisher

Google

Task category

Text classification

Tags

Not stated by the source

Size category

10K<n<100K

Languages

en

Revision

35b264d03638db9f4ce671b711558bf7ff0f80d5

Last updated

2024-01-22

## SAVRN's Notes on boolq

BoolQ ships 12,697 yes/no reading-comprehension rows — 9,427 train, 3,270 validation — in a 5.0 MB download, though the card text claims 15,942 examples; the structure table is the number to plan against. The questions are naturally occurring search-style queries paired with Wikipedia passages, which makes it a cheap classification benchmark but also means overlap with any Wikipedia-heavy pretraining corpus. The inbound models on our page are all small decision or fine-tuned classifiers — Jev-Style-Qwen 2B variants, kev-4b, kev-8b, dev-0.4b — which is the right scale of use.

License is CC BY-SA 3.0, an unusual pick for a Google dataset: attribution is easy, but the share-alike clause can attach to adapted material in a commercial product, so have counsel look before fine-tuning customer-facing models on it. At 5.0 MB and 206.7k monthly downloads it is firmly a benchmark, not training fuel. Use it to sanity-check boolean reasoning; do not expect a 12k-row set of 2019-era queries to move model capability.

SAVRN Research

## Files

4 files, 5.0 MB in total.

Data2 files · 4.9 MB

Documentation1 file · 6.6 KB

Repository1 file · 1.2 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| data/train-00000-of-00001.parquet | Data | 3.7 MB | 4f028e992c0b |
| data/validation-00000-of-00001.parquet | Data | 1.3 MB | 52355d11524b |
| README.md | Documentation | 6.6 KB | — |
| .gitattributes | Repository | 1.2 KB | — |

## License and Download

License

cc-by-sa-3.0

Access

No access gate

[Download from Google](https://huggingface.co/datasets/google/boolq)

Released by Google through its official repository on Hugging Face.

## Models Trained on This Dataset

- Trained on (disclosed)[Jev-Style-Qwen3.5-2B-Decision-GGUF](https://savrn.com/models/jev-style-qwen3-5-2b-decision-gguf)
- Trained on (disclosed)[Jev-Style-Qwen3.5-2B-Decision-MLX-bf16](https://savrn.com/models/jev-style-qwen3-5-2b-decision-mlx-bf16)
- Trained on (disclosed)[hopper](https://savrn.com/models/hopper)
- Trained on (disclosed)[kev-4b](https://savrn.com/models/kev-4b)
- Trained on (disclosed)[kev-8b](https://savrn.com/models/kev-8b)
- Trained on (disclosed)[dev-0.4b](https://savrn.com/models/dev-0-4b)
- Trained on (disclosed)[bobcat-flash-1.2](https://savrn.com/models/bobcat-flash-1-2)

## Google

[All models and datasets](https://savrn.com/model-publishers/google)

## Explore More

- [The dataset directory](https://savrn.com/datasets)
- [The model directory](https://savrn.com/models)
- [Research papers](https://savrn.com/papers)

## Source

- Repository metadata, read 2026-10-19.
- [Google website](https://ai.google.dev/)
- [Hugging Face record](https://huggingface.co/datasets/google/boolq)
- [How the hub is built](https://savrn.com/model-hub/methodology)