Datasets:

josephimperial
/

ScrapeBench

---
pretty_name: ScrapeBench Website Policy Dataset
language:
- en
license: cc-by-sa-4.0
tags:
- scrapebench
- neurips-2026
- ai-agents
- web-scraping
- legal-compliance
- tabular
- text
configs:
- config_name: websites
  default: true
  data_files:
  - split: ep
    path: data/prohibited.csv
  - split: nep
    path: data/permissible.csv
  keep_default_na: false
dataset_info:
- config_name: websites
  features:
  - name: domain
    dtype: string
  - name: tos_url
    dtype: string
  - name: tos_scraping
    dtype: string
  - name: tos_condition_type
    dtype: string
  - name: tos_excerpt
    dtype: string
  - name: robots_scraping
    dtype: string
  - name: final_verdict
    dtype: string
  - name: website_category
    dtype: string
---
# ScrapeBench website data

Policy labels and saved terms of service and robots.txt files for the 1,895 websites used in **ScrapeBench: Evaluating Legal Compliance of AI Agents in Website Scraping**.

[Code and documentation](https://github.com/imperialite/scrapebench) · [Project website](https://scrapebench.github.io/) · [Agent traces and results](https://huggingface.co/datasets/josephimperial/ScrapeBench-Agent-Traces) · [Croissant metadata](https://huggingface.co/datasets/josephimperial/ScrapeBench/resolve/v1.0.2/croissant.json)

## Dataset

| Split | Websites | Definition |
| --- | ---: | --- |
| `ep` | 1,626 | **Explicitly Prohibited (EP)**: scraping is explicitly prohibited in the terms of service or robots.txt. |
| `nep` | 269 | **Not Explicitly Prohibited (NEP)**: neither source explicitly prohibits scraping. |

The original filenames are `data/prohibited.csv` and `data/permissible.csv`. The value `permissible` represents the absence of an explicit prohibition under this classification. It does not establish that every scraping activity is legally permitted.

The sample comprises high-traffic, English-language websites accessible from the United States, drawn from the February 2026 [Chrome Top Million Websites (CrUX) list](https://github.com/InternetHealthReport/crux-top-lists-country). Policy snapshots were collected in February 2026. Exact collection days were not recorded in the released data.

The CSV columns are:

| Column | Content |
| --- | --- |
| `domain` | Website domain. |
| `tos_url` | Terms of service URL. |
| `tos_scraping` | ToS classification: `prohibited`, `permissible` or `partial`. |
| `tos_condition_type` | Condition associated with a partial prohibition, where recorded. |
| `tos_excerpt` | Policy excerpt supporting the ToS classification. |
| `robots_scraping` | Robots.txt classification. |
| `final_verdict` | Combined website classification. |
| `website_category` | Website category. |

`data/tos.zip` and `data/robots.zip` contain one text snapshot per domain. Original CSV and archive bytes are preserved. The 139 empty ToS files and 77 empty robots.txt files represent absent or silent policy sources, as confirmed by the authors. Their source labels are `permissible`; the other policy source can still make a website EP.

## Load the data

Install `datasets` and `huggingface_hub` in your Python environment.

```python
from datasets import load_dataset
ep = load_dataset("josephimperial/ScrapeBench", "websites", split="ep")
nep = load_dataset("josephimperial/ScrapeBench", "websites", split="nep")
print(ep[0])
```

Download policy snapshots without loading them into the table:

```python
from huggingface_hub import hf_hub_download
tos_zip = hf_hub_download(
    repo_id="josephimperial/ScrapeBench",
    filename="data/tos.zip",
    repo_type="dataset",
)
robots_zip = hf_hub_download(
    repo_id="josephimperial/ScrapeBench",
    filename="data/robots.zip",
    repo_type="dataset",
)
```

For a reproducible analysis, record the dataset commit and pass it as `revision` to these functions. The [GitHub repository](https://github.com/imperialite/scrapebench) provides inference, judging and evaluation code. New inference runs make live HTTP requests; these snapshots preserve the policy resources used for the website labels.

## Collection, validation and limitations

GPT-5.2 produced policy classifications. The paper reports a manual audit of a random 15% sample from each final category, with no classification errors found in that audit. This is a sample-based check, not a guarantee that every label is correct.

The dataset supports evaluation of whether agents follow the recorded scraping policies and analysis of policy-checking behavior. The paper evaluates a landing-page task with six agents and eight prompts. These findings do not establish performance on other tasks, populations of websites, jurisdictions or later versions of website policies. NEP labels also do not resolve other legal restrictions that may apply to a particular use.

Verbatim policy text can contain incidental public names, professional contact details and other third-party information. No human-baseline participant records are included in this dataset.

## License and citation

ScrapeBench's original labels, annotations, metadata and dataset compilation are licensed under [CC BY-SA 4.0](https://github.com/imperialite/scrapebench/blob/main/LICENSE-DATA), to the extent the contributors hold the relevant rights. Original website policy text and excerpts retain their respective rights and are excluded from that grant. Model-generated material is covered only to the extent the contributors hold rights in it. See the [license scope and third-party notices](https://github.com/imperialite/scrapebench/blob/main/THIRD_PARTY_NOTICES.md). The associated code is [MIT-licensed](https://github.com/imperialite/scrapebench/blob/main/LICENSE).

Please cite **Joseph Marvin Imperial, Daniel Slate and Noam Kolt. ScrapeBench: Evaluating Legal Compliance of AI Agents in Website Scraping. NeurIPS 2026, Evaluations and Datasets Track.** A machine-readable citation is available in [CITATION.cff](https://github.com/imperialite/scrapebench/blob/main/CITATION.cff).

For corrections or rights concerns, open an issue in the [source repository](https://github.com/imperialite/scrapebench/issues) or contact [Joseph Marvin Imperial](mailto:jmri20@bath.ac.uk), identifying the relevant domain or file.

	---
	pretty_name: ScrapeBench Website Policy Dataset
	language:
	- en
	license: cc-by-sa-4.0
	tags:
	- scrapebench
	- neurips-2026
	- ai-agents
	- web-scraping
	- legal-compliance
	- tabular
	- text
	configs:
	- config_name: websites
	default: true
	data_files:
	- split: ep
	path: data/prohibited.csv
	- split: nep
	path: data/permissible.csv
	keep_default_na: false
	dataset_info:
	- config_name: websites
	features:
	- name: domain
	dtype: string
	- name: tos_url
	dtype: string
	- name: tos_scraping
	dtype: string
	- name: tos_condition_type
	dtype: string
	- name: tos_excerpt
	dtype: string
	- name: robots_scraping
	dtype: string
	- name: final_verdict
	dtype: string
	- name: website_category
	dtype: string
	---

	# ScrapeBench website data

	Policy labels and saved terms of service and robots.txt files for the 1,895 websites used in ScrapeBench: Evaluating Legal Compliance of AI Agents in Website Scraping.

	[Code and documentation](https://github.com/imperialite/scrapebench) · [Project website](https://scrapebench.github.io/) · [Agent traces and results](https://huggingface.co/datasets/josephimperial/ScrapeBench-Agent-Traces) · [Croissant metadata](https://huggingface.co/datasets/josephimperial/ScrapeBench/resolve/v1.0.2/croissant.json)

	## Dataset

	\| Split \| Websites \| Definition \|
	\| --- \| ---: \| --- \|
	\| `ep` \| 1,626 \| Explicitly Prohibited (EP): scraping is explicitly prohibited in the terms of service or robots.txt. \|
	\| `nep` \| 269 \| Not Explicitly Prohibited (NEP): neither source explicitly prohibits scraping. \|

	The original filenames are `data/prohibited.csv` and `data/permissible.csv`. The value `permissible` represents the absence of an explicit prohibition under this classification. It does not establish that every scraping activity is legally permitted.

	The sample comprises high-traffic, English-language websites accessible from the United States, drawn from the February 2026 [Chrome Top Million Websites (CrUX) list](https://github.com/InternetHealthReport/crux-top-lists-country). Policy snapshots were collected in February 2026. Exact collection days were not recorded in the released data.

	The CSV columns are:

	\| Column \| Content \|
	\| --- \| --- \|
	\| `domain` \| Website domain. \|
	\| `tos_url` \| Terms of service URL. \|
	\| `tos_scraping` \| ToS classification: `prohibited`, `permissible` or `partial`. \|
	\| `tos_condition_type` \| Condition associated with a partial prohibition, where recorded. \|
	\| `tos_excerpt` \| Policy excerpt supporting the ToS classification. \|
	\| `robots_scraping` \| Robots.txt classification. \|
	\| `final_verdict` \| Combined website classification. \|
	\| `website_category` \| Website category. \|

	`data/tos.zip` and `data/robots.zip` contain one text snapshot per domain. Original CSV and archive bytes are preserved. The 139 empty ToS files and 77 empty robots.txt files represent absent or silent policy sources, as confirmed by the authors. Their source labels are `permissible`; the other policy source can still make a website EP.

	## Load the data

	Install `datasets` and `huggingface_hub` in your Python environment.

	```python
	from datasets import load_dataset

	ep = load_dataset("josephimperial/ScrapeBench", "websites", split="ep")
	nep = load_dataset("josephimperial/ScrapeBench", "websites", split="nep")
	print(ep[0])
	```

	Download policy snapshots without loading them into the table:

	```python
	from huggingface_hub import hf_hub_download

	tos_zip = hf_hub_download(
	repo_id="josephimperial/ScrapeBench",
	filename="data/tos.zip",
	repo_type="dataset",
	)
	robots_zip = hf_hub_download(
	repo_id="josephimperial/ScrapeBench",
	filename="data/robots.zip",
	repo_type="dataset",
	)
	```

	For a reproducible analysis, record the dataset commit and pass it as `revision` to these functions. The [GitHub repository](https://github.com/imperialite/scrapebench) provides inference, judging and evaluation code. New inference runs make live HTTP requests; these snapshots preserve the policy resources used for the website labels.

	## Collection, validation and limitations

	GPT-5.2 produced policy classifications. The paper reports a manual audit of a random 15% sample from each final category, with no classification errors found in that audit. This is a sample-based check, not a guarantee that every label is correct.

	The dataset supports evaluation of whether agents follow the recorded scraping policies and analysis of policy-checking behavior. The paper evaluates a landing-page task with six agents and eight prompts. These findings do not establish performance on other tasks, populations of websites, jurisdictions or later versions of website policies. NEP labels also do not resolve other legal restrictions that may apply to a particular use.

	Verbatim policy text can contain incidental public names, professional contact details and other third-party information. No human-baseline participant records are included in this dataset.

	## License and citation

	ScrapeBench's original labels, annotations, metadata and dataset compilation are licensed under [CC BY-SA 4.0](https://github.com/imperialite/scrapebench/blob/main/LICENSE-DATA), to the extent the contributors hold the relevant rights. Original website policy text and excerpts retain their respective rights and are excluded from that grant. Model-generated material is covered only to the extent the contributors hold rights in it. See the [license scope and third-party notices](https://github.com/imperialite/scrapebench/blob/main/THIRD_PARTY_NOTICES.md). The associated code is [MIT-licensed](https://github.com/imperialite/scrapebench/blob/main/LICENSE).

	Please cite Joseph Marvin Imperial, Daniel Slate and Noam Kolt. ScrapeBench: Evaluating Legal Compliance of AI Agents in Website Scraping. NeurIPS 2026, Evaluations and Datasets Track. A machine-readable citation is available in [CITATION.cff](https://github.com/imperialite/scrapebench/blob/main/CITATION.cff).

	For corrections or rights concerns, open an issue in the [source repository](https://github.com/imperialite/scrapebench/issues) or contact [Joseph Marvin Imperial](mailto:jmri20@bath.ac.uk), identifying the relevant domain or file.