| --- |
| license: cc-by-4.0 |
| task_categories: |
| - text-classification |
| language: |
| - en |
| size_categories: |
| - n<1K |
| pretty_name: IAB URL Gold 784 |
| tags: |
| - iab-taxonomy |
| - url-classification |
| - domain-classification |
| - benchmark |
| - multi-label |
| --- |
| |
| # IAB URL Gold 784 |
|
|
| A **784-row gold benchmark for URL-only IAB classification**: given nothing but a bare |
| domain (rendered as a short text string), predict the |
| [IAB Tech Lab](https://iabtechlab.com/standards/content-taxonomy/) content and audience |
| categories of the web destination. |
|
|
| This is the held-out evaluation set used to benchmark |
| [`ZeroGPU/zlm-v1-iab-domain-classifier`](https://huggingface.co/ZeroGPU/zlm-v1-iab-domain-classifier) |
| against GPT-5.4-nano. On it, the fine-tuned 149M ModernBERT model reaches **content |
| micro-F1 0.3845** (P 0.4247 / R 0.3512) vs the nano baseline's **0.3526** |
| (P 0.3332 / R 0.3744), evaluated identically. |
|
|
| ## Schema |
|
|
| One JSON object per line in `data/gold.jsonl`: |
|
|
| | Field | Type | Description | |
| | --- | --- | --- | |
| | `id` | string | Stable row id | |
| | `text` | string | The model input: `"<host> \| <segmented words> \| tld:<tld>"` (e.g. `"espn.com \| espn \| tld:com"`) | |
| | `content_labels` | list[string] | Gold IAB **Content** taxonomy labels | |
| | `audience_labels` | list[string] | Gold IAB **Audience** taxonomy labels (pipe-delimited paths) | |
| | `strat_tier1` | string | IAB content tier-1 category used for stratification | |
|
|
| ## Provenance |
|
|
| - Domains were drawn from large public domain rankings, stratified across IAB content |
| tier-1 categories. |
| - Gold labels were produced by **GPT-5.5** acting as an independent referee — a stronger |
| model than either system evaluated on this set, and **not** the producer of the |
| classifier's training labels, so the benchmark does not favor the fine-tuned model. |
| - All 784 rows were **excluded (by id and text) from the classifier's training corpus**. |
|
|
| ## Evaluation protocol |
|
|
| Score **content micro-F1** against `content_labels`: for each row take the system's |
| predicted content labels (top-k = 6 for free-form LLM baselines; calibrated |
| score-threshold cut for the classifier), accumulate true/false positives and false |
| negatives over all rows, and compute precision, recall, and F1. Rows with empty |
| `content_labels` are skipped. |
|
|
| ## Considerations |
|
|
| - Labels are model-generated (GPT-5.5), not human-annotated; treat them as high-quality |
| silver-standard gold. |
| - The taxonomy includes sensitive categories (health, religion, adult content). The rows |
| describe **web destinations**, not people. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{zerogpu2026iaburlgold784, |
| title = {IAB URL Gold 784: a gold benchmark for URL-only IAB classification}, |
| author = {ZeroGPU}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/ZeroGPU/iab-url-gold-784} |
| } |
| ``` |
|
|
