---
license: cc-by-nc-nd-4.0
dataset_info:
  features:
  - name: sentences
    sequence: string
  - name: labels
    sequence: string
  splits:
  - name: test
    num_bytes: 1259522
    num_examples: 20
  download_size: 318366
  dataset_size: 1259522
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
task_categories:
- text-classification
language:
- en
pretty_name: Built-Bench-Clustering-P2P
size_categories:
- 1K<n<10K
---

### Data sources
- Industry Foundation Classes (IFC) published by buildingSmart International: https://ifc43-docs.standards.buildingsmart.org/
- Uniclass product tables published by NBS: https://www.thenbs.com/our-tools/uniclass

### License

- cc-by-nc-nd-4.0: https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en

### How to cite
Research paper on the dataset development and validations: https://arxiv.org/abs/2411.12056 

```
@article{shahinmoghadam2024benchmarking,
  title={Benchmarking pre-trained text embedding models in aligning built asset information},
  author={Shahinmoghadam, Mehrzad and Motamedi, Ali},
  journal={arXiv preprint arXiv:2411.12056},
  year={2024}
}
```