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README.md
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---
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dataset_info:
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features:
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- name: sentences
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data_files:
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- split: test
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path: data/test-*
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---
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---
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license: cc-by-nc-nd-4.0
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dataset_info:
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features:
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- name: sentences
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data_files:
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- split: test
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path: data/test-*
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task_categories:
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- text-classification
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language:
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- en
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pretty_name: Built-Bench-Clustering-P2P
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size_categories:
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- 1K<n<10K
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---
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### Data sources
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- Industry Foundation Classes (IFC) published by buildingSmart International: https://ifc43-docs.standards.buildingsmart.org/
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- Uniclass product tables published by NBS: https://www.thenbs.com/our-tools/uniclass
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### License
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- cc-by-nc-nd-4.0: https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en
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### How to cite
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Research paper on the dataset development and validations: https://arxiv.org/abs/2411.12056
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```
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@article{shahinmoghadam2024benchmarking,
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title={Benchmarking pre-trained text embedding models in aligning built asset information},
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author={Shahinmoghadam, Mehrzad and Motamedi, Ali},
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journal={arXiv preprint arXiv:2411.12056},
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year={2024}
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}
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```
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