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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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+
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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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+
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+ ### License
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+
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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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+
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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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+ ```
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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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+ ```