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--- |
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license: cc-by-4.0 |
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task_categories: |
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- tabular-classification |
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language: |
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- en |
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tags: |
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- geospatial |
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- gis |
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- benchmark |
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- boundaries |
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- coordinates |
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- uncertainty |
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- spatial-analysis |
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- llm-evaluation |
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pretty_name: BoundaryBench v1 |
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size_categories: |
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- 10K<n<100K |
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--- |
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# BoundaryBench |
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**A National Benchmark for Geographic Boundary Resolution with Calibrated Uncertainty** |
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[](https://doi.org/10.5281/zenodo.18090588) |
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**DOI:** [10.5281/zenodo.18090588](https://doi.org/10.5281/zenodo.18090588) |
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## Dataset Summary |
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BoundaryBench is a benchmark dataset of 13,000 synthetic coordinate queries across 50 U.S. states plus D.C., designed to evaluate geographic boundary resolution systems. Points are stratified by distance-to-boundary difficulty tiers and complex polygon geometries. |
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- **Points**: 13,000 |
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- **Layers**: county, ZCTA, tract |
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- **Difficulties**: easy, medium, hard, boundary, edge |
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- **Version**: v1.0.0 |
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- **License**: CC-BY-4.0 |
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- **DOI**: 10.5281/zenodo.18090588 |
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*Independent research; not endorsed by any organization.* |
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## How to Load |
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```python |
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from datasets import load_dataset |
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# Load the dataset |
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ds = load_dataset("nidhipandya/boundarybench") |
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# Or load parquet files directly |
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import pandas as pd |
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df = pd.read_parquet("hf://datasets/nidhipandya/boundarybench/data/boundarybench_v1.parquet") |
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print(f"Total points: {len(df)}") |
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print(df.head()) |
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``` |
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## Data Fields |
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| Field | Type | Description | |
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|-------|------|-------------| |
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| `lat` | float | Latitude (EPSG:4269 / NAD83) | |
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| `lon` | float | Longitude (EPSG:4269 / NAD83) | |
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| `layer` | string | Administrative layer: `county`, `zcta`, or `tract` | |
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| `label_id` | string | Ground-truth region identifier | |
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| `difficulty` | string | One of: `easy`, `medium`, `hard`, `boundary`, `edge` | |
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| `dist_to_boundary_m` | float | Distance to nearest boundary in meters | |
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| `state_fips` | string | State FIPS code | |
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| `split` | string | Dataset split: `train`, `dev`, or `test` | |
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## Difficulty Stratification |
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| Difficulty | Distance Range | Count | |
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|------------|---------------|-------| |
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| easy | ≥500m | 4,550 | |
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| medium | 100-500m | 3,250 | |
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| hard | 10-100m | 3,250 | |
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| boundary | 0-10m | 1,300 | |
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| edge | 10-100m | 650 | |
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## Versioning |
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- **Version**: v1.0.0 |
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- **Code**: [GitHub](https://github.com/nidhip1611/boundarybench) |
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- **Zenodo (concept)**: [10.5281/zenodo.18090588](https://doi.org/10.5281/zenodo.18090588) |
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- **Zenodo (v1.0.0)**: [10.5281/zenodo.18090589](https://doi.org/10.5281/zenodo.18090589) |
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## Citation |
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```bibtex |
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@dataset{pandya2025boundarybench, |
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title={BoundaryBench: Evaluating Geographic Boundary Resolution with Calibrated Uncertainty}, |
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author={Pandya, Nidhi}, |
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year={2025}, |
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doi={10.5281/zenodo.18090588}, |
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url={https://doi.org/10.5281/zenodo.18090588}, |
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license={CC-BY-4.0} |
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} |
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``` |
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## License |
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[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/) |
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## Contact |
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- **Author**: Nidhi Pandya |
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- **Email**: nidhipandya1606@gmail.com |
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- **GitHub**: https://github.com/nidhip1611/boundarybench |
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