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--- |
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dataset_info: |
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features: |
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- name: title |
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dtype: string |
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- name: paper_category |
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dtype: string |
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- name: error_category |
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dtype: string |
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- name: error_location |
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dtype: string |
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- name: error_severity |
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dtype: string |
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- name: error_annotation |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 35801 |
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num_examples: 91 |
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download_size: 22781 |
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dataset_size: 35801 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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license: cc-by-4.0 |
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language: |
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- en |
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size_categories: |
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- n<1K |
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--- |
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# SPOT-MetaData |
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> Metadata & Annotations for **Scientific Paper ErrOr DeTection** (SPOT) |
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> *SPOT contains 83 papers and 91 human-validated errors to test academic verification capabilities.* |
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## 📖 Overview |
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SPOT-MetaData contains all of the **annotations** for the SPOT benchmark—**no** paper PDFs or parsed content are included here. This lightweight repo is intended for anyone who needs to work with the ground-truth error labels, categories, locations, and severity ratings. |
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Parse contents are available at: [link](https://huggingface.co/datasets/amphora/SPOT). |
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For codes see: [link](https://github.com/guijinSON/SPOT). |
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> **Benchmark at a glance** |
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> - **83** published manuscripts |
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> - **91** confirmed errors (errata or retractions) |
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> - **10** scientific domains (Math, Physics, Biology, …) |
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> - **6** error types (Equation/Proof, Fig-duplication, Data inconsistency, …) |
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> - Average paper length: ~12 000 tokens & 18 figures |
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## 📜 License |
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This repository (metadata & annotations) is released under the CC-BY-4.0 license. |
