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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: 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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---
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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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> **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.
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