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---
dataset_info:
features:
- name: title
dtype: string
- name: paper_category
dtype: string
- name: error_category
dtype: string
- name: error_location
dtype: string
- name: error_severity
dtype: string
- name: error_annotation
dtype: string
splits:
- name: train
num_bytes: 35801
num_examples: 91
download_size: 22781
dataset_size: 35801
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
language:
- en
size_categories:
- n<1K
---
# SPOT-MetaData
> Metadata & Annotations for **Scientific Paper ErrOr DeTection** (SPOT)
> *SPOT contains 83 papers and 91 human-validated errors to test academic verification capabilities.*
## 📖 Overview
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.
Parse contents are available at: [link](https://huggingface.co/datasets/amphora/SPOT).
For codes see: [link](https://github.com/guijinSON/SPOT).
> **Benchmark at a glance**
> - **83** published manuscripts
> - **91** confirmed errors (errata or retractions)
> - **10** scientific domains (Math, Physics, Biology, …)
> - **6** error types (Equation/Proof, Fig-duplication, Data inconsistency, …)
> - Average paper length: ~12 000 tokens & 18 figures
## 📜 License
This repository (metadata & annotations) is released under the CC-BY-4.0 license. |