---
license: mit
language:
- en
task_categories:
- visual-document-retrieval
pretty_name: Author and Affiliation Parsing Benchmark Dataset
tags:
- scholarly-documents
- scientific-papers
- author-extraction
- affiliation-extraction
- metadata-parsing
- grobid
- open-science
size_categories:
- 10K<n<100K
---

# Author and Affiliation Parsing Benchmark Dataset

This dataset provides a benchmark suite for evaluating **author name parsing and author-affiliation linking systems** in scientific documents.

The goal of this benchmark is to assess the ability of document parsing systems to accurately extract:

- author names
- author ordering
- affiliations

The benchmark combines several existing evaluation datasets covering different document types and scientific domains.

## Dataset Overview

Scientific document parsing remains a challenging task due to the diversity of publication layouts, author representations, and affiliation formats.

The benchmark focuses specifically on the **author and affiliation extraction task**.

The benchmark is composed of the following subsets:

| Subset | Source | Description |
|---|---|---|
| `etd-author-affiliations` | `cometadata/etd-author-affiliations` | Electronic theses and dissertations with annotated author and affiliation information |
| `arxiv-author-affiliations` | `cometadata/arxiv-author-affiliations` | arXiv scientific articles with author-affiliation annotations |
| `PMC_sample_1943` | [GROBID evaluation dataset](https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/#datasets) | Sample of PubMed Central articles used for GROBID evaluation |
| `eLife_984` | [GROBID evaluation dataset](https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/#datasets) | eLife articles benchmark subset |
| `biorxiv-10k-test-2000` | [GROBID evaluation dataset](https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/#datasets) | bioRxiv article benchmark subset |
| `PLOS_1000` | [GROBID evaluation dataset](https://grobid.readthedocs.io/en/latest/End-to-end-evaluation/#datasets) | PLOS articles benchmark subset |