README.md

---
language:
  - en
  - pt
  - es
  - fr
  - de
  - it
  - ru
  - zh
license: cdla-permissive-1.0
size_categories:
  - 1K<n<10K
task_categories:
  - token-classification
  - text-generation
tags:
  - citation-parsing
  - bibliographic-references
  - jats-xml
  - scholarly-communication
  - information-extraction
  - named-entity-recognition
pretty_name: RenoBench
dataset_info:
  features:
    - name: citing_article_doi
      dtype: string
    - name: plaintext
      dtype: string
    - name: xml
      dtype: string
    - name: source
      dtype: string
  splits:
    - name: train
      num_examples: 10000
---

# RenoBench: A Citation Parsing Benchmark

RenoBench (**Re**ference An**no**tation **Bench**mark) is a standardized evaluation benchmark for citation parsing—the task of annotating plain-text bibliographic references with structured components following the [JATS (Journal Article Tag Suite)](https://jats.nlm.nih.gov/) standard.

## Dataset Description

RenoBench contains 10,000 plain-text citations paired with their corresponding JATS XML annotations. The dataset was assembled by extracting plain-text references from public domain PDFs and matching them to publisher-provided structured annotations.

### Data Sources

Citations are sourced from four scholarly publishing platforms:

| Source | Description | Percentage |
|--------|-------------|------------|
| [SciELO](https://scielo.org/) | Scientific Electronic Library Online | 47% |
| [Redalyc](https://www.redalyc.org/) | Red de Revistas Científicas de América Latina | 24% |
| [Open Research Europe](https://open-research-europe.ec.europa.eu/) | European Commission open access platform | 14% |
| [PKP](https://pkp.sfu.ca/) | Public Knowledge Project OJS journals | 14% |

### Dataset Composition

- **59%** of citations include a persistent identifier (DOI)
- **14%** of citing articles are preprints
- **Languages**: English (32%), Portuguese (30%), Spanish (23%), French (7%), German (3%), Italian (2%), Russian (2%), Chinese (1%)
- **Publication types**: Journal articles (53%), books (30%), webpages (8%), theses (5%), conference proceedings (4%)

## Data Fields

| Field | Type | Description |
|-------|------|-------------|
| `citing_article_doi` | string | DOI of the article containing the citation (may be null) |
| `plaintext` | string | The plain-text citation as extracted from the PDF |
| `xml` | string | JATS XML annotation with structured bibliographic fields |
| `source` | string | Publishing platform source (`scielo`, `redalyc`, `ore`, `pkp`) |

## Example
**Plain-text citation:**
```
Stone NJ, Robinson JG, Lichtenstein AH, et al. 2013 ACC/AHA Guideline on the
Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk
in Adults. Circulation 2014;129(25 Suppl 2):S1-S45. doi:10.1161/01.cir.0000437738.63853.7a.
```

**JATS XML annotation:**
```xml
<mixed-citation publication-type="journal">
  <person-group person-group-type="author">
    <string-name><surname>Stone</surname> <given-names>NJ</given-names></string-name>,
    <string-name><surname>Robinson</surname> <given-names>JG</given-names></string-name>,
    <string-name><surname>Lichtenstein</surname> <given-names>AH</given-names></string-name>,
    <etal>et al</etal>
  </person-group>.
  <article-title>2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol...</article-title>.
  <source>Circulation</source>
  <year>2014</year>;<volume>129</volume>(<issue>25</issue>):<fpage>S1</fpage>-<lpage>S45</lpage>.
  <pub-id pub-id-type="doi">10.1161/01.cir.0000437738.63853.7a</pub-id>.
</mixed-citation>
```

## JATS XML Elements

The annotations use standard JATS reference elements:

| Element | Description |
|---------|-------------|
| `<surname>` | Author family name |
| `<given-names>` | Author given name(s) or initials |
| `<article-title>` | Title of the cited article |
| `<source>` | Journal name, book title, or publisher |
| `<year>` | Publication year |
| `<volume>` | Journal volume |
| `<issue>` | Journal issue |
| `<fpage>`, `<lpage>` | First and last page numbers |
| `<pub-id pub-id-type="doi">` | Digital Object Identifier |

## Data Collection

1. **PDF Extraction**: Article PDFs were converted to markdown using [markitdown](https://github.com/microsoft/markitdown)
2. **Citation Extraction**: Plain-text citations were extracted using `Llama-3.1-8B-Instruct`, with programmatic verification that extracted text appeared in the source document
3. **Matching**: Plain-text citations were matched to JATS XML annotations using normalized edit distance (threshold ≥ 0.75)
4. **Filtering**: Automated quality checks removed citations with structural errors, malformed fields, or annotation inconsistencies
5. **Sampling**: Balanced sampling across languages, publication types, and sources using learned sampling weights

## Intended Use

RenoBench is designed for:

- **Benchmarking** citation parsing systems (GROBID, neural parsers, LLMs)
- **Training** sequence labeling or text-to-text models for citation parsing
- **Evaluating** multilingual and cross-domain generalization

## Limitations

- Annotations reflect publisher practices, which may vary in completeness
- Some citation styles (legal, patents) are underrepresented
- Language distribution reflects source platform demographics

## Citation

Coming soon!