Datasets:
Modalities:
Text
Size:
10K - 100K
Tags:
citation-parsing
bibliographic-references
jats-xml
scholarly-communication
information-extraction
named-entity-recognition
License:
Update README.md
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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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splits:
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num_examples: 10000
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download_size: 3791819
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dataset_size: 8706980
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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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language:
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- en
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- pt
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- es
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- fr
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- de
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- it
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- ru
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- zh
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license: cc0-1.0
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size_categories:
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- 1K<n<10K
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task_categories:
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- token-classification
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- text2text-generation
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tags:
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- citation-parsing
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- bibliographic-references
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- jats-xml
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- scholarly-communication
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- information-extraction
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- named-entity-recognition
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pretty_name: RenoBench
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dataset_info:
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features:
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- name: citing_article_doi
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dtype: string
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- name: plaintext
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dtype: string
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- name: xml
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dtype: string
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- name: source
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dtype: string
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splits:
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- name: train
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num_examples: 10000
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---
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# RenoBench: A Citation Parsing Benchmark
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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.
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## Dataset Description
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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.
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### Data Sources
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Citations are sourced from four scholarly publishing platforms:
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| Source | Description | Percentage |
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|--------|-------------|------------|
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| [SciELO](https://scielo.org/) | Scientific Electronic Library Online | 47% |
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| [Redalyc](https://www.redalyc.org/) | Red de Revistas Científicas de América Latina | 24% |
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| [Open Research Europe](https://open-research-europe.ec.europa.eu/) | European Commission open access platform | 14% |
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| [PKP](https://pkp.sfu.ca/) | Public Knowledge Project OJS journals | 14% |
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### Dataset Composition
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- **59%** of citations include a persistent identifier (DOI)
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- **14%** of citing articles are preprints
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- **Languages**: English (32%), Portuguese (30%), Spanish (23%), French (7%), German (3%), Italian (2%), Russian (2%), Chinese (1%)
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- **Publication types**: Journal articles (53%), books (30%), webpages (8%), theses (5%), conference proceedings (4%)
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## Data Fields
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| Field | Type | Description |
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|-------|------|-------------|
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| `citing_article_doi` | string | DOI of the article containing the citation (may be null) |
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| `plaintext` | string | The plain-text citation as extracted from the PDF |
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| `xml` | string | JATS XML annotation with structured bibliographic fields |
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| `source` | string | Publishing platform source (`scielo`, `redalyc`, `ore`, `pkp`) |
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## Example
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**Plain-text citation:**
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```
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Stone NJ, Robinson JG, Lichtenstein AH, et al. 2013 ACC/AHA Guideline on the
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Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk
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in Adults. Circulation 2014;129(25 Suppl 2):S1-S45. doi:10.1161/01.cir.0000437738.63853.7a.
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```
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**JATS XML annotation:**
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```xml
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<mixed-citation publication-type="journal">
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<person-group person-group-type="author">
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<string-name><surname>Stone</surname> <given-names>NJ</given-names></string-name>,
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<string-name><surname>Robinson</surname> <given-names>JG</given-names></string-name>,
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<string-name><surname>Lichtenstein</surname> <given-names>AH</given-names></string-name>,
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<etal>et al</etal>
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</person-group>.
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<article-title>2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol...</article-title>.
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<source>Circulation</source>
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<year>2014</year>;<volume>129</volume>(<issue>25</issue>):<fpage>S1</fpage>-<lpage>S45</lpage>.
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<pub-id pub-id-type="doi">10.1161/01.cir.0000437738.63853.7a</pub-id>.
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</mixed-citation>
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```
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## JATS XML Elements
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The annotations use standard JATS reference elements:
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| Element | Description |
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|---------|-------------|
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| `<surname>` | Author family name |
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| `<given-names>` | Author given name(s) or initials |
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| `<article-title>` | Title of the cited article |
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| `<source>` | Journal name, book title, or publisher |
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| `<year>` | Publication year |
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| `<volume>` | Journal volume |
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| `<issue>` | Journal issue |
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| `<fpage>`, `<lpage>` | First and last page numbers |
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| `<pub-id pub-id-type="doi">` | Digital Object Identifier |
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## Data Collection
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1. **PDF Extraction**: Article PDFs were converted to markdown using [markitdown](https://github.com/microsoft/markitdown)
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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
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3. **Matching**: Plain-text citations were matched to JATS XML annotations using normalized edit distance (threshold ≥ 0.75)
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4. **Filtering**: Automated quality checks removed citations with structural errors, malformed fields, or annotation inconsistencies
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5. **Sampling**: Balanced sampling across languages, publication types, and sources using learned sampling weights
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## Intended Use
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RenoBench is designed for:
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- **Benchmarking** citation parsing systems (GROBID, neural parsers, LLMs)
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- **Training** sequence labeling or text-to-text models for citation parsing
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- **Evaluating** multilingual and cross-domain generalization
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## Limitations
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- Annotations reflect publisher practices, which may vary in completeness
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- Some citation styles (legal, patents) are underrepresented
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- Language distribution reflects source platform demographics
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## Citation
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Coming soon!
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