# Digging Up Citations: FOSSIL, a Dataset and Workflow for Reference Extraction in Law and the Humanities

arXiv: https://arxiv.org/abs/2606.01109 · HTML: https://mlsanity.com/paper/2606.01109/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 14 references that are in the map.
- First posted on arXiv 31 May 2026.

## Builds on (most cited first, 4 of 4)

- [Comprehensive Analysis of Transparency and Accessibility of ChatGPT, DeepSeek, And other SoTA Large Language Models](https://mlsanity.com/paper/2502.18505/) (2025)
- [Citation Parsing and Analysis with Language Models](https://mlsanity.com/paper/2505.15948/) (2025)
- [Large Language Models for History, Philosophy, and Sociology of Science: Interpretive Uses, Methodological Challenges, and Critical Perspectives](https://mlsanity.com/paper/2506.12242/) (2025)
- [Structured references from PDF articles: assessing the tools for bibliographic reference extraction and parsing](https://mlsanity.com/paper/2205.14677/) (2022)

## Abstract (arXiv)

Citation extraction tools are designed for the structured end-of-document bibliographies of the natural sciences, but law and humanities scholarship cites references primarily in footnotes, where bibliographic data is interleaved with commentary and cross-references and varies widely across languages and styles. To address the scarcity of suitable gold-standard resources, we present FOSSIL (Footnote-based Open-access SSH Scientific Instance Labels), an openly licensed multilingual dataset of 96 annotated scholarly articles containing over 7,600 footnote-embedded references, together with PDF-TEI Editor (a collaborative web annotation tool), a documented seven-annotator workflow, and a Grobid specialization for footnote-based citations. In end-to-end evaluation, the specialized pipeline nearly doubles extraction quality over default Grobid (micro-F1 from 0.36 to 0.72), driven largely by improved recall, while showing that substantial headroom remains for cross-references and mixed-content footnotes. This extended abstract presents work in progress; annotations of citations segmentation and parsing, and cross-reference resolution are ongoing.