Digging Up Citations: FOSSIL, a Dataset and Workflow for Reference Extraction in Law and the Humanities
For researchers and practitioners needing to extract citations from footnotes in law and humanities scholarship, this work provides a new dataset and improved extraction pipeline, though it is work in progress with remaining challenges.
The authors present FOSSIL, a multilingual dataset of 96 law and humanities articles with over 7,600 footnote-embedded references, and a specialized Grobid pipeline that nearly doubles citation extraction quality (micro-F1 from 0.36 to 0.72) compared to default Grobid.
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.