DNB-AI-Project at SemEval-2025 Task 5: An LLM-Ensemble Approach for Automated Subject Indexing
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Abstract (arXiv)
This paper presents our system developed for the SemEval-2025 Task 5: LLMs4Subjects: LLM-based Automated Subject Tagging for a National Technical Library's Open-Access Catalog. Our system relies on prompting a selection of LLMs with varying examples of intellectually annotated records and asking the LLMs to similarly suggest keywords for new records. This few-shot prompting technique is combined with a series of post-processing steps that map the generated keywords to the target vocabulary, aggregate the resulting subject terms to an ensemble vote and, finally, rank them as to their relevance to the record. Our system is fourth in the quantitative ranking in the all-subjects track, but achieves the best result in the qualitative ranking conducted by subject indexing experts.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 13 of its 27 references that are in the map. First posted on arXiv 30 Apr 2025.
Builds on
13 of 27 references.
References · 13
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Built on by
Citing papers per year: 2025: 2; 2026: 2.
4 papers.
- 2025Annif at the GermEval-2025 LLMs4Subjects Task: Traditional XMTC Augmented by Efficient LLMscited by 2
- 2026LCSHBench: A Multilingual, Consensus-Grounded Benchmark for Library of Congress Subject Heading Assignmentcited by 1
- 2025NFDI4DS Shared Tasks for Scholarly Document Processingcited by 0
- 2026Does generative AI supersede supervised XMLC? A Benchmark Study on Automated Subject Indexing with German Scientific Literaturecited by 0
- 2026Does generative AI supersede supervised XMLC? A Benchmark Study on Automated Subject Indexing with German Scientific Literature16 Jul 2026
- 2026LCSHBench: A Multilingual, Consensus-Grounded Benchmark for Library of Congress Subject Heading Assignment3 Jun 2026
- 2025NFDI4DS Shared Tasks for Scholarly Document Processing26 Sep 2025
- 2025Annif at the GermEval-2025 LLMs4Subjects Task: Traditional XMTC Augmented by Efficient LLMs21 Aug 2025