Cross-Lingual Abstractive Keyphrase Generation for Historical Newspapers

Simon Clematide, Jenifer L. Meyer, Juri Opitz, Maud Ehrmann, Kaspar Beelen


Abstract
We investigate large language models (LLMs) for cross-lingual abstractive keyphrase generation from historical newspapers. The task consists of producing a small set of English keyphrases for articles written in German, French, and Luxembourgish, combining translation, abstraction, and normalization. We conduct a human-centered pilot study comparing model outputs using human selections, LLM-as-judge assessments, and inter-annotator agreement analysis, followed by a medium-scale application to multilingual data from the Impresso corpus. Results show that LLM-generated keyphrases can support semantic enrichment and exploratory analysis of historical collections, while highlighting the subjective and methodologically challenging nature of keyphrase evaluation.
Anthology ID:
2026.llms4ssh-1.23
Volume:
Proceedings of Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities (LLMs4SSH) @ LREC 2026
Month:
May
Year:
2026
Address:
Palma de Mallorca (Spain)
Editors:
Arturo Montejo-Raez, Cristina Grisot, Joanna Blochowiak, Nikola Ljubešić, Elena Battaner, German Rigau
Venues:
LLMs4SSH | WS
SIG:
Publisher:
ELRA Language Resources Association (ELRA)
Note:
Pages:
218–223
Language:
External URL:
https://lrec.elra.info/lrec2026-ws-llms4ssh-23
DOI:
10.63317/2qijz2a9nwpd
Bibkey:
Cite (ACL):
Simon Clematide, Jenifer L. Meyer, Juri Opitz, Maud Ehrmann, and Kaspar Beelen. 2026. Cross-Lingual Abstractive Keyphrase Generation for Historical Newspapers. In Proceedings of Shaping Multilingual, Multimodal AI for the Social Sciences and Humanities (LLMs4SSH) @ LREC 2026, pages 218–223, Palma de Mallorca (Spain). ELRA Language Resources Association (ELRA).
Cite (Informal):
Cross-Lingual Abstractive Keyphrase Generation for Historical Newspapers (Clematide et al., LLMs4SSH 2026)
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