CLEF HIPE-2026: Evaluating Accurate and Efficient Person-Place Relation Extraction from Multilingual Historical Texts

Juri Opitz, Corina Raclé, Emanuela Boros, Andrianos Michail, Matteo Romanello +2 more
2/19/2026
cs.AIcs.CLcs.IR

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Abstract

HIPE-2026 is a CLEF evaluation lab dedicated to person-place relation extraction from noisy, multilingual historical texts. Building on the HIPE-2020 and HIPE-2022 campaigns, it extends the series toward semantic relation extraction by targeting the task of identifying person--place associations in multiple languages and time periods. Systems are asked to classify relations of two types - $at$ ("Has the person ever been at this place?") and $isAt$ ("Is the person located at this place around publication time?") - requiring reasoning over temporal and geographical cues. The lab introduces a three-fold evaluation profile that jointly assesses accuracy, computational efficiency, and domain generalization. By linking relation extraction to large-scale historical data processing, HIPE-2026 aims to support downstream applications in knowledge-graph construction, historical biography reconstruction, and spatial analysis in digital humanities.

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Cite this paper

@article{opitz2026clef,
  title  = {CLEF HIPE-2026: Evaluating Accurate and Efficient Person-Place Relation Extraction from Multilingual Historical Texts},
  author = {Juri Opitz and Corina Raclé and Emanuela Boros and Andrianos Michail and Matteo Romanello and Maud Ehrmann and Simon Clematide},
  year   = {2026},
  eprint = {2602.17663},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2602.17663v1}
}

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