CLEF HIPE-2026: Evaluating Accurate and Efficient Person-Place Relation Extraction from Multilingual Historical Texts
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 - ("Has the person ever been at this place?") and ("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.
Keywords
Cite
@article{arxiv.2602.17663,
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},
journal= {arXiv preprint arXiv:2602.17663},
year = {2026}
}
Comments
ECIR 2026. CLEF Evaluation Lab. Registration DL: 2026/04/23. Task Homepage at https://hipe-eval.github.io/HIPE-2026/