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HIPE-2026 evaluates person-place relation extraction from historical texts · 3 sources tracked

By PulseAugur Editorial · [3 sources] ·

The HIPE-2026 evaluation campaign focused on extracting person-place relationships from multilingual historical texts, building upon previous HIPE editions that concentrated on named entity recognition. This year's challenge involved identifying two types of temporal relationships: '$at$' (person was at a place before publication) and '$isAt$' (person was at a place contemporaneous with publication). The evaluation considered accuracy, computational efficiency, and cross-domain generalization across French, German, and English texts from the 19th and 20th centuries, as well as early modern French literature. AI

IMPACT This research advances methods for extracting structured information from historical texts, potentially improving knowledge graph construction and digital humanities research.

RANK_REASON The cluster describes the results of an academic evaluation campaign and associated research paper.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

HIPE-2026 evaluates person-place relation extraction from historical texts · 3 sources tracked

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COVERAGE [3]

  1. arXiv cs.CL TIER_1 English(EN) · Juri Opitz, Maud Ehrmann, Corina Racl\'e, Andrianos Michail, Matteo Romanello, Simon Clematide ·

    Overview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Texts

    arXiv:2606.25935v1 Announce Type: new Abstract: Was this person ever at that place, and if so, when? Answering such questions from noisy, multilingual historical documents is the central challenge of HIPE-2026, the third edition of the HIPE evaluation series. Moving from named en…

  2. arXiv cs.CL TIER_1 English(EN) · Juri Opitz, Corina Racl\'e, Emanuela Boros, Andrianos Michail, Matteo Romanello, Maud Ehrmann, Simon Clematide ·

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

    arXiv:2602.17663v2 Announce Type: replace-cross 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 …

  3. arXiv cs.AI TIER_1 English(EN) · Simon Clematide ·

    Overview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Texts

    Was this person ever at that place, and if so, when? Answering such questions from noisy, multilingual historical documents is the central challenge of HIPE-2026, the third edition of the HIPE evaluation series. Moving from named entity recognition and linking (HIPE-2020, HIPE-20…

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