mlsanityData to 7 Oct 2026

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

arXiv 2602.17663 ↗First posted 19 Feb 2026cs.AI cs.CL cs.IRcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 19 Feb 2026.

Builds on

14 of 31 references.

References · 14

  1. 2019DocRED: A Large-Scale Document-Level Relation Extraction Datasetcited by 239
  2. 2020TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Taskcited by 96
  3. 2021Re-TACRED: Addressing Shortcomings of the TACRED Datasetcited by 73
  4. 2023A Comprehensive Survey on Automatic Knowledge Graph Constructioncited by 63
  5. 2022Revisiting DocRED -- Addressing the False Negative Problem in Relation Extractioncited by 57
  6. 2021NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learnedcited by 52
  7. 2024A Closer Look at Classification Evaluation Metrics and a Critical Reflection of Common Evaluation Practicecited by 26
  8. 2025GLiREL -- Generalist Model for Zero-Shot Relation Extractioncited by 11
  9. 2022HiCLRE: A Hierarchical Contrastive Learning Framework for Distantly Supervised Relation Extractioncited by 8
  10. 2022Biographical: A Semi-Supervised Relation Extraction Datasetcited by 7
  11. 2023HistRED: A Historical Document-Level Relation Extraction Datasetcited by 7
  12. 2022Improving Distantly Supervised Relation Extraction by Natural Language Inferencecited by 3
2 more
  1. 2024Guided Distant Supervision for Multilingual Relation Extraction Data: Adapting to a New Languagecited by 3
  2. 2019Following the footsteps of giants: Modeling the mobility of historically notable individuals using Wikipediacited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Overview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Textscited by 2
  2. 2026DistilledGemma: Balanced Efficiency-Accuracy for Person-Place Relation Extraction from Multilingual Historical Articlescited by 0