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.

翻译：HIPE-2026是CLEF评估实验室的一个专项任务，专注于从噪声多语言历史文本中抽取人地关系。该任务在HIPE-2020和HIPE-2022评测活动的基础上，将系列任务扩展至语义关系抽取领域，其核心目标是在多种语言和不同历史时期中识别人与地点之间的关联。系统需对两类关系进行分类——$at$（“此人是否曾到过该地点？”）和$isAt$（“此人是否在文献发表时期位于该地点？”）——这要求对时间和地理线索进行推理。该实验室引入了一个三重评估框架，综合考量准确性、计算效率与领域泛化能力。通过将关系抽取与大规模历史数据处理相结合，HIPE-2026旨在支持知识图谱构建、历史传记重建以及数字人文领域空间分析等下游应用。