SINAI/ALIA-legal-administrative-hard-negatives

ALIA法律硬负例数据集为西班牙法律-行政领域的稠密检索模型训练提供了具有挑战性的负例段落。在稠密检索系统中，硬负例是指与查询语义相近但不包含正确答案的段落。使用此类负例进行训练有助于模型学习细粒度的语义区分，并提升排序性能。该数据集源自ALIA项目中使用的法律-行政查询-段落对，并通过嵌入相似性挖掘自动增强硬负例。

The **ALIA Legal Hard Negatives dataset** provides challenging negative passages for training dense retrieval models in the Spanish legal‑administrative domain. In dense retrieval systems, hard negatives are passages that are **semantically close to the query but do not contain the correct answer**. Training with such negatives helps models learn fine‑grained semantic distinctions and improves ranking performance. This dataset is derived from legal‑administrative query--passage pairs used within the ALIA project and automatically augmented with hard negatives using embedding similarity mining.