CSI-lab/RCW_2025_Positive_Query_Pairs

华盛顿法律基准（WLB）是一个大规模合成数据集，专门用于推进法律信息检索（IR）和语义搜索。它弥合了自然语言（公民、地方政府和普通英语用户描述法律场景的方式）与正式法定法律术语（法律实际书写的方式）之间的关键“语义鸿沟”。数据集包含数十万精心配对的示例，将普通英语查询、假设场景和地方立法草案直接映射到其管辖的华盛顿州法规（修订的华盛顿法典 - RCW）。该数据集非常适合使用对比学习技术（如多负面排名损失）来微调密集检索器（如bge、e5或MiniLM）。

The **Washington Law Benchmark (WLB)** is a large-scale, synthetic dataset designed specifically to advance Legal Information Retrieval (IR) and Semantic Search. It bridges the critical "semantic gap" between natural language (how citizens, local governments, and plain-English users describe legal scenarios) and formal statutory legalese (how laws are actually written). The dataset contains hundreds of thousands of meticulously paired examples mapping plain-English queries, hypothetical scenarios, and local legislative drafts directly to their governing **Washington State Statutes (Revised Code of Washington - RCW)**. This dataset is ideal for fine-tuning dense retrievers (like `bge`, `e5`, or `MiniLM`) using contrastive learning techniques such as Multiple Negatives Ranking (MNR) loss.