zilliz/natural_questions-context-relevance-with-think

该数据集用于训练RAG系统中的语义高亮模型，包含查询-上下文对及其相关性标注，帮助识别文档中与查询语义相关的部分。关键特征包括上下文跨度、相关性标签和思考过程。数据集基于Open Provence项目的训练数据集，并进行了修改和重新标注。

This dataset is used for training the `zilliz/semantic-highlight-bilingual-v1` model for semantic highlighting in RAG (Retrieval-Augmented Generation) systems. It contains query-context pairs with relevance annotations for context spans. The annotations help identify which parts of a document are semantically relevant to a query, even when they dont contain exact keyword matches. Key features include context spans, relevance labels, and think process. The dataset is derived from `hotchpotch/natural-questions-context-relevance`, which is based on training datasets from the Open Provence project, with modifications and re-annotation.