Gul55555/ragbench-queries

RAGBench Queries

A collection of evaluation queries designed for benchmarking Retrieval-Augmented Generation (RAG) systems.

Dataset Description

RAGBench Queries contains test queries used to evaluate different retrieval and chunking strategies in a RAG pipeline.

The dataset was created as part of the RAGBench project, which compares retrieval performance using different document chunking approaches.

Purpose

The queries are designed to evaluate whether a RAG system can retrieve the correct information from a collection of documents.

The benchmark can be used to compare:

• —Semantic chunking
• —Parent-child chunking
• —Other retrieval strategies
• —Different embedding models
• —RAG pipelines and retrieval configurations

Dataset Structure

The dataset is provided in JSON format.

Each query contains information required to evaluate retrieval performance, including the query and its expected relevant document.

Example:

{
  "query": "Example question about the document",
  "relevant_doc": "document_1"
}