Speaker
Description
This methodology session explains how retrieved evidence is transformed into a grounded answer through prompt construction and generation. Participants will learn the main components of a grounded RAG prompt: the user query, retrieved evidence, system instructions and required answer format. The session discusses how prompt instructions can constrain the model to answer only from available sources, cite supporting evidence, avoid unsupported claims and state when the retrieved context is insufficient. It also covers context construction decisions, including how much evidence to include, how to order passages and how to separate facts from caveats. Special attention is given to source attribution and citation granularity, particularly in public-service or administrative domains where users need traceability. By the end, participants will understand that generation quality depends not only on the LLM, but also on retrieval quality, prompt design and evidence organisation. These principles are then implemented in the following hands-on end-to-end RAG tutorial.
