Effective prompts for information extraction hinge on clear and precise instructions regarding the target data. Providing few-shot examples that demonstrate desired input-output pairs significantly boosts accuracy, alongside specifying the exact output format, such as JSON or bullet points. Furthermore, incorporating explicit constraints and rules, including what *not* to extract, helps refine the model's focus and reduce irrelevant information. Techniques like chain-of-thought prompting, which asks the model to break down its reasoning, and assigning a specific persona to the AI, can further enhance extraction quality and contextual understanding. More details: https://www.lolinez.com/?https://infok.com.ua/