## Technical Document: Prompt for Response Generation ### Overview The image displays a structured text document titled "Prompt for Response Generation." It is a template or instruction set designed to guide an AI or evaluator in analyzing a provided question/solution pair. The document defines specific fields for evaluation, provides a template with placeholders for dynamic content, and mandates a strict output format. The text is entirely in English. ### Content Structure The document is organized into several distinct sections within a bordered frame with a dark blue header. 1. **Header:** "Prompt for Response Generation" in white text on a dark blue background. 2. **Primary Task Description:** A paragraph outlining the core task: to examine a question/solution pair, determine solution correctness, and identify the first error step if the solution is incorrect. 3. **Field Definitions:** A detailed section defining the evaluation criteria: * **Solution Correctness:** Asks if the solution correctly answers the question with justifiable reasoning and selected corrected options. * **First Error Step:** Defines three categories for each step: * *Correct:* Sound logic, correct computation, leads to correct answer. * *Neutral:* Explanatory or background-focused, no obvious mistakes, but unclear if it leads to the correct answer. * *Incorrect:* Contains factual, computational, or logic errors that may or may not derail the reasoning. * **Error Reason:** Requires specifying the errors in the identified first error step and suggesting a rectified reasoning step. 4. **Template Section with Placeholders:** This section contains the dynamic parts of the prompt, marked by curly braces `{}`. * `{k_shot_demo}`: A placeholder, likely for inserting few-shot demonstration examples. * "Below is the question and solution for you to solve:" * `Question: {sol['Question']}` * `Options: {sol['Options']}` * `Step by Step Solution: {sol['Model_Solution_Steps']}` * `{hint_sent}`: Another placeholder, likely for optional hints. 5. **Mandated Response Format:** A final section instructing the responder to follow a specific format without any additional introductory or concluding statements. The required format is: * `Solution Analysis: [Give a step by step analysis on the solution correctness here]` * `Solution Correctness: [Input 'correct'/'incorrect' here to indicate the overall correctness of the solution]` * `First Error Step: [Input 'Step x' here to indicate the first error step here. Input 'N/A' if the solution is correct.]` * `Error Reason: [Input the error reason and the rectified reasoning of the first error step here. Input 'N/A' if the solution is correct.]` ### Detailed Analysis The document is a meta-prompt—a prompt designed to generate or structure another AI's response. Its primary function is to enforce a rigorous, step-by-step evaluation of a solution's logical validity. * **Key Definitions:** The definitions for "Correct," "Neutral," and "Incorrect" steps are precise. A "Neutral" step is particularly interesting; it is not erroneous but is flagged for potentially being non-contributory or insufficiently directed toward the answer. * **Placeholders:** The use of `{sol['Subject']}`, `{sol['Question']}`, etc., indicates this is a template where specific problem data is inserted programmatically. `{k_shot_demo}` suggests the prompt can be augmented with examples to guide the evaluator's style. * **Strict Format:** The final instruction ("Please follow this format without any additional introductory or concluding statements") is absolute, aiming to produce standardized, machine-parsable output. ### Key Observations 1. **Focus on Process over Outcome:** The evaluation is heavily weighted on the *reasoning process* ("step by step analysis") rather than just the final answer. Identifying the "First Error Step" is a core requirement. 2. **Granular Error Classification:** The system distinguishes between steps that are outright wrong and steps that are merely unhelpful or neutral, allowing for nuanced feedback. 3. **Template-Driven Design:** The document is clearly a reusable component in a larger pipeline, likely for automated grading, model training, or generating critique datasets. 4. **Visual Layout:** The text is presented in a monospaced font (like Courier) within a light gray box, mimicking a code block or terminal output, which reinforces its technical, programmatic nature. ### Interpretation This document is a **prompt engineering template for automated solution evaluation**. Its purpose is to standardize the critique of step-by-step problem-solving, likely in an educational or AI training context. * **What it demonstrates:** It reveals a sophisticated approach to assessment that values logical soundness and process transparency. By requiring the identification of the *first* error, it encourages pinpointing the root cause of failure rather than just listing all mistakes. * **How elements relate:** The field definitions directly inform the mandated response format. The placeholders connect this static instruction set to dynamic problem data. The strict output format ensures consistency for downstream processing. * **Notable implications:** The inclusion of a "Neutral" step category is insightful. It acknowledges that not all explanatory text is erroneous, but some may be inefficient or off-topic—a subtle distinction important for training models to generate concise, relevant reasoning. The entire structure is designed to minimize ambiguity and subjective judgment in the evaluation process.