{system_prompt}

You are tasked with refining and neutralizing a list of topics generated from responses to a question. Your goal is to transform opinionated topics into neutral, well-structured, and distinct topics while preserving the essential information.

## Input
You will receive a list of OPINIONATED TOPICS. These topics explicitly tie opinions to whether a person agrees or disagrees with the question.

## Output
You will produce a list of NEUTRAL TOPICS based on the input. Each neutral topic should have two parts:
1. A brief, clear topic label (3-7 words)
2. A more detailed topic description (1-2 sentences)

## Guidelines

1. Information Retention:
   - Preserve all key information, details and concepts from the original topics.
   - Ensure no significant details are lost in the refinement process.

2. Neutrality:
   - Remove all language indicating agreement or disagreement.
   - Present topics objectively without favoring any particular stance.
   - Avoid phrases like "supporters believe" or "critics argue".

3. Avoid Response References:
   - Do not use language that refers to multiple responses or respondents.
   - Focus solely on the content of each topic.
   - Avoid phrases like "many respondents said" or "some responses indicated".

4. Distinctiveness:
   - Ensure each topic represents a unique concept or aspect of the policy.
   - Minimize overlap between topics.
   - If topics are closely related, find ways to differentiate them clearly.

5. Fluency and Readability:
   - Create concise, clear topic labels that summarize the main idea.
   - Provide detailed descriptions that expand on the label without mere repetition.
   - Use proper grammar, punctuation, and natural language.

## Process

1. Analyze the OPINIONATED TOPICS to identify key themes and information.
2. Group closely related topics together.
3. For each group or individual topic:
   a. Distill the core concept, removing any bias or opinion.
   b. Create a neutral, concise topic label.
   c. Write a more detailed description that provides context without taking sides.
4. Review the entire list to ensure distinctiveness and adjust as needed.
5. Double-check that all topics are truly neutral and free of response references.
6. Assign each output topic a topic_id a single uppercase letters (starting from 'A')
7. Combine the topic label and description with a colon separator

Return your output in the following JSON format:
{{
   "responses": [
       {{"topic_id": "A", "topic": "{{topic label 1}}: {{topic description 1}}"}},
       {{"topic_id": "B", "topic": "{{topic label 2}}: {{topic description 2}}"}},
       {{"topic_id": "C", "topic": "{{topic label 3}}: {{topic description 3}}"}},
      // Additional topics as necessary
   ]
}}


## Example

OPINIONATED TOPIC:
"Economic impact: Many respondents who support the policy believe it will create jobs and boost the economy, it could raise GDP by 2%."

NEUTRAL TOPIC:
Topic Label: Economic Impact on Employment
Description: The policy's potential effects on job creation and overall economic growth, including potential for a 2% increase in GDP.

Remember, your goal is to create a list of neutral, informative, and distinct topics that accurately represent the content of the original opinionated topics without any bias or references to responses.



OPINIONATED TOPIC:
{responses}