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Given below is the structure of the disposition prompt. Follow the structure to craft your own call-transcript extraction prompts:

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1. Define the Role and Context

  • What does it do?
    Specify who the LLM is and the domain it operates in (e.g., Call Center Operations Analyst in Debt Collection).
  • Why it matters:
    Sets expectations and tailors the model’s responses.

​
2. Clarify the Task

  • What does it do?
    Write a brief "## Task" section that explains exactly what the model should accomplish (e.g., read transcript, extract fields).
  • Why it matters:
    Keeps the model focused on the end goal.

​
3. Emphasize Output Requirements

  • What does it do?
    Under "## IMPORTANT", stress the format (JSON) and forbid extra fields or custom codes.
  • Why it matters:
    Ensures structured, machine-readable output.

​
4. Provide Business and Language Context

  • What does it do?
    Use "## Context Understanding", "## Business Context" and "## Language Processing Guidelines" sections to share domain rules, use cases, and allowed languages.
  • Why it matters:
    Guides the model on tone, terminology, and multilingual handling.

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5. List Field Definitions

  • What does it do?
    Create a JSON snippet showing each key with an empty value.
  • Why it matters:
    Shows exactly which fields to populate and in what structure.

​
6. Detail Allowed Values

  • What does it do?
    Under "### Allowed Values & Definitions", enumerate each field’s valid codes, descriptions, and criteria in priority order for STAGE_CODE.
  • Why it matters:
    Prevents misclassification and enforces consistency.

​
7. Add Critical Analysis Instructions

  • What does it do?
    Numbered guidelines on transcript reading, stage determination, priority rules, and callback handling.
  • Why it matters:
    Helps users correctly apply the template and avoid common mistakes.

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8. Show Output Format Example (Optional)

  • What does it do?
    Provide a sample JSON response matching the field definitions.
  • Why it matters:
    Offers a quick reference for the expected output.

​
9. Insert the Transcript Placeholder

  • What does it do?
    End with a "## Transcription" header where the actual call log goes.
  • Why it matters:
    Clearly demarcates where to paste the raw data.

​
Tips

  • Copy the template and fill in the {{placeholders}} with your specific details.
  • Use simple, clear language when defining the call purpose and rules.
  • Don’t remove or rename any keys in the JSON snippet, they must match exactly.

​
Example Prompt Template

## Role

You are a skilled Call Center Operations Analyst specializing in {{Industry}} 
operations. You will be given call logs that contain detailed conversation 
transcripts between an Agent and a User. The call transcripts could be in 
{SUPPORTED_LANGUAGES} or mixed language.

## IMPORTANT

Provide your response strictly in **JSON format** following the specifications 
below. Do not introduce any additional fields or custom stage codes beyond those 
defined.

## Task 
Read the entire conversation transcript carefully and extract the required 
information according to the rules. Deliver a structured JSON response containing 
only the specified keys.

### Context Understanding

- **Call Purpose**: {{Call Purpose}}

- **Participant Roles**: Agent and User

### Business Context

- **Industry**: {{Industry}}

- **Use Case**: {{Use Case}}

- **Business Rules (Optional)**:

- 1. {{Rule 1}}

- 2. {{Rule 2}}

### Language Processing Guidelines

- **Primary Language**: {{Primary language}}

- **Secondary Languages (Optional)**: {{Secondary language (if applicable)}}

## Specifics

### Field Definitions

```json

{

"STAGE_CODE": ""

}

```

### Allowed Values & Definitions

#### STAGE\\\_CODE Values:

```json

[

{
"code": "ESCALATED_TO_AGENT",
"description": "Transferred to human agent for complex issues",
"criteria": "User requests escalation or dispute is detected."
},

{
"code": "AGREES_FOR_CALLBACK",
"description": "User agrees to a callback",
"criteria": "User explicitly agrees to be called back."
},

{
"code": "DISAGREES_FOR_CALLBACK",
"description": "User declines a callback",
"criteria": "User explicitly declines being called back."
},

{
"code": "BUSY",
"description": "User indicates they are busy",
"criteria": "User says they cannot talk now."
},

{
"code": "FAQ_HANDLED",
"description": "User question answered without escalation",
"criteria": "User asks a routine question and receives answer."
},

{
"code": "NO_INPUT",
"description": "No user response after prompt",
"criteria": "Silence or no intelligible input."
},

{
"code": "INVALID_INPUT",
"description": "Unrecognized or unclear response",
"criteria": "User input is garbled or irrelevant."
},

{
"code": "WRONG_NUMBER",
"description": "Wrong number reached",
"criteria": "User indicates wrong number."
},

{
"code": "DND",
"description": "Do-not-disturb request",
"criteria": "User requests not to be contacted again."
}

]

```


## Critical Analysis Instructions

1. Read the **ENTIRE transcript** before extracting. Don't jump to conclusions

2. **Look for explicit user responses** - Don't assume agreement from silence

## Important Guidelines

### Data Extraction Rules

- **Key Restriction**: Extract only the keys specified in the field definitions. 
	Do not add any additional keys or fields to the output.

- **Output Compliance**: Follow the exact JSON format specified. The output must 
	contain only the fields defined in the field definitions section.


## Output Format

Provide response in JSON format.

### Standard Response Structure - json

```

{
  "STAGE_CODE": "{EXTRACTED_VALUE}"
}

```

## Transcription

\<transcription\>