## Documentation Index

Fetch the complete documentation index at: [/llms.txt](https://docs.cognigy.com/llms.txt)

Use this file to discover all available pages before exploring further.

The _Inheritance Mechanism_ feature lets parent Intents use example sentences from their child Intents. This mechanism helps the AI Agent better understand user inputs and determine the intended action.

### Key Benefits

- **Wider Scope for Parent Intents**. Parent Intents get a better trained NLU model by including examples from child Intents.
- **Clear Hierarchy**. You can see how Intents relate to each other and how they’re scored.

## Prerequisites

Before using the inheritance mechanism, make sure you have a multilevel Intent structure. For example, Level 1 parent Intents with Level 2 or Level 3 child Intents.

## How to Use

To activate the inheritance mechanism, follow these steps:

1. In the Flow editor, go to **NLU > Intents** and select the parent Intent you want to set up.
2. Activate the **Inherit Example Sentences from Child Intents** setting.
3. Save your changes and rebuild the model to apply them.

### Intent Hierarchy Matching

The parent Intent includes examples from its child Intents in its training data. When a user sends an input, during Intent matching, both parent and child Intents can score highly. The child Intent’s details are saved in the `input.intent` Input object, while the parent Intent’s details appear in `input.nlu.intentMapperResults.scores`. For a deeper understanding of the resolution process, you can trace the Intent path using `input.intentLevel` and `input.nlu.intentMapperResults.intentPath.

Input Object

```
{
  "input": {
    "intent": "Child Intent",
    "nlu": {
      "intentMapperResults": {
        "scores": [
          {
            "intent": "Child Intent",
            "score": 0.6833273843878324
          },
          {
            "intent": "Parent Intent",
            "score": 0.5099832885597476
          }
        ],
        "intentPath": [
          "Parent Intent",
          "Child Intent"
        ]
      }
    },
    "intentLevel": {
      "level1": "Parent Intent",
      "level2": "Child Intent",
      "level3": null
    }
  }
}
```

### Example

Consider the inheritance mechanism in a customer support AI Agent. The parent Intent (`Support`) inherits example sentences from its child Intents (`Technical Support` and `Billing Support`). This structure enables the AI Agent to handle general inquiries while accurately identifying specific Intents.

Intent Data

| **Level** | **Name** | **Intent Name** | **Example Sentences** | **Description** |
| --- | --- | --- | --- | --- |
| Level 1 | Parent | `Support` | `I need assistance`<br>`Can you help me?`<br>`I have an issue` | The high-level parent Intent recognizing broad customer queries. |
| Level 2 | Child | `Technical Support` | `My internet is down`<br>`I can't connect to the Wi-Fi`<br>`My computer is broken` | The child Intent under the `Support` parent for issues related to technology. |
| Level 2 | Child | `Billing Support` | `I need help with my invoice`<br>`I have a question about my bill`<br>`Can you explain this charge?` | The child Intent under the `Support` parent for issues related to billing. |

Result

| **User Input** | **Recognized Intent** |
| --- | --- |
| `I need assistance` | `Support` (Parent Intent) |
| `My internet is down` | `Technical Support` (Child Intent) |
| `I need help with my invoice` | `Billing Support` (Child Intent) |

## More Information

- [Overview](https://docs.cognigy.com/ai/platform-features/nlu/intents/overview)
- [Intent Mapping Priority](https://docs.cognigy.com/ai/platform-features/nlu/intents/intent-hierarchy/intent-mapping-priority)