> ## Documentation Index
> Fetch the complete documentation index at: https://docs-classic.cognigy.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Inheritance Mechanism

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`.

> [accordion] Input Object
>
> ```json theme={null}
> {
>   "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.

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

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


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