This solution meets the goal. By creating a custom entity named "Age group" with items corresponding to each age range (e.g., "18-25"), and then listing every individual age within that range as a synonym (e.g., "18", "19", "20"...), the chatbot can directly map a user's numerical age input to the correct group. When a question node uses this entity in its "Identify" property, Power Virtual Agents will use the extensive synonym list to resolve the user's specific age to the appropriate age group item, thus fulfilling the requirement.

B. No: This is incorrect because the proposed method is functionally valid. While using condition nodes after capturing a number would be more efficient to build, this entity-based approach will successfully categorize the user's age into the defined groups.

1. Microsoft Learn | Power Virtual Agents - Create and use entities: This document explains the creation of custom entities

including closed-list entities. It details how to add items and synonyms. The proposed solution directly applies this concept: "Synonyms let you map multiple terms to a single item. For example

for the item 'hiking

' you could have 'trekking' and 'mountaineering' as synonyms." In the question's scenario

"18"

"19"

etc.

are treated as synonyms for the item "18-25". (See section: "Create a custom entity from a list").

2. Microsoft Learn | Power Virtual Agents - Ask a question: This documentation describes the components of a question node

including the "Identify" property. It states that you can select a custom entity to extract specific information from the user's response. The proposed solution correctly utilizes this feature to identify the "Age group" entity from the user's answer. (See section: "Entity and slot filling").