
Description
A Question Node is used to ask a question that requests specific information from the user. When the Node is triggered, the Entrypoint shifts to this Node so that the conversation continues only after the user answers. Also, a new Input object is generated. When a user input is received, it’s scored based on natural language understanding (NLU). If an attached Flow has an Intent that scores higher than Intents in the current Flow, the attached Flow is executed. The Intent scoring occurs before validation of the Question Node is completed. After the AI Agent asks a question and the user answers, the answer is validated according to its type. If it passes, the answer is valid and stored, and the conversation continues.Question Nodes and Intent Execution
Question Nodes and Intent Execution
Parameters
Question Types
Question Types
Channels and Output Types
Channels and Output Types
LLM Entity Extraction Options
LLM Entity Extraction Options
Advanced
Advanced
Reprompt Options
Reprompt Options
true.Reprompt Methods- Simple Text
- Channel Message
- LLM Prompt
- Execute Flow and Return
Result Storage
Result Storage
Escalation - Intents
Escalation - Intents
Escalation Action: Output Message
Escalation Action: Output Message
Escalation Action: Skip Question
Escalation Action: Skip Question
Escalation Action: Go To Node
Escalation Action: Go To Node
Escalation Action: Execute Flow and Return
Escalation Action: Execute Flow and Return
Escalation Action: Handover to Human Agent
Escalation Action: Handover to Human Agent
Escalation - Wrong Answers
Escalation - Wrong Answers
Escalation Action: Output Message
Escalation Action: Output Message
Escalation Action: Skip Question
Escalation Action: Skip Question
Escalation Action: Go To Node
Escalation Action: Go To Node
Escalation Action: Execute Flow and Return
Escalation Action: Execute Flow and Return
Escalation Action: Handover to Human Agent
Escalation Action: Handover to Human Agent
Reconfirmation Options
Reconfirmation Options
ANSWER, which is replaced with a short form version of the given answer (for example, “3 EUR” in a Money question). The short form answer is taken from input.activeQuestion.tentativeShortFormAnswer;Reconfirmation Questions can have a specific re-prompt set, which is output before the question if the answer to the question is not of yes/no style.Advanced
Advanced
true. For example, if you enter input.slots.EMAIL[0].endsWith("cognigy.com") in this parameter for an email question type, only email addresses ending with cognigy.com pass the validation.Result LocationBy default, when the Question Node recognizes the user’s answer, the Node stores the answer under result in the Input object. The Result Location parameter lets you replace the recognized answer with a value from another JSON path, for example, input.bookingReference. The Result Location parameter only works if the user’s answer is recognized and if the path you set is valid. If the path is invalid, the original answer isn’t recognized, and the user is reprompted.1 this means that the question has to be answered on the next user input. If a user input comes back to the question at a later stage, it is treated as if the question was hit for the first time and the question is asked.Handover to Human Agent
Handover to Human Agent
AI-Enhanced Output
AI-Enhanced Output
Answer Preprocessing
Answer Preprocessing
text type question or when asking for a part number using a slot question.In addition to the Text Cleaner functions, users have the option to rerun NLU after the cleaning process. This approach allows for tasks such as re-detecting slots or properly filling any remaining slots.Exclude from Transcript
Excludes the Node output from the conversation transcript. The output remains visible to the end user but isn’t stored in thetranscript object or shared with the LLM provider.
You can use this parameter to:
- Hide sensitive or irrelevant data, such as legal disclaimers, so the model doesn’t see or repeat them.
- Prevent the model from copying patterns (called in-context learning) you didn’t want it to learn.
Example
Example
Question Information in Input
When a question is active, meaning that the AI Agent is waiting for the answer, information regarding the question is added to the Input object.Slot Fillers
Slot Fillers
1: Note that not all LLM models support streaming.