Add Training data
Add or modify user utterances (training phrases) to an intent in your NLX workspace
Last updated
Add or modify user utterances (training phrases) to an intent in your NLX workspace
Last updated
Training phrases comprise the samples of what users might say to a bot to trigger a task that the intent satisfies. Your chosen AI model (NLP or LLM) becomes trained on these samples to better match a user's utterance to the appropriate intent.
For an OrderRoomService intent, training phrases such as 'Order something to eat,’ 'I want room service’ or even ‘I’m hungry’ can let an AI model know the user's intent matches OrderRoomService.
The minimum number of training phrases recommended is 5, but providing a strong variety of ways in which users may construct their request results in better performance.
NLPs and LLMs also help address variations, misspellings, and other unexpected conversational elements.
If your intent flow will be triggered automatically from a application's Default behaviors OR will only be accessed via a Redirect from other intent flows, you may select the Skip training option under the intent's Settings tab.
Click Training phrases tab of intent > Select + Add new training phrase
Enter SHIFT + RETURN/ENTER to bring up another field. Min. of 5 phrases is recommended
Make changes by typing into the phrase field. Remove a phrase by clicking the remove icon
Click Save
Leverage slots in training phrases by attaching them to your intent first.
Saved changes do not take effect with bots that are already deployed. To experience changes to training phrases with bots in production, create a new build and redeploy.
Predicting what users might say to in order for the right intent to be triggered is a challenging task. Users may say a lot or say very little when explaining what they want to accomplish.
Take a deep dive on organizing intents and developing training data with our favorite best practices.
To start, keep training phrases short. NLPs are able to identify filler words , misspellings, uncapitalized words, and politeness from user utterances, so no need to worry about creating multiple variations to account for them:
✔️place an order for room service
✔️would like to order room service
❌Can I please place an order for room service for my family this evening?
Slots help you capture dynamic info that determine the parameters to a user's request or choice. Small/medium/large or yes/no are common examples. Introducing slots into training phrases can reduce creating different intents that would have similar training phrases or prevent the need for drafting multiple variations of a single training phrase:
✔️would like a {size} pizza
✔️look up {accounttype} account balance
❌look up savings account balance; look up checking account balance, etc.
Want to enhance your Training phrases pool in record time? Use the Generate using AI feature:
Create a sample set of at least 5 training phrases to allow the AI to learn and expand on phrases with similar characteristics
Click Save
Select Generate using AI to create phrases in batches of five
Modify before or after adding the phrases to your pool
Repeat the process as needed (recommended pool size: 15-30)
If you have slots you'd like GenAI to reference in its training phrases, include them in your sample set first.
Upload: Allows for a .json, .csv, or .txt file to be ingested with training phrase data
Download: Prompts existing training phrase data to be downloaded to a .csv or .json file for editing. Tap the .csv/.json button beside the Download link to swap formats
