Not getting list(enumerated) || Multi select list not showing headline even though mentioned

Hi,
I am not getting list instead getting buttons / quick replies

Also, can you please let me know how can i loop through the values obtained from multi-select entity so that each loop will have another dialog task to call .Is it possible in kore.ai?

Please try to reply ASAP.

@harshit.kumar2
Which entity are you haing an issue with? The string or the list of value one?
Different templates have different ways of rendering.

Example:
Button template


image

In a string entity, for the multi-select template mentioned in

image

When you select multiple values, provided you used this template for String entity, it will store it as
image
It is sometimes wise to use do not auto correct if your use case has some unconventional display titles or values.
image

Now for your question on how you can process the values, you can do something like
image
But only one transition will work at a time. If you want to transition to another ‘dialog’, and make a setting like


the bot flow will come down to that point. You can have a following node to check for further conditions or values selected in your entity. But no parallel execution of dialogs may be expected. One transition at a time will be executed.

@harshit.kumar2
As @swagata.sengupta mentioned, the type of entity is important.

I’d like to add a couple of extra general points.

  • The type of entity governs the type of data to look for and how much training you have to do. An LoV entity’s training maps something the user might say (the synonym) to an internal value. A string entity has no training, it accepts anything.

    (Because of this greediness then generally avoid the string if you are looking for specific signals in the user’s utterance.)

  • It is generally recommended to be as flexible as possible in LoV synonyms, the user can say anything and therefore the bot needs to be able to select a choice on the basis on anything that might be distinct.

  • Button templates are merely a shorthand way of typing in the text message box. There is no connection between a button and anything else. Indeed a payload text of a button could easily trigger something completely different if the training misaligns.

    For example, I often see buttons with very precise and specific payloads. But this just appears to the NLU engine as ordinary text and it undergoes the same NLP pipeline processing as every other utterance. This means that tokenization and corrections can tweak the utterance so that some LoV synonym become non-matching. In reality the button payload only needs to send something unique for that choice.

  • Remember the user can always type something, they do not have to click a button. The LoV synonym training should reflect that possibility. The user is unlikely to type something formal and exact and will say something short and unique.