LUIS.ai returns different intents for almost similar utterances

Question

I use LUIS as a Language Understanding Service for our Chat Bot built with Microsoft Bot Framework. And I observe the strange behavior:

1. I added a string "what is my deductible?" to the intent "Deductible".
2. A user sends "what is my deductible" string ---> LUIS returns the desired intent "Deductible". OK!
3. A user sends "what is my deductibl?" OR "what is my deductible" (misspelling in the first case, lack of a question mark in the second case) ---> LUIS returns some other intents (which are not related to deductible AT ALL). NOT OK!
4. Also, I don't see any utterances like those in "Review Endpoint Utterances" section so I could reassign the utterances to the desired intent. NOT OK AT ALL!

Any ideas how to fix it, how to improve the recognition for utterances with misspellings, lack of symbols and also - it's very important - with synonyms of the words?

Answer 1

To improve the utterances with misspellings, lack of symbols and other requirements, there is a need to add the templates of utterance using correct syntax.

misspellings

The below code is V2 prediction end point

{
  "query": "Book a flite to London?",
  "alteredQuery": "Book a flight to London?",
  "topScoringIntent": {
    "intent": "BookFlight",
    "score": 0.780123
  },
  "entities": []
}

The below code is V3 prediction end point

{
    "query": "Book a flite to London?",
    "prediction": {
        "normalizedQuery": "book a flight to london?",
        "topIntent": "BookFlight",
        "intents": {
            "BookFlight": {
                "score": 0.780123
            }
        },
        "entities": {},
    }
}

To perform the utterances perfect creation using valid syntaxes, Using the following resources.

https://blog.botframework.com/2018/06/07/improving-accuracy-in-luis-with-patterns/

https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-model-intent-pattern

https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-data-alteration?tabs=V3