This article “Why a user slot is a logical solution” reports
Using custom slot types for grammar, as described above, usually satisfies this desire and improves the accuracy of NLP training. If you still want everything, you can create a custom slot called "CatchAll" and the corresponding intention and statement: CatchAllIntent {CatchAll}. If you use the same training data that you would use for LITERAL, you will get the same results. People generally find that adding slightly more scenario-specific training data improves accuracy.
If you still do not get results, try setting the CatchAll values ​​to about twenty-2 word random phrases (from the random word generator - be really random). When the user says something that matches your other statements, these intentions will be sent. When it does not match any of them, it enters the CatchAll slot. If you go this route, you will lose accuracy because you are not fully using Alexas NLP, so you will need to test hard.
And by the way, the literal slot returned in January 2017, but it is not recommended.
Based on developer feedback, we will not remove the LITERAL slot type, and you can continue to transfer skills that include its functionality.
This is a link to LITERAL Dictionary Type Link
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