Adrien Ball

Hi @satnam2012 , The sample dataset which is mentioned in the tutorial and that you used is very small and its purpose is more to describe the data format and...

Hey @samarth12 , Can you elaborate a bit ? The dataset is just a JSON file, so you can add new intents by adding new key/value pairs inside the `"intents"`...

Hey @samarth12 , That is a reasonable use case indeed. The Snips NLU library will not handle this logic for you though, so, as you said, you will have to...

From my understanding of what you are trying to achieve, that's the user who should provide the labelling (both intent and slots) of new inputs that are not recognized. Only...

@samarth12 > Okay so the user just provides the right intent (which they think is right) for the new input sentence, the entity and slot should be automatically identified and...

Hi @ffos , I tried on my side with the latest version of snips-nlu (0.20.1) and it works as expected, so I suggest you upgrade the lib on your side....

Hi @syl22-00 , You can use [synonyms](https://snips-nlu.readthedocs.io/en/latest/data_model.html#entity-values-synonyms) and map different values in various languages to the same reference value (LANDLINE in your case). In your example, that could translate like...

Indeed, the reference value will be considered as a valid entity value. The namespacing solution that you mentioned is a valid workaround. There is a feature that we discussed recently...

Hey @joffreyvillard , Thanks for the feedback, it is indeed a bug. We'll have a look at it and will keep you updated here. Best, Adrien

> Intent 1 has 8 variable entities each with thousands some millions of possible permutations. It's likely that what takes most time in the processing is just the lookup of...