Unlabel automatically flagged entity

Question

When you create Intents and enter their sample utterances in LUIS, the parser will sometimes classify some words as being entities. This is a nice feature when it accurately identifies them, but sometimes it mislabels them.

For example, if you have an entity for statuses of a switch (on/off), constructed as a List with "true" and "false" being the values for which "on" and "off" are synonyms, respectively, then every time you use the words "on" or "off" (which have various meanings, uses and purposes) in an intent's sample utterances, they get labeled as that entity, often inaccurately.

The documentation (https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-add-example-utterances) states that List type entities cannot be removed from utterances. Is there any way to avoid simple words that may be used as synonyms in entities from being matched as entities?

Thanks!

Answer 1

I think the only way to do it is to remove those simple words as synonyms (on, off, etc.) from the List entity synonyms (clicking x next to the synonym). Per the message when you create a List entity, they behave differently than other entity types and are direct matching:

Unlike other entity types, additional values for list entities aren't discovered during training. This entity type is identified in utterances by the direct matching of utterance text to the defined values, rather than learning from context.

You could also use simple entities along with Phrase Lists to help boost the signal to those instances where on/off would be an entity that you would want to capture. Adequately supplied phrase lists to help identify those types of instances would be needed.