How to get one word answers into entities

[lgrinberg (Leo@Vocinity)]

If your entities will come from a fixed set of values, then use lookup tables, as Juste has recommended. If your entities can have totally random values and they will overlap with other entities, then use the approach described here.

Providing conversation context to the NLU using microservices

Many thanks @lgrinberg for sharing your concept. Your example is related to word with different meaning (e. g. last name vs. city). This is a good example where context matters, but there are so much more situation where context is key. Also words, which are not ambiguous, can have a different meaning depending on the context. Let’s say we have a chatbot that talks about renting or buying real estate: Context: None / User message: “apartment” Since we have no context, we basically do not kn…