Let's return to the first style of identifying an entity that you care about. In the first approach, we showed you in Recognizing entities, we went to the intent examples, and highlighted the entity that we cared about in that example. We refer to this as the annotator approach to entity recognition. Annotators are a much more powerful way of identifying the entities. Rather than setting a rule, such as the word hot is a temperature entity, the annotator approach builds a machine learning algorithm that takes in the context of the surrounding words in the sentence. In doing so, it calculates the probability that hot is referring to a temperature. In a sentence such as The water is hot, it makes sense to recognize hot as being a temperature. But in another sentence, such as The market is hot, it should be taken to be the relative value people place on a particular product.
As your conversational agent gets more sophisticated, you will likely want to...