1. A method for using human perception in training a language understanding model on a computing device, comprising: accessing, on the computing device, tagged items that are used by the language understanding model; creating a first query using the tagged items; obtaining, from a knowledge source in communication with the computing device, a first result for the first query; obtaining, by the computing device, a first human perception rating for the first result; after obtaining the first human perception rating, automatically modifying at least one of the tagged items in the first query, wherein the modifying includes changing the value of the at least one of the tagged items; in response to the modification, creating a second query using the at least one of the modified tagged items; obtaining, from the knowledge source a second result for the second query; obtaining, by the computing device, a second human perception rating for the second result, wherein obtaining the human perception rating for the first result and the second result comprises displaying a human perception rating user interface that is configured to receive a human perception rating for a respective result; determining one or more values corresponding to a relative importance of each of the tagged items in the first query and the second query using the first human perception rating and the second human perception rating; and providing the one or more values as input to a language understanding model to train the language understanding model to determine the relative importance of each of the tagged items as determined from the human perception rating.