1. A method comprising: via computer processor hardware, performing operations of: parsing an utterance to identify syntactic relationships amongst words in the utterance; creating sets of words from the utterance based on the syntactic relationships; mapping each set of the sets of words to a respective candidate intent value to produce a list of candidate intent values for the utterance; ranking the candidate intent values in the list based on usage of the sets of words in previously received utterances; selecting, from the list, a candidate intent value as being representative of an intent of the utterance; detecting that the selected candidate intent value maps to multiple possible labels in a label listing, an entry in the label listing indicating that the selected candidate intent value maps to the multiple possible labels, the multiple possible labels including a majority label representing a first classification and a minority label representing a second classification; selecting the majority label; assigning the selected majority label to the utterance to indicate that the utterance falls into the first classification, the selected majority label representative of a dominant subject matter likely intended by the utterance.
1. A method comprising: via computer processor hardware, performing operations of: parsing an utterance to identify syntactic relationships amongst words in the utterance; creating sets of words from the utterance based on the syntactic relationships; mapping each set of the sets of words to a respective candidate intent value to produce a list of candidate intent values for the utterance; ranking the candidate intent values in the list based on usage of the sets of words in previously received utterances; selecting, from the list, a candidate intent value as being representative of an intent of the utterance; detecting that the selected candidate intent value maps to multiple possible labels in a label listing, an entry in the label listing indicating that the selected candidate intent value maps to the multiple possible labels, the multiple possible labels including a majority label representing a first classification and a minority label representing a second classification; selecting the majority label; assigning the selected majority label to the utterance to indicate that the utterance falls into the first classification, the selected majority label representative of a dominant subject matter likely intended by the utterance. 10. The method as in claim 1 further comprising: maintaining statistical information for the previously received utterances, the statistical information indicating a frequency of receiving utterances of different intent types; and updating the statistical information to reflect that the utterance was assigned the selected candidate intent value.