1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain audio data regarding an utterance of a user, wherein the utterance comprises a new search query to search a catalog; generate a transcription of at least a portion of the utterance using the audio data and an automatic speech recognition module, wherein the transcription comprises a sequence of tokens corresponding to at least a portion of the new search query; identify a first subset of the sequence of tokens as a reference to an entity in the transcription based at least partly on a first frequency with which the first subset occurs in a plurality of previously generated transcriptions, wherein individual transcriptions of the plurality of previously generated transcriptions comprise search queries; identify a second subset of the sequence of tokens as a reference to an attribute of the entity in the transcription based at least partly on a second frequency with which the second subset occurs with the first subset in the plurality of previously generated transcriptions, wherein the second subset occurring with the first subset comprises the second subset and first subset both occurring in a same transcription of the plurality of previously generated transcriptions; generate search terms using the reference to the entity and the reference to the attribute, wherein the search terms include the first subset and second subset, and wherein the search terms exclude a third subset of the sequence of tokens; and generate search results responsive to the search query by identifying an item in the catalog using the search terms, wherein the catalog indicates the item comprises an instance of the entity having the attribute.
1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain audio data regarding an utterance of a user, wherein the utterance comprises a new search query to search a catalog; generate a transcription of at least a portion of the utterance using the audio data and an automatic speech recognition module, wherein the transcription comprises a sequence of tokens corresponding to at least a portion of the new search query; identify a first subset of the sequence of tokens as a reference to an entity in the transcription based at least partly on a first frequency with which the first subset occurs in a plurality of previously generated transcriptions, wherein individual transcriptions of the plurality of previously generated transcriptions comprise search queries; identify a second subset of the sequence of tokens as a reference to an attribute of the entity in the transcription based at least partly on a second frequency with which the second subset occurs with the first subset in the plurality of previously generated transcriptions, wherein the second subset occurring with the first subset comprises the second subset and first subset both occurring in a same transcription of the plurality of previously generated transcriptions; generate search terms using the reference to the entity and the reference to the attribute, wherein the search terms include the first subset and second subset, and wherein the search terms exclude a third subset of the sequence of tokens; and generate search results responsive to the search query by identifying an item in the catalog using the search terms, wherein the catalog indicates the item comprises an instance of the entity having the attribute. 2. The system of claim 1 , wherein the one or more processors are further programmed by the executable instructions to generate a structure prediction model using weakly supervised training data, wherein the structure prediction model comprises a conditional random field model, a hidden Markov model, or a maximum entropy Markov model.