Abstract: Systems and processes for processing natural language input are described. An example process for processing natural language input includes receiving a natural language input and determining a domain corresponding to the natural language input. The example process further includes, in accordance with determining the domain corresponding to the natural language input, determining, based on the natural language input, a first value for a first property of the domain and determining, based on a named entity model and the natural language input, a second value for the first property of the domain, where the second value defines a parameter for a task corresponding to the natural language input. The example process further includes performing the task based on the parameter and providing a result based on the performed task.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. An example process receives natural language input and determines a first and a second parsing result for the natural language input. The first and the second parsing results include respective mappings of one or more properties of a domain corresponding to the natural language input to one or more words of the natural language input. The process determines whether the second parsing result corresponds to a data item in a knowledge base, and in accordance with determining that the second parsing result corresponds to the data item in the knowledge base, the process ranks the second parsing result higher than the first parsing result. Based on the ranking, the process generates a task flow using the second parsing result and executes the task flow to provide an output based on the data item.

Abstract: Systems and processes for processing natural language input are described. An example process for processing natural language input includes receiving a natural language input and determining a domain corresponding to the natural language input. The example process further includes, in accordance with determining the domain corresponding to the natural language input, determining, based on the natural language input, a first value for a first property of the domain and determining, based on a named entity model and the natural language input, a second value for the first property of the domain, where the second value defines a parameter for a task corresponding to the natural language input. The example process further includes performing the task based on the parameter and providing a result based on the performed task.

Abstract: Systems and processes for natural language processing using vocabularies with compressed serialized tries are described in the present disclosure. In one example process, natural language input is received. The natural language input is parsed, using a vocabulary, to determine a corresponding user intent. The parsing includes using a data structure of the vocabulary to map a first word of the natural language input to first semantic information and a second word of the natural language input to second semantic information. The data structure includes pointers that map to a same semantic data object of the vocabulary. The first semantic information and the second semantic information are determined using the same semantic data object. The user intent is determined based on the first semantic information and the second semantic information. Performance of a task corresponding to the determined user intent is initiated.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. An example process receives natural language input and determines a first and a second parsing result for the natural language input. The first and the second parsing results include respective mappings of one or more properties of a domain corresponding to the natural language input to one or more words of the natural language input. The process determines whether the second parsing result corresponds to a data item in a knowledge base, and in accordance with determining that the second parsing result corresponds to the data item in the knowledge base, the process ranks the second parsing result higher than the first parsing result. Based on the ranking, the process generates a task flow using the second parsing result and executes the task flow to provide an output based on the data item.

Abstract: Systems and processes for natural language processing using vocabularies with compressed serialized tries are described in the present disclosure. In one example process, natural language input is received. The natural language input is parsed, using a vocabulary, to determine a corresponding user intent. The parsing includes using a data structure of the vocabulary to map a first word of the natural language input to first semantic information and a second word of the natural language input to second semantic information. The data structure includes pointers that map to a same semantic data object of the vocabulary. The first semantic information and the second semantic information are determined using the same semantic data object. The user intent is determined based on the first semantic information and the second semantic information. Performance of a task corresponding to the determined user intent is initiated.