Natural language processing of declarative statements

A method comprising:

• receiving first input data representing a first natural language declarative statement;
• determining that the first input data corresponds to a declarative intent;
• determining, based at least in part on the first input data corresponding to the declarative intent, first data representing a first state described by at least a portion of the first input data;
• generating, by a first machine learning model, second data based at least in part on the first data, wherein the second data represents a predicted action for the first natural language declarative statement;
• generating output data representing a request for clarification based at least in part on the predicted action;
• receiving second input data representing a response to the request for clarification;
• determining an action intended to be taken in response to the first input data based at least in part on the second input data and the first input data;
• storing the first data representing the first state in association with third data representing the action in a first data structure;
• receiving third input data representing a second natural language declarative statement different from the first natural language declarative statement;
• determining that the third input data corresponds to the declarative intent;
• determining fourth data representing a second state described by at least a portion of the second natural language declarative statement;
• determining that the second state corresponds to the first state;
• receiving, from the first data structure, the third data representing the action;
• and
• generating a natural language prompt as output data, the natural language prompt representing a prompt for executing the action.

A system comprising:

• at least one processor;
• and
• at least one non-transitory computer-readable memory storing instructions that, when executed by the at least one processor, are effective to program the at least one processor to:
• receive first input data representing a first natural language declarative statement;
• determine that the first input data corresponds to a declarative intent;
• determine, based at least in part on the first input data corresponding to the declarative intent, first data representing a first state described by at least a portion of the first input data;
• generate, by a first machine learning model, second data based at least in part on the first data, wherein the second data represents a predicted action for the first natural language declarative statement;
• generate output data representing a request for clarification based at least in part on the predicted action;
• receive second input data representing a response to the request for clarification;
• determine an action intended to be taken in response to the first input data based at least in part on the second input data and the first input data;
• store the first data representing the first state in association with third data representing the action in a first data structure;
• receive third input data representing a second natural language declarative statement different from the first natural language declarative statement;
• determine that the third input data corresponds to the declarative intent;
• determine fourth data representing a second state described by at least a portion of the second natural language declarative statement;
• determine that the second state corresponds to the first state;
• receive, from the first data structure, the third data representing the action;
• and
• generate a natural language prompt as output data, the natural language prompt representing a prompt for executing the action.