Abstract: The technology described herein receives a natural-language sequence of words comprising multiple entities. The technology then identifies a plurality of entities in the natural-language sequence. The technology generates a masked natural-language sequence by masking a first entity in the natural-language sequence. The technology retrieves, from a knowledge base, information related to a second entity in the plurality of entities. The technology then trains a natural-language model to respond to a query. The training uses a first representation of the masked natural-language sequence, a second representation of the information, and the first entity.

Abstract: A server computer system comprises a communications module; a processor coupled with the communications module; and a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to provide, via the communications module and to a computing device, a graphical user interface that includes interface elements that represent a series of activation steps and identifies one of the activation steps as a current activation step, the representation of the current activation step selectable to communicate with a dedicated server computer system performing the current activation step to display information related to the current activation step; determine that the current activation step has been completed; and update the graphical user interface to disable the representation of the current activation step as selectable; identify another one of the activation steps as a next current activation step; and enable the representation of the next

Abstract: The technology described herein receives a natural-language sequence of words comprising multiple entities. The technology then identifies a plurality of entities in the natural-language sequence. The technology generates a masked natural-language sequence by masking a first entity in the natural-language sequence. The technology retrieves, from a knowledge base, information related to a second entity in the plurality of entities. The technology then trains a natural-language model to respond to a query. The training uses a first representation of the masked natural-language sequence, a second representation of the information, and the first entity.

Abstract: A server computer system comprises a communications module; a processor coupled with the communications module; and a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to provide, via the communications module and to a computing device, a graphical user interface that includes interface elements that represent a series of activation steps and identifies one of the activation steps as a current activation step, the representation of the current activation step selectable to communicate with a dedicated server computer system performing the current activation step to display information related to the current activation step; determine that the current activation step has been completed; and update the graphical user interface to disable the representation of the current activation step as selectable; identify another one of the activation steps as a next current activation step; and enable the representation of the next