Sourcing object creation from natural language inputs

A system comprising:

• at least one data processor;
• and
• memory storing instructions which, when executed by the at least one data processor, result in operations comprising:
• receiving user-generated input comprising a sequence of words associated with initiation of a computer-implemented event;
• parsing the user-generated input using at least one pre-trained language model that classifies each word to one of a plurality of pre-defined classes, a first of the pre-defined classes being unknown and a second of the pre-defined classes being event type;
• determining, by a machine learning model using the parsed user-generated input, a suggested template comprising a plurality of fields for initiating the event, the machine learning model being different than the pre-trained language model, wherein the words classified as being unknown are ignored by the machine learning model;
• and
• providing the suggested template for presentation.

A non-transitory computer program product storing instructions which, when executed by at least one computing device, result in operations comprising:

• receiving user-generated input comprising a sequence of words associated with initiation of a computer-implemented event;
• parsing the user-generated input using at least one pre-trained language model that classifies each word to one of a plurality of pre-defined classes, a first of the pre-defined classes being unknown and a second of the pre-defined classes being event type;
• determining, by a machine learning model using the parsed user-generated input, a suggested template comprising a plurality of fields for initiating the event, the machine learning model being different than the pre-trained language model, wherein the words classified as being unknown are ignored by the machine learning model;
• and
• providing the suggested template for presentation.