Abstract: The present disclosure involves systems, software, and computer implemented methods for creating line item information from tabular data. One example method includes receiving event data values at a system. Column headers of columns in the event data values are identified. At least one column header is not included in standard line item terms used by the system. Column values of the columns in the event data values are identified. The identified column headers and the identified column values are processed using one or more models to map each column to a standard line item term used by the system. The processing includes using context determination and content recognition to identify standard line item terms. An event is created in the system, including the creation of line items from the identified column value. Each line item includes standard line item terms mapped to the columns.

Abstract: User-generated input is received that includes a sequence of words associated with initiation of a computer-implemented event. Thereafter, such input is parsed using at least one natural language processing (NLP) model. This parsed input is then used by a machine learning model to determine a suggested template having a plurality of fields for initiating the event. The template can then be presented in a graphical user interface. Related apparatus, systems, techniques and articles are also described.

Abstract: The present disclosure involves systems, software, and computer implemented methods for creating line item information from tabular data. One example method includes receiving event data values at a system. Column headers of columns in the event data values are identified. At least one column header is not included in standard line item terms used by the system. Column values of the columns in the event data values are identified. The identified column headers and the identified column values are processed using one or more models to map each column to a standard line item term used by the system. The processing includes using context determination and content recognition to identify standard line item terms. An event is created in the system, including the creation of line items from the identified column value. Each line item includes standard line item terms mapped to the columns.

Abstract: The present disclosure involves systems, software, and computer implemented methods for creating line item information from tabular data. One example method includes receiving event data values at a system. Column headers of columns in the event data values are identified. At least one column header is not included in standard line item terms used by the system. Column values of the columns in the event data values are identified. The identified column headers and the identified column values are processed using one or more models to map each column to a standard line item term used by the system. The processing includes using context determination and content recognition to identify standard line item terms. An event is created in the system, including the creation of line items from the identified column value. Each line item includes standard line item terms mapped to the columns.

Abstract: User-generated input is received that includes a sequence of words associated with initiation of a computer-implemented event. Thereafter, such input is parsed using at least one natural language processing (NLP) model. This parsed input is then used by a machine learning model to determine a suggested template having a plurality of fields for initiating the event. The template can then be presented in a graphical user interface. Related apparatus, systems, techniques and articles are also described.

Abstract: User-generated input is received that includes a sequence of words associated with initiation of a computer-implemented event. Thereafter, such input is parsed using at least one natural language processing (NLP) model. This parsed input is then used by a machine learning model to determine a suggested template having a plurality of fields for initiating the event. The template can then be presented in a graphical user interface. Related apparatus, systems, techniques and articles are also described.

Abstract: The present disclosure involves systems, software, and computer implemented methods for creating line item information from tabular data. One example method includes receiving event data values at a system. Column headers of columns in the event data values are identified. At least one column header is not included in standard line item terms used by the system. Column values of the columns in the event data values are identified. The identified column headers and the identified column values are processed using one or more models to map each column to a standard line item term used by the system. The processing includes using context determination and content recognition to identify standard line item terms. An event is created in the system, including the creation of line items from the identified column value. Each line item includes standard line item terms mapped to the columns.

Abstract: User-generated input is received that includes a sequence of words associated with initiation of a computer-implemented event. Thereafter, such input is parsed using at least one natural language processing (NLP) model. This parsed input is then used by a machine learning model to determine a suggested template having a plurality of fields for initiating the event. The template can then be presented in a graphical user interface. Related apparatus, systems, techniques and articles are also described.