Adaptable and explainable application modernization disposition

A computer program product comprising one or more computer readable storage media having program instructions collectively stored on the one or more computer readable storage media, the program instructions executable to:

• receive a natural language problem statement corresponding to application modernization needs of a user, the natural language problem statement including at least one technical entity, business constraint and disposition information;
• provide extracted structured information by extracting information from the natural language problem statement using a neural word segmentation method;
• generate standardized technical entities, standardized business entities, and standardized dispositions by inputting the extracted structured information to at least one machine learning model;
• and;
• and
• generate at least one recommended disposition of at least one technical entity to a second technical entity based at least on a business constraint corresponding to the natural language problem statement using the standardized technical entities, standardized business entities, and standardized dispositions, the at least one recommended disposition corresponding to one or more possible target environments along with explanation generated based on the business constraints and mentions of technical entities present in the natural language problem statement.

A system comprising:

• a processor set, one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable to:
• receive a natural language problem statement corresponding to application modernization needs of a user, the natural language problem statement including at least one technical entity, and business constraint—;
• provide extracted structured information by extracting information from the natural language problem statement using a neural word segmentation method;
• generate standardized technical entities, and standardized business entities, by inputting the extracted structured information to at least one machine learning model;
• and
• retrieve structured knowledge corresponding to the natural language problem statement from the at least one knowledge database by querying the at least one knowledge database with the extracted structured information;
• and
• generate at least one recommended disposition of at least one technical entity to a second technical entity based at least on the structured knowledge corresponding to the natural language problem statement from the at least one knowledge database, a business constraint corresponding to the natural language problem statement using the standardized technical entities and standardized business entities.