Automated electronic document creation through machine learning

A system for automated creation of an electronic document, comprising:

• one or more processors;
• and
• a memory storing instructions that, when executed by the one or more processors, cause the system to:
• provide, as inputs to a natural language processing machine learning model, contents of a source electronic document and a prompt that instructs the natural language processing machine learning model to extract a particular data item from the contents of the source electronic document;
• receive the particular data item from the natural language processing machine learning model in response to the inputs;
• perform a lexical search for the particular data item among a plurality of stored data items;
• determine a confidence score based on the lexical search;
• perform a semantic search for the particular data item among the plurality of stored data items based on the confidence score not exceeding a threshold;
• identify a stored data item of the plurality of stored data items that matches the particular data item based on the semantic search;
• automatically generate the electronic document by populating an electronic document template using the stored data item;
• receive feedback with respect to the electronic document via a user interface, wherein the natural language processing machine learning model or a rule related to the lexical search or the semantic search is modified based on the feedback to produce an updated natural language processing machine learning model or an updated rule;
• and
• automatically generate a subsequent electronic document based on the updated natural language processing machine learning model or the updated rule.

A non-transitory computer readable medium comprising instructions that, when executed by one or more processors of a computing system, cause the computing system to:

• provide, as inputs to a natural language processing machine learning model, contents of a source electronic document and a prompt that instructs the natural language processing machine learning model to extract a particular data item from the contents of the source electronic document;
• receive the particular data item from the natural language processing machine learning model in response to the inputs;
• perform a lexical search for the particular data item among a plurality of stored data items;
• determine a confidence score based on the lexical search;
• perform a semantic search for the particular data item among the plurality of stored data items based on the confidence score not exceeding a threshold;
• identify a stored data item of the plurality of stored data items that matches the particular data item based on the semantic search;
• and
• automatically generate the electronic document by populating an electronic document template using the stored data item;
• receive feedback with respect to the electronic document via a user interface, wherein the natural language processing machine learning model or a rule related to the lexical search or the semantic search is modified based on the feedback to produce an updated natural language processing machine learning model or an updated rule;
• and
• automatically generate a subsequent electronic document based on the updated natural language processing machine learning model or the updated rule.