12. The non-transitory storage medium of claim 11 , further comprising: instructions executable by the processor to create the data profiler by using the annotated corpus; and instructions executable by the processor to recognize numerical characteristics comprising an average length of the extracted information.
11. A non-transitory computer readable storage medium comprising a plurality of instructions executable by a processor, the instructions comprising: instructions executable by the processor to apportion the document into major sections by accessing the document and recognizing a hierarchical structure of the document; instructions executable by the processor to divide the document into the major sections according to the hierarchical structure; instructions executable by the processor to access a machine learning model including a plurality of classifiers configured to classify portions of the document, each of the plurality of classifiers for a respective level of the hierarchical structure; instructions executable by the processor to classify each of the major sections of the document by using a first classifier included in the plurality of classifiers, and map the major sections to the key elements; instructions executable by the processor to search, with the processor, one major section that is mapped to one key element, and identify sub-sections within the one major section, the sub-sections including granular level pieces of information comprising sub-granular clause types; instructions executable by the processor to select a second classifier from the plurality of classifiers according to features of the one major section, wherein the features achieve a maximum confidence score by the second classifier, wherein the maximum confidence score indicates that the sub-sections associate with at least one of the key elements; instructions executable by the processor to classify, with the processor, each of the granular level pieces of information using the second classifier selected for the one major section, and map each of the sub-sections to at least one of the key elements; instructions executable by the processor to extract granular level pieces of information corresponding to the sub-granular clause types from the identified sub-sections by using sequence modelers and linguistic characteristics provided by a data profiler, the data profiler configured to recognize linguistics characteristics of the extracted information, wherein the linguistics characteristics comprise predicates, structures, neighboring characters, and types of data that induce regular expressions of the extracted information, wherein the sequence modelers are previously trained based on an annotated corpus; instructions executable by the processor to generate the hierarchical semantic map of the document by using the extracted information according to the hierarchical structure, and store the extracted information and the hierarchical semantic map in a database; and instructions executable by the processor to present in a user interface in a user display device drop down selections of the key elements of the document, and in response to a selection of one of the key elements, display the extracted information associated with the selected key element.