10. The computer-implemented method of claim 1 , wherein headers provide a first context for row labels and column labels, and row labels and column labels provide a second context for content cells, and wherein the format of the first language section is further based on the first and second context.
1. A computer implemented method of generating a language section from tabular data in an electronic document, the method comprising: identifying, by a processor, in a first tabular portion of the electronic document, a set of categories used to organize tabular data, wherein the set of categories includes headers, labels, and content cells; determining that the set of categories includes a content cell that contains an image by detecting an image file extension associated with the content cell; identifying, by the processor and using heuristics and machine learning, contextual relationships between the tabular data, wherein the contextual relationships are created by the set of categories and the identifying is based in part on the position of each category in the set of categories in the first tabular portion and based on the tabular data that each category modifies; identifying, by the processor, a content characteristic for each of the set of categories in the first tabular portion, wherein identifying a content characteristic for the content cell that contains an image comprises utilizing optical character recognition techniques; and generating, by the processor, a first language section from at least two distinct categories of the set of categories, wherein a format of the first language section is based on the content characteristic and contextual relationships for each of the at least two distinct categories of the set of categories and is governed by a formatting table, wherein the formatting table comprises example combinations of content characteristics for example categories of an example tabular portion and formatting rules for generating example language sections from those example combinations.