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Here is an example of what I mean...
Attachment "sample Table.png" shows a typical example of tabular data set of data in a table that some clients want to be able to extract. In this case, these are analysis results of ground soil for a proposed golf course. The client wants to extract the data from each row as 4 pieces of data, with the data in each row related.
The way we do this now is to write parsing rules on the text file derived from that pdf. Attachment "data from sample table in CA Studio with correct annotations.pdf" shows how this looks in CA Studio after the rules have been successfully built. Each pink highlighted row is essentially a set of 4 measurements all related to the first column. The yellow box shows the main annotation (the covered text), with the various features (in this case the features are the related measurements).
So we have been successful here, but it took a few hours to design the rules and a couple of days to build them, test them, refine them and test them again. If we could do this mapping and extraction in SDU, we could have the training done in minutes. In addition, it is likely SDU will be more accurate, as the rules apporahc asumes all tables are rendered the same way in the text file after the OCR. This is not always the case with pdf documents.