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I have a large number of different XML documents with associated style sheets (SEC financial filings). Are there any natural language processing (or other) tools that I can use to try to automatically extract section headings?

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  • $\begingroup$ Are the section headings tags in the xml, or are you trying to derive them via natural language processing methods? $\endgroup$
    – Kyle.
    Commented Nov 13, 2015 at 19:39
  • $\begingroup$ There will inevitably be some kind of tags associated with the headings, but its not standard between documents. Here's one example (which happens to be html) sec.gov/Archives/edgar/data/320340/000143774915020747/… $\endgroup$ Commented Nov 13, 2015 at 19:54
  • $\begingroup$ NLP is not a tool to extract headings. Extract the text and use tags as features. And html is not the same as xml - it will be different tools for extraction. $\endgroup$
    – paparazzo
    Commented Nov 13, 2015 at 20:25

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It seems you are lucky and the section headings are XML-tagged. So you can use XSLT transformations or Python lxml.etree to get rid of them or to extract them.

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