HTML SEC Filings Parser
Wanted to ask what the best way to approach this task would be. Essentially, I want to convert SEC filings (ex.AAPL 10k), which are large HTML files, into a hierarchical JSON format.The use case is to make it easier to read the filing by converting the following html:Image 5-13-23 at 7.10 PM1686×418 60.2 KBInto a JSON like the following structure (but HTML rather than text):Part 1Item 1. BusinessCompany BackgroundThe Company designs, manufactures, …ProductsWould there be a way to essentially loop through every html element, and then compare it with the previous in a comparison function that would decide where to add the element in the structure? This function can be pre trained with data from manually doing this process.Was curious if this is a feasible solution, creating the training set is obviously feasible, but is it cost effective it run this over the few thousand html elements in a filing? Are there any limits with the size of each html element? Also, can the text classifier HF model classify HTML as well? Finally, is there a better way to go about this?Thanks!