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I also had a look at structured Wikipedia databases like DBPedia but those only have the same structured I already have, they don't provide any structure in the Wiki text itself.Your IP address has been temporarily blocked due to a large number of HTTP requests. Ideally, there's be a library to solve this problem, but I haven't found one yet that is up to this job. Or, I could start with the rendered HTML output and parse that, but my worry is that it's just as fragile and complex to parse in a structured way.

Have a lot of work deleting unwanted elements as well as 'mimicing' I could continue my current path of semi-structured parsing where I'd.I'd like to avoid writing a 100 regular expressions to process all of this and see how I can parse this in a smarter way. And there are dozens of notations like this that have special meaning. Removing this entire block would break the sentence. Yet there are also blocks that I simply cannot remove, such as: That's fairly easy by filtering out ] blocks. For example, I'd like to remove all images. I can read these paragraphs, but I'd like to 'clean' them in a specific way, because ultimately I will have to display it in my app and it has no sense of Wiki markup. These are returned by the API in Wiki format or HTML format, I'm currently working with the Wiki format. However, I'm also trying to parse the text paragraphs.

I can detect that this page is a 'specie' page, and I can also parse the Taxobox (on the right) information into a structure.

I'm trying to parse specific Wikipedia content in a structured way.

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