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Hey, I don't disagree completely, but it's hard to decide how to answer this kind of question. In short, we are trying to figure out a way to identify a class of stories, based on a single example and on the observation that it has some common elements with other stories we happen to know. The difficulty is in the fact that there are many such "common elements" we might decide to focus on, or ignore, and each set thereof can substantially change the stories we identify as "similar to" our single example, the Sorcerer's Apprentice.

So, for instance, we could broaden the description to include any story of losing control over one's, or someone else's creation- therefore "covering" stories as diverse as the legend of Icarus, Mary Shelley's Frankenstein and of course the stories of Sañjīva, Phaethon and Abhimanyu. We might focus on the moral dimension of the story, which draws more stark parallels to the story of Sañjīva but also King Midas. We might choose to stay as close as possible to the them of "magical automation" in which case, we 'll only include stories like the original tale in Lucian's work, the Sorcerer's Apprentice many versions, and the story of the Golem of Prague, all of which include something like the Paperclip Optimiser AGI. And so on.

I guess now I make it sound like navel-gazing, but this is actually a legitimate problem with very real applications. For example imagine trying to organise the stories I list above, plus who knows how many others, in appropriate categories _automatically_ based on their narrative characteristics. It's probably impossible to do that sort of thing with current NLP techniques, or at least to do it in a way that would satisfy a majority of human classifiers. Not to mention, the problem of choosing what part of a _story_ (as opposed to what portions of _text_) to attend to when categorising a document is also not something we can currently solve convincingly.

So it's an ill-defined, hard, classification problem. Perfect subject for a machine learning paper :)

Interesting take on the topic, thanks! I think part of the problem is trying to categories stories on some kind of taxonomy rather than seeing them as bundles of attributes.

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