[DevAccount]

Could you possibly automate the items that do have enough information and collect the ones which don't for later manual review?

[polyfractal]

I think this will be the solution I go with, but I'm a bit unsure how it would work in practice. I don't know how I would evaluate the accuracy of automated clustering?

Another solution might be a sort of automated-manual hybrid: e.g. identify common words/phrases in a particular category manually, write a script to find all items that have those, add to category.

[DevAccount]

Well to write the automatic bit you'll have to manually figure out the rules :)

But yeah, something like that would be a good start. I don't know anything about this domain so I'm of limited help here. It might be too hard to categorize based solely on words if they're not distinct enough.

[ig1]

You could use an algorithm to identify keywords in your dataset and the manually classify the most common ones.