Earlier quoted context omitted.
> I'd invite you to look at ontologies as nothing more than representations of things we know in some text-based format. That's because we know how to interpret the concepts used in these representations, in relation to each other. It's just a syntactic change. You might have a point if it's used as a kind of search engine: "show me wikipedia articles where X causes Y?" (although there is at least one source besides…
> There's no other relation than "causes". Looking at their Neo4j graph, they also retain the provenance of the causal relation in "claimedIn" relations between the reified triple of each cause-effect pair. So, that's at least marginally useful for fact-checking or quality evals. > they just take noun phrases and slap an underscore between the words and call it a concept. Not to defend lazy approaches, but you could…
I think we look at it from different sides. Mine is "how good will this be in independently running code" (where 80% correctness is minimally needed), yours seems to be more "how well does this represent our knowledge" (from different angles).
> you could make this point about tokens also ("take any bunch of characters that happens often enough, and call it a token").
My reason was more that such an approach doesn't work well with (unrestricted natural language) text. E.g. side_effects => physical_damage: What side effects? (Why plural?) Not all cause physical damage. And not all side effects that cause physical damage cause the same damage. The differences are described elsewhere in the text, but not consistent enough to extend the token with that information, so just associating literal excerpts from a text will practically guarantee underspecification (except for practically unambiguous term). The effectiveness will be language dependent, of course.
Anyway...