> You point out a real problem but it does not feel like an unsurmountable and terminal one
In our spoken language the agents doing the parsing are human AI's (actual intelligences) able to deal with most of the finer nuances in semantics, and still making numerous errors in many contexts that lead to misunderstanding, i.e. parse errors.
There was this hand-waving promise in semantic web movement of "if only we make everything machine-readable, then .." magic would happen. Undoubtedly unlocking numerous killer apps, if only we had these (increasingly complex) linked data standards and related tools to define and parse 'universal meaning'.
An overreach, imho. Semantic web was always overpromising yet underdelivering. There may be new use cases in combinations of SM with ML/LLM but I don't think they'll be a vNext of the web anytime soon.
In our spoken language the agents doing the parsing are human AI's (actual intelligences) able to deal with most of the finer nuances in semantics, and still making numerous errors in many contexts that lead to misunderstanding, i.e. parse errors.
There was this hand-waving promise in semantic web movement of "if only we make everything machine-readable, then .." magic would happen. Undoubtedly unlocking numerous killer apps, if only we had these (increasingly complex) linked data standards and related tools to define and parse 'universal meaning'.
An overreach, imho. Semantic web was always overpromising yet underdelivering. There may be new use cases in combinations of SM with ML/LLM but I don't think they'll be a vNext of the web anytime soon.