I would make a similar critique of basically-all the computational approaches I’ve seen to date. They generally try to back out “semantics” from a text corpus, which means their “semantics” grounds out in relations between words; neither the real world nor mental content make any appearance. They may use Bayes’ rule and latents like this post does, but such models can’t address the kinds of questions this post is asking at all.
(I suppose my complaints are more about structuralism than about model-theoretic foundations per se. Internally I’d been thinking of it more as an issue with model-theoretic foundations, since model theory is the main route through which structuralism has anything at all to say about the stuff which I would consider semantics.)
Of course you might have in mind some body of work on computational linguistics/semantics with which I am unfamiliar, in which case I would be quite grateful for my ignorance to be corrected!
I see. I’m afraid I don’t have much great literature to recommend on computational semantics (though Josh Tenenbaum’s PhD dissertation seems relevant). I still wonder whether, even if you disagree with the approaches you have seen in that domain, those might be the kind of people well-placed to help with your project. But that’s your call of course.
Depending on your goals with this project, you might get something out of reading work by relevance theorists like Sperber, Wilson, and Carston (if you haven’t before). I find Carston’s reasoning about how variousaspects of language works quite compelling. You won’t find much to help solve your mathematical problems there, but you might find considerations that help you disambiguate between possible things you want your model of semantics to do (e.g., do you really care about semantics, per se, or rather concept formation?).
I would make a similar critique of basically-all the computational approaches I’ve seen to date. They generally try to back out “semantics” from a text corpus, which means their “semantics” grounds out in relations between words; neither the real world nor mental content make any appearance. They may use Bayes’ rule and latents like this post does, but such models can’t address the kinds of questions this post is asking at all.
(I suppose my complaints are more about structuralism than about model-theoretic foundations per se. Internally I’d been thinking of it more as an issue with model-theoretic foundations, since model theory is the main route through which structuralism has anything at all to say about the stuff which I would consider semantics.)
Of course you might have in mind some body of work on computational linguistics/semantics with which I am unfamiliar, in which case I would be quite grateful for my ignorance to be corrected!
I see. I’m afraid I don’t have much great literature to recommend on computational semantics (though Josh Tenenbaum’s PhD dissertation seems relevant). I still wonder whether, even if you disagree with the approaches you have seen in that domain, those might be the kind of people well-placed to help with your project. But that’s your call of course.
Depending on your goals with this project, you might get something out of reading work by relevance theorists like Sperber, Wilson, and Carston (if you haven’t before). I find Carston’s reasoning about how various aspects of language works quite compelling. You won’t find much to help solve your mathematical problems there, but you might find considerations that help you disambiguate between possible things you want your model of semantics to do (e.g., do you really care about semantics, per se, or rather concept formation?).