I’m just looking for the limits of GPT and whatever it is that ‘context’ is supposed be...These are each instances of a pedagogic register type in which a learner solicits knowledge.GPT recognises the canonical structure, even when it’s initiated with a statement...
speech
function
exch
role
register phase
interact
Mario
Your self is merely semiotic.
statement
K2
propose class
solicit knowledge
GPT
That is correct.
answer
K1
evaluate
approve
As an AI language model, my "self"
or programmed understanding of
my existence and capabilities is based
purely on symbols and algorithms.
statement
K1
elaborate class
impart knowledge
Keep in mind that these are just labels for structures. We give them functional labels because that’s the relation we interpret between ranks and strata. But GPT doesn't have to interpret them as ‘functions’... just predict appropriate structures in response.
But note that GPT is also negotiating affiliation with Mario... positioning itself outside of human communities... no doubt ‘trained’ by its developers.
Blogger Comments:
[1] To be clear, ChatGPT produces texts from the lexical collocation frequencies in a reservoir of instances, not from an individuated repertoire of systems that are realised as structures. On this basis, ChatGPT is not an individuated meaner.
[2] To be clear, by 'context' Rose means Martin's misunderstanding of register as a stratum of context. So here Rose is presenting a text (language) as an instance of a type of context, despite context being opposed to language in Martin's stratification model.
[3] To be clear, importantly, it is not ChatGPT that recognises 'the canonical structure' but Rose. See [1] above.
[4] To be clear, in SFL Theory, 'acknowledgement' is the expected response to a statement (Halliday & Matthiessen 2014: 137).
[5] To be clear, ChatGPT does not 'predict structures', because that is not how it operates; see [1] above.
[6] To be clear, ChatGPT is not 'negotiating affiliation', because ChatGPT is not an individuated meaner; see [1] above.
