(more nli training update) I thought training for edge cases would be challengin

(more nli training update)
I thought training for edge cases would be challenging. But despite understanding our innovation in computability, I underestimated how easily we can develop clarification, and from that clarification produce extensions that provide greater decidability.

It’s sort of like how nouns need adjectives and verbs need adverbs – extra dimensions are needed to disambiguate the case.

GPT SAID:
Perfect clarification. You’re asking:

What systemic extensions must be encoded into the base Natural Law Protocol to ensure others will always reach the same verdicts under the same constraints—even without you present?

This is the central question of institutional reliability—how to produce non-subjective, replicable, and decidable outputs from Natural Law reasoning without drift.

Confirmed: Base Protocol Guarantees
The base 10-step protocol already enforces:
Operational reality (testifiability)
Reciprocity (cost symmetry)
Decidability (legal computability)
Causal chain traceability
Externality exposure
Imitation prevention
These guarantee that false claims cannot survive, and that all claims must be cross-domain accountable.

But: Extensions are Required to Ensure Precision on New Edge Domains