While acknowledging a certain level of utility in that description, that definition takes as an assumption that there are only two possible truth values.
What if both true and false are in reality only available in a limited range of contexts, and in many more contexts truth states are defined by sets of probability vectors?
Thus most use of the terms “true” and “false” are examples of distinction category errors within a paradigm set.
What if reality, rather than following causal rules, is really a complex stochastic system constrained only within certain low level probability distributions, that at the macro-scale of human perception deliver approximations to causality that are within the measurement errors of our best tools?
That delivers a rather different context!