Instead, we attempt to design tasks which capture humans' linguistic behavior in as natural a setting as possible (acknowledging that truly natural annotation is difficult) with the hope that models trained to perform such tasks will be the best match for the ''real world'' settings in which we hope to deploy them.
we generally prefer to punt on precise definitions, and instead train our models to ''do what humans do''.