In some sense, this task strikes me as similar to ideal learner computational models — we want to see what information is useful in the available input. For the HSP, we do this by seeing what a learner with adult-level cognitive resources can extract. For ideal learners, we do this by seeing what inferences a learner with unlimited computational resources can make, based on the information available.
(3) General discussion point at the end about unambiguous data: This is a really excellent point, since we don’t like to have to rely on the presence of unambiguous data too much in real life (because typically when we go look for it in realistic input, it’s only very rarely there). Something I’d be interested in is how often unambiguous data for this pronoun categorization issue does actually occur. If it’s never (or almost never, relatively speaking), then this becomes a very nice selling point for this learning model.