When telling a story, a speaker needs to refer to story characters using appropriate expressions, which requires a mental model of the discourse. We hypothesize that, compared to those of adults, children's discourse models are based more on factors that are less cognitively demanding, such as animacy, and as they grow older, discourse factors…

We propose that machine-learned computational models (MLCMs), in which the model parameters and perhaps even structure are learned from data, can complement extant approaches to the study of text and discourse. Such models are particularly useful when theoretical understanding is insufficient, when the data are rife with nonlinearities and…