On Processing Models and Their Complexity Several commentators ask how our proposal fits within a larger theory of language interpretation and processing, so let us start there. Following Rohde, Levy & Kehler (2011) and others, we envision our results situated in a strongly incremental theory, one in which both sentence-level and discourse-level decisions are made utilizing a broad variety of information sources on a moment-by-moment basis. This comes with two important ramifications. First, it predicts a particular time course of processing, whereby linguistic expressions influence context at the time they are encountered, and hence many only affect the interpretation of a subsequent pronoun indirectly. For instance, in interpreting a passage like Amanda fired Brittany and she immediately filed a lawsuit, the comprehender will have a particular set of biases toward coherence and next mention after the first clause (presumably favoring Explanation and Brittany respectively, since fired is an object-biased IC verb), which then get updated when and is encountered, and then again when the pronoun she is encountered. Crucially, the updates proceed along opposite paths in these two cases. On the one hand, and updates P(CR) to increase the likelihood of the coherence relations with which it is most compatible (Occasion, Result, Parallel) and to decrease it for others (e.g., Explanation will drop to near zero), which cascades to update P(referent). On the other hand, she updates P(referent) to become P(referent | pronoun) (by including the production probability P(pronoun | referent)) which, in pulling the distribution toward the subject referent, cascades to update P(CR) to increase the likelihood of subject-biased relations per the results of Rohde & Kehler (2008). The second ramification is that interpretation does not stop there; these probabilities will continue to be updated as subsequent linguistic material is encountered through the end of the clause. This answers Arnold’s and de Hoop’s question about how an ultimate
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