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This talk presents an integrated theory of tense, pronouns and mood under attitudes on the basis of the theory in (Schlenker, 1999), which will be elaborated and improved in certain details. The centre of the paper will be the analysis of certain temporal phenomena that have been worrying me for the last ten years. The coverage of the theory is more general, however. A. Ideas. The central ideas of the approach are these. 1. Each finite verb has a world, a time and a person argument, whose semantic properties are checked by the person, tense and mood morphology of the verb. Call them the egocentric arguments of the verb. 2. With the possible exception of the third person, the said arguments of the verb are variables. Variables with features will always be interpreted with respect to the context of utterance. The result is that variables with these features are deictic expressions. 3. Features of semantically bound variables are deleted at LF and therefore not interpreted (Heim’s principle of feature transmission; see e.g. (Heim, 2001)). 4. Attitudes (modals and certain temporal auxiliaries) may bind the egocentric variables of their verbal complement under agreement and therefore may produce bound person/tense/mood readings. Under these circumstances the variables lose their referential character entirely. That certain verbs (as opposed to noun phrases) can bind variables is crucial for understanding the functioning of de se pronouns (e.g. PRO, logophors, Engl. I under attitudes), sequence of tense rules, certain readings of temporal adverbs such as in two days, shiftable deictic modals such as ought or should. The talk tries to clarify the following point: while (Kaplan, 1979) is wrong in his claim that pronouns such as I or you are always directly referential, Schlenker’s (1999) criticism of Kaplan’s Prohibition against Monsters is not warranted. Schlenker’s attitudes are arguably purely intensional operators. There is no expression of natural language that denotes a genuine monster such as Stalnaker’s diagonal operator. B. Data. Here are some of the data that will be discussed in the talk:
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