Proceedings of the 13 ESSLLI Student Session - Multiple Choices ...

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Proceedings of the 13 th ESSLLI Student Session to analyze epistemic modals one must develop a framework in which assertions can significantly change a context without providing information. Since this papers framework postulates that epistemic modals affect the salient possibilities in a context rather than its information, the non-informative yet non-trivial effects of epistemic modals are properly represented. One advantage of this analysis is that it is able to account for the felicity of a modalized construction as an answer to a question. For example: (1) A: Where are my keys? B: They might be in the basement. (2) A: Are John and Bill coming to the party? B: They might. In dialogue (1), B doesnt answers As questions by saying where her keys are (because, if hes acting felicitously, he doesnt know where they are), but by suggesting a possibility for her to consider. Similarly in (2): B suggests that A should not overlook the possibility that Bill and John come to the party. If she really dislikes them, the very possibility that they attend may be reason enough for her to skip the party. Enemies of salient possibilities may think that a modal answer to a question really says nothing more than I dont know, or Any answer is consistent with my knowledge. Against this, consider the following case: suppose A is frantically looking for her husband Joe, and comes across B, who has never met Joe and has never given him one thought. If she asks him Where is Joe? and he responds I dont know, this is perfectly acceptable. However, if he responds He might be in Boston this is completely infelicitous: if A takes him seriously, shes on her way to a wild goose chase. Intuitively, this is because she seriously takes into account his (inappropriate) suggestion to consider the possibility that Joe is in Boston. A classical partition theory of questions has difficulty accounting for (1) and (2). This is the case because in a partition theory an answer to a question has to give information. However, as dialogues (1) and (2) demonstrate, answers to questions do not need to be informative: it suffices that they suggest informative answers. Below, I give a more detailed and formal discussion of the problem partition theories of questions face from noninformative answers to questions, and discuss the similarities and differences between the theory presented in this paper and a partition theory. This analysis also accounts for a puzzling feature of the behavior of epistemic modals under attitude reports. Statements of the form x believes that might φ mean, in part, that the attitude holder x considers φ to be a salient possibility. For example, sup-pose that John has never given a thought to what the weather is like in Amsterdam. Then (3) certainly seems wrong: (3) John believes it might be raining in Amsterdam. Using this papers theory, one could account for (3) by analyzing a belief state as composed of both information and salient possibilities. The content of (3) then states, roughly, that its consistent with Johns beliefs that its raining in Amsterdam and that this is a salient 28
Proceedings of the 13 th ESSLLI Student Session possibility in his belief state. Several contemporary theories of epistemic modality do not appeal to any notion similar to that of a salient possibility, and hence have no clear way of accounting for (3) (e.g. DeRose (1991) and Egan et. al. (2005); for similar reasons these theories also have problems accounting for the question and answer data presented above). Due to constraints on length we will not formalize this theory of the interaction between epistemic modals and attitude reports below. As mentioned above, the analysis is carried out in a dynamic semantic framework. In dynamic semantics, the meaning of a formula is not identified with its truth conditions, but rather with the way it changes a context. More specifically, our theory is a version of update semantics in the style of Veltman (1996), i.e. we give a definition of an information state and the meanings of formulas are functions from information states to information states. 2 Questions and Salient Possibilities In this section, we define a 1st-order language with a question operator and an epistemic possibility operator. We then define the structures (information states) used to give a semantics for this language and define the notion of a salient possibility. Finally, we give the semantics for this language and define what it means for a formula to be an answer to a question. This definition will allow modal and non-modal formulas to answer questions. DEFINITION 1. We define the languages L1, L2, and L3 as follows: (i) If P is an n-place predicate and t1...tn are terms, then P(t1...tn) ∈ L1 (ii) If φ,ψ ∈ L1, then φ ∧ ψ ∈ L1 and ¬ φ ∈ L1 (iii) If φ ∈ L1, then ⋄φ ∈ L2 (iv) If φ,ψ ∈ L2, then φ ∧ ψ ∈ L2 and ¬ φ ∈ L2 (v) If φ ∈ L1, then ?φ ∈ L3 (vi) If φ,ψ ∈ L3, then φ ∧ ψ ∈ L3 The language L we discuss in this paper is defined L = L1 ∪ L2 ∪ L3. As a notational convention, we write atomic sentences (i.e. atomic formulas with no free variables) and Boolean combinations of atomic sentences as p, q, ¬q,p ∧ q, etc. In a standard update semantics, information states are sets of indices, where an index assigns an individual from a domain D to each constant of the language and an n-ary relation to each n-place predicate. In this papers framework, an information state is a set of sets of indices A such that there is an I* ∈ A that for all I m ∈ A, I m ⊆ I*. The intui-tion behind this definition is that this maximal set I* represents the common ground at a point in a conversation. Any subset of I* is a possible future state of the common ground, and hence could be a possibility that the discourse participants are interested in. However, recalling the introduction, all such subsets are not always of interest to the discourse participants. With that in mind we think of the subsets I m of I* as salient possibilities. We formally define information states below: DEFINITION 2. Let I be the set of all indices for the language L. We define an information state to be a set Γ = {P1,...,Pn,...} such that: (i) Pi ⊆ I for all n (ii) For some i, Pi = Γ (iii) There is an i such that for all j, Pj ⊆ Pi. This maximal set Pi is called the common ground. We write CG (common ground) for the maximal set Pi defined in (iii), and write Γ = {CG,P1,...,Pn,...,∅}. In some cases, we refer to information states as contexts. 29
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Page 3 and 4: Contents Preface . . . . . . . . .
Page 5 and 6: Preface Proceedings of the 13 th ES
Page 9 and 10: mechanism of the encoded function.
Page 13 and 14: The table below presents experiment
Page 17 and 18: SIMULATING SPOKEN DIALOGUE WITH A F
Page 19 and 20: 21 Speech Generation Speech generat
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Page 31 and 32: We now state our update semantics f
Page 33 and 34: 3 Comparison With a Partition Seman
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Page 37 and 38: BARE PREDICATION AND KINDS ∗ Bert
Page 39 and 40: The reason why the b-variants are o
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Page 43 and 44: 43 Non-bare predication and non-uni
Page 45 and 46: References Proceedings of the 13 th
Page 47 and 48: DIAGRAMMATIC REASONING WITH ENHANCE
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Page 57 and 58: FICTIONAL CONTINGENCIES Gemma Celes
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Proceedings of the 13 th ESSLLI Stu
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only one increasing chain completel
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the minimal step width seems to be
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etrieved in order to check it again
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Results The percentages of correct
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The complexity of relative clauses
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References Proceedings of the 13 th
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A SALIENCE-DRIVEN APPROACH TO SPEEC
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2. the linguistic salience or “re
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where the expectations provided by
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A LOGIC WITH A CONDITIONAL PROBABIL
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• v : F orC × W −→ {0, 1} is
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Lemma 4 M ∗ is a measurable model
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is a tautology. Now we can equivale
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A PROOF-THEORETIC APPROACH TO FRENC
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References Abeillé, A., Godard, D.
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INFINITE GAMES FROM AN INTUITIONIST
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6 Further problems Proceedings of t
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pointers to the text, containing th
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example in a comparatively short te
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Such an example is: Constant modifi
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WORD SPACE MODELS OF SEMANTIC SIMIL
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tween semantic similarity and seman
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wu & palmer 0.0 0.2 0.4 0.6 0.8 1.0
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frequency F−score 0 100 200 300 4
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EXAMINING THE NOTICING FUNCTION OF
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effects of input flood and individu
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CDIPROVER3: A TOOL FOR PROVING DERI
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Example 8. Consider the TRS given i
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THE RANK(S) OF A TOTALLY LEXICALIST
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EXPRESSING CONJUNCTIVE AND AGGREGAT
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(Rule) (Semantic Action) Qwh → In
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(⇐) We will prove, by induction o
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1 Introduction INTERROGATION IN DYN
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to hold for questions to be felicit
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5 Further research One goal for a s
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THE SEMANTIC CHANGE OF THE FRENCH -
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6 Conclusion In this paper, I inves
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ADVERSARY IMPLICATURES ∗ Grégoir
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2.2.1 The derivation of Q-Implicatu
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of the first, the relation of Contr
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List of authors Martin Avanzini Mar
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