In this paper we motivate and describe a dialogue manager (called Frolog) which uses classical planning to infer causal implicatures. A causal implicature is a type of Gricean relation implicature, a highly context dependent form of inference. As we shall see, causal implicatures are important for understanding the structure of task-oriented dialogues. Such dialogues locate conversational acts ...

Plural nouns do not strictly refer to more than one object, which suggests that they are not semantically marked to mean “more than one” and that plurality inferences are made via a scalar implicature. Consistent with that hypothesis, recent evidence using a picture-matching paradigm supports founds that participants were equally fast to respond to a picture of a single object as a picture of m...

This paper offers a novel conversational implicature account of the pragmatic sensitivity of knowledge attributions. Developing an account I first suggested elsewhere (Locke, Inquiry 57:28–54, 2014b) and independently proposed by Lutz (in Synthese 191:1717–1740, 2014), this paper explores the idea that the relevant implicatures are generated by a constitutive relationship between believing a pr...

Grice’s distinction between what is said and what is implicated has greatly clarified our understanding of the boundary between semantics and pragmatics. Although border disputes still arise and there are certain difficulties with the distinction itself (see the end of §1), it is generally understood that what is said falls on the semantic side and what is implicated on the pragmatic side. But ...

Knott's empirical study of cue phrases has resulted in a taxonomic classiication of some 150 cue phrases. The taxonomy can be viewed as a partial ordering on the set of phrases, and hence we can view cue phrase selection in terms of scalar implicature, following Hirschberg. We draw out some of the immediate consequences of this view, including the problematic status of the conventional/conversa...

Opinions may be expressed implicitly via inference over explicit sentiments and events that positively/negatively affect entities (goodFor/badFor events). We investigate how such inferences may be exploited to improve sentiment analysis, given goodFor/badFor event information. We apply Loopy Belief Propagation to propagate sentiments among entities. The graph-based model improves over explicit ...