By Henk Zeevat, Hans-Christian Schmitz

The contributions during this quantity concentrate on the Bayesian interpretation of ordinary languages, that's wide-spread in components of man-made intelligence, cognitive technology, and computational linguistics. this can be the 1st quantity to soak up issues in Bayesian normal Language Interpretation and make proposals in line with details idea, chance concept, and similar fields. The methodologies provided right here expand to the objective semantic and pragmatic analyses of computational average language interpretation. Bayesian ways to typical language semantics and pragmatics are in accordance with tools from sign processing and the causal Bayesian versions pioneered by means of specifically Pearl. In sign processing, the Bayesian procedure reveals the main possible interpretation via discovering the person who maximizes the made from the earlier likelihood and the possibility of the translation. It hence stresses the significance of a creation version for interpretation as in Grice’s contributions to pragmatics or in interpretation by means of abduction.

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2012). Presupposition projection and entailment relations. D. thesis, Universitat Pompeu Fabra. Gazdar, G. (1979). Pragmatics: Implicature presupposition and logical form. New York: Academic Press. Heim, I. (1983). On the projection problem for presuppositions. In M. Barlow, D. Flickinger, & M. ), Second Annual West Coast Conference on Formal Linguistics (pp. 114–126). Stanford University. , Martin, P. (1990). Interpretation as abduction. Technical Report 499, SRI International, Menlo Park, California.

It follows that, in order to determine implicature, it is only necessary to know which values xi of a variable Xi are consistent with an utterance of F. Hence, it suffices to know for which xi Pi| j (xi |F) > 0. 10 Whenever a probability appears in the denominator, we implicitly assume that it is greater than zero. If X or Y is a singleton set, for example Y = {y}, the brackets around y are omitted in argument positions of probability distributions. Causal Bayesian Networks, Signalling Games … 35 This definition is justified by Grice’s contention (1989, p.

3 Inferences from Comparatively Modified Numerals Although comparatively modified numerals do not give rise to the neo–Gricean scalar implicature, they allow for some conversational inferences. The following examples are taken from either Cummins (2011), Cummins et al. (2012), or Cummins (2013). Consider: Causal Bayesian Networks, Signalling Games … 29 (6) London has more than 1000 inhabitants. ’, (6) is obviously underinformative. It conveys the impression that London is a small city, and a naïve addressee would clearly exclude the possibility that London has a million, let alone 10 million inhabitants.

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Bayesian Natural Language Semantics and Pragmatics by Henk Zeevat, Hans-Christian Schmitz
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