@article{Clarke2015,
	title = {Efficiency in {Ambiguity} : {Two} {Models} of {Probabilistic} {Semantics} for {Natural} {Language}},
	abstract = {This paper explores theoretical issues in constructing an adequate probabilistic semantics for natural language. Two approaches are contrasted. The first extends Montague Semantics with a probability distribution over models. It has nice theoretical properties, but does not account for the ubiquitous nature of ambiguity; moreover inference is NP-hard. An alternative approach is described in which a sequence of pairs of sentences and truth values is generated randomly. By sacrificing some of the nice theoretical properties of the first approach it is possible to model ambiguity naturally; moreover inference now has polynomial time complexity. Both approaches provide a compositional semantics and account for the gradience of semantic judgements of belief and inference.},
	journal = {Proceedings of the 11th International Conference on Computational Semantics, London, UK, April 15-17 2015},
	author = {Clarke, Daoud and Keller, Bill},
	year = {2015},
	keywords = {Probabilistic linguistics},
	pages = {129--139},
}

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