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Efficiency in ambiguity: two models of probabilistic semantics for natural language
conference contribution
posted on 2023-06-08, 20:34 authored by Daoud Clarke, Bill KellerThis 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.
Funding
A Unified Model of Compositional and Distributional Semantics: Theory and Applications; EPSRC; EP/I037458/1
History
Publication status
- Published
File Version
- Accepted version
Journal
Proceedings of the 11th International Conference on Computational SemanticsPublisher
Association for Computational LinguisticsPublisher URL
Page range
129-139Event name
IWCS 2015: 11th International Conference on Computational SemanticsEvent location
Queen Mary University, LondonEvent type
conferenceEvent date
April 15 - 17, 2015Place of publication
London, UKISBN
978-1-941643-33-4Department affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- No
Legacy Posted Date
2015-04-22First Open Access (FOA) Date
2019-02-11First Compliant Deposit (FCD) Date
2015-04-21Usage metrics
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