Article | Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa), September 30 - October 2, Turku, Finland | Predicates as Boxes in Bayesian Semantics for Natural Language Linköping University Electronic Press Conference Proceedings
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Title:
Predicates as Boxes in Bayesian Semantics for Natural Language
Author:
Jean-Philippe Bernardy: Department of philosophy, linguistics and theory of science, Centre for linguistics and studies in probability, Gothenburg Univeristy, Sweden Rasmus Blanck: Department of philosophy, linguistics and theory of science, Centre for linguistics and studies in probability, Gothenburg Univeristy, Sweden Stergios Chatzikyriakidis: Department of philosophy, linguistics and theory of science, Centre for linguistics and studies in probability, Gothenburg Univeristy, Sweden Shalom Lappin: Department of philosophy, linguistics and theory of science, Centre for linguistics and studies in probability, Gothenburg Univeristy, Sweden Aleksandre Maskharashvili: Department of philosophy, linguistics and theory of science, Centre for linguistics and studies in probability, Gothenburg Univeristy, Sweden
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Full text (pdf)
Year:
2019
Conference:
Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa), September 30 - October 2, Turku, Finland
Issue:
167
Article no.:
037
Pages:
333--337
No. of pages:
4
Publication type:
Abstract and Fulltext
Published:
2019-10-02
ISBN:
978-91-7929-995-8
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Series:
NEALT Proceedings Series
Publisher:
Linköping University Electronic Press, Linköpings universitet


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In this paper, we present a Bayesian approach to natural language semantics. Our main focus is on the inference task in an environment where judgments require probabilistic reasoning. We treat nouns, verbs, adjectives, etc. as unary predicates, and we model them as boxes in a bounded domain. We apply Bayesian learning to satisfy constraints expressed as premises. In this way we construct a model, by specifying boxes for the predicates. The probability of the hypothesis (the conclusion) is evaluated against the model that incorporates the premises as constraints.

Keywords: Bayesian models probabilistic semantics generalised quantifiers vague predicates compositionality Inference

Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa), September 30 - October 2, Turku, Finland

Author:
Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, Aleksandre Maskharashvili
Title:
Predicates as Boxes in Bayesian Semantics for Natural Language
References:
No references available

Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa), September 30 - October 2, Turku, Finland

Author:
Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, Aleksandre Maskharashvili
Title:
Predicates as Boxes in Bayesian Semantics for Natural Language
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Last updated: 2019-11-06