@inproceedings{bernardy-etal-2019-predicates,
title = "Predicates as Boxes in {B}ayesian Semantics for Natural Language",
author = "Bernardy, Jean-Philippe and
Blanck, Rasmus and
Chatzikyriakidis, Stergios and
Lappin, Shalom and
Maskharashvili, Aleksandre",
editor = "Hartmann, Mareike and
Plank, Barbara",
booktitle = "Proceedings of the 22nd Nordic Conference on Computational Linguistics",
month = sep # "{--}" # oct,
year = "2019",
address = "Turku, Finland",
publisher = {Link{\"o}ping University Electronic Press},
url = "https://aclanthology.org/W19-6137",
pages = "333--337",
abstract = "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.",
}
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%0 Conference Proceedings
%T Predicates as Boxes in Bayesian Semantics for Natural Language
%A Bernardy, Jean-Philippe
%A Blanck, Rasmus
%A Chatzikyriakidis, Stergios
%A Lappin, Shalom
%A Maskharashvili, Aleksandre
%Y Hartmann, Mareike
%Y Plank, Barbara
%S Proceedings of the 22nd Nordic Conference on Computational Linguistics
%D 2019
%8 sep–oct
%I Linköping University Electronic Press
%C Turku, Finland
%F bernardy-etal-2019-predicates
%X 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.
%U https://aclanthology.org/W19-6137
%P 333-337
Markdown (Informal)
[Predicates as Boxes in Bayesian Semantics for Natural Language](https://aclanthology.org/W19-6137) (Bernardy et al., NoDaLiDa 2019)
ACL
- Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, and Aleksandre Maskharashvili. 2019. Predicates as Boxes in Bayesian Semantics for Natural Language. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 333–337, Turku, Finland. Linköping University Electronic Press.