RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant

RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant

This paper presents a library of commonsense knowledge, RestKB, developed in modular action language ALM and containing background knowledge relevant to the understanding of restaurant narratives, including stories that describe exceptions to the normal unfolding of such scenarios. We highlight feat...

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Main Author: Daniela Inclezan
Format: Article
Language:English
Published: Open Publishing Association 2019-09-01
Series:Electronic Proceedings in Theoretical Computer Science
Online Access:http://arxiv.org/pdf/1909.08239v1
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spelling doaj-fb0c870077ef4ef2ad62b15f195ba4e62020-11-25T01:07:48ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802019-09-01306Proc. ICLP 201912613910.4204/EPTCS.306.19:64RestKB: A Library of Commonsense Knowledge about Dining at a RestaurantDaniela Inclezan0 Miami University This paper presents a library of commonsense knowledge, RestKB, developed in modular action language ALM and containing background knowledge relevant to the understanding of restaurant narratives, including stories that describe exceptions to the normal unfolding of such scenarios. We highlight features that KR languages must possess in order to be able to express pertinent knowledge, and expand action language ALM as needed. We show that encoding the knowledge base in ALM facilitates its piecewise construction and testing, and improves the generality and quality of the captured information, in comparison to an initial ASP encoding. The knowledge base was used in a system for reasoning about stereotypical activities, evaluated on the restaurant domain.http://arxiv.org/pdf/1909.08239v1
collection DOAJ
language English
format Article
sources DOAJ
author Daniela Inclezan
spellingShingle Daniela Inclezan
RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant
Electronic Proceedings in Theoretical Computer Science
author_facet Daniela Inclezan
author_sort Daniela Inclezan
title RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant
title_short RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant
title_full RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant
title_fullStr RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant
title_full_unstemmed RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant
title_sort restkb: a library of commonsense knowledge about dining at a restaurant
publisher Open Publishing Association
series Electronic Proceedings in Theoretical Computer Science
issn 2075-2180
publishDate 2019-09-01
description This paper presents a library of commonsense knowledge, RestKB, developed in modular action language ALM and containing background knowledge relevant to the understanding of restaurant narratives, including stories that describe exceptions to the normal unfolding of such scenarios. We highlight features that KR languages must possess in order to be able to express pertinent knowledge, and expand action language ALM as needed. We show that encoding the knowledge base in ALM facilitates its piecewise construction and testing, and improves the generality and quality of the captured information, in comparison to an initial ASP encoding. The knowledge base was used in a system for reasoning about stereotypical activities, evaluated on the restaurant domain.
url http://arxiv.org/pdf/1909.08239v1
work_keys_str_mv AT danielainclezan restkbalibraryofcommonsenseknowledgeaboutdiningatarestaurant
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