Natural language directed inference from ontologies

Chris Mellish; Jeff Z. Pan

doi:10.1016/j.artint.2008.01.003

Natural language directed inference from ontologies

Chris Mellish, Jeff Z. Pan

Computing Science

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21 Citations (Scopus)

Abstract

This paper presents an investigation into the problem of content determination in natural language generation (NLG), using its an example the problem of determining what to say when asked "What is an A?", where A is a concept defined in an OWL ontology. It is shown that a naive approach to this problem, which just presents a set of the stated axioms, will often inadvertantly violate maxims of cooperative conversation. What is required instead is a kind of inference that generates logical conclusions of the axioms that are suitable for natural language presentation-natural language directed inference (NLDI). Although NLDI, in this case a kind of non-standard inference in description logics, is hard to formalise in general, for this problem we isolate a significant subproblem-that of enumerating subsumers of A that are suitable for natural language presentation. For this problem, which on the face of it appears intractable, we show how factors relevant to natural language presentation enable an optimised solution that is realistic in practice.

The paper makes a contribution to the increasingly important practical problem of explaining concepts in an ontology. It also makes a first step towards the development of domain independent principles for content determination. (c) 2008 Elsevier B.V. All rights reserved.

Original language	English
Pages (from-to)	1285-1315
Number of pages	31
Journal	Artificial Intelligence
Volume	172
Issue number	10
Early online date	4 Mar 2008
DOIs	https://doi.org/10.1016/j.artint.2008.01.003
Publication status	Published - Jun 2008

Bibliographical note

A paid open access option is available for this journal.
Voluntary deposit by author of pre-print allowed on Institutions open scholarly website and pre-print servers
Voluntary deposit by author of authors post-print allowed on institutions open scholarly website including Institutional Repository
Deposit due to Funding Body, Institutional and Governmental mandate only allowed where separate agreement between repository and publisher exists
Set statement to accompany deposit
Published source must be acknowledged
Must link to journal home page or articles' DOI
Publisher's version/PDF cannot be used
Articles in some journals can be made Open Access on payment of additional charge
NIH Authors articles will be submitted to PMC after 12 months
Authors who are required to deposit in subject repositories may also use Sponsorship Option
Pre-print can not be deposited for The Lancet

Keywords

ontologies
natural language generation
non-standard reasoning
content determination

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10.1016/j.artint.2008.01.003

Cite this

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title = "Natural language directed inference from ontologies",

abstract = "This paper presents an investigation into the problem of content determination in natural language generation (NLG), using its an example the problem of determining what to say when asked {"}What is an A?{"}, where A is a concept defined in an OWL ontology. It is shown that a naive approach to this problem, which just presents a set of the stated axioms, will often inadvertantly violate maxims of cooperative conversation. What is required instead is a kind of inference that generates logical conclusions of the axioms that are suitable for natural language presentation-natural language directed inference (NLDI). Although NLDI, in this case a kind of non-standard inference in description logics, is hard to formalise in general, for this problem we isolate a significant subproblem-that of enumerating subsumers of A that are suitable for natural language presentation. For this problem, which on the face of it appears intractable, we show how factors relevant to natural language presentation enable an optimised solution that is realistic in practice.The paper makes a contribution to the increasingly important practical problem of explaining concepts in an ontology. It also makes a first step towards the development of domain independent principles for content determination. (c) 2008 Elsevier B.V. All rights reserved.",

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author = "Chris Mellish and Pan, {Jeff Z.}",

note = "A paid open access option is available for this journal. Voluntary deposit by author of pre-print allowed on Institutions open scholarly website and pre-print servers Voluntary deposit by author of authors post-print allowed on institutions open scholarly website including Institutional Repository Deposit due to Funding Body, Institutional and Governmental mandate only allowed where separate agreement between repository and publisher exists Set statement to accompany deposit Published source must be acknowledged Must link to journal home page or articles' DOI Publisher's version/PDF cannot be used Articles in some journals can be made Open Access on payment of additional charge NIH Authors articles will be submitted to PMC after 12 months Authors who are required to deposit in subject repositories may also use Sponsorship Option Pre-print can not be deposited for The Lancet",

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N2 - This paper presents an investigation into the problem of content determination in natural language generation (NLG), using its an example the problem of determining what to say when asked "What is an A?", where A is a concept defined in an OWL ontology. It is shown that a naive approach to this problem, which just presents a set of the stated axioms, will often inadvertantly violate maxims of cooperative conversation. What is required instead is a kind of inference that generates logical conclusions of the axioms that are suitable for natural language presentation-natural language directed inference (NLDI). Although NLDI, in this case a kind of non-standard inference in description logics, is hard to formalise in general, for this problem we isolate a significant subproblem-that of enumerating subsumers of A that are suitable for natural language presentation. For this problem, which on the face of it appears intractable, we show how factors relevant to natural language presentation enable an optimised solution that is realistic in practice.The paper makes a contribution to the increasingly important practical problem of explaining concepts in an ontology. It also makes a first step towards the development of domain independent principles for content determination. (c) 2008 Elsevier B.V. All rights reserved.

AB - This paper presents an investigation into the problem of content determination in natural language generation (NLG), using its an example the problem of determining what to say when asked "What is an A?", where A is a concept defined in an OWL ontology. It is shown that a naive approach to this problem, which just presents a set of the stated axioms, will often inadvertantly violate maxims of cooperative conversation. What is required instead is a kind of inference that generates logical conclusions of the axioms that are suitable for natural language presentation-natural language directed inference (NLDI). Although NLDI, in this case a kind of non-standard inference in description logics, is hard to formalise in general, for this problem we isolate a significant subproblem-that of enumerating subsumers of A that are suitable for natural language presentation. For this problem, which on the face of it appears intractable, we show how factors relevant to natural language presentation enable an optimised solution that is realistic in practice.The paper makes a contribution to the increasingly important practical problem of explaining concepts in an ontology. It also makes a first step towards the development of domain independent principles for content determination. (c) 2008 Elsevier B.V. All rights reserved.

KW - ontologies

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KW - non-standard reasoning

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DO - 10.1016/j.artint.2008.01.003

M3 - Article

SN - 0004-3702

VL - 172

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EP - 1315

JO - Artificial Intelligence

JF - Artificial Intelligence

IS - 10

ER -

Natural language directed inference from ontologies

Abstract

Bibliographical note

Keywords

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