What Do You Mean? Arguing for Meaning

• Autore: Tom M. Van Engers - Adamwyner
• Carica: Professor in Legal Knowledge Management at the University of Amsterdam - Research Associate at University of Liverpool, Department of Computer Science.
• Pagine: 299-306

What Do You Mean? Arguing for Meaning

TOM M. VAN ENG ERS , ADAM WYN ER∗

SUMM ARY:1. Introduction – 2. Using CNL for Policy-making Discussions – 3. Con-

ceptualization Issues in Arguments – 4. Conclusions and Future Work

1. INT RODU CTI ON

Building ontologies has proven to be a complex issue in part because a

community must commit to the conceptualization that the ontology rep-

resents. The community members must align their concepts and co-create.

Arguing about a useful conceptualization is therefore an essential part of the

process of designing an ontology. The creation of ontologies is usually done

in small teams as part of informal knowledge engineering activities where

participants discuss the conceptualization. Except where a minority has dis-

cretionary power to def‌ine the concepts, such a formatis not suited for creat-

ing shared meaning between members of a larger community. However, in

practice, people can cope with the task. For instance, where someone mis-

understands, clarifying questions are asked and explanations given. Thus,

the shared conceptualisation emerges from discussion; arguing about a use-

ful conceptualization is an intrinsic part of communication. While it is not

always easy for human beings to acknowledge and adjust to a different con-

ceptualization, the problems of detecting conceptual differences and creating

reconceptualizations are problems which are hard to solve in AI.

While one might expect that logicians working at formal theories on ar-

gumentation would have addressed the problems of conceptualization, thus

far little attention has been paid to combining formal argumentation with

conceptualization. Instead, argumentation theories focus on arguments

based on propositional logic, which is not f‌ine-grained enough to argue

about domain conceptualization.

Computational linguists have made signif‌icant progress in building on-

tologies from sentences expressed in natural languages. In order to address

the hard AI problem of understanding natural language, researchers in this

∗T.M. van Engers is Professor in Legal Knowledge Management at the University of

Amsterdam; A. Wyner is Research Associate at University of Liverpool, Department of

Computer Science. The Authors wish to thank the European Commission for sponsoring

the IMPACT project.