During my time at the Leibniz Center for Law working on the IMPACT, I and my colleagues Tom van Engers and Kiavash Bahreini prepared and submitted three papers to conferences and workshops. The drafts of the papers are linked below along with the abstracts. Comments welcome.
A Framework for Enriched, Controlled On-line Discussion Forums for e-Government Policy-making
Adam Wyner and Tom van Engers
Submitted to eGOV 2010
Abstract
The paper motivates and proposes a framework for enriched on-line discussion forums for e-government policy-making, where pro and con statements for positions are structured, recorded, represented, and evaluated. The framework builds on current technologies for multi-threaded discussion lists by integrating modes, natural language processing, ontologies, and formal argumentation frameworks. With modes other than the standard reply “comment”, users specify the semantic relationship between a new statement and the previous statement; the result is an argument graph. Natural language processing with a controlled language constrains the domain of discourse, eliminates ambiguity and unclarity, allows a logical representation of statements, and facilitates information extraction. However, the controlled language is highly expressive and natural . Ontologies represent the knowledge of the domain. Argumentation frameworks evaluate the argument graph and generate sets of consistent statements. The output of the system is a rich and articulated representation of a set of policy statements which supports queries, information extraction, and inference
From Policy-making Statements to First-order Logic
Adam Wyner, Tom van Engers, and Kiavash Bahreini
Submitted to eGOVIS 2010
Abstract
Within a framework for enriched on-line discussion forums for e-government policy-making, pro and con statements for positions are input, structurally related, then logically represented and evaluated. The framework builds on current technologies for multi-threaded discussion, natural language processing, ontologies, and formal argumentation frameworks. This paper focuses on the natural language processing of statements in the framework. A small sample policy discussion is presented. We adopt and apply a controlled natural language (Attempto Controlled English) to constrain the domain of discourse, eliminate ambiguity and unclarity, allow a logical representation of statements which supports inference and consistency checking, and facilitate information extraction. Each of the polity statements is automatically translated into rst-order logic. The result is logical representation of the policy discussion which we can query, draw inferences (given ground statements), test for consistency, and extract detailed information.
Towards Web-base Mass Argumentation in Natural Language
Adam Wyner and Tom van Engers
Submitted to EKAW 2010
Abstract
Within the artificial intelligence community, argumentation has been studied for quite some years now. Despite progress, the field has not yet succeeded in creating support tools that members of the public could use to contribute their views to discussions of public policy. One important reason for that is that the input statements of participants in policy-making discussions are put forward in natural language, while translating the statements into the formal models used by argumentation scientists is cumbersome. These formal models can be used to automatically reason with, query, or transmit domain knowledge using web-based technologies. Making this knowledge explicit, formal, and expressed in a language which a machine can process is a labour, time, and knowledge intensive task. To make such translation and it requires expertise that most participants in policy-making debates do not have. In this paper we describe an approach with which we aim at contributing to a solution of this knowledge acquisition bottle-neck. We propose a novel, integrated methodology and framework which adopts and adapts existing technologies. We use semantic wikis which support mass, collaborative, distributive, dynamic knowledge acquisition. In particular, ACEWiki incorporates NLP tools, enabling linguistically competent users to enter their knowledge in natural language, while yielding a logical form that is suitable for automated processing. In the paper we will explain how we can extend the ACEWiki and augment it with argumentation tools which elicit knowledge from users, making implicit information explicit, and generate subsets of consistent knowledge bases from inconsistent knowledge bases. To a set of consistent propositions, we can apply automated reasoners, allowing users to draw inferences and make queries. The methodology and framework take a fragmentary, incremental development approach to knowledge acquisition in complex domains.
By Adam Wyner
Distributed under the Creative Commons
Attribution-Non-Commercial-Share Alike 2.0
