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Ho-Pun Lam

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FLAP Journal 2021 Journal Article

NLP Techniques for Normative Mining.

  • Gabriela Ferraro
  • Ho-Pun Lam

Natural Language Processing (NLP) is a branch of artificial intelligence that study the interactions between computers and human (natural) language. In the field of legal informatics, the focus has been centered on mining and formalising normative information such that the legal norms extracted can be interpreted and reasoned by machines in an automated fashion. In this article, we focus our attention on discussing the challenges of normative mining from a NLP perspective, and present a detailed overview of existing techniques on semantic parsing, and their strengths and limitations on mining legal norms.

KR Conference 2016 Short Paper

On the Justification of Statements in Argumentation-based Reasoning

  • Pietro Baroni
  • Guido Governatori
  • Ho-Pun Lam
  • Regis Riveret

requirement for a knowledge representation and reasoning formalism. Surprisingly, the current versions of several well-known structured argumentation formalisms fail to satisfy this simple requirement, equating, for instance, the justification status of S4 with the one of S3, or with that of S1 and S2, or even the justification status of S3 with that of S1 and S2. While this may appear a severe drawback, we argue that this is not due to an intrinsic limitation of the argumentation formalisms themselves, rather to the relatively limited attention paid to the notion of justification of statements, often treated as a mere appendix of the notions of acceptance and justification of arguments, that (not surprisingly) are among the main focuses in formal argumentation studies. In order to overcome this limitation, we suggest that the issue of statement justification, in the context of argumentation-based reasoning, can be a subject of analysis on its own, where general, formalism-independent, principles and properties can be investigated, to be then applied uniformly across different specific formalisms. This paper makes some initial steps in this research direction by introducing a generic labelling-based model of argumentation-based reasoning process, where the notions of argument acceptance, argument justification, and statement justification are clearly distinguished and defined in a formalism-independent way, paving the way towards tunable statement justification. In the study of argumentation-based reasoning, argument justification has received far more attention than statement justification, often treated as a simple byproduct of the former. As a consequence, counterintuitive results and significant losses of sensitivity can be identified in the treatment of statement justification by otherwise appealing formalisms. To overcome this limitation, we propose to reappraise statement justification as a formalism-independent component. To this purpose, we introduce a novel general model of argumentationbased reasoning based on multiple levels of labellings, one of which is devoted to statement justification. This model is able to encompass several literature proposals as special cases: we illustrate this ability for the case of the ASPIC+ formalism and provide a first example of tunable statement justification in this context.

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