# Dealing with Qualitative and Quantitative Features in Legal Domains

## TL;DR

This paper enhances argumentation formalism for legal reasoning by integrating qualitative and quantitative feature labels, enabling more nuanced and knowledge-aware argument analysis within legal domains.

## Contribution

It introduces a formal method to incorporate and propagate feature meta-data in argumentation graphs for legal reasoning.

## Key findings

- Effective propagation of feature labels in argumentative graphs
- Improved reasoning capabilities in legal argumentation models
- Enhanced formalism for handling diverse data types in legal contexts

## Abstract

In this work, we enrich a formalism for argumentation by including a formal characterization of features related to the knowledge, in order to capture proper reasoning in legal domains. We add meta-data information to the arguments in the form of labels representing quantitative and qualitative data about them. These labels are propagated through an argumentative graph according to the relations of support, conflict, and aggregation between arguments.