GEA is a fully-implemented, complete and modular NLG system for generating user tailored evaluative arguments. GEA covers all aspects of generating evaluative arguments from selecting and organizing the content of the argument, to expressing the selected content into natural language. For content selection and organization, GEA applies an argumentation strategy based on guidelines from argumentation theory. For expressing the content into natural language, GEA relies on a set of techniques that extend and integrate previous work in computational linguistics on micro-planning and realizing evaluative arguments. Finally, a quantitative model of user preferences expressed as an additive multiattribute value function (AMVF) is the key knowledge source used by GEA in tailoring the content, organization and phrasing of the generated arguments to its users.