This paper introduces ALEXChat, a hybrid generative-symbolic chatbot designed to enhance the accessibility and explainability of legal expert systems. It integrates symbolic reasoning with large language models (LLMs) to bridge the gap between complex legal reasoning and user comprehension. ALEXChat combines the extraction of legally relevant facts from scenarios, rule-based prolog reasoning and an argumentation framework for conformity assessment, with the linguistic power of LLMs for accessible user fruition.

Billi, M., Parenti, A., Pisano, G., Sanchi, M. (2026). ALEXChat: a Generative - Symbolic Approach to Legal eXplainability. New York : Association for Computing Machinery [10.1145/3769126.3769234].

ALEXChat: a Generative - Symbolic Approach to Legal eXplainability

Billi, Marco;Parenti, Alessandro;Pisano, Giuseppe;Sanchi, Marco
2026

Abstract

This paper introduces ALEXChat, a hybrid generative-symbolic chatbot designed to enhance the accessibility and explainability of legal expert systems. It integrates symbolic reasoning with large language models (LLMs) to bridge the gap between complex legal reasoning and user comprehension. ALEXChat combines the extraction of legally relevant facts from scenarios, rule-based prolog reasoning and an argumentation framework for conformity assessment, with the linguistic power of LLMs for accessible user fruition.
2026
ICAIL '25: Proceedings of the Twentieth International Conference on Artificial Intelligence and Law
491
492
Billi, M., Parenti, A., Pisano, G., Sanchi, M. (2026). ALEXChat: a Generative - Symbolic Approach to Legal eXplainability. New York : Association for Computing Machinery [10.1145/3769126.3769234].
Billi, Marco; Parenti, Alessandro; Pisano, Giuseppe; Sanchi, Marco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1044574
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