A Chatbot Framework for the Children's Legal Centre

Jay Morgan (1) , Adeline Paiement (1, 2) , Monika Seisenberger (1) , Jane Williams (1) , Adam Wyner (1)

1 Swansea University
2 DYNI - DYNamiques de l’Information

This paper presents a novel method to address legal rights for children through a chatbot framework by integrating machine learning, a dialogue graph, and information extraction. The method addresses a significant problem: we cannot presume that children have common knowledge about their rights or express themselves as an adult might. In our framework, a chatbot user begins a conversation, where based on the circumstance described, a neural network predicts both speech acts, relating to a dialogue graph, and legal types. Based on the legal types, relevant legal rights are returned to the user. Information is extracted throughout the conversation in order to create a case for a legal advisor. In collaboration with the Children's Legal Centre Wales, who advocate for the improvement and dissemination of legal rights in Wales, a corpus has been constructed and a prototype chatbot developed. The framework has been evaluated with classification measures and a user study. The framework can be extended and adapted to other domains.

Mots clés: Machine Learning; Natural Language Processing; Children's Legal Rights; Recurrent Neural Networks; Chatbot

Domaines: Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Réseau de neurones [cs.NE]; Ordinateur et société [cs.CY]; Interface homme-machine [cs.HC]; Recherche d'information [cs.IR]; Traitement du texte et du document; Droit

Jay Morgan, Adeline Paiement, Monika Seisenberger, Jane Williams, Adam Wyner. A Chatbot Framework for the Children's Legal Centre. The 31st international conference on Legal Knowledge and Information Systems (JURIX), Dec 2018, Groningen, Netherlands. ⟨hal-01878545v2⟩