Real Life Application of a Question Answering System Using BERT Language Model

Abstract

Real life scenarios are often left untouched by the newest advances in research. They usually require the resolution of some specific task applied to a restricted domain, all the while providing small amounts of data to begin with. In this study we apply one of the newest innovations in Deep Learning to a task of text classification. The goal is to create a question answering system in Italian that provides information about a specific subject, e-invoicing and digital billing. Italy recently introduced a new legislation about e-invoicing and people have some legit doubts, therefore a large share of professionals could benefit from this tool. We gathered few pairs of question and answers; afterwards, we expanded the data, using it as a training corpus for BERT language model. Through a separate test corpus we evaluated the accuracy of the answer provided. Values show that the automatic system alone performs surprisingly well. The demo interface is hosted on Telegram, which makes the system immediately available to test.