Before revision:  We lastly introduce a novel large-scale dataset constructed from online Terms-of-Service documents, on which we compare against various traditional and deep learning baselines, showing significantly better performance of Transformer-based methods.
After revision:  We lastly introduce a novel large-scale dataset constructed from online Terms-of-Service documents, including hierarchical topic annotations, which we use for training. Results show that our proposed system significantly outperforms baselines, and adapts well to structural peculiarities of legal documents. We release both data and trained models to the research community for future URL