Finally, to further confirm the large potential of BERT, even in tasks which involve many labels, a lack of training data, and a very specific style of communication, we have obtained a clear improvement over all other systems when employing this state-of-the-art architecture, trained on manifesto quasi-sentences and further fine-tuned on motions.
2 these are unsuitable due to, in the former case, the fact that they incorporate no opinion or policy preference information, and for the latter, being unsystematic, insufficient in both quantity and coverage of the topics that appear in Hansard, and not future-proof (that is, they do not cover unseen topics that may arise (Abercrombie and Batista-Navarro, 2018b)).