Fig. 2

Detection of actionable reports with BERT (a) without and (b) with order information. Each sequence was fed into the BERT classifier after adding special tokens (e.g., [CLS] and [SEP]) and padding with [PAD] tokens that are required by the standard specification of BERT. Generally, BERT models output a 512 × 768 hidden state matrix (indicated by **), part of which is a 768-dimensional feature vector for classification tasks (indicated by *). We used only the feature vector for classification tasks and discarded the rest of the hidden state matrix, as in the standard procedure