• We derive pre-trained contextual character embeddings from Flair<cite> (Akbik et al., 2018)</cite> , apply them to a state-of-the art time normalizer (Laparra et al., 2018a) , and obtain major performance improvements over the previous state-of-the-art: 51% error reduction in news and 33% error reduction in clinical notes.