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