Electronic patient records, including the Emergency Department (ED) Triage Note (TN), provide a rich source of textual information. Processing clinical texts to create important pieces of structured information will be useful to clinicians treating patients, clinicians in training, and researchers and practitioners in biosurveillance. This work applies natural language processing (NLP) and information extraction (IE) techniques to the TN genre of text. In particular, it presents the Triage Note Temporal Information Extraction System (TN-TIES), which combines a shallow parser, machine learned classifiers, and handwritten rules to identify, extract, and interpret temporal information in TNs in preparation for the automatic creation of a timeline of events leading up to a patient's visit to the ED. The success of TN-TIES suggests that NLP and IE techniques are appropriate for the genre and that the automatic production of a timeline of TN events is a realistic application.