%C Denver, Colorado %L discovery10065714 %V 9 %E Matt Post %E Min-Yen Kan %E Steven Bird %J Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015) %X We present two approaches to time expression identification, as entered in to SemEval2015 Task 6, Clinical TempEval. The first is a comprehensive rule-based approach that favoured recall, and which achieved the best recall for time expression identification in Clinical TempEval. The second is an SVM-based system built using readily available components, which was able to achieve a competitive F1 in a short development time. We discuss how the two approaches perform relative to each other, and how characteristics of the corpus affect the suitability of different approaches and their outcomes. %A H Tissot %A G Gorrell %A A Roberts %A L Derczynski %A MDD Fabro %T UFPRSheffield: Contrasting Rule-based and Support Vector Machine Approaches to Time Expression Identification in Clinical TempEval %O Licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License. Permission is granted to make copies for the purposes of teaching and research. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License. %D 2015 %B Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015) %I Association for Computational Linguistics %S International Workshop on Semantic Evaluation (SemEval 2015) %P 835-839