Paper: IxaMed: Applying Freeling and a Perceptron Sequential Tagger at the Shared Task on Analyzing Clinical Texts

ACL ID S14-2061
Title IxaMed: Applying Freeling and a Perceptron Sequential Tagger at the Shared Task on Analyzing Clinical Texts
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This paper presents the results of the Ix- aMed team at the SemEval-2014 Shared Task 7 on Analyzing Clinical Texts. We have developed three different sys- tems based on: a) exact match, b) a general-purpose morphosyntactic analyzer enriched with the SNOMED CT termi- nology content, and c) a perceptron se- quential tagger based on a Global Linear Model. The three individual systems re- sult in similar f-score while they vary in their precision and recall. We have also tried direct combinations of the individual systems, obtaining considerable improve- ments in performance.