Extraction of Biomedical Events

Abstract

In this paper we describe a memory-based machine learning system that extracts biomedical events from texts relying on information from contextual and syntactic features. The main characteristics of the system are that it uses information from dependency syntax and that it integrates classifiers that learn event triggers and event participants jointly. The results show that this system is more efficient than a similar memory-based system that used shallow context information and integrated classifiers in a traditional pipeline architecture.