We present the design, preparation, results and analysis of the Cancer Genetics (CG) event extraction task, a main task of the BioNLP Shared Task (ST) 2013. The CG task is an information extraction task targeting the recognition of events in text, represented as structured n-ary associations of given physical entities. In addition to addressing the cancer domain, the CG task is differentiated from previous event extraction tasks in the BioNLP ST series in addressing a wide range of pathological processes and multiple levels of biological organization, ranging from the molecular through the cellular and organ levels up to whole organisms. Final test set submissions were accepted from six teams. The highest-performing system achieved an Fscore of 55.4%. This level of performance is broadly comparable with the state of the art for established molecular-level extraction tasks, demonstrating that event extraction resources and methods generalize well to higher levels of biological organization and are applicable to the analysis of scientific texts on cancer. The CG task continues as an open challenge to all interested parties, with tools and resources available from http://2013. bionlp-st.org/.
In the Cancer Genetics (CG) task of BioNLP ST 2013 REF , which aims to identify biological processes as related to the development and progression of cancer, the types of events are extended to include pathological and anatomical processes such as 'Carcinogenesis' and 'Cell differentiation'.
Overview of the Cancer Genetics (CG) task of BioNLP Shared Task 2013
BioNLP
Computer Science