IEEE/ACM Trans Comput Biol Bioinform 2019 Mar 11. Epub 2019 Mar 11.
We present an analysis of the problem of identifying biolog- ical context and associating it with biochemical events in biomedical texts. This constitutes a non-trivial, inter-sentential relation extraction task. We focus on biological context as descr iptions of the species, tissue type and cell type that are associated with biochemical events. We present a new cor pus of open access biomedical texts that have been annotated by biology subject matter exper ts to highlight context- event relations. Using this cor pus, we evaluate several classiers for context-event association along with a detailed analysis of the impact of a var iety of linguistic features on classier perfor mance. We finnd that gradient tree boosting performs by far the best, achieving an F1 of 0.865 in a cross-validation study.