Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.04.233049v1?rss=1 Authors: Slater, L. T., Bradlow, W., Hoehndorf, R., Motti, D. F., Ball, S., Gkoutos, G. V. Abstract: Komenti is a reasoner-enabled semantic query and information extraction tool. It is the only text mining tool that enables querying inferred knowledge from biomedical ontologies. It also contains multiple novel components for vocabulary construction and context disambiguation, which can improve the power of text mining and ontology-based analysis tasks, with a view towards making full use of the semantic provision of biomedical ontologies in the text extraction and characterisation space. Here, we describe Komenti, its features, and a use case wherein we automate a clinical audit process, classifying the medications of patients with hypertrophic cardiomyopathy from text records, revealing a high precision, and a subcohort of candidate patients who have atrial fibrillation but were not anti-coagulated, and are therefore at a higher risk of stroke. Copy rights belong to original authors. Visit the link for more info