The performance of clinical natural language processing and text mining systems is significantly affected by the previous recognition and definition resolution of medical abbreviations. To promote the development of such key components, the second Biomedical Abbreviation Recognition and Resolution (BARR2) competition was organised The overall aim of this effort was to evaluate strategies for detecting automatically mentions of abbreviations in running text, as well as returning their corresponding definition given the corresponding context from Spanish clinical case
studies. A Spanish clinical case corpus (SPACCC) was provided, annotated by hand by domain experts with abbreviation mentions together with their corresponding definitions, resulting in the BARR2 corpus.
