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Lexical, Terminological and Ontological Resources for Biological Text Mining
Biomedical terminologies and ontologies are frequently described as enabling resources in text mining systems [e.g., 1, 2, 3]. These resources are used to supports tasks such as entity recognition (i.e., the identification of biomedical entities in text) and relation extraction (i.e., the identification of relationships among biomedical entities). Although a significant part of current text mining efforts focuses on the analysis of documents related to molecular biology, the use of lexical, terminological and ontological resources is mentioned in research systems developed for the analysis of clinical narratives (e.g., MedSyndikate ) or the biological literature (e.g., BioRAT , GeneScene , EMPathIE  and PASTA ). Of note, some systems initially developed for extracting clinical information have later been adapted to extract relations among biological entities (e.g., MedLEE  / GENIES , SemRep / SemGen ). Commercial systems such as TeSSIi also make use of such resources.