The EU-ADR corpus: annotated drugs, diseases, targets, and their relationships.

van Mulligen, Erik M; Fourrier-Reglat, Annie; Gurwitz, David; Molokhia, Mariam; Nieto, Ainhoa; Trifiro, Gianluca; Kors, Jan A; Furlong, Laura I · J Biomed Inform · 2012

other · Level V

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Abstract

Corpora with specific entities and relationships annotated are essential to train and evaluate text-mining systems that are developed to extract specific structured information from a large corpus. In this paper we describe an approach where a named-entity recognition system produces a first annotation and annotators revise this annotation using a web-based interface. The agreement figures achieved show that the inter-annotator agreement is much better than the agreement with the system provided annotations. The corpus has been annotated for drugs, disorders, genes and their inter-relationships. For each of the drug-disorder, drug-target, and target-disorder relations three experts have annotated a set of 100 abstracts. These annotated relationships will be used to train and evaluate text-mining software to capture these relationships in texts.

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