| Literature DB >> 22554700 |
Erik M van Mulligen1, Annie Fourrier-Reglat, David Gurwitz, Mariam Molokhia, Ainhoa Nieto, Gianluca Trifiro, Jan A Kors, Laura I Furlong.
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.Entities:
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Year: 2012 PMID: 22554700 DOI: 10.1016/j.jbi.2012.04.004
Source DB: PubMed Journal: J Biomed Inform ISSN: 1532-0464 Impact factor: 6.317