Network-based approaches have become extremely important in systems biology to 
achieve a better understanding of biological mechanisms. For network 
representation, the Biological Expression Language (BEL) is well designed to 
collate findings from the scientific literature into biological network models. 
To facilitate encoding and biocuration of such findings in BEL, a BEL 
Information Extraction Workflow (BELIEF) was developed. BELIEF provides a 
web-based curation interface, the BELIEF Dashboard, that incorporates text 
mining techniques to support the biocurator in the generation of BEL networks. 
The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several 
named entity recognition processes and relationship extraction methods to detect 
concepts and BEL relationships in literature. The BELIEF Dashboard allows easy 
curation of the automatically generated BEL statements and their context 
annotations. Resulting BEL statements and their context annotations can be 
syntactically and semantically verified to ensure consistency in the BEL 
network. In summary, the workflow supports experts in different stages of 
systems biology network building. Based on the BioCreative V BEL track 
evaluation, we show that the BELIEF Pipeline automatically extracts 
relationships with an F-score of 36.4% and fully correct statements can be 
obtained with an F-score of 30.8%. Participation in the BioCreative V 
Interactive task (IAT) track with BELIEF revealed a systems usability scale 
(SUS) of 67. Considering the complexity of the task for new users-learning BEL, 
working with a completely new interface, and performing complex curation-a score 
so close to the overall SUS average highlights the usability of BELIEF.Database 
URL: BELIEF is available at http://www.scaiview.com/belief/.