Figure 1.

System overview. ezTag connects multiple resources to provide efficient and effective biological concept tagging. Input and output documents are handled using the BioC format, and user-provided lexicons are used for string match and machine learning-based taggers. The options for automatic concept tagging in text are (i) the string match-based tagger using a lexicon, (ii) the machine learning-based tagger using TaggerOne for customized tagging modules and (iii) the pre-trained taggers.