{"refrec":{"BRefID":252984,"RR":"<b>Thessen, A.E.; Parr, C.S.</b> (2014). Knowledge extraction and semantic annotation of text from the Encyclopedia of Life. <i>PLoS One 9(3)</i>: e89550. <a href=\"http://dx.doi.org/10.1371/journal.pone.0089550\" target=\"_blank\">dx.doi.org/10.1371/journal.pone.0089550</a>","BEntID":244797,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>PLoS One 9(3)</i>: e89550. <a href=\"https://dx.doi.org/10.1371/journal.pone.0089550\" target=\"_blank\">https://dx.doi.org/10.1371/journal.pone.0089550</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Thessen, A.E.; Parr, C.S.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Thessen, A.E.; Parr, C.S.","Englishabstract":"Numerous digitization and ontological initiatives have focused on translating biological knowledge from narrative text to machine-readable formats. In this paper, we describe two workflows for knowledge extraction and semantic annotation of text data objects featured in an online biodiversity aggregator, the Encyclopedia of Life. One workflow tags text with DBpedia URIs based on keywords. Another workflow finds taxon names in text using GNRD for the purpose of building a species association network. Both workflows work well: the annotation workflow has an F1 Score of 0.941 and the association algorithm has an F1 Score of 0.885. Existing text annotators such as Terminizer and DBpedia Spotlight performed well, but require some optimization to be useful in the ecology and evolution domain. 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