@article{
 title = {Annotation guidelines for machine learning-based named entity recognition in microbiology},
 type = {article},
 year = {2006},
 keywords = {annotation guidelines,machine learning,named entity recognition},
 pages = {40–54},
 websites = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.112.6401&rep=rep1&type=pdf},
 publisher = {Citeseer},
 id = {4e2e0ad6-9fef-399c-8707-68f2c6b464f3},
 created = {2011-12-28T07:04:55.000Z},
 file_attached = {false},
 profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},
 group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},
 last_modified = {2017-03-14T14:36:19.698Z},
 tags = {named entities},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Nedellec2006},
 private_publication = {false},
 abstract = {Recent challenges on machine learning application to named-entity recognition in biology trigger discussions on the manual annotation guidelines for annotating the learning corpora. Some sources of potential inconsistency have been identified by corpus annotators and challenge participants. We go one step further by proposing specific annotation guidelines for biology and evaluating their effect on performances of machine learning methods. We show that a significant improvement can be achieved by this way that is not due to the feature set neither to the ML methods.},
 bibtype = {article},
 author = {Nédellec, C and Bessieres, P and Bossy, Robert and Kptoujanksy, A and Manine, A P},
 journal = {Machine Learning}
}

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