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Towards reliable named entity recognition in the biomedical domain
[article]
2019
bioRxiv
pre-print
Motivation: Automatic biomedical named entity recognition (BioNER) is a key task in biomedical information extraction (IE). For some time, state-of-the-art BioNER has been dominated by machine learning methods, particularly conditional random fields (CRFs), with a recent focus on deep learning. However, recent work has suggested that the high performance of CRFs for BioNER may not generalize to corpora other than the one it was trained on. In our analysis, we find that a popular deep
doi:10.1101/526244
fatcat:b2w22dcs4bezzjrtlyfwdrwllm