A neural SRL model that attends to labels of similar training sentences via an associated memory network reaches 89.6 F1 on CoNLL-2009 English in-domain, 79.7 on Brown, and 83.8 on Chinese, with small, consistent gains over its BiLSTM baseline.
Learning for Biomedical Information Extraction: Methodological Review of Recent Advances
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abstract
Biomedical information extraction (BioIE) is important to many applications, including clinical decision support, integrative biology, and pharmacovigilance, and therefore it has been an active research. Unlike existing reviews covering a holistic view on BioIE, this review focuses on mainly recent advances in learning based approaches, by systematically summarizing them into different aspects of methodological development. In addition, we dive into open information extraction and deep learning, two emerging and influential techniques and envision next generation of BioIE.
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Semantic Role Labeling with Associated Memory Network
A neural SRL model that attends to labels of similar training sentences via an associated memory network reaches 89.6 F1 on CoNLL-2009 English in-domain, 79.7 on Brown, and 83.8 on Chinese, with small, consistent gains over its BiLSTM baseline.