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Biomedical triple extraction systems aim to automatically extract biomedical entities and relations between entities.
Multi-fusion chinese wordnet (mcw): Compound of machine learning and manual correction
Mingchen Li, Zili Zhou, and Yanna Wang. 2020 · 2002
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Polysearch: a web-based text mining system for extracting relationships between human diseases, genes, mutations, drugs and metabolites
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Chemprot: a disease chemical biology database
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Constructing a semantic predication gold standard from the biomedical literature
Halil Kilicoglu, Graciela Rosemblat, Marcelo Fiszman, and Thomas C Rindflesch. 2011 · 2011
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Semeval-2013 task 9: Extraction of drug-drug interactions from biomedical texts (ddiextraction 2013)
Isabel Segura-Bedmar, Paloma Martínez Fernández, and María Herrero Zazo. 2013 · 2013
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Pubtator: a web-based text mining tool for assisting biocuration
Chih-Hsuan Wei, Hung-Yu Kao, and Zhiyong Lu. 2013 · 2013
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Bert: Pre-training of deep bidirectional transformers for language understanding
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Biorelex 1.0: Biological relation extraction benchmark
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Xiangrong Zeng, Shizhu He, Daojian Zeng, Kang Liu, Shengping Liu, and Jun Zhao. 2019 · 2019
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Broad-coverage biomedical relation extraction with semrep
Halil Kilicoglu, Graciela Rosemblat, Marcelo Fiszman, and Dongwook Shin. 2020 · 2020
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Pubmed 2.0
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Drug repurposing for covid-19 via knowledge graph completion
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Lasuie: Unifying information extraction with latent adaptive structure-aware generative language model
Unirel: Unified representation and interaction for joint relational triple extraction
Wei Tang, Benfeng Xu, Yuyue Zhao, Zhendong Mao, Yifeng Liu, Yong Liao, and Haiyong Xie. 2022 · 2022
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Dialogue relation extraction with document-level heterogeneous graph attention networks
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