Joint Inference for Knowledge Extraction from Biomedical Literature

@inproceedings{Poon2010JointIF,
  title={Joint Inference for Knowledge Extraction from Biomedical Literature},
  author={Hoifung Poon and Lucy Vanderwende},
  booktitle={HLT-NAACL},
  year={2010}
}
Knowledge extraction from online repositories such as PubMed holds the promise of dramatically speeding up biomedical research and drug design. After initially focusing on recognizing proteins and binary interactions, the community has recently shifted their attention to the more ambitious task of recognizing complex, nested event structures. State-ofthe-art systems use a pipeline architecture in which the candidate events are identified first, and subsequently the arguments. This fails to… CONTINUE READING
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  • On the BioNLP’09 Shared Task dataset, it reduced F1 errors by more than 10% compared to the previous best joint approach.

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