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On Generative Models And Joint Architectures For Document-Level Relation Extraction, Aviv Brokman
On Generative Models And Joint Architectures For Document-Level Relation Extraction, Aviv Brokman
Theses and Dissertations--Statistics
Biomedical text is being generated at a high rate in scientific literature publications and electronic health records. Within these documents lies a wealth of potentially useful information in biomedicine. Relation extraction (RE), the process of automating the identification of structured relationships between entities within text, represents a highly sought-after goal in biomedical informatics, offering the potential to unlock deeper insights and connections from this vast corpus of data. In this dissertation, we tackle this problem with a variety of approaches.
We review the recent history of the field of document-level RE. Several themes emerge. First, graph neural networks dominate the …