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Found 6 papers, 1 papers with code
Multi-layer Sequence Labeling-based Joint Biomedical Event Extraction
Hence, we propose MLSL, a method based on multi-layer sequence labeling for joint biomedical event extraction.
Pipelined Biomedical Event Extraction Rivaling Joint Learning
Biomedical event extraction is an information extraction task to obtain events from biomedical text, whose targets include the type, the trigger, and the respective arguments involved in an event.
Joint Learning-based Causal Relation Extraction from Biomedical Literature
Causal relation extraction of biomedical entities is one of the most complex tasks in biomedical text mining, which involves two kinds of information: entity relations and entity functions.
Modeling Graph Structure in Transformer for Better AMR-to-Text Generation
Recent studies on AMR-to-text generation often formalize the task as a sequence-to-sequence (seq2seq) learning problem by converting an Abstract Meaning Representation (AMR) graph into a word sequence.
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