A BERT-powered multi-head selection model with soft label embedding and weak-supervision NER pretraining reaches F1 0.876 single and 0.892 ensembled on the SKE Chinese information extraction benchmark.
”Kernel methods for relation extraction.” Journal of machine learning research 3.Feb (2003): 1083-1106
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BERT-Based Multi-Head Selection for Joint Entity-Relation Extraction
A BERT-powered multi-head selection model with soft label embedding and weak-supervision NER pretraining reaches F1 0.876 single and 0.892 ensembled on the SKE Chinese information extraction benchmark.