From: Exploiting sequence labeling framework to extract document-level relations from biomedical texts
System | Method | Concept level | P | R | F1 |
---|---|---|---|---|---|
CD-REST [6] | SVM + SVM | Sen + Doc | 0.596 | 0.440 | 0.507 |
Gu et al. (2016) [7] | ME + ME | Sen + Doc | 0.620 | 0.551 | 0.583 |
Zhou et al. [17] | LSTM-SVM | Sen | 0.649 | 0.493 | 0.560 |
LSTM-SVM + pp | Sen + Doc | 0.556 | 0.684 | 0.613 | |
Gu et al. (2017) [8] | CNN + ME | Sen + Doc | 0.609 | 0.595 | 0.602 |
CNN + ME + pp | Sen + Doc | 0.557 | 0.681 | 0.613 | |
RPCNN [9] | CNN-RNN | Doc | 0.552 | 0.636 | 0.591 |
BRAN [10] | Transformer | Doc | 0.499 | 0.638 | 0.555 |
Transformer-NER | Doc | 0.556 | 0.708 | 0.621 | |
Zheng et al. [11] | LSTM-CNN | Doc | 0.543 | 0.659 | 0.595 |
LSTM-CNN + pp | Doc | 0.562 | 0.680 | 0.615 | |
Bio-Seq | LSTM-CRF | Doc | 0.600 | 0.675 | 0.635 |