Biaffine attention

Reported on 2 benchmarks across 1 task · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing2 results

Relation ExtractiononCoNLL04
NER Macro F1· 2018-12-29
86.2
best: 87 (Deeper)
SOTA
End-to-end neural relation extraction using deep biaffine attention arXiv:1812.11275
Relation ExtractiononCoNLL04
RE+ Macro F1 · 2018-12-29
64.4
best: 76.65 (REBEL)
SOTA
End-to-end neural relation extraction using deep biaffine attention arXiv:1812.11275