It is common that entity mentions can contain other mentions recursively. This paper introduces a scalable transition-based method to model the nested structure of mentions... (read more)
PDFTASK | DATASET | MODEL | METRIC NAME | METRIC VALUE | GLOBAL RANK | BENCHMARK |
---|---|---|---|---|---|---|
Nested Mention Recognition | ACE 2004 | Neural transition-based model | F1 | 73.1 | # 6 | |
Nested Named Entity Recognition | ACE 2004 | Neural transition-based model | F1 | 73.3 | # 7 | |
Named Entity Recognition | ACE 2004 | Neural transition-based model | F1 | 73.3 | # 6 | |
Nested Mention Recognition | ACE 2005 | Neural transition-based model | F1 | 73.0 | # 8 | |
Named Entity Recognition | ACE 2005 | Neural transition-based model | F1 | 73.0 | # 10 | |
Nested Named Entity Recognition | ACE 2005 | neural transition-based model | F1 | 73.0 | # 10 | |
Named Entity Recognition | GENIA | Neural transition-based model | F1 | 73.9 | # 9 | |
Nested Named Entity Recognition | GENIA | Neural transition-based model | F1 | 73.9 | # 12 |
METHOD | TYPE | |
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🤖 No Methods Found | Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet |