Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Updated SOTA NYT freebase and WikiData for RE (ACL 2021) #555

Merged
merged 1 commit into from
Jul 5, 2021
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Updated SOTA NYT freebase and WikiData for RE
Hi,
Please consider the pull request for the updated SOTA table for NYT freebase and Wikidata for relation extraction.

Abhishek
  • Loading branch information
nadgeri14 committed Jun 2, 2021
commit 789d7d617e63065ebdadeddee8f7529932f4c6f9
2 changes: 2 additions & 0 deletions english/relationship_extraction.md
Original file line number Diff line number Diff line change
Expand Up @@ -119,6 +119,7 @@ has increased over the years as systems improve, with earlier systems having ver

| Model | P@10% | P@30% | Paper / Source | Code |
| ----------------------------------- | ----- | ----- | --------------- | -------------- |
| KGPOOL (Nadgeri et al., 2021) | 92.3 | 86.7 | [KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction](https://arxiv.org/pdf/2106.00459.pdf) | [KGPOOL](https://github.com/nadgeri14/KGPool) |
| RECON (Bastos et al., 2021) | 87.5 | 74.1 | [RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network](https://arxiv.org/pdf/2009.08694.pdf) | [RECON](https://github.com/ansonb/RECON) |
| HRERE (Xu et al., 2019) | 84.9 | 72.8 | [Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation Extraction](https://arxiv.org/abs/1903.10126) | [HRERE](https://github.com/billy-inn/HRERE) |
| PCNN+noise_convert+cond_opt (Wu et al., 2019) | 81.7 | 61.8 | [Improving Distantly Supervised Relation Extraction with Neural Noise Converter and Conditional Optimal Selector](https://arxiv.org/pdf/1811.05616.pdf) | |
Expand All @@ -137,6 +138,7 @@ The sentential RE ignores any other occurrence of the given entity pair, thereby

| Model | F1 | Paper / Source | Code |
| ----------------------------------- | ----- | --------------- | -------------- |
| KGPOOL (Nadgeri et al., 2021) | **88.60** | [KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction](https://arxiv.org/pdf/2106.00459.pdf) |
| RECON (Bastos et al., 2021) | **87.23** | [RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network](https://arxiv.org/pdf/2009.08694.pdf) |
| GPGNN (Zhu et al., 2019) | 82.29 | [Graph Neural Networks with Generated Parameters for Relation Extraction](https://www.aclweb.org/anthology/P19-1128.pdf) |
| ContextAware (Sorokin and Gurevych, 2017) | 72.07 | [Context-Aware Representations for Knowledge Base Relation Extraction](https://www.aclweb.org/anthology/D17-1188.pdf) |
Expand Down