351-joint-entity-and-relation-extraction-with-set-prediction-networks
Science Score: 18.0%
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (1.5%) to scientific vocabulary
Last synced: 9 months ago
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Repository
Basic Info
- Host: GitHub
- Owner: SZU-AdvTech-2023
- Language: Python
- Default Branch: main
- Size: 8.05 MB
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- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 2 years ago
· Last pushed over 2 years ago
Metadata Files
Citation
https://github.com/SZU-AdvTech-2023/351-Joint-Entity-and-Relation-Extraction-with-Set-Prediction-Networks/blob/main/
## ### Requirement: ``` Python: 3.7 PyTorch: >= 1.5.0 Transformers: 2.6.0 ``` ### model train * BERT_DIRBERT ```shell python -m main --bert_directory BERT_DIR --num_generated_triples 15 --na_rel_coef 1 --max_grad_norm 1 --max_epoch 100 --max_span_length 10 ``` ### or ```shell python -m main --bert_directory BERT_DIR --num_generated_triples 15 --max_grad_norm 2.5 --na_rel_coef 0.25 --max_epoch 100 --max_span_length 10 ```
Owner
- Name: SZU-AdvTech-2023
- Login: SZU-AdvTech-2023
- Kind: organization
- Repositories: 1
- Profile: https://github.com/SZU-AdvTech-2023
Citation (citation.txt)
@article{REPO351,
author = "Sui, Dianbo and Zeng, Xiangrong and Chen, Yubo and Liu, Kang and Zhao, Jun",
journal = "IEEE Transactions on Neural Networks and Learning Systems",
title = "{Joint Entity and Relation Extraction with Set Prediction Networks}",
year = "2023"
}