no code implementations • 13 Jan 2022 • Chao Zhao, Daojian Zeng, Lu Xu, Jianhua Dai
Document-level Relation Extraction (DRE) aims to recognize the relations between two entities.
Ranked #5 on
Relation Extraction
on CDR
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan, Heng Ji, Daojian Zeng, Fei Cheng, Daisuke Kawahara, Sadao Kurohashi
We propose a novel Sequence-to-Unordered-Multi-Tree (Seq2UMTree) model to minimize the effects of exposure bias by limiting the decoding length to three within a triplet and removing the order among triplets.
2 code implementations • 24 Nov 2019 • Daojian Zeng, Ranran Haoran Zhang, Qianying Liu
The model is extremely weak at differing the head and tail entity, resulting in inaccurate entity extraction.
Ranked #12 on
Relation Extraction
on WebNLG
no code implementations • IJCNLP 2019 • Xiangrong Zeng, Shizhu He, Daojian Zeng, Kang Liu, Shengping Liu, Jun Zhao
Existing works didn{'}t consider the extraction order of relational facts in a sentence.
1 code implementation • ACL 2018 • Xiangrong Zeng, Daojian Zeng, Shizhu He, Kang Liu, Jun Zhao
The relational facts in sentences are often complicated.
Ranked #13 on
Relation Extraction
on WebNLG