A Neural Edge-Editing Approach for Document-Level Relation Graph Extraction - ACL Anthology

This is an internal, incomplete preview of a proposed change to the ACL Anthology. For efficiency reasons, we generate only three BibTeX files per volume, and the preview may be incomplete in other ways, or contain mistakes. Do not treat this content as an official publication.

A Neural Edge-Editing Approach for Document-Level Relation Graph Extraction

Kohei Makino, Makoto Miwa, Yutaka Sasaki

Anthology ID:: 2021.findings-acl.234
Volume:: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:: August
Year:: 2021
Address:: Online
Editors:: Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
Venue:: Findings
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 2653–2662
Language:
URL:: https://aclanthology.org/2021.findings-acl.234
DOI:: 10.18653/v1/2021.findings-acl.234
Bibkey:
Cite (ACL):: Kohei Makino, Makoto Miwa, and Yutaka Sasaki. 2021. A Neural Edge-Editing Approach for Document-Level Relation Graph Extraction. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 2653–2662, Online. Association for Computational Linguistics.
Cite (Informal):: A Neural Edge-Editing Approach for Document-Level Relation Graph Extraction (Makino et al., Findings 2021)
Copy Citation:
PDF:: https://preview.aclanthology.org/dois-2013-emnlp/2021.findings-acl.234.pdf
Video:: https://preview.aclanthology.org/dois-2013-emnlp/2021.findings-acl.234.mp4
Code: tti-coin/edge-editing

PDF Search Code Video