Not Just Plain Text! Fuel Document-Level Relation Extraction with Explicit Syntax Refinement and Subsentence Modeling
Zhichao Duan, Xiuxing Li, Zhenyu Li, Zhuo Wang, Jianyong Wang
Abstract
Document-level relation extraction (DocRE) aims to identify semantic labels among entities within a single document. One major challenge of DocRE is to dig decisive details regarding a specific entity pair from long text. However, in many cases, only a fraction of text carries required information, even in the manually labeled supporting evidence. To better capture and exploit instructive information, we propose a novel expLicit syntAx Refinement and Subsentence mOdeliNg based framework (LARSON). By introducing extra syntactic information, LARSON can model subsentences of arbitrary granularity and efficiently screen instructive ones. Moreover, we incorporate refined syntax into text representations which further improves the performance of LARSON. Experimental results on three benchmark datasets (DocRED, CDR, and GDA) demonstrate that LARSON significantly outperforms existing methods.- Anthology ID:
- 2022.findings-emnlp.140
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2022
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates
- Editors:
- Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1941–1951
- Language:
- URL:
- https://aclanthology.org/2022.findings-emnlp.140
- DOI:
- 10.18653/v1/2022.findings-emnlp.140
- Cite (ACL):
- Zhichao Duan, Xiuxing Li, Zhenyu Li, Zhuo Wang, and Jianyong Wang. 2022. Not Just Plain Text! Fuel Document-Level Relation Extraction with Explicit Syntax Refinement and Subsentence Modeling. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 1941–1951, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
- Cite (Informal):
- Not Just Plain Text! Fuel Document-Level Relation Extraction with Explicit Syntax Refinement and Subsentence Modeling (Duan et al., Findings 2022)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2022.findings-emnlp.140.pdf