基于深度学习的实体关系抽取研究综述(Review of Entity Relation Extraction based on deep learning)
Zhentao Xia (夏振涛), Weiguang Qu (曲维光), Yanhui Gu (顾彦慧), Junsheng Zhou (周俊生), Bin Li (李斌)
Abstract
作为信息抽取的一项核心子任务,实体关系抽取对于知识图谱、智能问答、语义搜索等自然语言处理应用都十分重要。关系抽取在于从非结构化文本中自动地识别实体之间具有的某种语义关系。该文聚焦句子级别的关系抽取研究,介绍用于关系抽取的主要数据集并对现有的技术作了阐述,主要分为:有监督的关系抽取、远程监督的关系抽取和实体关系联合抽取。我们对比用于该任务的各种模型,分析它们的贡献与缺 陷。最后介绍中文实体关系抽取的研究现状和方法。- Anthology ID:
- 2020.ccl-1.33
- Volume:
- Proceedings of the 19th Chinese National Conference on Computational Linguistics
- Month:
- October
- Year:
- 2020
- Address:
- Haikou, China
- Editors:
- Maosong Sun (孙茂松), Sujian Li (李素建), Yue Zhang (张岳), Yang Liu (刘洋)
- Venue:
- CCL
- SIG:
- Publisher:
- Chinese Information Processing Society of China
- Note:
- Pages:
- 349–362
- Language:
- Chinese
- URL:
- https://aclanthology.org/2020.ccl-1.33
- DOI:
- Cite (ACL):
- Zhentao Xia, Weiguang Qu, Yanhui Gu, Junsheng Zhou, and Bin Li. 2020. 基于深度学习的实体关系抽取研究综述(Review of Entity Relation Extraction based on deep learning). In Proceedings of the 19th Chinese National Conference on Computational Linguistics, pages 349–362, Haikou, China. Chinese Information Processing Society of China.
- Cite (Informal):
- 基于深度学习的实体关系抽取研究综述(Review of Entity Relation Extraction based on deep learning) (Xia et al., CCL 2020)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2020.ccl-1.33.pdf
- Data
- SemEval-2010 Task-8