Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy (ECAI2020)
0. 引言 1. 摘要 实体和关系联合提取的目的是利用单一模型检测实体对及其关系。以往的工作通常采用先提取后分类或统一标注的方式来解决这个问题。但是，这些方法在提取实体和关系的过程中要么存在冗余实体对，要么忽略了重要的内部结构。针对这些局限性，本文首先将联合抽取任务分解为两个相互关联的子任务，即HE抽取和TER抽取。前一个子任务是区分所有可能涉及到目标关系的头实体，后一个子任务是识别每个提取的头实
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相关文章
- 1. [IJCAI-ECAI2018]Joint Extraction of Entities and Relations Based on a Novel Graph Scheme
- 2. 论文阅读笔记－CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
- 3. [ACL2017]Going out on a limb:Joint Extraction of Entity Mentions and Relations without Depende...
- 4. 实体-关系联合抽取：CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
- 5. 实体-关系联合抽取：Incremental Joint Extraction of Entity Mentions and Relations
- 6. 【Bilinear Pooling】《A Novel DR Classfication Scheme based on Compact Bilinear Pooling CNN and GBDT》
- 7. 【论文笔记】Discrete-State Variational Autoencoders for Joint Discovery and Factorization of Relations
- 8. embedding entities and relations for learning and inference knowledge base
- 9. Knowledge Graph Embedding: A Survey of Approaches and Applications 摘要
- 10. A perceptual quantization strategy for HEVC based on a convolutional neural network trained on natur