Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions

时间 2020-12-30

标签 sentence-level Attention 繁體版

原文原文链接

主要贡献作者提出了基于句子级别的Attention模型来选择有效的句子。从FreeBase和Wikipedia页面去获取实体描述，从而弥补背景知识不足的缺陷，从而给实体更好的representation。做了很多实验，效果很好。任务定义所有句子被分到N组bags中， {B1,B2,⋯,Bi} { B 1 , B 2 , ⋯ , B i } 每个bag中的的句子都描述了同一组实

>>阅读原文<<

1. 【Part two: Related Work】Relation Extraction with Distant Supervision(DS)
2. 论文浅尝 | Distant Supervision for Relation Extraction
3. Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
4. 《GAN Driven Semi-distant Supervision for Relation Extraction》解读
5. 论文解读：Combining Distant and Direct Supervision for Neural Relation Extraction
6. 《Neural Relation Extraction with Selective Attention over Instances》浅析
7. [ACL2016]Neural Relation Extraction with Selective Attention over Instances
8. 论文笔记8：Distant Supervision for Relation Extraction beyond the Sentence Boundary
9. Distant supervision for relation extraction without labeled data论文理解
10. [论文研读]Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
更多相关文章...
• Swift for 循环 - Swift 教程
• Scala for循环 - Scala教程
• RxJava操作符（七）Conditional and Boolean
• 算法总结-股票买卖

最新文章

1. CVPR 2020 论文大盘点-光流篇
2. Photoshop教程_ps中怎么载入图案？PS图案如何导入？
3. org.pentaho.di.core.exception.KettleDatabaseException:Error occurred while trying to connect to the
4. SonarQube Scanner execution execution Error --- Failed to upload report - 500: An error has occurred
5. idea 导入源码包
6. python学习 day2——基础学习
7. 3D将是页游市场新赛道？
8. osg--交互
9. OSG-交互
10. Idea、spring boot 图片(pgn显示、jpg不显示)解决方案

本站公众号

欢迎关注本站公众号,获取更多信息

1. 【Part two: Related Work】Relation Extraction with Distant Supervision(DS)
2. 论文浅尝 | Distant Supervision for Relation Extraction
3. Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
4. 《GAN Driven Semi-distant Supervision for Relation Extraction》解读
5. 论文解读：Combining Distant and Direct Supervision for Neural Relation Extraction
6. 《Neural Relation Extraction with Selective Attention over Instances》浅析
7. [ACL2016]Neural Relation Extraction with Selective Attention over Instances
8. 论文笔记8：Distant Supervision for Relation Extraction beyond the Sentence Boundary
9. Distant supervision for relation extraction without labeled data论文理解
10. [论文研读]Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks

>>更多相关文章<<