Global Normalization of Convolutional Neural Networks for Joint Entity and Relation Classification

时间 2020-12-30

标签 ner nlp 繁體版

原文原文链接

这篇是2017年EMNLP收录的论文。本文提出了一种新的实体分类(EC)和关系抽取(RE)的方法。如果对BiLSTM+crf有一定了解的话理解这篇论文就容易得多，因为他的整体思想是基于BiLSTM+crf的。作者提出关系抽取对命名实体的识别有很大的作用，比如可以消除歧义问题，如mercedes可以是person，location，organization，但当提取出关系（live-in）后，就

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1. [EMNLP2017]Global Normalization of Convolutional Neural Networks for Joint Entity and Relation
2. Bag of Tricks for Image Classification with Convolutional Neural Networks
3. Recurrent Convolutional Neural Networks for Text Classification
4. Appearance-and-Relation Networks for Video Classification
5. Convolutional Neural Networks for Sentence Classification
6. Understanding Convolutional Neural Networks for NLP
7. [转] Understanding Convolutional Neural Networks for NLP
8. Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
9. 《Convolutional Neural Networks for Sentence Classification》
10. How to Use Convolutional Neural Networks for Time Series Classification

>>更多相关文章<<