Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy (ECAI2020)
0. 引言 1. 摘要 實體和關係聯合提取的目的是利用單一模型檢測實體對及其關係。以往的工作通常採用先提取後分類或統一標註的方式來解決這個問題。但是，這些方法在提取實體和關係的過程中要麼存在冗餘實體對，要麼忽略了重要的內部結構。針對這些侷限性，本文首先將聯合抽取任務分解爲兩個相互關聯的子任務，即HE抽取和TER抽取。前一個子任務是區分所有可能涉及到目標關係的頭實體，後一個子任務是識別每個提取的頭實
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相關文章
- 1. [IJCAI-ECAI2018]Joint Extraction of Entities and Relations Based on a Novel Graph Scheme
- 2. 論文閱讀筆記－CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
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- 4. 實體-關係聯合抽取：CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
- 5. 實體-關係聯合抽取：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. 【論文筆記】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