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Context-Aware Representations for Knowledge Base Relation Extraction論文筆記
時間 2020-12-26
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**文中提出的非常重要的觀點就是 當前 sentence的context中存在的relation會有利於提取當前sentence的relation。 ** 在進行預測的時候使用了context representation 主要的核心思想就是使用了LSTM encoder main contribution就是一個全新的網絡框架。 其實應該還有這個context representation的id
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相關文章
1.
[EMNLP2017]Context-Aware Representations for Knowledge Base Relation Extraction(short paper))
2.
Open Relation Extraction: Relational Knowledge Transfer論文解析
3.
論文淺嘗 | Global Relation Embedding for Relation Extraction
4.
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5.
【論文筆記】Enhancing Pre-Trained Language Representations with Rich Knowledge for MRC
6.
論文筆記8:Distant Supervision for Relation Extraction beyond the Sentence Boundary
7.
論文筆記:Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
8.
論文解讀:Improved Neural Relation Detection for Knowledge Base Question Answering
9.
論文筆記《Knowledge Enhanced Contextual Word Representations》
10.
Improved Neural Relation Detection for Knowledge Base Question Answering
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