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Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions
時間 2020-12-30
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sentence-level Attention
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主要貢獻 作者提出了基於句子級別的Attention模型來選擇有效的句子。 從FreeBase和Wikipedia頁面去獲取實體描述,從而彌補背景知識不足的缺陷,從而給實體更好的representation。 做了很多實驗,效果很好。 任務定義 所有句子被分到N組bags中, {B1,B2,⋯,Bi} { B 1 , B 2 , ⋯ , B i } 每個bag中的的句子都描述了同一組實
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相關文章
1.
【Part two: Related Work】Relation Extraction with Distant Supervision(DS)
2.
論文淺嘗 | Distant Supervision for Relation Extraction
3.
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4.
《GAN Driven Semi-distant Supervision for Relation Extraction》解讀
5.
論文解讀:Combining Distant and Direct Supervision for Neural Relation Extraction
6.
《Neural Relation Extraction with Selective Attention over Instances》淺析
7.
[ACL2016]Neural Relation Extraction with Selective Attention over Instances
8.
論文筆記8:Distant Supervision for Relation Extraction beyond the Sentence Boundary
9.
Distant supervision for relation extraction without labeled data論文理解
10.
[論文研讀]Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
>>更多相關文章<<