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[ACL2016]End-to-end Relation Extraction using LSTMs on Sequence and Tree Structures
時間 2020-12-30
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框架圖解釋了文章的思想: 1: 利用一個三層網絡框架識別實體,實體用B(begin), I(Inside), L(Last), S(single), O(Outside)的表示, 第一層用BiLSTM更好的表示單詞的語義,中間hidden層,輸出層softmax, 輸出層節點用的個數等於4×len(實體類型)+1,這個1的意思就是outside, 比如實體的類型有人名,就表示爲B-PER, I-P
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相關文章
1.
知識圖譜4-【再看一篇論文《End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures》】
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9.
"RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information"簡略筆記
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