論文閱讀筆記－CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases 文章綜述 本文主要解決在遠程監督的過程中面臨的三大挑戰：需要事先訓練的命名實體抽取器限制了領域的擴展；講實體抽取和關係抽取分開導致錯誤的傳遞累計、在遠程監督當中面臨的標籤噪聲問題（遠程監督假設失效問題）。本文通過利用實體和關係的聯合抽取來解決這
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相關文章
- 1. 實體-關係聯合抽取：CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
- 2. Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy (ECAI2020)
- 3. [IJCAI-ECAI2018]Joint Extraction of Entities and Relations Based on a Novel Graph Scheme
- 4. 閱讀筆記 Joint Event and Temporal Relation Extraction with Shared Representations and Structured ...
- 5. 【論文筆記】Discrete-State Variational Autoencoders for Joint Discovery and Factorization of Relations
- 6. Joint Training of Candidate Extraction and Answer Selection for Reading Comprehension 論文閱讀筆記
- 7. 【論文閱讀筆記】Span-based Joint Entity and Relation Extraction with Transformer Pre-training
- 8. embedding entities and relations for learning and inference knowledge base
- 9. 【論文閱讀筆記】Linguistic Knowledge and Transferability of Contextual Representations
- 10. EMNLP2020 | 近期必讀Relation Extraction精選論文