[ACL2017]Going out on a limb:Joint Extraction of Entity Mentions and Relations without Depende...
本文聲稱是第一個神經網絡聯合模型， 同時抽取實體，關係以及關係類型。在解析句子中每一個詞時，同時輸出實體標籤和關係標籤。 另外在特徵部分只使用了word_embedding, 沒有用POS和dependency tree等其他特徵 本文的網絡架構是一個輸入層，兩個輸出層（一個輸出層用來輸出實體標籤，一個輸出層用來輸出關係標籤） 在說明文中模型之前，先了解下entity label的形式，實體是由一
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相關文章
- 1. 實體-關係聯合抽取：Incremental Joint Extraction of Entity Mentions and Relations
- 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. [ACL2016]End-to-end Relation Extraction using LSTMs on Sequence and Tree Structures
- 5. 論文閱讀筆記－CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
- 6. Entity-Relation Extraction as Multi-turn Question Answering
- 7. 論文學習16-Going out on a limb: without Dependency Trees
- 8. 【Part two: Related Work】Relation Extraction with Distant Supervision(DS)
- 9. 【論文筆記】Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems
- 10. 實體-關係聯合抽取：CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases