[ACL2017]Going out on a limb:Joint Extraction of Entity Mentions and Relations without Depende...
本文声称是第一个神经网络联合模型， 同时抽取实体，关系以及关系类型。在解析句子中每一个词时，同时输出实体标签和关系标签。 另外在特征部分只使用了word_embedding, 没有用POS和dependency tree等其他特征 本文的网络架构是一个输入层，两个输出层（一个输出层用来输出实体标签，一个输出层用来输出关系标签） 在说明文中模型之前，先了解下entity label的形式，实体是由一
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相关文章
- 1. 实体-关系联合抽取：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. 论文阅读笔记－CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
- 6. Entity-Relation Extraction as Multi-turn Question Answering
- 7. 论文学习16-Going out on a limb: without Dependency Trees
- 8. 【Part two: Related Work】Relation Extraction with Distant Supervision(DS)
- 9. 【论文笔记】Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems
- 10. 实体-关系联合抽取：CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases