Entity Discovery

Entity Recognition

  1. A unified MRC framework for named entity recognition
  2. Leveraging multi-token entities in document-level named entity recognition
  3. Multi-grained named entity recognition
  4. Neural architectures for named entity recognition
  5. Named entity recognition with bidirectional LSTM-CNNs

Entity Typing

  1. Label embedding for zero-shot fine-grained named entity typing
  2. Label noise reduction in entity typing by heterogeneous partial-label embedding

Entity Disambiguation

  1. Improving entity linking by modeling latent relations between mentions
  2. Deep joint entity disambiguation with local neural attention
  3. Entity disambiguation by knowledge and text jointly embedding
  4. Leveraging deep neural networks and knowledge graphs for entity disambiguation

Entity Alignment

  1. Entity alignment between knowledge graphs using attribute embeddings
  2. Multi-view knowledge graph embedding for entity alignment
  3. Co-training embeddings of knowledge graphs and entity descriptions for cross-lingual entity alignment
  4. Bootstrapping entity alignment with knowledge graph embedding
  5. Cross-lingual entity alignment via joint attribute-preserving embedding
  6. Iterative entity alignment via joint knowledge embeddings


Data Scientist

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