ABSTRACT
Topic entity detection is to find out the main entity asked in a question, which is significant in question answering. Traditional methods ignore the information of entities, especially entity types and their hierarchical structures, restricting the performance. To take full advantage of Knowledge Base(KB) and detect topic entities correctly, we propose a deep neural model to leverage type hierarchy and relations of entities in KB. Experimental results demonstrate the effectiveness of the proposed method.
- Antoine Bordes, Nicolas Usunier, Sumit Chopra, and Jason Weston. 2015. Largescale Simple Question Answering with Memory Networks. CoRR abs/1506.02075 (2015).Google Scholar
- Xiao Ling and Daniel S. Weld. 2012. Fine-Grained Entity Recognition. In Proceedings of AAAI (2012). Google ScholarDigital Library
- Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014. Glove: Global Vectors forWord Representation. In Proceedings of the conference on EMNLP (2014).Google Scholar
- Wenpeng Yin, Mo Yu, Bing Xiang, Bowen Zhou, and Hinrich Schütze. 2016. Simple question answering by attentive convolutional neural network. In Proceedings of COLING (2016).Google Scholar
- Mo Yu, Wenpeng Yin, Kazi Saidul Hasan, Cicero dos Santos, Bing Xiang, and Bowen Zhou. 2017. Improved Neural Relation Detection for Knowledge Base Question Answering. In Proceedings of ACL (2017).Google ScholarCross Ref
Index Terms
- Hierarchical Type Constrained Topic Entity Detection for Knowledge Base Question Answering
Recommendations
Knowledge Graph Embedding Based Question Answering
WSDM '19: Proceedings of the Twelfth ACM International Conference on Web Search and Data MiningQuestion answering over knowledge graph (QA-KG) aims to use facts in the knowledge graph (KG) to answer natural language questions. It helps end users more efficiently and more easily access the substantial and valuable knowledge in the KG, without ...
Joint Detection of Topic Entity and Relation for Simple Question Answering
Knowledge Science, Engineering and ManagementAbstractKnowledge Base is a machine-readable set composed of well-structured relation information between entities, and has become an essential role in automatic question answering. There are two components significant to Knowledge Base Question Answering,...
Joint linking of entity and relation for question answering over knowledge graph
AbstractEntity linking and relation linking are two crucial components in many question answering systems over knowledge graphs, which aim to identify the relevant entity or relation mentions in a question and link them to the target entity or relation in ...
Comments