Abstract
The emerging Linked Open Data provides an opportunity to answer the natural language question based on knowledge bases (KB). One challenge of the question answering (QA) problem is to link the entity mention in the question with the entity in the existing knowledge base. This study proposes an approach to link entity mention with a DBpedia entity. We propose an entity-centric indexing model to help search candidate entities in KB. After obtaining the candidate entities, we expand the context of the entity mention with WordNet and ConceptNet, we compute the context similarity between the expanded context and the property value of the candidate entity and the popularity of the candidate entity. Finally, we rerank the candidate entities by leveraging these features. Evaluations are performed on DBpedia version 2015, the evaluation tests show that our approach is promising in dealing with linking named entity in DBpedia.
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Acknowledgments
The work is supported by the Natural Science Foundation of Jiangsu Province under Grant BK20140643 and the National Natural Science Foundation of China under grant No. 61502095.
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Li, H., Shi, J. (2016). Linking Named Entity in a Question with DBpedia Knowledge Base. In: Li, YF., et al. Semantic Technology. JIST 2016. Lecture Notes in Computer Science(), vol 10055. Springer, Cham. https://doi.org/10.1007/978-3-319-50112-3_20
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DOI: https://doi.org/10.1007/978-3-319-50112-3_20
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