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Adaptive Multilingual Representations for Cross-Lingual Entity Linking with Attention on Entity Descriptions Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Cross-Lingual Entity Linking in Wikipedia Infoboxes

Authors : Juheng Yang, Zhichun Wang

Published in: Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding

Publisher: Springer Singapore

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Abstract

Infoboxes in Wikipedia are valuable resources for extracting structured information of entities, several large-scale knowledge graphs are built by processing infobox data, including DBpedia, YAGO, etc. Entity links annotated by hyper-links in infoboxes are the keys for extracting entity relations. However, many entity links in infoboxes are missing because the mentioned entities do not exist in the current language versions of Wikipedia. This paper presents an approach for automatically linking mentions in infoboxes to their corresponding entities in another language, when the target entities are not in current language. Our approach first builds a cross-lingual mention-entity vocabulary from the cross-lingual links in Wikipedia, which is then used to generate cross-lingual candidate entities for mentions. After that, our approach performs entity disambiguation by using a cross-lingual knowledge graph embedding model. Experiments show that our approach can discover cross-lingual entity links with high accuracy.

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previous chapter Construction and Application of Teaching System Based on Crowdsourcing Knowledge Graph
next chapter Incorporating Domain and Range of Relations for Knowledge Graph Completion
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Metadata
Title
Cross-Lingual Entity Linking in Wikipedia Infoboxes
Authors
Juheng Yang
Zhichun Wang
Copyright Year
2019
Publisher
Springer Singapore
Book
Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding

Print ISBN: 978-981-15-1955-0

Electronic ISBN: 978-981-15-1956-7

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-15-1956-7_4

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