Learning from Knowledge Graphs: Neural Fine-Grained Entity Typing with Copy-Generation Networks

Learning from Knowledge Graphs: Neural Fine-Grained Entity Typing with Copy-Generation Networks

Fine-grained entity typing (FET) aims to identify the semantic type of an entity in a plain text, which is a significant task for downstream natural language processing applications. However, most existing methods neglect rich known typing information about these entities in knowledge graphs. To add...

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Bibliographic Details
Main Authors: Zongjian Yu, Anxiang Zhang, Huali Feng, Huaming Du, Shaopeng Wei, Yu Zhao
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Entropy
Subjects:
knowledge graphs
fine-grained entity typing
copy-generation networks
cross-entropy
Online Access:https://www.mdpi.com/1099-4300/24/7/964

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https://www.mdpi.com/1099-4300/24/7/964

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