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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Detalles Bibliográficos
Autores principales: Yu, Zongjian, Zhang, Anxiang, Feng, Huali, Du, Huaming, Wei, Shaopeng, Zhao, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9316539/
https://www.ncbi.nlm.nih.gov/pubmed/35885187
http://dx.doi.org/10.3390/e24070964

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9316539/
https://www.ncbi.nlm.nih.gov/pubmed/35885187
http://dx.doi.org/10.3390/e24070964

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