Patel, RajatFerraro, Francis2020-12-082020-12-082020-11-19Rajat Patel and Francis Ferraro, On the Complementary Nature of Knowledge Graph Embedding, Fine Grain Entity Types, and Language Modeling, Proceedings of Deep Learning Inside Out (DeeLIO): The First Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, pp 89-99, DOI: 10.18653/v1/2020.deelio-1.11https://doi.org/10.18653/v1/2020.deelio-1.11http://hdl.handle.net/11603/20205Deep Learning Inside Out (DeeLIO): The First Workshop on Knowledge Extraction and Integration for Deep Learning ArchitecturesWe demonstrate the complementary natures of neural knowledge graph embedding, fine-grain entity type prediction, and neural language modeling. We show that a language model-inspired knowledge graph embedding approach yields both improved knowledge graph embeddings and fine-grain entity type representations. Our work also shows that jointly modeling both structured knowledge tuples and language improves both.11 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Text