Papers › DBLPLink: An Entity Linker for the DBLP Scholarly Knowledge Graph

DBLPLink: An Entity Linker for the DBLP Scholarly Knowledge Graph

14 Sep 2023arXiv:2309.07545archive 2025-07-28

Debayan Banerjee, Arefa, Ricardo Usbeck, Chris Biemann

In this work, we present a web application named DBLPLink, which performs entity linking over the DBLP scholarly knowledge graph. DBLPLink uses text-to-text pre-trained language models, such as T5, to produce entity label spans from an input text question. Entity candidates are fetched from a database based on the labels, and an entity re-ranker sorts them based on entity embeddings, such as TransE, DistMult and ComplEx. The results are displayed so that users may compare and contrast the results between T5-small, T5-base and the different KG embeddings used. The demo can be accessed at https://ltdemos.informatik.uni-hamburg.de/dblplink/.

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Entity EmbeddingsEntity Linking

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AdafactorAttentionAttention DropoutBPEDense ConnectionsDropoutGated Linear UnitInverse Square Root ScheduleLayer NormalizationLinear LayerMulti-Head AttentionResidual ConnectionSentencePieceSoftmaxT5TransE

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