42 citations · 121 across the 24 of their papers we have counts for
5 papers · 1 filter
End-to-End Entity Linking and Disambiguation leveraging Word and Knowledge Graph Embeddings
Rostislav Nedelchev, Debanjan Chaudhuri, Jens Lehmann +1
Entity linking - connecting entity mentions in a natural language utterance to knowledge graph (KG) entities is a crucial step for question answering over KGs. It is often based on…
Pretrained Transformers for Simple Question Answering over Knowledge Graphs
D. Lukovnikov, A. Fischer, J. Lehmann
Answering simple questions over knowledge graphs is a well-studied problem in question answering. Previous approaches for this task built on recurrent and convolutional neural netw…
A Scalable Framework for Quality Assessment of RDF Datasets
Gezim Sejdiu, Anisa Rula, Jens Lehmann +1
Over the last years, Linked Data has grown continuously. Today, we count more than 10,000 datasets being available online following Linked Data standards. These standards allow dat…
The KEEN Universe: An Ecosystem for Knowledge Graph Embeddings with a Focus on Reproducibility and Transferability
Mehdi Ali, Hajira Jabeen, Charles Tapley Hoyt +1
There is an emerging trend of embedding knowledge graphs (KGs) in continuous vector spaces in order to use those for machine learning tasks. Recently, many knowledge graph embeddin…
Incorporating Joint Embeddings into Goal-Oriented Dialogues with Multi-Task Learning
Firas Kassawat, Debanjan Chaudhuri, Jens Lehmann
Attention-based encoder-decoder neural network models have recently shown promising results in goal-oriented dialogue systems. However, these models struggle to reason over and inc…