The wealth of structured (e. g. Wikidata) and unstructured data about the world available today presents an incredible opportunity for tomorrow's Artificial Intelligence.
The occurrence of a fact (edge) is modeled as a multivariate point process whose intensity function is modulated by the score for that fact computed based on the learned entity embeddings.
Hyperbolic embeddings have recently gained attention in machine learning due to their ability to represent hierarchical data more accurately and succinctly than their Euclidean analogues.
#10 best model for Link Prediction on WN18RR
Previous cross-lingual knowledge graph (KG) alignment studies rely on entity embeddings derived only from monolingual KG structural information, which may fail at matching entities that have different facts in two KGs.
Named entity recognition (NER) is one of the best studied tasks in natural language processing.
#3 best model for Nested Mention Recognition on ACE 2005
Linked Open Data has been recognized as a valuable source for background information in many data mining and information retrieval tasks.
SOTA for Node Classification on BGS