Entity Embeddings
Leaderboards
Greatest papers with code
Entity Embeddings of Categorical Variables
• entron/entity-embedding-rossmann
• 
As entity embedding defines a distance measure for categorical variables it can be used for visualizing categorical data and for data clustering.
DeepType: Multilingual Entity Linking by Neural Type System Evolution
The wealth of structured (e. g. Wikidata) and unstructured data about the world available today presents an incredible opportunity for tomorrow's Artificial Intelligence.
End-to-End Neural Entity Linking
Entity Linking (EL) is an essential task for semantic text understanding and information extraction.
SOTA for Entity Linking on AIDA-CoNLL (Micro-F1 metric )
Jointly Learning Entity and Relation Representations for Entity Alignment
IJCNLP 2019
• THU-KEG/Entity_Alignment_Papers
•
Entity alignment is a viable means for integrating heterogeneous knowledge among different knowledge graphs (KGs).
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
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.
Multi-relational Poincaré Graph Embeddings
NeurIPS 2019
• ibalazevic/multirelational-poincare
• 
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.
Multi-relational Poincaré Graph Embeddings
NeurIPS 2019
• ibalazevic/multirelational-poincare
•
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
Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network
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.
Merge and Label: A novel neural network architecture for nested NER
ACL 2019
• fishjh2/merge_label
•
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
ENTITY EMBEDDINGS NAMED ENTITY RECOGNITION NESTED MENTION RECOGNITION
RDF2Vec: RDF Graph Embeddings and Their Applications
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
ENTITY EMBEDDINGS INFORMATION RETRIEVAL KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LANGUAGE MODELLING NODE CLASSIFICATION RECOMMENDATION SYSTEMS