• Knowledge Graphs
  • Gi et al 2020 - A Survey on Knowledge Graphs: Representation, Acquisition and Applications
• Knowledge Graph Completion
  • A Survey on Knowledge Graph Embeddings for Link Prediction
  • Arora 2020 - A Survey on Graph Neural Networks for Knowledge Graph Completion

See also Relation Extraction.

• Dong et al 2020 - AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

• Bansal et al 2019 - A2N: Attending to neighbors for knowledge graph inference
• Das et al 2020 - Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion

This is a relatively unexplored area, see Wood 2021 (NAACL 2021 Video).

• Zhang et al 2019 - OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference
• Yao et al 2019 - KG-BERT: BERT for Knowledge Graph Completion Says “most knowledge graph embedding models only use structure information in observed triple facts, which suffer from the sparseness of knowledge graphs. Some recent studies incorporate textual information to enrich knowledge representation (Socher et al. 2013; Xie et al. 2016; Xiao et al. 2017), but they learn unique text embedding for the same entity/relation in different triples, which ignore contextual information.”
• Wood et al 2021 - Integrating Lexical Information into Entity Neighbourhood Representations for Relation Prediction Builds upon OpenKI. Says “Relation prediction informed from a combination of text corpora and curated knowledge bases, combining knowledge graph completion with relation extraction, is a relatively little studied task.”

• Das et al 2020 - A Simple Approach to Case-Based Reasoning in Knowledge Bases

• DBpedia

• Information Extraction