| Zhong et al. (20,150 [29] | text descriptions of entities | Link prediction, Triplet classification, Relational fact extraction, and Analogical reasoning |
| SEEA [32] | Semantical Information of Attributes of Entities | Entity aligment |
| TADW [33] | Text features of vertices | Multi-class classification of vertices |
| CANE [34] | Structure –based information, Text-based context information | Link prediction, Vertex classification |
| CKE [35] | Structural knowledge, Textual knowledge and visual knowledge, The information of users and items | Movie and book recommendation |
| DKRL [39] | semantic of entity descriptions | KG completion entity classification (in Zero-shot Scenario) |
| TransC [43] | Differentiating concepts and instance in entities | Link prediction, Triple classification |
| KALE [43] | Jointly embedding KGs and logical rules | Link prediction, Triple classification |
| Rocktaschel et al. (2015) [45] | Logical Background Knowledge | Relation Extraction |
| Newman-Griffis et al. (2018) [46] | Entities and surfaces forms, Text information | Analogy completion, Entity sense disambiguation |
| SSE [47] | Additional Semantic information (Semantically Smooth Embedding) | Link prediction, Triple classification |
| TKRL [48] | Hierarchical entity type information | KG completion, Triple classification |
| Jointly (A-LSTM) [49] | Both structural and textual information of entities | Link prediction, Triple classification |
| TEKE [50] | Textual context information (Text-enchanced knowledge embedding) | Link prediction, Triple classification (Capability to handle 1-to-N, N-to 1, N-to-N relations, and KG spareseness) |