ENT-DESC involves retrieving abundant knowledge of various types of main entities from a large knowledge graph (KG), which makes the current graph-to-sequence models severely suffer from the problems of information loss and parameter explosion while generating the descriptions.
Source: ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
Variants: ENT-DESC
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| KG-to-Text Generation | MGCN+sum | ENT-DESC: Entity Description Generation by … | 2020-04-30 |
Recent papers with results on this dataset: