# Radar Station data file. This repo contains the data necessary for the paper 'Radar Station: Using KG Embeddings for Semantic Table Interpretation and Entity Disambiguation.' The second part of the data is available at https://zenodo.org/record/6522921 Its structure of it is as follows: ''' ├─readme.md ├─DAGOBAHSL_Scoring │ ├─Limaye_Result │ ├─T2D_Result │ ├─2T_Result │ ├─ShortTable_Result ├─Embeddings │ ├─RotetE │ ├─ComplEx │ ├─TransE │ ├─Dismult ├─Datasets │ ├─Key_Column_Index │ │ ├─Limaye │ │ ├─T2D │ ├─ShortTable ├─Wikidata_Ground_Truth │ ├─Wikidata_GS_Limaye │ ├─Wikidata_GS_T2D │ ├─Wikidata_GS_2T │ ├─Wikidata_GS_ShortTable ''' ## DAGOBAHSL_Scoring It contains the result of the candidate scoring step after the four datasets were processed through a previous annotation system. In this score step, we did not filter any candidates during the calculation and always kept their scores. ## Embeddings This folder contains four embeddings used during our experiment. We provide four embeddings for the experiments: TransE, RotatE, Dismult, and ComplEx. In which the RotatE embeddings are from the pre-trained embeddings of GraphVite: https://graphvite.io/docs/latest/pretrained_model.html TransE, Dismult, and ComplEx are trained using Pytorch-BigGraph with Wikidata dump version 2021 May. **NOTICE**: the Dismult and ComplEx Embeddings should be further added to this folder. ## Datasets ### Key_Column_Index Key_Column_Index folder contains the index of the key column position for T2D and Limaye that are manually annotated. It tells Radar Station in which column we should run. ### ShortTable It contains the ShortTable dataset with tables of only two rows. ## Wikidata_Ground_Truth It contains the ground truth of the four datasets with Wikidata entities.