/KnowledgeGraphCompletionDataSet

Knowledge Graph Completion DataSet

    Refined Training and Test dataset for Knowledge Graph Model

Data overview

    This repository contains refinement dataset to train and evaluate knowledge graph model.
    If you have any questions or comments, please fell free to contact us by email [leewangon@gmail.com].

Data format

   This data is represented by a sequence of the following n-triple format.
   n-triple - a format for storing and transmitting data. 
            - a line-based, plain text serialisation format for RDF (Resource Description Framework) graphs.
            - a subset of the Turtle (Terse RDF Triple Language) format.
   <subject, relation, object>

Data Set

Kor-KB NELL-995 FB15K-237 NDSL DBpedia DBpia KData
Size 42MB 26MB 41MB 26MB 711MB 64MB 139MB
Triples 1,315,146 308,426 544,230 221,253 14,000,000 912,412 2,776,394
Entities 488,926 63,917 14,505 246,850 4,250,000 409,693 1,140,000
Relations 157 396 237 5 717 4 10,409
Classes 921 267 354 5 451 6 113

Kor-KB

Task #1 : nationality
Task #2 : job
Task #3 : employer

NELL-995 Link

FB15K-237 Link

NDSL Link

DBpedia Link

DBpia Link

KData Link

The institute to construct dataset

  • The AI Lab in Soongsil University

Citation

    @article{jagvaral2020path,
      title={Path-based reasoning approach for knowledge graph completion using CNN-BiLSTM with attention mechanism},
      author={Jagvaral, Batselem and Lee, Wan-Kon and Roh, Jae-Seung and Kim, Min-Sung and Park, Young-Tack},
      journal={Expert Systems with Applications},
      volume={142},
      pages={112960},
      year={2020},
      publisher={Elsevier}
    }