Knowledge graphs (KG) play a crucial role in many modern applications. However, constructing a KG from natural language text is challenging. One of the problem is the lack of the evaluation standard. In here, we provide two datasets as the guideline for the knowledge graph creation task. Note that the difference between the knowledge population task and the knowledge creation task is that in the knowledge population task a given KG is populated with triples, while the KG creation task considers the construction of the KG.
- Natthawut Kertkeidkachorn and Ryutaro Ichise. "Leveraging Distributed Representations of Elements in Triples for Predicate Linking." In International Conference on Hybrid Artificial Intelligence Systems, pp. 75-87. Springer, Cham, 2017.
- Natthawut Kertkeidkachorn and Ryutaro Ichise. "T2KG: An end-to-end system for creating knowledge graph from unstructured text." In Proceedings of AAAI Workshop on Knowledge-based Techniques for Problem Solving and Reasoning, pp. 743-749. 2017.
- Natthawut Kertkeidkachorn and Ryutaro Ichise. "An Automatic Knowledge Graph Creation Framework from Natural Language Text." IEICE TRANSACTIONS on Information and Systems 101, no. 1 pp. 90-98, 2018.