# ICDM 2019 Knowledge Graph Contest: Team UWA

arXiv: https://arxiv.org/abs/1909.01807 · HTML: https://mlsanity.com/paper/1909.01807/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Sep 2019.

## Built on by (most cited first, 4 of 4)

- [A Survey on State-of-the-art Techniques for Knowledge Graphs Construction and Challenges ahead](https://mlsanity.com/paper/2110.08012/) (2021)
- [DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research](https://mlsanity.com/paper/2309.01808/) (2023)
- [Textbook to triples: Creating knowledge graph in the form of triples from AI TextBook](https://mlsanity.com/paper/2111.10692/) (2021)
- [Knowledge mining of unstructured information: application to cyber-domain](https://mlsanity.com/paper/2109.03848/) (2021)

## Abstract (arXiv)

We present an overview of our triple extraction system for the ICDM 2019 Knowledge Graph Contest. Our system uses a pipeline-based approach to extract a set of triples from a given document. It offers a simple and effective solution to the challenge of knowledge graph construction from domain-specific text. It also provides the facility to visualise useful information about each triple such as the degree, betweenness, structured relation type(s), and named entity types.