ICDM 2019 Knowledge Graph Contest: Team UWA
Michael Stewart, Majigsuren Enkhsaikhan, Wei Liu

TL;DR
This paper describes a pipeline-based system for extracting triples from domain-specific texts to construct knowledge graphs, including visualization features for analysis.
Contribution
It introduces a simple, effective triple extraction pipeline with visualization capabilities for knowledge graph construction from text.
Findings
Effective triple extraction from domain-specific text
Visualization tools for triple analysis
Successful application in knowledge graph construction
Abstract
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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Multimodal Machine Learning Applications
