Maintaining Match Confidence on the Graph Edge: The Cost of Discarding Splink Scores
Discarding match probabilities impacts the accuracy of knowledge graphs. Retaining them as edge properties improves system reliability.
Many entity resolution processes discard the most valuable information they produce. Match probabilities are crucial for the system to accurately identify entities. When this data is thrown away before reaching the knowledge graph, low-confidence matches are overlooked. Retaining match probabilities as edge properties enhances the system's ability to provide accurate and reliable data.