Linking Graph Entities with Multiplicity and Provenance

TL;DR

This paper introduces Certus, a graph-based entity linking system that manages multiple, conflicting, and provenance-rich representations of entities across databases and text, enhancing data integration and resolution.

Contribution

It presents a versatile graph model for entity profiles that handles multiple attribute values and provenance, along with system architecture and performance evaluation in HBase and Postgres.

Findings

Effective handling of multiple attribute values and provenance descriptions.

Performance evaluation of update operations in HBase and Postgres.

Versatile graph model improves entity resolution accuracy.

Abstract

Entity linking and resolution is a fundamental database problem with applications in data integration, data cleansing, information retrieval, knowledge fusion, and knowledge-base population. It is the task of accurately identifying multiple, differing, and possibly contradicting representations of the same real-world entity in data. In this work, we propose an entity linking and resolution system capable of linking entities across different databases and mentioned-entities extracted from text data. Our entity linking/resolution solution, called Certus, uses a graph model to represent the profiles of entities. The graph model is versatile, thus, it is capable of handling multiple values for an attribute or a relationship, as well as the provenance descriptions of the values. Provenance descriptions of a value provide the settings of the value, such as validity periods, sources, security requirements, etc. This paper presents the architecture for the entity linking system, the logical, physical, and indexing models used in the system, and the general linking process. Furthermore, we demonstrate the performance of update operations of the physical storage models when the system is implemented in two state-of-the-art database management systems, HBase and Postgres.