EABlock: A Declarative Entity Alignment Block for Knowledge Graph Creation Pipelines

TL;DR

EABlock introduces a declarative approach to entity alignment within RML mapping rules, enhancing the efficiency and transparency of knowledge graph creation pipelines by integrating entity recognition and linking functions.

Contribution

The paper presents EABlock, a novel framework that incorporates entity alignment functions into RML mapping rules, streamlining knowledge graph construction processes.

Findings

EABlock significantly speeds up knowledge graph creation pipelines.

EABlock effectively links recognized entities to Wikidata, DBpedia, and UMLS.

The approach is adaptable to any RML-compliant engine.

Abstract

Despite encoding enormous amount of rich and valuable data, existing data sources are mostly created independently, being a significant challenge to their integration. Mapping languages, e.g., RML and R2RML, facilitate declarative specification of the process of applying meta-data and integrating data into a knowledge graph. Mapping rules can also include knowledge extraction functions in addition to expressing correspondences among data sources and a unified schema. Combining mapping rules and functions represents a powerful formalism to specify pipelines for integrating data into a knowledge graph transparently. Surprisingly, these formalisms are not fully adapted, and many knowledge graphs are created by executing ad-hoc programs to pre-process and integrate data. In this paper, we present EABlock, an approach integrating Entity Alignment (EA) as part of RML mapping rules. EABlock includes a block of functions performing entity recognition from textual attributes and link the recognized entities to the corresponding resources in Wikidata, DBpedia, and domain specific thesaurus, e.g., UMLS. EABlock provides agnostic and efficient techniques to evaluate the functions and transfer the mappings to facilitate its application in any RML-compliant engine. We have empirically evaluated EABlock performance, and results indicate that EABlock speeds up knowledge graph creation pipelines that require entity recognition and linking in state-of-the-art RML-compliant engines. EABlock is also publicly available as a tool through a GitHub repository(https://github.com/SDM-TIB/EABlock) and a DOI(https://doi.org/10.5281/zenodo.5779773).