WikiConflict: A New Dataset for Conflicting Data Reconciliation in Knowledge Graph Construction

The construction of a knowledge graph (KG) can be performed manually. Nevertheless, ensuring minimal coverage of a KG often requires the automatic data extraction from multiple sources. However, sources and extraction algorithms often vary in quality, may provide conflicting data with different levels of specificity or even contradict each other for the same entity. To reconcile these conflicting data and integrate them consistently within the KG, numerous fusion models can be adopted that simultaneously evaluate both the quality of the sources and the data provided. However, most of these models are usually evaluated on datasets that do not specifically represent differences in specificity, the heterogeneity of data types, or the presence of long-tail entities. These three challenges are frequently encountered in KG construction, making the data fusion process more complex. In this paper, we propose to overcome these limitations by introducing WikiConflict, a dataset built from the Wikidata revision history and designed for KG construction.