Taxonomical hierarchy of canonicalized relations from multiple Knowledge Bases

TL;DR

This paper constructs a comprehensive taxonomical hierarchy of 623 canonical relations between entity types using Wikipedia, Wikidata, and DBpedia, aiding relation extraction tasks.

Contribution

It introduces a data-driven method to identify and unify relations from multiple knowledge bases into a unified hierarchy, covering a broad set of relations.

Findings

Hierarchy contains 623 canonical relations.

Wikipedia contributes the most relations to the hierarchy.

The relation list covers 85% of relations in RE datasets.

Abstract

This work addresses two important questions pertinent to Relation Extraction (RE). First, what are all possible relations that could exist between any two given entity types? Second, how do we define an unambiguous taxonomical (is-a) hierarchy among the identified relations? To address the first question, we use three resources Wikipedia Infobox, Wikidata, and DBpedia. This study focuses on relations between person, organization and location entity types. We exploit Wikidata and DBpedia in a data-driven manner, and Wikipedia Infobox templates manually to generate lists of relations. Further, to address the second question, we canonicalize, filter, and combine the identified relations from the three resources to construct a taxonomical hierarchy. This hierarchy contains 623 canonical relations with highest contribution from Wikipedia Infobox followed by DBpedia and Wikidata. The generated relation list subsumes an average of 85% of relations from RE datasets when entity types are restricted.