DaMuEL: A Large Multilingual Dataset for Entity Linking

TL;DR

DaMuEL is a comprehensive multilingual dataset for entity linking, combining a knowledge base with Wikipedia texts across 53 languages, enabling improved multilingual entity disambiguation and linking tasks.

Contribution

It introduces a large-scale, multilingual dataset with a unified knowledge base and annotated texts, facilitating research in multilingual entity linking.

Findings

Contains 27.9 million entities in the knowledge base.

Includes 12.3 billion tokens from Wikipedia texts.

Supports 53 languages for multilingual entity linking.

Abstract

We present DaMuEL, a large Multilingual Dataset for Entity Linking containing data in 53 languages. DaMuEL consists of two components: a knowledge base that contains language-agnostic information about entities, including their claims from Wikidata and named entity types (PER, ORG, LOC, EVENT, BRAND, WORK_OF_ART, MANUFACTURED); and Wikipedia texts with entity mentions linked to the knowledge base, along with language-specific text from Wikidata such as labels, aliases, and descriptions, stored separately for each language. The Wikidata QID is used as a persistent, language-agnostic identifier, enabling the combination of the knowledge base with language-specific texts and information for each entity. Wikipedia documents deliberately annotate only a single mention for every entity present; we further automatically detect all mentions of named entities linked from each document. The dataset contains 27.9M named entities in the knowledge base and 12.3G tokens from Wikipedia texts. The dataset is published under the CC BY-SA license at https://hdl.handle.net/11234/1-5047.