Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Entity linking (EL) is the process of linking entity mentions appearing in web text with their
corresponding entities in a knowledge base. EL plays an important role in the fields of …

Entities are at the center of how we represent and aggregate knowledge. For instance,
Encyclopedias such as Wikipedia are structured by entities (eg, one per Wikipedia article) …

We introduce CM3, a family of causally masked generative models trained over a large
corpus of structured multi-modal documents that can contain both text and image tokens …

Abstract Linked Open Data has been recognized as a valuable source for background
information in data mining. However, most data mining tools require features in propositional …

Entity Linking (EL) is an essential task for semantic text understanding and information
extraction. Popular methods separately address the Mention Detection (MD) and Entity …

The large number of potential applications from bridging web data with knowledge bases
have led to an increase in the entity linking research. Entity linking is the task to link entity …

Abstract Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical
ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental …

The embeddings of entities in a large knowledge base (eg, Wikipedia) are highly beneficial
for solving various natural language tasks that involve real world knowledge. In this paper …

Named Entity Disambiguation (NED) refers to the task of resolving multiple named entity
mentions in a document to their correct references in a knowledge base (KB)(eg, Wikipedia) …