An enormous amount of digital information is expressed as natural-language (NL) text that is
not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for …

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 …

This survey presents a comprehensive description of recent neural entity linking (EL)
systems developed since 2015 as a result of the “deep learning revolution” in natural …

We introduce ReFinED, an efficient end-to-end entity linking model which uses fine-grained
entity types and entity descriptions to perform linking. The model performs mention …

We propose a global entity disambiguation (ED) model based on BERT. To capture global
contextual information for ED, our model treats not only words but also entities as input …

Abstract Local models for Entity Disambiguation (ED) have today become extremely
powerful, in most part thanks to the advent of large pre-trained language models. However …

Entity alignment (EA) is the task of identifying the entities that refer to the same real-world
object but are located in different knowledge graphs (KGs). For entities to be aligned …

Despite of the recent success of collective entity linking (EL) methods, these" global"
inference methods may yield sub-optimal results when the" all-mention coherence" …